Fuzzy model of residential energy decision-making considering behavioral economic concepts Appl. Energy (IF 7.182) Pub Date : 2017-11-20 Constantine Spandagos, Tze Ling Ng
To gain a fundamental understanding of the factors driving consumer energy behavior and for more effective policy-making, the development of energy consumption models taking into account key behavioral economic concepts is essential. In this direction, this paper presents a fuzzy logic decision-making model incorporating the concepts of bounded rationality, time discounting of gains, and pro-environmental behavior. The fuzzy model is used to characterize and predict consumer energy efficiency and curtailment behaviors in the context of residential cooling energy consumption. The model is developed from the perspective of the human decision-maker and the rules based on human reasoning and intuition. It takes into consideration monetary, personal comfort and environmental responsibility variables to yield predictions of one’s air-conditioning purchase and usage decisions. The results from running the model multiple times to simulate a real large urban population are found to match historical cooling energy use data reasonably well. This allows modelers some degree of confidence in the model. Moreover, perturbing key input variables produces plausible behaviors, thus providing additional validation to the model. This work demonstrates the feasibility of fuzzy logic as a powerful method for combining quantitative economic and physical factors with qualitative behavioral concepts in a single mathematical framework for better prediction of human energy behavior, and greater fundamental understanding of the “why” behind energy use that conventional building energy simulation models do not address.
Market equilibrium analysis with high penetration of renewables and gas-fired generation: An empirical case of the Beijing-Tianjin-Tangshan power system Appl. Energy (IF 7.182) Pub Date : 2017-11-15 Hongye Guo, Qixin Chen, Qing Xia, Chongqing Kang
Facing stricter energy policies, the power mix in China is experiencing significant changes. First, the proportion of renewables, which have intermittent and stochastic generation, is assumed to be rapidly increasing. Thus, there is an increasing requirement to install more flexible generation capacity in the power system. According to the Chinese government’s energy planning, in the near future, the proportion of gas-fired units will be greatly promoted to add flexibility to the power system. The impacts incurred by developing a high proportion of both renewables and gas-fired generation on the power market should be formulated and analyzed. In this study, a modified Nash-Cournot equilibrium model is proposed, considering renewable curtailment situations during valley times. Then, a large-scale and multi-period unit commitment model that considers the combined heat and power characteristics is presented to simulate market behaviors. On this basis, an empirical analysis of the Beijing-Tianjin-Tangshan power system equilibrium is illustrated as numerical examples, presenting the influences of the changing power mix on electricity prices, renewable energy integration, carbon emissions and air pollutant emissions. Finally, some suggestions on future electrical and environmental policies are presented.
Experimental investigation into the effectiveness of a super-capacitor based hybrid energy storage system for urban commercial vehicles> Appl. Energy (IF 7.182) Pub Date : 2017-11-15 Ottorino Veneri, Clemente Capasso, Stanislao Patalano
This paper is aimed to experimentally analyse the effectiveness of a hybrid storage system, when powering a commercial vehicle for urban use. The hybrid energy storage system is composed by two ZEBRA batteries, combined with an electric double layer capacitor (EDLC) module. The integration of those storage systems is obtained by means of a bidirectional DC/DC converter, which balances the electric power fluxes between batteries and super-capacitors, depending on the driving operative conditions. Modeling and simulations are preliminarily conducted with reference to the specific case study of an electric version of the Renault Master, supplied by the above described hybrid storage system. That theoretical activity allows the optimization of rule based energy management strategies for the hybrid energy storage system, in terms of the effectiveness in reducing the negative effects of high charging/discharging currents on battery durability. Then, the experimentation of the real power train, connected to the mentioned hybrid storage system, is carried out through a 1:1 laboratory test bench, able to perform the analysed energy management strategies on standard driving cycles, representative of the urban mission of the commercial vehicle under study. The obtained experimental results, expressed through electrical and mechanical parameters in a wide range of road operative conditions, show that the super-capacitors can improve the expected battery lifespan, with values of maximum effectiveness up to 52%, for driving patterns without negative road slopes. The procedure followed and presented in this paper definitely demonstrates the good performance of the evaluated hybrid storage system, controlled by the DC/DC power converter, to reduce the negative consequences of the power peaks associated with the urban use of commercial vehicles.
Simulation of a biomimetic façade using TRNSYS Appl. Energy (IF 7.182) Pub Date : 2017-11-14 Matthew Webb, Lu Aye, Ray Green
Biomimicry – innovation inspired by nature – is a creative methodology that translates characteristics from the biological world to the domain of human technology. Functional biomimicry offers opportunities to advance the development of flexible building facades. Following biomimetic principles, external fur and bioheat transfer (blood perfusion) and were combined into a mathematical model of a commercial office building façade for a west-facing wall of an office building situated in Melbourne, Australia. TRaNsient SYstem Simulation (TRNSYS) software tool was used to determine temperatures and heat transfer of this biomimetic façade in summer design conditions compared to a reference. The biomimetic façade was simulated to provide cooling of greater than 50 W m−2 and reduced mean surface temperatures in the occupied zone by 2.8 °C, compared with the reference.
Improving economics of lignocellulosic biofuels: An integrated strategy for coproducing 1,5-pentanediol and ethanol Appl. Energy (IF 7.182) Pub Date : 2017-11-14 Kefeng Huang, Wangyun Won, Kevin J. Barnett, Zachary J. Brentzel, David M. Alonso, George W. Huber, James A. Dumesic, Christos T. Maravelias
A biorefinery strategy for the coproduction of ethanol and 1,5-pentanediol (1,5-PDO), which can be used as polyester and polyurethane component, from lignocellulosic biomass is proposed. This strategy integrates biomass fractionation with simultaneous conversion of hemicellulose and cellulose constituents into 1,5-PDO and ethanol, respectively. An experimentally-based process model is developed to determine the economic potential of the integrated strategy. The coproduction strategy becomes competitive with the ethanol-only strategy when 1,5-PDO can be sold at $1140/ton, which is well below the market price of 1,5-PDO. The most important process parameters include biomass loading for biomass fractionation, enzyme loading for enzymatic hydrolysis and fermentation, and overall achievable yields from C5 sugars to 1,5-PDO.
Integrated strategic and tactical optimization of forest-based biomass supply chains to consider medium-term supply and demand variations Appl. Energy (IF 7.182) Pub Date : 2017-11-13 Shaghaygh Akhtari, Taraneh Sowlati, Verena C. Griess
Using forest-based biomass to produce bio-energy and bio-fuels could provide economic, environmental, and social benefits for communities. However, variability in biomass availability and high cost of delivered feedstock impact the profitability of the supply chain. Therefore, optimization models were developed in previous studies to design cost effective and profitable biomass-based supply chains at strategic level. Medium term variations in biomass supply and demand are not usually accounted for in strategic models. This may affect the feasibility of strategic plans prescribed by the optimization model at tactical level. To solve this issue, an integrated model is developed in this paper that includes strategic and tactical decisions simultaneously in order to optimize forest-based biomass supply chains. In addition to yearly variations in biomass supply, which can occur due to changes in harvest level, monthly variations in biomass availability, bioenergy/biofuels demand, and losses during preprocessing and storage of biomass are incorporated in the model. Other unique features of this model compared to the few integrated models developed in previous studies are as follows. (1) Decision regarding opening a new conversion facility is made yearly, not just at the beginning of the planning horizon. (2) A multi-product (heat, electricity, bio-oil and pellets) supply chain is considered. (3) The impact of fossil-based energy prices on bio-conversion investment decisions are accounted for in the model. (4) The optimization problem is modeled in a way that the global optimum solution is obtained within a reasonable time. Using a case study in Interior British Columbia, it is shown in the paper that the capacity of conversion technologies and the amount of procured biomass prescribed by the strategic model would not be sufficient to meet the monthly demand of bioenergy. Moreover, the net present value of the strategic model is overestimated due to underestimating the demand and procurement cost, and ignoring storage costs. It is shown that these issues are resolved using the integrated model.
Bed configuration effects on the finned flat-tube adsorption heat exchanger performance: Numerical modeling and experimental validation Appl. Energy (IF 7.182) Pub Date : 2017-11-10 Milad Mohammadzadeh Kowsari, Hamid Niazmand, Mikhail Mikhailovich Tokarev
A three dimensional numerical scheme has been developed to examine geometrical configuration effects on the performance of a single bed adsorption chiller with a trapezoidal aluminum finned flat-tube heat exchanger (FFT HEx). A mathematical distributed model along with the linear driving force (LDF) model and Darcy’s law have been considered to take into account the effects of heat and both intra/inter-grain mass transfer resistances. The developed numerical scheme has also been validated experimentally by using a composite sorbent SWS-1L and water as a working pair. Additionally, rectangular beds with identical working conditions and bed dimensions as the tested trapezoidal beds have been examined in similar details to identify, which type of the fin geometry provides a superior performance. It was found that in this particular HEx, the heat transfer resistance is mainly influenced by both of the fin pitch and height, while the inter-grain mass transfer resistance is independently controlled by the bed length. This fact makes the role of the fin pitch and fin height almost interchangeable with respect to the cycle time and specific cooling power (SCP) especially in rectangular beds. However, the coefficient of performance (COP) is more influenced by the fin height than the fin pitch. In addition, higher SCP can be achieved at smaller bed dimensions at the expense of lower COP. Moreover, it was found that using rectangular bed is more appropriate, since its SCP is either the same or higher than its corresponding trapezoidal bed especially at shorter bed lengths, while COP remains almost the same for both bed types in all considered ranges of bed dimensions. Finally, a bed designing procedure has been proposed for proper designing of effective adsorption HExs based on the performed parametric studies.
Process integration of a multiperiod sugarcane biorefinery Appl. Energy (IF 7.182) Pub Date : 2017-11-10 Cássia M. Oliveira, Leandro V. Pavão, Mauro A.S.S. Ravagnani, Antonio J.G. Cruz, Caliane B.B. Costa
Process integration in sugarcane biorefineries allows reducing steam consumption. As a consequence, the bagasse surplus can be diverted to second generation ethanol production. Furthermore, sugarcane plants can vary the production of ethanol and electricity, depending on the demand. For those reasons, equipment present in the plant might be required to operate under different conditions. This study presents the energy integration of a sugarcane biorefinery. A Mixed Integer Nonlinear Programming (MINLP) optimization model is proposed to solve the problem of synthesizing a Heat Exchanger Network (HEN) able to periodically operate under the distinct conditions required in the biorefinery, i.e., a multiperiod HEN. For solving the MINLP problem, a hybrid metaheuristic approach was used, which combines Simulated Annealing and Rocket Fireworks Optimization. The proposed strategy achieved lower HEN total annualized cost (TAC) when compared with the project energy integration that is commonly found in Brazilian plants. This reduction in TAC, in particular in utilities demand, allows the surplus bagasse to be available for the most suitable application: produce 2G ethanol or more electricity.
