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  • Bi-level optimal low-carbon economic dispatch for an industrial park with consideration of multi-energy price incentives
    Appl. Energy (IF 8.426) Pub Date : 2020-01-25
    Haifei Gu; Yang Li; Jie Yu; Chen Wu; Tianli Song; Jinzhou Xu

    Under the retail electricity market reform and the development of demand-side integrated energy systems in China, the Integrated Energy Service Agency (IESA) is responsible for purchasing energy from the external market and supplying it to multi-energy users (MEUs). However, with the increase in the types of MEUs, the IESA has gained more sales options. How to meet the required MEU participation level in the integrated demand response (IDR) plan to ensure that the IESA sets the optimal integrated energy price is an urgent problem. In this paper, a bi-level optimal low-carbon economic dispatch model for an industrial park is proposed considering multi-energy price incentives; at the upper level, the model takes the optimal net income of the IESA as the target, and the carbon emission constraints of the real-time unit integrated energy supply are considered, so that the IESA can reasonably dispatch a comprehensive energy supply, optimize the operation of energy conversion equipment, and set reasonable energy selling prices based on energy prices in the external market. At the lower level, the model takes the minimum integrated energy cost to MEUs as the goal. MEUs take the initiative to obtain retail energy price signals, formulate optimal multi-energy use strategies, and actively participate in the IDR plan. At the same time, coordination between the upper and lower levels helps to optimize the price of the energy sold and the power used by the IDR and is therefore used to achieve the overall environmental and economic requirements of the industrial park. The prime dual path following the interior point method is used to solve the nonlinear, multidimensional, and double-iterative optimization model, and three typical examples are used to illustrate that the model and method can improve the net income of the IESA, ensure the economic and environmental protection of the cooperative multi-energy operation, and encourage MEUs to actively participate in the IDR plan.

    更新日期:2020-01-26
  • Development of a framework for sequential Bayesian design of experiments: Application to a pilot-scale solvent-based CO2 capture process
    Appl. Energy (IF 8.426) Pub Date : 2020-01-25
    Joshua C. Morgan; Anderson Soares Chinen; Christine Anderson-Cook; Charles Tong; John Carroll; Chiranjib Saha; Benjamin Omell; Debangsu Bhattacharyya; Michael Matuszewski; K. Sham Bhat; David C. Miller

    In this paper, a methodology is developed for sequential design of experiments (SDoE) for process systems and applied to a solvent-based CO2 capture system. In this approach, the prior knowledge of the system is used to prioritize process data collection at specific operating conditions. These data are then incorporated into a Bayesian inference methodology for updating a stochastic model by refining estimations of its underlying parameters, and the updated model is then used to generate the next set of test runs. Thus, the new knowledge obtained from the data is used to guide subsequent iterations of the experimental runs, ensuring that the overall data collection is maximally informative given that most experimental campaigns, especially at pilot or higher-scale plants, are costly, time-consuming, and resource-limited. The test run objective for this work was to minimize the maximum model prediction uncertainty for key output variables, but the methodology is generic and can be readily applied to other test run objectives. This methodology is applied to an aqueous monoethanolamine (MEA) pilot plant campaign at the National Carbon Capture Center (NCCC) in Wilsonville, Alabama, USA. The SDoE framework was utilized for two iterations, while collecting 18 sets of data representing different process conditions, and this resulted in an overall average reduction in uncertainty of approximately 50% in the prediction of CO2 capture percentage. Moreover, 11 additional data sets were obtained with variation of absorber packing height for further model validation. This work shows the capability of the SDoE framework to maximize learning given limited resources, allowing for the reduction of model uncertainty, which is of great importance for many applications including reduction of technical risk associated with scale-up and economic analysis.

    更新日期:2020-01-26
  • Are all jobs created equal? Regional employment impacts of a U.S. carbon tax
    Appl. Energy (IF 8.426) Pub Date : 2020-01-25
    Marilyn A. Brown; Yufei Li; Anmol Soni

    While the environmental benefits of carbon taxes are well documented, their employment impacts are not. We simulate an escalating $25/tCO2 tax on the U.S. electricity system and estimate the resulting employment effects using a computable general equilibrium model. Meta-modeling of the results reveals how carbon taxes influence costs, prices, fuel shares and jobs. Overall, we estimate that the carbon tax would increase U.S. employment – e.g., by 511,000 jobs in 2030. Regional heterogeneities are explained, in part, by the path dependency of electricity portfolios and by regional resource variations. The carbon tax would motivate significant CO2 emission reductions, as well as utility bill increases that could on average be offset by carbon tax dividends. The possibility of inter-regional wealth transfers is highlighted, underscoring the importance of revenue recycling and other policy features that promote inclusive benefits.

