Interregional carbon flows of China Appl. Energy (IF 7.182) Pub Date : 2018-01-12 Cuncun Duan, Bin Chen, Kuishuang Feng, Zhu Liu, Tasawar Hayat, Ahmed Alsaedi, Bashir Ahmad
In this paper, multi-regional input–output analysis (MRIO) and ecological network analysis (ENA) are combined to assess carbon flows within China and identify key regions and sectors in the context of spatial heterogeneity for effective carbon mitigation. An interregional carbon network model is established by articulating the directions and magnitudes of carbon flows based on MRIO. ENA is then used to unveil indirect carbon flows and mutual relationships among regions. The results show that the northwest is the largest controller for most regions in China. Most carbon emissions in the rest of China are induced by the east’s final demand and substantial consumption. In addition, at sectoral level, the control and dependence abilities vary by region in China. This study provides an integrated framework to investigate interregional carbon emission structure, identify efficient pathways for coordinated emission mitigation, and reduce global carbon inequality across regions.
A Geodesign method for managing a closed-loop urban system through algae cultivation Appl. Energy (IF 7.182) Pub Date : 2018-01-12 Perry Pei-Ju Yang, Steven Jige Quan, Daniel Castro-Lacouture, Ben J. Stuart
This paper discusses how a Geodesign method facilitates a process of managing a closed-loop urban system through algae cultivation by turning urban waste streams into renewable energy. The method informs six stages of processes for designing an algae-powered urban system: objective model, representational model, performance model, scenario model, evaluation model and decision model. Three sites in Atlanta were tested to explore to what extent the system performance can move toward a “net-zero” urban environment. The results show that the three neighborhoods have the highest potential to reach 12–18% of the total building energy demand met by the energy production in the algae system in the extreme scenario. Other renewable energy resources need to be added and more efforts of building energy reduction need to be made to move the performance of urban system closer to “net-zero”.
Finite sum based thermoeconomic and sustainable analyses of the small scale LNG cold utilized power generation systems ☆ Appl. Energy (IF 7.182) Pub Date : 2018-01-05 Baris Burak Kanbur, Liming Xiang, Swapnil Dubey, Fook Hoong Choo, Fei Duan
Liquefied natural gas (LNG) cold utilized micro cogeneration systems are the feasible and sustainable solutions for the inland regions where the large scale LNG cold utilization or the conventional pipeline systems are not economically applicable. The present study investigates the single and combined systems in three LNG importing countries by using the finite sum modeling which is firstly performed for the LNG cold utilization systems with the sustainability index assessment. To generate electricity, the microturbine is integrated with an LNG vaporizer and an LNG pump in the single system while the combined system includes a Stirling engine and a thermal energy storage tank in addition to the microturbine and LNG cold utilization components. Thermodynamic, environmental, thermoeconomic and sustainable analyses are performed to obtain their yearly performance maps that are extremely difficult to obtain with the conventional dynamic modeling. The yearly performance trends of the net power generation rate, exergetic efficiency, and the levelized product cost are found similar to each other while they have contrary yearly trends with the overall energetic efficiency and the Stirling engine performance parameters. The net generated power rate, the Stirling engine performance parameters, the levelized product cost, the emission rate and the sustainability index have significant changes which must be considered for the real applications while the other factors are able to be neglected during the dynamic analysis since their fluctuations are small. The most convenient time are found at 08:00 am in all the case countries though the corresponding months change for each case country. The combined system is found more feasible than the single system from the thermodynamic, thermoeconomic, environmental and sustainable viewpoints.