Energy conversion and gas emissions from production and combustion of poultry-litter-derived hydrochar and biochar Appl. Energy (IF 7.182) Pub Date : 2017-11-10 Vivian Mau, Amit Gross
Growing amounts of poultry litter call for improved treatment solutions. Its conversion to renewable energy can offer a solution while concomitantly reducing environmental impact and reliance on fossil fuels. We compared the production and combustion of biochar by slow pyrolysis to that of hydrochar by hydrothermal carbonization (HTC) in terms of char behavior, energetics, and gas emissions. Poultry litter is significantly different from other feedstocks when treated by slow pyrolysis and HTC, and requires a detailed study of its combustion behavior before it can be utilized in large-scale energy generation. Poultry litter was converted to biochar at 450 °C, and to hydrochar at 180, 200, 220 and 250 °C. Their chemical composition, combustion behavior and gaseous emissions were characterized by TGA–FTIR analysis. Hydrochar produced at 250 °C was more energy-dense than biochar, resulting in 24% higher net energy generation. Combustion behavior of hydrochar produced at 180, 200 and 220 °C was similar to that of the original litter, which is typical of biomass. On the other hand, hydrochar produced at 250 °C and biochar were more similar to coal. The main gaseous emissions during char production were CO2, CH4 and H2S. During the combustion step, NO and SO2 emissions were higher for hydrochar than biochar. Increasing HTC production temperature decreased emissions of CH4 and NH3 during hydrochar combustion. Biochar’s emissions were more significant during the production step than during combustion, whereas the opposite held true for hydrochar. Thus, HTC was seen to convert poultry litter more efficiently into a solid fuel that can potentially replace 10% of coal in the generation of electricity, thereby significantly reducing greenhouse gas emissions associated with electricity generation and agricultural waste.
Market equilibria and interactions between strategic generation, wind, and storage Appl. Energy (IF 7.182) Pub Date : 2017-11-10 Ali Shahmohammadi, Ramteen Sioshansi, Antonio J. Conejo, Saeed Afsharnia
Rising wind penetrations can suppress wholesale energy prices by displacing higher-cost conventional generation from the merit order. Wind suffers disproportionately from this price suppression, because the price is most suppressed when wind availability is high, hindering wind-investment incentives. One way to mitigate this price suppression is by wind exercising market power, which introduces efficiency losses. An alternative is to use energy storage, which allows energy to be stored when wind availability is high. This stored energy is later discharged when wind availability is lower and prices are higher. This paper proposes a bilevel equilibrium model to study market equilibrium interactions between energy storage and wind and conventional generators. We represent the market interaction using an equilibrium problem with equilibrium constraints. An illustrative case study is used to demonstrate the social welfare and profit benefits of using energy storage in this manner.
Power load probability density forecasting using Gaussian process quantile regression Appl. Energy (IF 7.182) Pub Date : 2017-11-10 Yandong Yang, Shufang Li, Wenqi Li, Meijun Qu
Accurately predicting the power load in certain areas is of great importance for grid management and power dispatching. A great deal of research has been conducted within the smart grid system community in developing an assortment of different algorithms that seek to increase the accuracy of these predictions. However, these predictions suffer from various sources of error, such as the variations in weather conditions, calendar effects, economic indicators, and many other sources, which are caused by the inherent stochastic and nonlinear characteristics of power demand. In order to quantify the uncertainty in load forecasting effectively, this paper proposes a comprehensive probability density forecasting method employing Gaussian process quantile regression (GPQR). GPQR is a type of Bayesian non-parametric method which can handle the uncertainties in power load data in a principled manner. Consequently, the probabilistic distribution of power load data can be statistically formulated. The effectiveness of the proposed method for short-term load forecasting has been assessed adopting the real dataset provided by American PJM electric power company. Numerical results demonstrate that the uncertainties in power load data can be effectively acquired based on the proposed method. Meanwhile, the competitive predictive performance could be yielded with respect to the conventional adopted methods.
PM2.5 footprint of household energy consumption Appl. Energy (IF 7.182) Pub Date : 2017-11-10 Siyuan Yang, Bin Chen, Muhammad Wakeel, Tasawar Hayat, Ahmed Alsaedi, Bashir Ahmad
Particulate matter 2.5 (PM2.5) as a major hazardous constituent is strongly associated with household energy consumption. In this paper, we investigate the PM2.5 footprint of household energy consumption in Beijing based on input–output analysis. An inventory of primary and secondary household energy consumption is developed to quantify the direct PM2.5 emissions. The household PM2.5 footprint is then traced through goods or services that ultimately consumed by households to unveil the indirect PM2.5 emissions triggered by economic activities. PM2.5 fingerprint is also proposed to describe the characteristic of household PM2.5 footprint. Results show that PM2.5 footprint of Beijing households in 2010 is 7831.36 kt, of which 92.61% is contributed by urban households. The source of direct PM2.5 emissions in urban area is diversified, which is composed of coal (42.07%), heat and electricity (32.83%), gasoline (21.29%), natural gas (3.04%) and liquefied petroleum gas (0.77%), while in rural area, coal (98.09%) plays a dominant role. The indirect PM2.5 accounts for 99.96% of the total footprint in urban area, about one third of which is contributed by sectors of “Food Processing and Production”, “Healthcare and Social Security”, and “Farming, Forestry, Animal Husbandry and Fishery”. The disparity between urban and rural households PM2.5 footprints is further evaluated with income levels. The PM2.5 footprint from living expenditures of urban households is found to be nearly twice as much as that of rural households. Such inventory of PM2.5 footprint and examination of drivers for PM2.5 emissions may be essential for urban pollution mitigation policy.
How to decarbonize the natural gas sector: A dynamic simulation approach for the market development estimation of renewable gas in Germany Appl. Energy (IF 7.182) Pub Date : 2017-11-10 Thomas Horschig, P.W.R. Adams, Erik Gawel, Daniela Thrän
The dedicated emission reduction and renewable implementation goals of several countries within the European Union led to the implementation of different support schemes and consequently to market development for biomethane. As the development and market penetration of biomethane as a renewable energy source is in most cases dependent on governmental support (in the form of incentive schemes or support programs) it is highly beneficial to be able to estimate the effects of planned actions. The current framework for biomethane encompasses high uncertainties within the market due to changing legislative conditions. Consequently this research presents a dynamic market model developed that is able to determine the effects of different policies and regulations to producing biomethane capacity, substitution pathways, land use and greenhouse gas emission reduction. It is the first model that encompasses the three sectors power, heat and transport in a dynamic model for biogenic energy carriers exploring the effects of new Government policies. Results indicate that a large proportion of the biomethane used today can no longer be produced economically when the financial support ends after a period of 20 years. Those plants, receiving a comparably high financial support, can only keep on producing and selling biomethane if there are other market opportunities than the CHP market. New instruments like blending could increase the biomethane sale in the direct heating market above the level shown in our results besides other measures like the prohibition of fossil fuels. The transport market would be able to compensate large proportions of the losses from the CHP market under a strong stepwise increment of the price for emission allowances.
Practical occupancy detection for programmable and smart thermostats Appl. Energy (IF 7.182) Pub Date : 2017-11-10 Elahe Soltanaghaei, Kamin Whitehouse
Home automation systems can save a huge amount of energy by detecting home occupancy and sleep patterns to automatically control lights, HVAC, and water heating. However, the ability to achieve these benefits is limited by a lack of sensing technology that can reliably detect zone occupancy states. We present a new concept called Walkway Sensing based on the premise that motion sensors are more reliable in walkways than occupancy zones, such as hallways, foyers, and doorways, because people are always moving and always visible in walkways. We present a methodology for deploying motion sensors and a completely automated algorithm called WalkSense to infer zone occupancy states. WalkSense can operate in both offline (batch) and online (real-time) mode. We implement our system using two types of sensors and evaluate them on 350 days worth of data from 6 houses. Results indicate that WalkSense achieves 96% and 95% average accuracies in offline and online modes, respectively, which translates to over 47% and 30% of reduced energy wastage, and 71% and 30% of reduced comfort issues per day, in comparison to the conventional offline and online approaches.
Optimal integration of renewable based processes for fuels and power production: Spain case study Appl. Energy (IF 7.182) Pub Date : 2017-11-10 Mariano Martín, Ignacio E. Grossmann
In this work we propose a data independent framework for the optimal integration of renewable sources of energy to produce fuels and power. A network is formulated using surrogate models for various technologies that use solar energy (photovoltaic, concentrated solar power or algae to produce oil), wind, biomass (to obtain ethanol, methanol, FT-liquids and thermal energy), hydroelectric, and waste (to produce power plant via biogas production). The optimization model is formulated as a mixed-integer linear programming model that evaluates the use of renewable resources and technologies and their integration to meet power and fuels demand; sustainability and CO2 emissions are also considered. The network can be applied to evaluate process integration at different scales, county to country level, including uncertainty availability of resources. Spain and particular regions are used as a case study. The framework suggests that larger integration uses the resources more efficiently, while considering uncertainty in resource availability shows larger cost to ensure meeting the demand. For the particular case considered, hydropower is widely used while biofuels are produced close to large populated regions when larger areas are evaluated; otherwise a more distributed solution is proposed. Reaching large fuel substitution is difficult at current biomass yields and technology state of development.