    更新日期:2020-01-26
  • Enhancing the efficiency of kW-class vanadium redox flow batteries by flow factor modulation: An experimental method
    Appl. Energy (IF 8.426) Pub Date : 2020-01-24
    Massimo Guarnieri; Andrea Trovò; Francesco Picano
    更新日期:2020-01-24
  • 更新日期:2020-01-24
  • An integrated assessment system for shale gas resources associated with graptolites and its application
    Appl. Energy (IF 8.426) Pub Date : 2020-01-24
    Jianming Gong; Zhen Qiu; Caineng Zou; Hongyan Wang; Zhensheng Shi

    Shale gas exploration or development has been carried out in many countries, and gas shales have become one of the major sources of future natural gas production worldwide. However, many differences of gas shales in China with those in other regions make shale gas development in China exceptionally challenging. Fortunately, the Wufeng-Longmaxi gas shales in China contain abundant graptolites, providing a potential method for evaluating the quality of these gas shale reservoirs in South China. Numerous exploration studies have shown that the shale gas sweet-spot intervals in the Wufeng-Longmaxi Shale coincide with graptolite biozones WF2-LM5, providing new insight for evaluating shale gas sweet-spot intervals. This paper, for the first time, proposes a new integrated method using graptolite zones to identify shale gas sweet-spot intervals. Once the sweet-spot interval of shale gas is determined quickly by using this method in an explored block, it can provide an important reference for well design and hydraulically fracturing treatments within short time, significantly enhancing the efficiency of shale gas exploration. More importantly, this new integrated assessment system can be utilized to quickly judge the potential of shale gas development for new shale gas blocks or poorly explored blocks.

    更新日期:2020-01-24
  • Conditions for a cost-effective application of smart thermostat systems in residential buildings
    Appl. Energy (IF 8.426) Pub Date : 2020-01-23
    Dominik Schäuble; Adela Marian; Lorenzo Cremonese

    High investment costs are a key impediment to the energetic refurbishment of residential buildings in Germany. A versatile consumer market for smart thermostat systems suggests that they might constitute a low-investment alternative that is also accessible for tenants. Here, we assess the cost-effectiveness of smart thermostat systems under different conditions and in comparison with other mitigation measures. A dynamic investment model is set up and applied to two typical home types, an average single-family house and an average apartment, built between 1949 and 1978. The impact of variables such as relative savings, building efficiency standard, investment cost, and heating fuel price on CO2 mitigation costs and payback times is investigated using sensitivity analyses. Smart thermostat systems are cost-effective for the two home types if relative savings of at least 5.7% (single-family house) and 7.7% (apartment) are achieved. Both CO2 mitigation costs and payback times strongly decrease with increasing relative savings for values below 10%. Similarly, the level of savings needed to achieve cost-effectiveness strongly increases with increasing building efficiency for values below 100 kWh/m2a. We demonstrate that smart thermostat systems can be a low-investment measure to cost-effectively reduce CO2 emissions and energy consumption in the residential building sector. They should be used primarily in buildings with a medium to low efficiency standard, where energetic refurbishment is unlikely in the coming years. To assess the economic mitigation potential of smart thermostat systems, broad and granular empirical data on realized heating energy savings is urgently needed.

    更新日期:2020-01-23
  • Sediment deformation and strain evaluation during methane hydrate dissociation in a novel experimental apparatus
    Appl. Energy (IF 8.426) Pub Date : 2020-01-22
    Yi Wang; Xuan Kou; Jing-Chun Feng; Xiao-Sen Li; Yu Zhang

    Natural gas hydrate is an efficient alternative future energy source because huge reserves of methane gas are caged in hydrate-bearing sediments. The research on the deformation of sediments during hydrate dissociation is important for safe hydrate production. In this work, a novel experimental apparatus was designed and built to investigate sediment deformation and strain evaluation during methane hydrate dissociation by depressurization. Experimental results are compared for methane hydrate dissociation for various hydrate saturations, porosities, and particle sizes of sediments. Experimental results illustrate that gas hydrate dissociation by depressurization experienced three main stages. The phenomenon secondary hydrate formation was found during hydrate dissociation by depressurization, which leads to the decrease of sediment permeability. The strain of the sediment is proportional to the volume of methane gas production. Higher hydrate saturation leads to larger sediment deformation by hydrate decomposition. Higher sediment porosity leads to looser sediment particles and larger sediment deformation during hydrate dissociation by depressurization. Larger sediment particle sizes lead to smaller interface areas between hydrate and sediment particles, and larger sediment deformation during hydrate dissociation by depressurization.

    更新日期:2020-01-23
  • Dynamic measurement of HCCI combustion with self-learning of experimental space limitations
    Appl. Energy (IF 8.426) Pub Date : 2020-01-21
    Maximilian Wick; Julian Bedei; Jakob Andert; Bastian Lehrheuer; Stefan Pischinger; Eugen Nuss

    Homogeneous Charge Compression Ignition offers a great potential for increasing the efficiency of combustion engines while simultaneously reducing nitrogen oxide raw emissions. However, the broad application has not yet been realized for production engines, mainly owing to low combustion stability at the edges of the operating range and high sensitivity to changing boundary conditions. Owing to strong cycle-to-cycle coupling by negative valve overlap, the cylinder state of the last combustion has an enormous influence on the subsequent combustion. Therefore, the condition of the previous combustion must be taken into account to control the following combustion event. For this purpose, the interactions between feedback variables and cycle individual control interventions need to be measured in a wide operating range. Against this backdrop, a new measurement methodology is presented in this article, which sets up the transient limitations for Homogeneous Charge Compression Ignition combustion, while maintaining the limits of stability, maximum pressure gradient, and other factors automatically. Hence, an algorithm has been developed that sets the manipulated variables on a cyclic basis, dependent on the previous cycle in several dimensions. The new algorithm was then used to gain dynamic measurement data that were used to train artificial neural networks. It is demonstrated that the models are able to predict misfires under certain conditions. Additionally, a feasibility study regarding the usability of the newly gained models was performed based on a data-driven control algorithm, which was carried out and validated on a single-cylinder test engine.