A multi-objective MILP model for the design and operation of future integrated multi-vector energy networks capturing detailed spatio-temporal dependencies Appl. Energy (IF 7.182) Pub Date : 2017-12-29 Sheila Samsatli, Nouri J. Samsatli
Energy-efficient control of electric vehicles based on linear quadratic regulator and phase plane analysis Appl. Energy (IF 7.182) Pub Date : 2017-12-28 Zhongliang Han, Nan Xu, Hong Chen, Yanjun Huang, Bin Zhao
Electric vehicles (EVs) have advantages in the aspect of energy, environment, and vehicle motion control. However, it is still not competitive enough to conventional vehicles because of the limited driving range and the high cost of the battery. Therefore, the energy efficiency is of the most importance for the control of EVs. Existing range extension control systems on EVs mostly focus on longitudinal front and rear axle torque distribution or lower-level yaw moment allocation. It is a challenge to maintain the vehicle’s stability at the cost of the minimum energy when the vehicle is cornering, this paper proposes a phase plane-based controller for EVs, focusing on the energy-efficient upper-level yaw stability control. The phase plane-based controller is automatically adaptive to driving situations through the optimization of weights on the performance of the vehicle handling and stability. Firstly, a friction constrained desired model is presented for the model-following control. Secondly, β - β ̇ phase plane analysis is conducted based on a nonlinear vehicle model to graphically identify the vehicle lateral stability in real time. The self-stable region can be determined by the vehicle velocity, the road friction coefficient, and the wheel steering angle. Then, energy optimizing (i.e. gain scheduling of LQR controllers) rules are designed based on the vehicle lateral stability identification. Finally, the proposed phase plane-based controller is evaluated and the yaw moment costs are compared to other controllers’ in a realistic 7-DOF vehicle model. The results demonstrate that the proposed controller presents an excellent yaw stability control capability, and compared to the widely used Shino’s controller, the proposed controller reduces the energy consumption by 9.68% and 3% at the ‘light’ and ‘severe’ maneuver, respectively.
The influence of complicated fluid-rock interactions on the geothermal exploitation in the CO2 plume geothermal system ☆ Appl. Energy (IF 7.182) Pub Date : 2017-12-06 Guodong Cui, Shaoran Ren, Zhenhua Rui, Justin Ezekiel, Liang Zhang, Hongsheng Wang
The ubiquitous natural sedimentary reservoirs and their high permeability have made the CO2 plume geothermal system increasingly attractive. However, the complicated fluid-rock interactions during the geothermal exploitation can cause severe reservoir damage, constraining the excellent heat mining performance of the CO2 and decreasing the possible applications of the CO2 plume geothermal system. In order to analyze and solve this energy issue affecting the geothermal exploitation, in this study, a comprehensive numerical simulation model was established, which can consider formation water evaporation, salt precipitation, CO2-water-rock geochemical reactions, and the changes in reservoir porosity and permeability in the CO2 plume geothermal (CPG) system. Using this model, the geochemical reactions and salt precipitation and their effects on the geothermal exploitation were analyzed, and some measures were proposed to reduce the influence of fluid-rock interactions on the heat mining rate. The simulation results show that the gravity and the negative gas-liquid capillary pressure gradient induced by evaporation can cause the formation water to flow toward the injector. The back flow of the formation water results in salt precipitation accumulation in the injection well region, which can cause severe reservoir damage and consequent reductions to the heat mining rate. The CO2-water-rock geochemical reactions could result in the dissolution of certain minerals and precipitation of others, but its minimal influence on the heat mining rate can be ignored. However, salt precipitation can affect the geochemical reactions by influencing the CO2 flow and distribution, which can reduce the heat mining rate up to 2/5 of the original. Sensitivity studies show that the reservoir condition can affect the salt precipitation and heat mining rate, so a sedimentary reservoir with high temperature, high porosity and permeability, and low salinity should be selected for CPG application, with an appropriately high injection-production pressure difference. The injection of low salinity water before CO2 injection and the combined injection of CO2 and water vapor can be applied to reduce the salt precipitation and increase the heat mining rate in the CPG system.