Asymptotic analysis for the inlet relative humidity effects on the performance of proton exchange membrane fuel cell Appl. Energy (IF 7.182) Pub Date : 2017-11-10 Yongfeng Liu, Lei Fan, Pucheng Pei, Shengzhuo Yao, Fang Wang
In order to study the inlet relative humidity (RH) effects on the performance of proton exchange membrane fuel cell (PEMFC), the inlet humidification efficiency (IHE) model is proposed. The total water content of PEMFC is consisted of two parts including the internal electro-migration water content and the external water content of the humidified gas. The dynamic inlet humidification efficiency is derived. The current density of PEMFC is calculated by the incorporating parameters including inlet humidification efficiency and water content of the humidified gas in the IHE model. Firstly, the schedule diagram of calculation is given and the geometric model is established according to actual size of PEMFC. The computational meshes are partitioned by using the software (Gambit). The IHE model is imported into the computational fluid dynamics software (Fluent). Secondly, the experimental system is established and experiments have been done at the operating temperature of 70 °C and at 40% RH, 55% RH, 70% RH, 85% RH and 100% RH, respectively. Finally, the contours of H2OH2O molar concentrations (both in anode channels and cathode channels), membrane water content (MWC) and polarization curves of the IHE model, the Fluent model and experimental are compared and analyzed at above experimental conditions. The results show that the species distribution uniformities of the IHE model such as H2OH2O molar concentrations (both in anode channels and cathode channels) and MWC are the best when the PEMFC at 100% RH. When the operating temperature is 70 °C (40% RH and <img height="18" border="0" style="vertical-align:bottom" width="97" alt="View the MathML source" title="View the MathML source" src="http://origin-ars.els-cdn.com/content/image/1-s2.0-S0306261917315878-si3.gif">350mA/cm2), the accuracy of the IHE model is improved by 79% compared with the Fluent model. When the operating temperature is 70 °C (40% RH and <img height="18" border="0" style="vertical-align:bottom" width="97" alt="View the MathML source" title="View the MathML source" src="http://origin-ars.els-cdn.com/content/image/1-s2.0-S0306261917315878-si3.gif">350mA/cm2), the inlet humidification efficiency reaches 57%.
Coordinating microgrid procurement decisions with a dispatch strategy featuring a concentration gradient Appl. Energy (IF 7.182) Pub Date : 2017-11-10 Mark A. Husted, Bharatkumar Suthar, Gavin H. Goodall, Alexandra M. Newman, Paul A. Kohl
A mathematical model designs and operates a hybrid power system consisting of diesel generators, photovoltaic cells and battery storage to minimize fuel use at remote sites subject to meeting variable demand profiles, given the following constraints: power generated must meet demand in every time period; power generated by any technology cannot exceed its maximum rating; and best practices should be enforced to prolong the life of the technologies. We solve this optimization model in two phases: (i) we obtain the design and dispatch strategy for an hourly load profile, and (ii) we use the design strategy, derived in (i), as input to produce the optimal dispatch strategy at the minute level. Our contributions consist of: combining a year-long hourly optimization procurement strategy with a minute-level dispatch strategy, and using a high-fidelity battery model at the minute-level derived from electrochemical engineering principles that incorporate temperature and voltage transient effects. We solve both phases of the optimization problem to within 5% of optimality and demonstrate that solutions from the minute-level model more closely match the load, more closely capture battery and generator behavior, and provide fuel savings from a few percent to 30% over that provided by the hour-level model for the tested scenarios.
Performance assessment of five MCP models proposed for the estimation of long-term wind turbine power outputs at a target site using three machine learning techniques Appl. Energy (IF 7.182) Pub Date : 2017-11-10 Santiago Díaz, José A. Carta, José M. Matías
Various models based on measure-correlate-predict (MCP) methods have been used to estimate the long-term wind turbine power output (WTPO) at target sites for which only short-term meteorological data are available. The MCP models used to date share the postulate that the influence of air density variation is of little importance, assume the standard value of 1.225 kg m−3 and only consider wind turbines (WTs) with blade pitch control.A performance assessment is undertaken in this paper of the models used to date and of newly proposed models. Our models incorporate air density in the MCP model as an additional covariable in long-term WTPO estimation and consider both WTs with blade pitch control and stall-regulated WTs. The advantages of including this covariable are assessed using different functional forms and different machine learning algorithms for their implementation (Artificial Neural Network, Support Vector Machine for regression and Random Forest).The models and the regression techniques used in them were applied to the mean hourly wind speeds and directions and air densities recorded in 2014 at ten weather stations in the Canary Archipelago (Spain). Several conclusions were drawn from the results, including most notably: (a) to clearly show the notable effect of air density variability when estimating WTPOs, it is important to consider the functional ways in which the features air density and wind speed and direction intervene, (b) of the five MCP models under comparison, the one that separately estimates wind speeds and air densities to later predict the WTPOs always provided the best mean absolute error, mean absolute relative error and coefficient of determination metrics, independently of the target station and type of WT under consideration, (c) the models which used Support Vector Machines (SVMs) for regression or random forests (RFs) always provided better metrics than those that used artificial neural networks, with the differences being statistically significant (5% significance) for most of the cases assessed, (d) no statistically significant differences were found between the SVM- and RF-based models.
An integrated systemic method for supply reliability assessment of natural gas pipeline networks Appl. Energy (IF 7.182) Pub Date : 2017-11-09 Huai Su, Jinjun Zhang, Enrico Zio, Nan Yang, Xueyi Li, Zongjie Zhang
A systematic method is developed for supply reliability assessment of natural gas pipeline networks. In the developed method, the integration of stochastic processes, graph theory and thermal-hydraulic simulation is performed accounting for uncertainty and complexity. The supply capacity of a pipeline network depends on the unit states and the network structure, both of which change stochastically because of stochastic failures of the units. To describe this, in this work a capacity network stochastic model is developed, based on Markov modeling and graph theory. The model is embedded in an optimization algorithm to compute the capacities of the pipeline network under different scenarios and analyze the consequences of failures of units in the system. Indices of supply reliability and risk are developed with respect to two aspects: global system and individual customers. In the case study, a gas pipeline network is considered and the results are analyzed in detail.
Generating biocrude from partially defatted Cryptococcus curvatus yeast residues through catalytic hydrothermal liquefaction Appl. Energy (IF 7.182) Pub Date : 2017-11-09 Zheting Bi, Ji Zhang, Zeying Zhu, Yanna Liang, Tomasz Wiltowski
Research and development on hydrothermal liquefaction (HTL) of wet microbial biomass have been on a dramatic rise. Although microalgae have been the main feedstocks, investigations of HTL of yeast species were few, not to mention yeast biomass cultivated on cellulosic hydrolysates. In this study, six catalysts were tested regarding their effects on yields of biocrude and biochar from partially defatted Cryptococcus curvatus. Among the six, K2CO3 at 350 and 300 °C and KOH at 350 °C led to the highest yield of biocrude, 68.9%, 63.9% and 67.0%, respectively. These biocrudes had low content of sulfur and nitrogen but high HHVs in the range of 36.9 and 39.0 MJ/kg. The biocrudes from the top three running conditions were dominated by fatty acids and fatty acid esters based on GC/MS identification. The corresponding aqueous phase samples contained high concentrations of fatty acids among all that were identifiable. The successful HTL of the partially defatted yeast cell residues promises a platform where lignocellulosic sugars can be converted to biodiesel from yeast cell lipids and biocrude from the remaining yeast cells.
Quantifying demand flexibility of power-to-heat and thermal energy storage in the control of building heating systems Appl. Energy (IF 7.182) Pub Date : 2017-11-09 Christian Finck, Rongling Li, Rick Kramer, Wim Zeiler
In the future due to continued integration of renewable energy sources, demand-side flexibility would be required for managing power grids. Building energy systems will serve as one possible source of energy flexibility. The degree of flexibility provided by building energy systems is highly restricted by power-to-heat conversion such as heat pumps and thermal energy storage possibilities of a building. To quantify building demand flexibility, it is essential to capture the dynamic response of the building energy system with thermal energy storage. To identify the maximum flexibility a building’s energy system can provide, optimal control is required. In this paper, optimal control serves to determine in detail demand flexibility of an office building equipped with heat pump, electric heater, and thermal energy storage tanks. The demand flexibility is quantified using different performance indicators that sufficiently characterize flexibility in terms of size (energy), time (power) and costs. To fully describe power flexibility, the paper introduces the instantaneous power flexibility as power flexibility indicator. The instantaneous power flexibility shows the potential power flexibility of TES and power-to-heat in any case of charging, discharging or idle mode. A simulation case study is performed showing that a water tank, a phase change material tank, and a thermochemical material tank integrated with building heating system can be designed to provide flexibility with optimal control.
Bidirectional low temperature district energy systems with agent-based control: Performance comparison and operation optimization Appl. Energy (IF 7.182) Pub Date : 2017-11-09 Felix Bünning, Michael Wetter, Marcus Fuchs, Dirk Müller
Bidirectional low temperature networks are a novel concept that promises more efficient heating and cooling of buildings. Early research shows theoretical benefits in terms of exergy efficiency over other technologies. Pilot projects indicate that the concept delivers good performance if heating and cooling demands are diverse. However, the operation of these networks is not yet optimized and there is no quantification of the benefits over other technologies in various scenarios. Moreover, there is a lack of understanding of how to integrate and control multiple distributed heat and cold sources in such networks. Therefore, this paper develops a control concept based on a temperature set point optimization and agent-based control which allows the modular integration of an arbitrary number of sources and consumers. Afterwards, the concept is applied to two scenarios representing neighborhoods in San Francisco and Cologne with different heating and cooling demands and boundary conditions. The performance of the system is then compared to other state-of-the-art heating and cooling solutions using dynamic simulations with Modelica. The results show that bidirectional low temperature networks without optimization produce 26% less emissions in the San Francisco scenario and 63% in the Cologne scenario in comparison to the other heating and cooling solutions. Savings of energy costs are 46% and 27%, and reductions of primary energy consumption 52% and 72%, respectively. The presented operation optimization leads to electricity use reductions of 13% and 41% when compared to networks with free-floating temperature control and the results indicate further potential for improvement. The study demonstrates the advantage of low temperature networks in different situations and introduces a control concept that is extendable for real implementation.
Predicting the visual impact of onshore wind farms via landscape indices: A method for objectivizing planning and decision processes Appl. Energy (IF 7.182) Pub Date : 2017-11-09 Petr Sklenicka, Jan Zouhar
Visual impact is one of the main factors influencing the acceptance of wind farms by the public and by the authorities. It therefore often sets the environmental and social limits of energy policy and energy use. However, the assessment of visual impacts is subjective, as is often pointed out by critics of the evaluation process. The study presented here for the first time uses accurately and objectively measurable landscape indices to directly predict the visual impact of onshore wind turbines. The method also for the first time evaluates map-based landscape indices in a panoramic simulation, and this provides a better match of visual preferences with landscape indices than the cartographic projection used until now. 400 respondents from four Central European countries (Austria, Germany, Poland and Czechia) provided an evaluation of their scenic perception of 32 different landscapes, in each case with and without wind turbines. At the same time, we analysed 12 indices characterizing the principal landscape components (relief, land cover and landscape pattern) on the basis of the 32 landscape photographs. These were further tested as predictors of visual impact. The most prominent predictors of visual impact were the Percentage of Industrial Area (including Commercial, Logistic and Mining Areas), Percentage of Forest Cover, Density of Technical Infrastructure, Number of Elevation Landmarks, and Elevation Variation. None of the three landscape pattern indices was statistically significant. On the basis of a regression model that is able to predict the potential visual impact in large areas of four Central European countries (over 830,000 km2), we present the general principles of an objectivized method for predicting the visual impact of onshore wind farms. The method makes an automatic assessment of the visual impact in large areas of entire regions or countries via a GIS analysis of Sentinel data and DEM data. This forms a good basis for both preventive evaluation and causal evaluation, and provides significant support for objectivizing the planning and decision process in order to mitigate negative environmental and social impacts of the use of wind energy.
Effects of personal carbon trading on the decision to adopt battery electric vehicles: Analysis based on a choice experiment in Jiangsu, China Appl. Energy (IF 7.182) Pub Date : 2017-11-08 Wenbo Li, Ruyin Long, Hong Chen, Tong Yang, Jichao Geng, Muyi Yang
The implementation of personal carbon trading (PCT) to influence transport choices has recently been suggested as a method to reduce private carbon emissions. In this study, we conducted a choice experiment in Jiangsu, China, to evaluate if PCT influences individual decisions to adopt battery electric vehicles (BEVs). The results showed that PCT can effectively change the decision to adopt and encourage the adoption of BEVs. PCT was shown to be more effective than free parking as well as eliminating road tolls, vehicle and vessel tax, and purchase tax, but less effective than government subsidies. In addition, we found that improving some BEV performance attributes was preferred to policy incentives, including PCT. These results improve our understanding of the effectiveness of PCT and the individual decision to adopt BEVs. Our findings could facilitate the practical implementation of PCT and provide suitable guidelines for developing BEV promotion strategies.
Optimization-based distribution grid hosting capacity calculations Appl. Energy (IF 7.182) Pub Date : 2017-11-08 Mansoor Alturki, Amin Khodaei, Aleksi Paaso, Shay Bahramirad
The distribution grid hosting capacity is defined as the amount of new production or consumption that can be added to the grid without adversely impacting the reliability or voltage quality for other customers. In this paper, an optimization-based method for determining the hosting capacity in distribution grids is proposed. The proposed method is developed based on a set of linear power flow equations that enable linear programming formulation of the hosting capacity model. Linearization further helps with determining a near-optimal solution in a short amount of time. The proposed method is examined on a test radial distribution grid to show its effectiveness and acceptable performance. Performance is further measured against existing iterative hosting capacity calculation methods. Results demonstrate that the proposed method outperforms traditional methods in terms of computation time while offering comparable results.
Investigation of soot formation and oxidation of ethanol and butanol fuel blends in a DISI engine at different exhaust gas recirculation rates Appl. Energy (IF 7.182) Pub Date : 2017-11-08 M. Koegl, B. Hofbeck, S. Will, L. Zigan
The soot formation and in-cylinder soot oxidation in an optically accessible DISI-engine is analyzed for gasoline-ethanol and -butanol mixtures. The volumetric extinction measurement technique used is capable of determining quantitative soot volume fractions and in-cylinder soot oxidation at low gas and soot particle temperatures. Toliso, a fuel mixture containing isooctane and toluene (65 vol% isooctane and 35 vol% toluene) was utilized as a surrogate gasoline fuel. The EGR-dependence (EGR-exhaust gas recirculation) on soot formation and -oxidation of the fuels was studied at part load operation. The studied operating point is characterized by an early injection timing leading to distinct piston wetting and a sooting pool-fire. The measurements without EGR showed a low soot formation for Toliso, while EGR leads to higher soot formation. E20 and B20 showed a strong sooting behaviour without EGR. An EGR increase reduced the soot formation for E20 and B20. It can be concluded that the physical fuel properties determine the spray formation and piston wetting. The fuel dependent evaporation of the liquid wall film as well as local mixing conditions play a major role on soot formation and oxidation.
Simulated building energy demand biases resulting from the use of representative weather stations Appl. Energy (IF 7.182) Pub Date : 2017-11-06 Casey D. Burleyson, Nathalie Voisin, Z. Todd Taylor, Yulong Xie, Ian Kraucunas
Numerical building models are typically forced with weather data from a limited number of “representative cities” or weather stations representing different climate regions. The use of representative weather stations reduces computational costs, but often fails to capture spatial heterogeneity in weather that may be important for simulations aimed at understanding how building stocks respond to a changing climate. We quantify the potential reduction in temperature and load biases from using an increasing number of weather stations over the western U.S. Our novel approach is based on deriving temperature and load time series using incrementally more weather stations, ranging from 8 to roughly 150, to evaluate the ability to capture weather patterns across different seasons. Using 8 stations across the western U.S., one from each IECC climate zone, results in an average absolute summertime temperature bias of ∼4.0 °C with respect to a high-resolution gridded dataset. The mean absolute bias drops to ∼1.5 °C using all available weather stations. Temperature biases of this magnitude could translate to absolute summertime mean simulated load biases as high as 13.5%. Increasing the size of the domain over which biases are calculated reduces their magnitude as positive and negative biases may cancel out. Using 8 representative weather stations can lead to a 20–40% bias of peak building loads during both summer and winter, a significant error for capacity expansion planners who may use these types of simulations. Using weather stations close to population centers reduces both mean and peak load biases. This approach could be used by others designing aggregate building simulations to understand the sensitivity to their choice of weather stations used to drive the models.
Assessing active and passive effects of façade building integrated photovoltaics/thermal systems: Dynamic modelling and simulation Appl. Energy (IF 7.182) Pub Date : 2017-11-02 Andreas K. Athienitis, Giovanni Barone, Annamaria Buonomano, Adolfo Palombo
This paper analyses the integration of air open-loop photovoltaic thermal systems on the façade of high-rise buildings, with a special focus on their active and passive effects. The system energy performance and its impact on the building heating and cooling demands and electrical production are assessed through a new dynamic simulation model. The developed numerical model of the proposed system, based on a detailed transient finite difference thermal network, is verified by comparing its outcomes to experimental results. With the aim to carry out whole building energy performance analyses, the model is implemented in a dynamic simulation tool for the building energy performance assessment, called DETECt 2.3, and suitably modified to analyse the main building integration energy issues.To assess the potentiality of the numerical model and the feasibility of the investigated system, a comprehensive case study relative to a multi-floor high rise office building located in several European climate zones is developed. A comparative and parametric analysis is also carried out with the aim to evaluate the system active and passive effects as a function of the building height. Simulation results show that by using building integrated air open-loop photovoltaic thermal systems, an interesting percentage reduction of the heating demand can be obtained. Both passive and active effects contribute to the variation of the thermal and electrical efficiencies. For the investigated weather zones, the innovative system leads to a reduction of the final energy consumptions ranging from 56.8 to 104.4%, approaching the nearly or net positive zero energy building target in the southern climate. Finally, the proposed analysis also aims to show the main implications linked to the design of the system, to be carefully taken into consideration by designers and stakeholders in case of new buildings or renovations.
Bayesian inference for thermal response test parameter estimation and uncertainty assessment Appl. Energy (IF 7.182) Pub Date : 2017-11-02 Wonjun Choi, Hideki Kikumoto, Ruchi Choudhary, Ryozo Ooka
The effective ground thermal conductivity and borehole thermal resistance constitute information needed to design a ground-source heat pump (GSHP). In situ thermal response tests (TRTs) are considered reliable to obtain these parameters, but interpreting TRT data by a deterministic approach may result in significant uncertainties in the estimates. In light of the impact of the two parameters on GSHP applications, the quantification of uncertainties is necessary. For this purpose, in this study, we develop a stochastic method based on Bayesian inference to estimate the two parameters and associated uncertainties. Numerically generated noisy TRT data and reference sandbox TRT data were used to verify the proposed method. The posterior probability density functions obtained were used to extract the point estimates of the parameters and their credible intervals. Following its verification, the proposed method was applied to in situ TRT data, and the relationship between test time and estimation accuracy was examined. The minimum TRT time of 36 h recommended by ASHRAE produced an uncertainty of ∼±21% for effective thermal conductivity. However, the uncertainty of estimation decreased exponentially with increasing TRT time, and was ±8.3% after a TRT time of 54 h, lower than the generally acceptable range of uncertainty of ±10%. Based on the obtained results, a minimum TRT time of 50 h is suggested and that of 72 h is expected to produce sufficiently accurate estimates for most cases.
Big data GIS analysis for novel approaches in building stock modelling Appl. Energy (IF 7.182) Pub Date : 2017-11-01 René Buffat, Andreas Froemelt, Niko Heeren, Martin Raubal, Stefanie Hellweg
Building heat demand is responsible for a significant share of the total global final energy consumption. Building stock models with a high spatio-temporal resolution are a powerful tool to investigate the effects of new building policies aimed at increasing energy efficiency, the introduction of new heating technologies or the integration of buildings within an energy system based on renewable energy sources. Therefore, building stock models have to be able to model the improvements and variation of used materials in buildings. In this paper, we propose a method based on generalized large-scale geographic information system (GIS) to model building heat demand of large regions with a high temporal resolution. In contrast to existing building stock models, our approach allows to derive the envelope of all buildings from digital elevation models and to model location dependent effects such as shadowing due to the topography and climate conditions. We integrate spatio-temporal climate data for temperature and solar radiation to model climate effects of complex terrain. The model is validated against a database containing the measured energy demand of 1845 buildings of the city of St. Gallen, Switzerland and 120 buildings of the Alpine village of Zernez, Switzerland. The proposed model is able to assess and investigate large regions by using spatial data describing natural and anthropogenic land features. The validation resulted in an average goodness of fit (R2R2) of 0.60.6.
Dynamic programming for optimal operation of a biofuel micro CHP-HES system Appl. Energy (IF 7.182) Pub Date : 2017-11-01 X.P. Chen, N. Hewitt, Z.T. Li, Q.M. Wu, Xufeng Yuan, Tony Roskilly
Combined heat and power systems (CHPs) have received much attention in recent years due to increasing use of bio-fuels and distributed generation (DG). Conventionally, they are connected to the power grid to balance electrical demands and supplies. This research investigated an off-grid (stand-alone) biofuel micro CHP system with hybrid energy storage (HES) (including battery banks and super-capacitors) by developing an energy management strategy based on dynamic programming (DP). DP is an optimization strategy which has been applied to energy systems in recent years. However, they suffer from dimension problems when the number of variables increases. This work is the first attempt to apply the decision tree (DT) to multi-dimension DP solutions in energy systems. The energy efficiency is improved from 45.77% to 57.97% using diesel-biofuels and the system has a potential for commercial applications. The experimental test results validate its feasibility and effectiveness.