NOX reduction in a 40 t/h biomass fired grate boiler using internal flue gas recirculation technology ☆ Appl. Energy (IF 7.182) Pub Date : 2017-12-06 Yaojie Tu, Anqi Zhou, Mingchen Xu, Wenming Yang, Keng Boon Siah, Prabakaran Subbaiah
A decoupled numerical modelling method is developed in this study to simulate the whole combustion process of biomass in a grate firing boiler, which includes the thermochemical conversion of biomass in the fuel-bed and gaseous combustion in the freeboard. With the aid of this modelling method, the objective of this study is to explore the NOX reduction mechanism as well as to investigate the potential of internal flue gas recirculation technology (IFGRT) on the combustion process and emissions formation in a 40 t/h biomass-fired grate boiler. Computational fluid dynamics (CFD) modelling results show that IFGRT can be realized in the grate boiler by establishing intense flue gas recirculation within the boiler, which allows for lower peak combustion temperatures and smaller flame kernel sizes, while improving the overall average gas temperature. Consequently, NOX emission can be reduced mainly via the thermal formation route in comparison with the conventional combustion case. More specifically, the parallel over-fired air (OFA) burner configuration is suggested for implementation to produce even lower NOX emission compared to the staggered OFA burner configuration. To further understand the reasons behind the NOX reduction, NOX formation and destruction mechanisms are also examined through reduced order modelling (ROM) with the help of detailed reaction chemistry. It is revealed that flue gas recirculation inhibits NOX formation from thermal, NNH and N2O routes. Although NOX destruction rate through reburning is suppressed, the net NOX production rate is found to be decreased under the condition of IFGRT. Moreover, as the flue gas recirculation ratio increases, final NOX emission shows a decreasing trend.
Multiregional input–output and ecological network analyses for regional energy–water nexus within China Appl. Energy (IF 7.182) Pub Date : 2017-12-01 Saige Wang, Yating Liu, Bin Chen
Water use and energy consumption are strongly interwoven in networks of economic activity. Tracking energy and water flows among regions and quantifying their interdependencies are fundamental for synergetic management of these two essential resources. In this work, we built an accounting framework to assess the performance of energy–water nexus networks within China. Water consumption for various energy types and energy consumption in all stages of water use were inventoried for different regions. Then, direct and indirect energy and water embodied in monetary flows among regions were calculated via multiregional input–output analysis to build an embodied energy network, embodied water-related energy network, embodied water network, and embodied energy-related water network. Finally, a set of ecological network analysis indices were used to analyze the properties and connection of these four networks. The results show disparities of water-related energy/total energy ratios among regions and the nexus impact on regional energy and water systems. Beijing and Shanghai have large ratios of final demand consumption because of their large population and rapid economic development. Embodied water and energy consumption in capital stock in Hainan, Ningxia represented 15% of total consumption by booming investments. We found that embodied water was transferred from western to eastern regions and northern to southern regions. Major energy export–import pairs were Xinjiang–Shanghai, Hebei–Beijing, Xinjiang–Zhejiang, and Jiangsu–Shanghai. Regions with controller/relier roles in the network were identified in the context of nexus impact, for which Beijing and Shanghai have a strong control and dependence relationship with other regions. The proposed nexus network approach may help bridge the gap between nexus modeling and regional resource management.
Methodology for optimization of component reliability of heat supply systems Appl. Energy (IF 7.182) Pub Date : 2017-11-24 Ivan Postnikov, Valery Stennikov, Ekaterina Mednikova, Andrey Penkovskii
The paper suggests a methodology to determine optimal reliability parameters (failure and restoration rates) of heat supply system components, which provide the required level of heat supply reliability. The methodological approach consists in the economically rational distribution of the total effect of reliability improvement among the system components, which is calculated using the average reliability parameters of the components. This task, along with the task to ensure structural reliability, is one of the key reliability tasks within a more general problem of optimal synthesis of heat supply systems and is urgent for both the systems under design and the existing insufficiently reliable systems. The methodology of solving the stated problem is based on the methods of the theory of hydraulic circuits, nodal reliability indices of heat supply, models of Markov random process and general regularities of cogeneration and heat transfer processes. The methodology also takes into account changes in thermal loads during the heating period and time redundancy of consumers related to heat storage. The results of the practical research based on the calculation experiment that confirms the viability of the presented methodology for the schemes of real heat supply systems are presented. The advantages of the proposed methodology compared to the existing approaches to solving this problem consist in joint optimization of the component reliability of heat source and heat network schemes, integration of procedures for the reduction in failure rates and the improvement in restoration rates of the components in one calculation pattern of search for the optimal system reliability, the absence of the need to conduct iterative calculations when using the average reliability parameters of components, considering the required levels of reliability indices.
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 H2O H 2 O 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 H2O H 2 O 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 350 mA / cm 2 ), 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 350 mA / cm 2 ), 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 (R2 R 2 ) of 0.6 0.6 .
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.
Some contents have been Reproduced by permission of The Royal Society of Chemistry.
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