Global available wind energy with physical and energy return on investment constraints Appl. Energy (IF 7.182) Pub Date : 2017-10-28 Elise Dupont, Rembrandt Koppelaar, Hervé Jeanmart
Looking ahead to 2050 many countries intend to utilise wind as a prominent energy source. Predicting a realistic maximum yield of onshore and offshore wind will play a key role in establishing what technology mix can be achieved, specifying investment needs and designing policy. Historically, studies of wind resources have however differed in their incorporation of physical limits, land availability and economic constraints, resulting in a wide range of harvesting potentials. To obtain a more reliable estimate, physical and economic limits must be taken into account.We use a grid-cell approach to assess the theoretical wind potential in all geographic locations by considering technological and land-use constraints. An analysis is then performed where the Energy Return on Investment (EROI) of the wind potential is evaluated. Finally, a top-down limitation on kinetic energy available in the atmospheric boundary layer is imposed.With these constraints wind farm designs are optimized in order to maximize the net energy flux. We find that the global wind potential is substantially lower than previously established when both physical limits and a high cut-off EROI > 10 is applied. Several countries’ potentials are below what is needed according to 100% renewable energy studies.
Experimental investigation of two-stage thermoelectric generator system integrated with phase change materials Appl. Energy (IF 7.182) Pub Date : 2017-10-27 Saeed Ahmadi Atouei, Ali Akbar Ranjbar, Alireza Rezania
Due to limitations in performance of thermoelectric materials, applying two-stage thermoelectric generator (TTEG) has been proposed to improve the performance of thermoelectric generator (TEG) system. In this paper, a novel prototype of a two-stage thermoelectric generator system is investigated experimentally. In the first stage, a TEG module installed between a phase change material (PCM) heat sink, as cooling system, and an electrical heater, as the heat source. Because of the inherent characteristics of PCMs to save the thermal energy as latent heat, the PCM heat sink is used as the heat source of the second stage TEGs. In the second stage, five smaller TEG modules are installed around the PCM with individual heat sinks for cooling with natural convection. In order to have a comparison between a common TEG system and the proposed two-stage TEG system, a one-stage thermoelectric generator with forced air cooling system has been tested. The results show the proposed TTEG system averagely generates 27% more electrical potential than the one-stage TEG system. Moreover, when the heater is off, the TTEG supplies 0.377 V open circuit voltage in average for about 7900 s, while the one-stage TEG generates this amount of voltage just for 2100 s. Therefore, the proposed design makes TEG systems more suitable for wireless sensor applications when the heat source does not provide steady thermal energy. In this study, four different patterns of thermal power applied to the TTEG system are considered. These patterns are used to simulate various transient thermal boundary conditions imposed to the system.
Thermal efficiency enhancement of the direct contact membrane distillation: Conductive layer integration and geometrical undulation ☆ Appl. Energy (IF 7.182) Pub Date : 2017-10-23 Isam Janajreh, Mohammed Noorul Hussain, Raed Hashaikeh, Rizwan Ahmed
The roles of high conductive layer integration and geometry undulation are investigated in order to improve the performance of the direct contact membrane distillation processes. In particular, the temperature polarization coefficient, mass flux and thermal efficiency are evaluated for the baseline and undulated flow under integrated superconductive layer membrane. This work caters for experimental and numerical model development. Experimentally, a countercurrent flow module for the desalination of sea water was developed using a flat-sheet electro-spun Polyvinylidene fluoride membrane generated and characterized by the author’s group for model validation. A steady state, conjugated heat, Navier-Stokes flow model computational fluid dynamics model was developed and subjected to the exact thermal and velocity flow conditions. The setup comprises two adjacent channel flows representing the hot saline feed and the cold fresh permeate channels. The two channels are thermally coupled through the hydrophobic membrane that is equipped with superconductive feathering layers. The results show agreement between the numerical model and experimental model measurements for the surface temperature distribution and the inferred temperature polarization co-efficient. In view of these plausible results and in line with numerous works on direct contact membrane distillation, a combined Knudsen and Poiseuille flow model is integrated to estimate the permeated mass and heat flux and explore improving the Membrane Distillation system in terms of thermal efficiency. While the role of superconductive feathering showed insignificant improvement in the temperature polarization coefficient, mass flux and thermal efficiency, the effect of combined undulated channels geometry was more pronounced. The gain obtained in the mass flux reaches 5.8% at lower feed temperature (50 °C), which is associated with a 5.8% gain in thermal efficiency and a 9.5% gain in temperature polarization co-efficient. It reaches a 6.1% gain in mass flux and thermal efficiency and a 9.5% gain for temperature polarization co-efficient at a higher feed inlet temperature.
Physical integration of a photovoltaic-battery system: A thermal analysis Appl. Energy (IF 7.182) Pub Date : 2017-10-21 Victor Vega-Garita, Laura Ramirez-Elizondo, Pavol Bauer
Systematic investigation on combustion characteristics and emission-reduction mechanism of potentially toxic elements in biomass- and biochar-coal co-combustion systems Appl. Energy (IF 7.182) Pub Date : 2017-10-21 Balal Yousaf, Guijian Liu, Qumber Abbas, Ruwei Wang, Muhammad Ubaid Ali, Habib Ullah, Ruijia Liu, Chuncai Zhou
Thermochemically converted biochar is considered as one of the promising alternative solid-fuel due to its high carbon contents of up to 80%, and has great potential to produce environmentally-friendly green-energy by improved fuel properties and emission-reduction of potentially toxic elements (PTEs). In this study, the biochar fuels, produced from peanut shell (PS) and wheat straw (WS) at 300, 500 and 700 °C, alone and blended with coal at mass ratio of 20% and 50% were systematically investigated for combustion characteristics and their potential to reduce the emission of PTEs including As, B, Ba, Be, Bi, Cd, Co, Cr, Cu, Ga, Ni, Pb, Sb, Sn, V and Zn in relation to partitioning, retention and volatilization in the co-combustion systems, using a variety of experimental techniques. Results indicated that the biochar-coal blended fuels in equal proportion showed steady state combustion over broad temperature range resulting increased the combustion efficiency and improved the thermal characteristics in comparison to coal and/or biomass-coal fuels. In addition, soot yield, CO emission and un-burned carbon in fly ash reduced significantly in biochar-blended fuels. However, CO2 emission from biochar-coal co-combustion was comparable to coal and/or biomass-coal fuels. Moreover, the present study illustrated that the volatilization potential of PTEs during combustion of biochar and their blends with coal decreased considerably up to 21% compared to that of coal, and enrichment of these contaminants occurred in the bottom and fly ashes ranged from 15.38–65% and 24.54–74.29%, respectively. Slagging and fouling problems were still found with biochar-coal co-combustion due to the higher inorganic fraction of biochar, which were overcome with the hydrothermal washing of fuels. Thus, it can be concluded that biochar-coal co-combustion is a suitable option for its use in existing coal-fired energy generation system to achieve the sustainable clean-green energy and reduction of gaseous PTEs emission.
Liquefaction of food waste and its impacts on anaerobic biodegradability, energy ratio and economic feasibility Appl. Energy (IF 7.182) Pub Date : 2017-10-21 S. Kavitha, J. Rajesh Banu, A. Arul Priya, Do Khac Uan, Ick Tae Yeom
Numerical study of gas production from methane hydrate deposits by depressurization at 274 K Appl. Energy (IF 7.182) Pub Date : 2017-10-21 Minghao Yu, Weizhong Li, Lanlan Jiang, Xin Wang, Mingjun Yang, Yongchen Song
Thermodynamic analysis and optimization of multistage latent heat storage unit under unsteady inlet temperature based on entransy theory Appl. Energy (IF 7.182) Pub Date : 2017-10-21 Y.K. Liu, Y.B. Tao
An optimization model for a multistage latent heat storage (LHS) unit with unsteady heat transfer fluid (HTF) inlet temperature was proposed. Thermodynamic analysis and optimization were performed based on the entransy theory. The expressions of the optimum phase change material (PCM) melting temperatures (Tm,opt) were derived. The effects of geometric parameters and unsteady HTF inlet temperature on the optimum phase change temperatures were investigated. The results indicate that with the increase of stage number (n), Tm1,opt increases and Tmn,opt decreases, which is beneficial to extend the selection range of PCM. For fixed entransy dissipation condition, increasing n will not change the fluctuation of the HTF outlet temperature; however a nearly uniform HTF outlet temperature can be obtained by increasing unit length (L). The unsteady HTF inlet temperature has great effects on the optimum phase change temperature. For a 3-stage LHS unit, the optimum phase change temperature of each stage increases by 14.9 K, 26.4 K and 38.0 K respectively with respect to the values obtained by steady method, which causes the heat storage capacity decreases by 6.1% and entransy dissipation decreases by 10.6%. The present work can provide guidance for the design of the multistage LHS unit with unsteady HTF inlet temperature.
Design of effective fins for fast PCM melting and solidification in shell-and-tube latent heat thermal energy storage through topology optimization Appl. Energy (IF 7.182) Pub Date : 2017-10-21 Alberto Pizzolato, Ashesh Sharma, Kurt Maute, Adriano Sciacovelli, Vittorio Verda
Measurements of crosswind influence on a natural draft dry cooling tower for a solar thermal power plant Appl. Energy (IF 7.182) Pub Date : 2017-10-21 Xiaoxiao Li, Hal Gurgenci, Zhiqiang Guan, Xurong Wang, Sam Duniam
Crosswind is a significant concern for natural draft dry cooling towers. The concern is more serious for shorter towers. Therefore, the crosswind influence is a significant threat to the use of natural draft dry cooling towers in concentrating solar thermal power plants, which are generally built at sizes smaller than conventional fossil-fired plants and employ relatively shorter towers. While some numerical studies and small lab-scale test reports exist, very few full scale experimental studies have been reported for conventional cooling towers and none for relatively short cooling towers suitable for renewable thermal power plants. To address this gap, a 20-m tall fully instrumented natural draft dry cooling tower was built by the University of Queensland. The tower was designed to serve a future 1-MWe concentrating solar thermal plant on the same site. Its performance was tested under different ambient temperatures and crosswind speeds. The detailed experimental data of the crosswind condition, air temperature distribution inside and outside of the cooling tower and the cooling performance are presented. The experimental data demonstrate the substantial yet complex impact of the crosswind on cooling tower performance. Significant non-uniformities in air and hot water temperature distributions and strong air vortices inside the tower were observed in high crosswind speeds. Unlike tall cooling towers used in large conventional plants, the cooling tower performance does not monotonously decrease with the increase of the crosswind speed. In fact, after the tower performance drops to its lowest level at a wind speed around 5 m/s, the trend is reversed and further increases in the crosswind speed help the tower performance. Analysis shows that this reversal occurs because the tower heat transfer mechanism changes. As crosswind rises above the critical speed, the airflow inside the cooling tower becomes increasingly controlled by the crosswind instead of the natural draft.
Optimal network design of hydrogen production by integrated utility and biogas supply networks Appl. Energy (IF 7.182) Pub Date : 2017-10-21 Soonho Hwangbo, Seungchul Lee, Changkyoo Yoo
Reverse electrodialysis heat engine for sustainable power production Appl. Energy (IF 7.182) Pub Date : 2017-10-21 A. Tamburini, M. Tedesco, A. Cipollina, G. Micale, M. Ciofalo, M. Papapetrou, W. Van Baak, A. Piacentino
A novel hybrid system based on a new proposed algorithm—Multi-Objective Whale Optimization Algorithm for wind speed forecasting Appl. Energy (IF 7.182) Pub Date : 2017-10-20 Jianzhou Wang, Pei Du, Tong Niu, Wendong Yang
In recent years, managers and researchers have paid increasing attention to accurate and stable wind speed prediction due to its significant effect on power dispatching and power grid security. However, most previous research has focused only on enhancing either accuracy or stability, with few studies addressing the two issues, simultaneously. This task is challenging due to the intermittency and complex fluctuations of wind speed. Therefore, we proposed a novel hybrid system based on a newly proposed called the MOWOA, which includes four modules: a data preprocessing module, optimization module, forecasting module, and evaluation module. An effective decomposing technique is also applied to eliminate redundant noise and extract the primary characteristics of wind speed data. In order to obtain high accuracy, and stability for wind speed prediction simultaneously, and overcome the weaknesses of single objective optimization algorithms, the optimization module of the proposed MOWOA is utilized to optimize the weights and thresholds of the Elman neutral network used in the forecasting module. Finally, the evaluation module, which includes hypothesis testing, evaluation criteria, and three experiments, is introduced perform comprehensive evaluation on the system. The results indicate that the proposed MOWOA performs better than the two recently developed MOALO and MODA algorithms, and that the proposed hybrid model outperforms all sixteen models used for comparison, which demonstrates its superior ability to generate forecasts in terms of forecasting accuracy and stability.
On the use of probabilistic forecasts in scheduling of renewable energy sources coupled to storages Appl. Energy (IF 7.182) Pub Date : 2017-10-20 Riccardo Remo Appino, Jorge Ángel González Ordiano, Ralf Mikut, Timm Faulwasser, Veit Hagenmeyer
Electric energy generation from renewable energy sources is generally non-dispatchable due to its intrinsic volatility. Therefore, its integration into electricity markets and in power system operation is often based on volatility-compensating energy storage systems. Scheduling and control of this kind of coupled systems is usually based on hierarchical control and optimization. On the upper level, one solves an optimization problem to compute a dispatch schedule and a coherent allocation of energy reserves. On the lower level, one performs online adjustments of the dispatch schedule using, for example, model predictive control. In the present paper, we propose a formulation of the upper level optimization based on data-driven probabilistic forecasts of the power and energy output of the uncontrollable loads and generators dependent on renewable energy sources. Specifically, relying on probabilistic forecasts of both power and energy profiles of the uncertain demand/generation, we propose a novel framework to ensure the online feasibility of the dispatch schedule with a given security level. The efficacy of the proposed scheme is illustrated by simulations based on real household production and consumption data.
Real-time implementation and validation of optimal damping control for a permanent-magnet linear generator in wave energy extraction Appl. Energy (IF 7.182) Pub Date : 2017-10-20 Daewoong Son, Ronald W. Yeung
To accommodate ocean-wave energy extraction in a wide operating range of sea-states, a nonlinear model predictive control (NMPC) methodology was applied to a lab-scale dual coaxial-cylinder wave-energy converter (WEC), coupled with a permanent-magnet linear generator (PMLG) as the power take-off (PTO). The paper focuses on the experimental implementation of the optimal damping control of the PMLG as guided by the NMPC process, which yielded intermediate values of damping subjected to prescribed damping capacity. This damping behavior was implemented electronically in the coupled PTO-WEC system by employing a solid-state relay (SSR) with pulse-width modulation (PWM) technique so as to mimic analog current flow. The effectiveness of the combination of SSR and PWM was demonstrated. Successful real-time lab-scale testing in regular and irregular waves was experimentally confirmed. Peak values of energy capture and a broadened bandwidth were favorably improved compared to those obtained using just constant, non-time-varying damping control.
Thermodynamic analysis and optimization of a novel combined power and ejector refrigeration cycle – Desalination system Appl. Energy (IF 7.182) Pub Date : 2017-10-18 Mohsen Sadeghi, Mortaza Yari, S.M.S. Mahmoudi, Moharram Jafari
A novel multi-generation hybrid system is proposed and analyzed in details from the viewpoint of thermodynamics. Using a zeotropic mixture as working fluid, the system consists of a power and ejector refrigeration cycle as well as a desalination system based on humidification and dehumidification processes. A parametric study is performed to specify the decision variables influencing the system performance prior to the optimization process. The optimization is conducted in two cases. In the first case, a single-objective optimization is carried out to maximize the overall exergy efficiency. In the second case, a multi-objective optimization is accomplished considering the net output power and refrigeration capacity as the objective functions.The results in the first case reveals a maximum overall exergy efficiency of 17.12% for which the net output power is 57.03 kW and the refrigeration capacity is 91.25 kW. In the case of multi-objective optimization, the results obtained from Pareto frontier shows a net produced power of 52.19 kW and a refrigeration capacity of 120.4 kW. With these data an overall exergy efficiency of 16.46% is calculated. The amount of fresh water calculated in case two is slightly higher than that obtained in case one.
Electrical behaviour of the pump working as turbine in off grid operation Appl. Energy (IF 7.182) Pub Date : 2017-10-18 Bernardo Capelo, Modesto Pérez-Sánchez, João F.P. Fernandes, Helena M. Ramos, P. Amparo López-Jiménez, P.J. Costa Branco
The use of pumps working as turbines (PATs) connected to the electric system, in the replacement of pressure reduction valves to reduce the excessive pressure in water distribution networks, have been studied for the last years. The introduction of PATs is very important in the water-energy nexus to promote the increase of the energy savings. As consequence, the majority of the water systems does not have access to the electrical grid and, therefore, the need to study the PATs operation off-grid is necessary. In this line, the novelty of this research is the application and optimization of a PAT in water systems when the recovery solution is off-grid type. To operate correctly, the induction machine requires an external source of reactive power, which is typically provided by the electrical grid. To supply the required reactive power, a bank of capacitors is installed at the machine terminals, so-called self-excited induction generator (SEIG). The analytical model, simulation and experimental works were performed, to analyse the SEIG behaviour. The results were applied in a SEIG-PAT system obtaining the global efficiency of the system for different speeds and loads. The global efficiency decreases 47% when off-grid operation, showing the need to optimize the electrical parameters of the generator to operate as off- grid with acceptable efficiency levels. In this framework, a tuning methodology for the SEIG capacitor bank values was developed to be automatically adjusted according to the operating point of the PAT to maximize its efficiency.
Portable personal conditioning systems: Transient modeling and system analysis Appl. Energy (IF 7.182) Pub Date : 2017-10-18 Rohit Dhumane, Jiazhen Ling, Vikrant Aute, Reinhard Radermacher
The existing Personal Conditioning Systems (PCS) have a limited market potential in spite of their energy savings potential and improved thermal comfort due to a combination of factors like retrofit costs, cooling limited to regions near installation and addition to building heat loads. We propose a novel concept of Portable Personal Conditioning System (PPCS) to address these challenges. PPCS includes a cooling system on an automated platform, which follows occupants to keep them comfortable. Four such cooling systems are presented: a vapor compression system (VCS), a chilled water based system, an ice storage based system and a phase change material storage based system. First-principles-based, transient multi-physics models were constructed for each system using Modelica to gain a more complete understanding of system performance and to quantify performance criteria such as minimum system weight and battery life. The article quantifies the trade-offs from the use of each system and is expected to motivate the development of portable personal cooling devices. System weights range from 19 to 31 kg with the chilled water system being the heaviest. The VCS consumes 40% more battery while delivering 170 W cooling at roughly twice the price of the chilled water system. The ice and phase change material based systems have weights comparable to the VCS and power consumption comparable to that of the chilled water based system.
Structural effects of expanded metal mesh used as a flow field for a passive direct methanol fuel cell Appl. Energy (IF 7.182) Pub Date : 2017-10-18 Aoyu Wang, Wei Yuan, Shimin Huang, Yong Tang, Yu Chen
The metal expanded mesh is an attractive alternative to be flow field plate of the direct methanol fuel cell (DMFC) for practical applications. This work investigates the structural effects of the stainless-steel expanded mesh used as a flow field in a passive DMFC. Three expanded meshes with different strand widths are tested at various methanol concentrations. Effects of its assembly diversity, in terms of two different mesh surfaces and orientations of the opening mesh, are also explored at both the anode and cathode. The influential mechanisms in the light of reactants and products management are analyzed by use of a visualization method. The mesh with a smaller strand width yields a better cell performance at a lower methanol concentration, which performs worse at a higher methanol concentration. Compared with the traditional perforated flow fields, the expanded mesh is preferred at lower methanol concentrations. The assembly mode combining BU at the anode and BL at the cathode is recommended. The visualization tests at both sides reveal the positive effects of above optimal configuration on the reactants and products management in a passive DMFC.
Advancing CO2 enhanced oil recovery and storage in unconventional oil play—Experimental studies on Bakken shales Appl. Energy (IF 7.182) Pub Date : 2017-10-18 Lu Jin, Steven Hawthorne, James Sorensen, Lawrence Pekot, Bethany Kurz, Steven Smith, Loreal Heebink, Volker Herdegen, Nicholas Bosshart, José Torres, Chantsalmaa Dalkhaa, Kyle Peterson, Charles Gorecki, Edward Steadman, John Harju
Although well logs and core data show that there is significant oil content in Bakken shales, the oil transport behavior in these source rocks is still not well understood. This lack of understanding impedes the drilling and production operations in the shale members. A series of experiments were conducted to investigate the rock properties of the Bakken shales and how to extract oil from the shales using supercritical CO2. High-pressure mercury injection tests showed that pore throat radii are less than 10 nm for most pores in both the upper and lower Bakken samples. Such small pore sizes yield high capillary pressure in the rock and make fluid flow difficult. Total organic carbon content was measured using 180 shale samples, and kerogen was characterized by Rock-Eval pyrolysis, which indicated considerable organic carbon present (10–15 wt%) in the shales. However, oil and gas are difficult to mobilize from organic matter using conventional methods. A systematic experimental procedure was carried out to reveal the potential for extracting hydrocarbons from the shale samples using supercritical CO2 under typical Bakken reservoir conditions (e.g., 34.5 MPa and 110 °C). Results showed that supercritical CO2 enables extraction of a considerable portion (15–65%) of hydrocarbons from the Bakken shales within 24 h. Measurement of CO2 adsorption isotherm showed that Bakken shale has a considerable capability to trap CO2 (up to 17 mg/g) under a wide range of pressures. The experimental results suggest the possibility of using supercritical CO2 injection to increase the ultimate oil recovery and store a considerable quantity of CO2 in the Bakken Formation.
Retrospective and predictive optimal scheduling of nitrogen liquefier units and the effect of renewable generation Appl. Energy (IF 7.182) Pub Date : 2017-10-18 Thomas Cummings, Richard Adamson, Andrew Sugden, Mark J. Willis
The construction and application of a multiple nitrogen liquefier unit (NLU) optimal scheduling tool is discussed. Constrained by customer demands and subject to electricity spot market prices over a week-ahead horizon, a retrospective optimiser (RO) determines the minimum scheduling costs. Plant start-up penalties and inter-site optimisation capabilities are incorporated into the optimisation model to emulate realistic operational flexibilities and costs. Using operational data, actual process schedules are compared to the RO results leading to improved process scheduling insights; such as increasing afternoon NLU operation during the spring to utilise lower power pricing caused by high solar generation. The RO is used to output a trackable load management key performance indicator to quantify potential and achieved scheduling improvements. Subsequently, correlations between renewable energy generation and spot market power prices are developed. Forecast pricing is used within a predictive optimiser (PO) to automatically generate an optimal schedule for the week ahead to meet projected customer demands. The RO provides potential hindsight savings of around 11%, and the PO up to 8% (representing significant cost savings for such energy intensive processes).
The role of technology diffusion in a decarbonizing world to limit global warming to well below 2 °C: An assessment with application of Global TIMES model Appl. Energy (IF 7.182) Pub Date : 2017-10-18 Weilong Huang, Wenying Chen, Gabrial Anandarajah
Low-carbon power generation technologies such as wind, solar and carbon capture and storage are expected to play major roles in a decarbonized world. However, currently high cost may weaken the competitiveness of these technologies. One important cost reduction mechanism is the “learning by doing”, through which cumulative deployment results in technology costs decline. In this paper, a 14-region global energy system model (Global TIMES model) is applied to assess the impacts of technology diffusion on power generation portfolio and CO2 emission paths out to the year 2050. This analysis introduces three different technology learning approaches, namely standard endogenous learning, multiregional learning and multi-cluster learning. Four types of low-carbon power generation technologies (wind, solar, coal-fired and gas-fired CCS) undergo endogenous technology learning. The modelling results show that: (1) technology diffusion can effectively reduce the long-term abatement costs and the welfare losses caused by carbon emission mitigation; (2) from the perspective of global optimization, developed countries should take the lead in low-carbon technologies’ deployment; and (3) the establishment of an effective mechanism for technology diffusion across boundaries can enhance the capability and willingness of developing countries to cut down their CO2 emission.
Driving force and resistance: Network feature in oil trade Appl. Energy (IF 7.182) Pub Date : 2017-10-17 Toshihiko Kitamura, Shunsuke Managi
This article examines the international crude oil trade and the international petroleum trade through econometric analysis and complex network analysis, focusing on the aspects of the driving forces and resistances for the oil trade and competitive or cooperative relationships among countries. The crude oil trade network and the petroleum trade network are constructed. Positional and role analysis reveals that countries can be divided into five positions in the crude oil trade network and twenty-five positions in the petroleum trade network. The relationships among countries within or between positions are discussed and recognized as competitive or cooperative. The bilateral oil trade analysis shows that various factors within countries have influence on bilateral trade volume. The analysis also implies that restrictions on trade partner selection due to geographical resistance forces neighboring oil-importing countries to choose similar oil-exporting countries, which corresponds with the results of the complex network analysis. The complex network analysis shows that the countries in the same position belong to the same region. Furthermore, the analysis results imply that the diversification in petroleum-exporting countries reduces the supply disruption risk for importing countries.
Techno-economic and greenhouse gas savings assessment of decentralized biomass gasification for electrifying the rural areas of Indonesia Appl. Energy (IF 7.182) Pub Date : 2017-10-17 Siming You, Huanhuan Tong, Joel Armin-Hoiland, Yen Wah Tong, Chi-Hwa Wang
This study explored the feasibility of decentralized gasification of oil palm biomass in Indonesia to relieve its over-dependence on fossil fuel-based power generation and facilitate the electrification of its rural areas. The techno-feasibility of the gasification of oil palm biomass was first evaluated by reviewing existing literature. Subsequently, two scenarios (V1 and V2, and M1 and M2) were proposed regarding the use cases of the village and mill, respectively. The capacity of the gasification systems in the V1 and M1 scenarios are determined by the total amount of oil palm biomass available in the village and mill, respectively. The capacity of the gasification systems in the V2 and M2 scenarios is determined by the respective electricity demand of the village and mill. The global warming impact and economic feasibility (net present value (NPV) and levelized cost of electricity (LCOE)) of the proposed systems were compared with that of the current practices (diesel generator for the village use case and biomass boiler combustion for the mill use case) using life cycle assessment (LCA) and cost-benefit analysis (CBA). Under the current daily demand per household (0.4 kWh), deploying the V2 system in 104 villages with 500 households each could save up to 17.9 thousand tons of CO2-eq per year compared to the current diesel-based practice. If the electricity could be fed into the national grid, the M1 system with 100% capacity factor could provide yearly GHG emissions mitigation of 5.8 × 104 ton CO2-eq, relative to the current boiler combustion-based reference scenario. M1 had a positive mean NPV if the electricity could be fed into the national grid, while M2 had a positive mean NPV at the biochar price of 500 USD/ton. Under the current electricity tariff (ET) (0.11 kWh) and the biochar price of 2650 USD/ton, daily household demands of 2 and 1.8 kWh were required to reach the break-even point of the mean NPV for the V2 system for the cases of 300 and 500 households, respectively. The average LCOE of V2 is approximately one-fourth that of the reference scenario, while the average LCOE of V1 is larger than that of the reference scenario. The average LCOE of M1 decreased to around 0.06 USD/kWh for the case of a 100% capacity factor. Sensitivity analysis showed that the capital cost of gasification system and its overall electrical efficiency had the most significant effects on the NPV. Finally, practical system deployment was discussed, with consideration of policy formulation and fiscal incentives.
Completion of wind turbine data sets for wind integration studies applying random forests and k-nearest neighbors Appl. Energy (IF 7.182) Pub Date : 2017-10-16 Raik Becker, Daniela Thrän
The importance of wind power as a renewable and cost-efficient power generation technology is growing globally. The impact of wind power on the existing power system, land use, and others over time has been widely studied. Such wind integration studies, especially when they are designed as retrospective bottom-up studies, rely on detailed wind turbine data, including the geographic locations, hub height, and dates of commission. Given the frequency of gaps present in these data sets, basic concepts have been developed to cope with missing data points. In this paper, multiple advanced algorithms were compared with respect to their ability to complete such data sets. One focus was on the selection of predictor variables to analyze the impact of different completion techniques depending on the specific gaps in the data set. A sample application using a German data set indicated that random forests are particularly well suited to the problem at hand.
Powering an island system by renewable energy—A feasibility analysis in the Maldives Appl. Energy (IF 7.182) Pub Date : 2017-10-16 Jiahong Liu, Chao Mei, Hao Wang, Weiwei Shao, Chenyao Xiang
Water and energy supply systems are essential parts of the infrastructure on islands. For small islands that are far from continents, water shortage is usually the main constraint on economic and social development. In order to maintain island water security, desalination plants are built to supply fresh water. The plants need a great deal of energy, which increases demand for energy and the cost of transportation. Thus, it is necessary to design a new island system driven by renewable energy. This study investigated the existing type of water and energy supply systems in some typical islands of the world, and analyzed their advantages and disadvantages. The energy supply systems can be classified into three categories: imported conventional energy supply system (ICESS); imported conventional energy & renewable energy supply system (ICE&RESS); and integrated energy supply system (IESS). Water supply systems can also be classified into three categories: imported water supply system (ImWSS); imported water and unconventional water supply system (IW&UWSS); and integrated water supply system (InWSS). The nexus of energy and water is very complicated on islands. This paper presents a framework for an interconnected energy and water system on an island. The new framework reveals a roadmap from “full input of energy & water (FIEW)” through “semi-input of energy & water (SIEW)” to “zero input of energy & water (ZIEW)”, which leads an island's energy and water resources to become gradually independent from the mainland. The new framework also reduces transportation costs and carbon emissions. The proposed framework is applied to the Maldives to aid design of a renewable energy-driven water supply system. The characteristics and mutual adaptability of three types of renewable energy (solar, wind, and biomass energy) and water supply systems is discussed. The results show that a ZIEW system can be realized in the Maldives with a reduction in the cost of renewable energy. ZIEW system has great potential for application in island regions in the future.
Evaluation of the energy performance of variable refrigerant flow systems using dynamic energy benchmarks based on data mining techniques Appl. Energy (IF 7.182) Pub Date : 2017-10-16 Jiangyan Liu, Jiangyu Wang, Guannan Li, Huanxin Chen, Limei Shen, Lu Xing
The variable refrigerant flow (VRF) system has extremely different energy performance at various operation conditions. Its power consumption is inconsistent even under the steady operation condition. In order to accurately evaluate the VRF system’s dynamic energy performance, this study proposed a data-mining-based method to benchmark and assess its energy uses. The correlation analysis is used for key factors selection and the interquartile range rule is employed to remove outliers of the database. In addition, the power consumption patterns are classified using decision tree (DT) method. The classification results are validated by the ANOVA analysis and post hoc test. Nine energy benchmarks are established based on the classified power consumption patterns. Moreover, an energy consumption rating system is established to provide quantitative assessment on the power consumption of the VRF system. A case study is conducted by comparatively analyzing the energy performance of the VRF system at multiple refrigerant charge fault cases. Results show that both the PLR and OT significantly affected the power consumption of the VRF system. However, the degree to which the refrigerant charge fault affects system power consumption varies with the power consumption patterns. For different patterns, the power consumptions of the VRF system were either lower, higher or similar to each other at various RCLs. Results also suggest that the energy benchmarking process provide reasonable classification criteria, and the grading process provide quantitative assessment on the energy consumption. Therefore, the proposed dynamic energy benchmarks are reliable and reasonable to evaluate the dynamic energy performance of VRF systems.
Cost-competitiveness of organic photovoltaics for electricity self-consumption at residential buildings: A comparative study of Denmark and Greece under real market conditions Appl. Energy (IF 7.182) Pub Date : 2017-10-16 Marios D. Chatzisideris, Alexis Laurent, Georgios C. Christoforidis, Frederik C. Krebs
To address sustainability challenges, photovoltaics (PV) are regarded as a promising renewable energy technology. Decreasing PV module costs and increasing residential electricity prices have made self-consumption of PV-generated electricity financially more attractive than exporting to the grid. Organic photovoltaics (OPV) are an emerging thin-film PV technology that shows promise of greatly improving the environmental and economic performances of PV technologies. Previous studies have estimated the current and future costs of OPV technologies, but the attractiveness of investing in OPV systems has not been evaluated under real market conditions, especially under PV self-consumption schemes. In this study, we investigate the self-consumption of electricity generation from conventional and organic PV systems installed at residential houses in two different countries, Denmark and Greece, under current PV regulatory frameworks. We then focus on modelling and assessing the cost-competitiveness of organic PV technologies based on cost estimations for existing pilot-scale (kW-range), and projected scale-up (100MW) and industrial-scale (100 GW) manufacturing capacity levels. Our generic results applying to all PV technologies show that PV systems installed at residential houses in Greece perform economically better than those in Denmark do in terms of self-sufficiency and gross electricity bill savings (i.e. excluding PV costs). Using the two country cases, which present very different settings, we characterise and discuss the influence of three key parameters of the economic performance of PV systems, namely the PV regulatory scheme, the solar irradiation level and the temporal match between the electricity consumption and solar irradiation profiles. Focusing on organic PV systems developed in an industrial-scale cost setting (1.53 €/Wp), we find that they deliver significant electricity bill savings for residential houses in Greece (38%) under current conditions, while they may not be sufficiently attractive for residential houses in Denmark (6.5%) due to mainly the different PV regulatory schemes. Based on these findings, we therefore recommend investors interested in renewable energy technologies to pursue scaling up the manufacturing capacity of OPV technologies, as well as assess a large number of countries to identify and prioritise financially attractive settings for PV self-consumption.
Projecting state-level air pollutant emissions using an integrated assessment model: GCAM-USA Appl. Energy (IF 7.182) Pub Date : 2017-10-16 Wenjing Shi, Yang Ou, Steven J. Smith, Catherine M. Ledna, Christopher G. Nolte, Daniel H. Loughlin
Some contents have been Reproduced by permission of The Royal Society of Chemistry.
- Acad. Manag. Ann.
- Acc. Chem. Res.
- Acc. Chem. Res.
- ACS Appl. Mater. Interfaces
- ACS Biomater. Sci. Eng.
- ACS Catal.
- ACS Cent. Sci.
- ACS Chem. Biol.
- ACS Chem. Neurosci.
- ACS Comb. Sci.
- ACS Earth Space Chem.
- ACS Energy Lett.
- ACS Infect. Dis.
- ACS Macro Lett.
- ACS Med. Chem. Lett.
- ACS Nano
- ACS Omega
- ACS Photonics
- ACS Sens.
- ACS Sustainable Chem. Eng.
- ACS Synth. Biol.
- Acta Mater.
- Acta Neuropathol.
- Adv. Drug Deliver. Rev.
- Adv. Electron. Mater.
- Adv. Energy Mater.
- Adv. Funct. Mater.
- Adv. Healthcare Mater.
- Adv. Mater.
- Adv. Mater.
- Adv. Opt. Mater.
- Adv. Opt. Photon.
- Adv. Phys.
- Adv. Sci.
- Adv. Synth. Catal.
- Adv. Synth. Catal.
- AlChE J.
- Alzheimers Dement.
- Am. J. Hum. Genet.
- Am. J. Psychiatry
- Am. J. Respir. Crit. Care Med.
- Anal. Chem.
- Anal. Chim. Acta
- Anal. Methods
- Angew. Chem. Int. Ed.
- Angew. Chem. Int. Ed.
- Ann. Intern. Med.
- Ann. Neurol.
- Ann. Oncol.
- Ann. Rheum. Dis.
- Annu. Rev. Anal. Chem.
- Annu. Rev. Astron. Astrophys.
- Annu. Rev. Biochem.
- Annu. Rev. Biomed. Eng.
- Annu. Rev. Biophys.
- Annu. Rev. Cell Dev. Biol.
- Annu. Rev. Clin. Psychol.
- Annu. Rev. Condens. Matter Phys.
- Annu. Rev. Earth Planet. Sci.
- Annu. Rev. Ecol. Evol. Syst.
- Annu. Rev. Entomol.
- Annu. Rev. Fluid Mech.
- Annu. Rev. Immunol.
- Annu. Rev. Mar. Sci.
- Annu. Rev. Mater. Res.
- Annu. Rev. Med.
- Annu. Rev. Microbiol.
- Annu. Rev. Neurosci.
- Annu. Rev. Nutr.
- Annu. Rev. Pathol. Mech. Dis.
- Annu. Rev. Pharmacol. Toxicol.
- Annu. Rev. Phys. Chem.
- Annu. Rev. Physiol.
- Annu. Rev. Phytopathol.
- Annu. Rev. Plant Biol.
- Annu. Rev. Psychol.
- Annu. Rev. Publ. Health
- Annu. Rev. Virol.
- Antivir. Res.
- Appl. Catal. A Gen.
- Appl. Catal. B Environ.
- Appl. Energy
- Appl. Phys. Lett.
- Appl. Phys. Rev.
- Arch. Pharm.
- Asian J. Org. Chem.
- CA: Cancer J. Clin.
- Cancer Cell
- Cancer Discov.
- Cancer Res.
- Carbohydr. Polym.
- Catal. Sci. Technol.
- Catal. Today
- Cell Chem. Bio.
- Cell Host Microbe
- Cell Metab.
- Cell Res.
- Cell Stem Cell
- Ceram. Int.
- Chem. Asian J.
- Chem. Bio. Drug Des.
- Chem. Commun.
- Chem. Commun.
- Chem. Educ. Res. Pract.
- Chem. Eng. J.
- Chem. Eur. J.
- Chem. Mater.
- Chem. Phys.
- Chem. Phys. Lett.
- Chem. Res. Toxicol.
- Chem. Rev.
- Chem. Rev.
- Chem. Sci.
- Chem. Sci.
- Chem. Soc. Rev.
- Chem. Soc. Rev.
- Circ. Res.
- Clin. Cancer Res.
- Clin. Microbiol. Rev.
- Compos. Part A Appl. Sci. Manuf.
- Comput. Fluids
- Coordin. Chem. Rev.
- Corros. Sci.
- Crit. Rev. Food Sci. Nutr.
- Cryst. Growth Des.
- Curr. Opin. Biotech.
- Curr. Opin. Cell Biol.
- Ecol. Lett.
- Electrochem. Commun.
- Electrochim. Acta
- Endocr. Rev.
- Energy Environ. Sci.
- Energy Environ. Sci.
- Energy Fuels
- Environ. Pollut.
- Environ. Sci. Technol.
- Environ. Sci. Technol. Lett.
- Environ. Sci.: Nano
- Environ. Sci.: Nano
- Environ. Sci.: Processes Impacts
- Environ. Sci.: Water Res. Technol.
- Eur. Heart J.
- Eur. J. Inorg. Chem.
- Eur. J. Med. Chem.
- Eur. J. Org. Chem.
- Eur. Polym. J.
- Eur. Respir. J.
- Eur. Urol.
- J Nucl. Med.
- J. Agric. Food Chem.
- J. Allergy Clin. Immunol.
- J. Alloys Compd.
- J. Am. Ceram. Soc.
- J. Am. Chem. Soc.
- J. Am. Chem. Soc.
- J. Am. Coll. Cardiol.
- J. Anal. At. Spectrom.
- J. Antibiot.
- J. Cachexia Sarcopenia Muscle
- J. Catal.
- J. Chem. Educ.
- J. Chem. Eng. Data
- J. Chem. Inf. Model.
- J. Chem. Phys.
- J. Chem. Theory Comput.
- J. Chromatogr. A
- J. Chromatogr. B
- J. Clin. Invest.
- J. Clin. Oncol.
- J. Comput. Chem.
- J. Comput. Phys.
- J. Control. Release
- J. Cryst. Growth
- J. Electrochem. Soc.
- J. Eur. Ceram. Soc.
- J. Exp. Med.
- J. Fluid Mech.
- J. Fluorine Chem.
- J. Funct. Foods
- J. Hazard. Mater.
- J. Hepatol.
- J. Mater. Chem. A
- J. Mater. Chem. B
- J. Mater. Chem. C
- J. Med. Chem.
- J. Membr. Sci.
- J. Nat. Gas Sci. Eng.
- J. Nat. Prod.
- J. Natl. Cancer Inst.
- J. Org. Chem.
- J. Photochem. Photobiol. C Photochem. Rev.
- J. Phys. Chem. A
- J. Phys. Chem. B
- J. Phys. Chem. C
- J. Phys. Chem. Lett.
- J. Pineal. Res.
- J. Power Sources
- J. Proteome Res.
- J. Virol.
- JACC Cardiovasc. Imag.
- JAMA Intern. Med.
- JAMA Neurol.
- JAMA Oncol.
- JAMA Pediatr.
- JAMA Psychiatry
- Macromol. Rapid Commun.
- Mass Spectrom. Rev.
- Mater. Chem. Front.
- Mater. Des.
- Mater. Horiz.
- Mater. Sci. Eng. A
- Mater. Sci. Eng. R Rep.
- Mater. Today
- Meat Sci.
- Med. Chem. Commun.
- Med. Res. Rev.
- Microbiol. Mol. Biol. Rev.
- Microchim. Acta
- Mol. Biosyst.
- Mol. Cancer Ther.
- Mol. Catal.
- Mol. Cell
- Mol. Pharmaceutics
- Mol. Psychiatry
- Mol. Syst. Des. Eng.