    更新日期:2020-01-22
  • Modeling of syngas biomethanation and catabolic route control in mesophilic and thermophilic mixed microbial consortia
    Appl. Energy (IF 8.426) Pub Date : 2020-01-21
    Antonio Grimalt-Alemany; Konstantinos Asimakopoulos; Ioannis V. Skiadas; Hariklia N. Gavala

    The syngas biomethanation process is a promising bioconversion route due to its high versatility, as it could be applied as a stand-alone technology, coupled to gasification plants, and integrated in anaerobic digestion or bioelectrochemical conversion systems. The biomethanation of syngas typically takes place through a rather complex network of interspecies metabolic interactions, which may vary significantly depending on the operating conditions applied and the diversity of microbial groups present. Despite there are several benefits derived from using microbial consortia, these also present challenges associated with limited process control and low product selectivity. To address the latter, the syngas biomethanation process carried out by mesophilic and thermophilic microbial consortia was modelled with the ultimate goal of studying possible catabolic route control strategies through the modulation of key operating parameters. The results showed that the thermophilic microbial consortium presented much higher apparent specific methane productivity (18.8 mmol/g VSS/d) than the mesophilic (4.6 mmol/g VSS/d) at an initial PCO of 0.2 atm, and that the difference increased with increasing initial PCO. This difference in productivity was found to derive from the catabolic routes used rather than the kinetic parameters of each microbial consortium. Additionally, the thermodynamic considerations included in the models revealed the possibility of controlling the catabolic routes used by each consortium through the modulation of the mass transfer and PCO2. Our results strongly indicate that modulating the PCO2 is a promising operational strategy for boosting the product selectivity towards CH4, the productivity of the system and the biomethane quality simultaneously.

    更新日期:2020-01-22
  • On the suitability of offshore wind energy resource in the United States of America for the 21st century
    Appl. Energy (IF 8.426) Pub Date : 2020-01-21
    X. Costoya; M. deCastro; D. Carvalho; M. Gómez-Gesteira
    更新日期:2020-01-22
  • A classification system for global wave energy resources based on multivariate clustering
    Appl. Energy (IF 8.426) Pub Date : 2020-01-21
    Iain Fairley; Matthew Lewis; Bryson Robertson; Mark Hemer; Ian Masters; Jose Horrillo-Caraballo; Harshinie Karunarathna; Dominic E. Reeve

    Better understanding of the global wave climate is required to inform wave energy device design and large-scale deployment. Spatial variability in the global wave climate is analysed here to provide a range of characteristic design wave climates. K-means clustering was used to split the global wave resource into 6 classes in a device agnostic, data-driven method using data from the ECMWF ERA5 reanalysis product. Classification using two sets of input data were considered: a simple set (based on significant wave height and peak wave period) and a comprehensive set including a wide range of relevant wave climate parameters. Both classifications gave resource classes with similar characteristics; 55% of tested locations were assigned to the same class. Two classes were low energy, found in enclosed seas and sheltered regions. Two classes were moderate wave energy classes; one swell dominated and the other in areas with wave action often generated by more local storms. Of the two higher energy classes; one was more often found in the northern hemisphere and the other, most energetic, predominantly on the tips of continents in the southern hemisphere. These classes match existing regional understanding of resource. Consideration of publicly available device power matrices showed good performance was primarily realised for the two highest energy resource classes (25–30% of potential deployment locations); it is suggested that effort should focus on optimising devices for additional resource classes. The authors hypothesise that the low-risk, low variability, swell dominated moderate wave energy class would be most suitable for future exploitation.

    更新日期:2020-01-22
  • Thermal desalination potential with parabolic trough collectors and geothermal energy in the Spanish southeast
    Appl. Energy (IF 8.426) Pub Date : 2020-01-21
    Antonio Colmenar-Santos; Elisabet Palomo-Torrejón; Francisco Mur-Pérez; Enrique Rosales-Asensio
    更新日期:2020-01-22
  • A model for evaluating the configuration and dispatch of PV plus battery power plants
    Appl. Energy (IF 8.426) Pub Date : 2020-01-21
    Nicholas DiOrio; Paul Denholm; William B. Hobbs

    An open-source model was developed to optimize energy storage operation for photovoltaic- (PV-) plus-battery systems with AC-coupled and DC-coupled configurations. It includes the ability to use forecast energy prices to optimize battery charge and discharge on a rolling time horizon. The model allows for exploration of different configurations, including capital costs, inverter performance, dispatch flexibility, and capturing otherwise clipped energy for the DC-coupled system. The model can run 20 full years of hourly data in approximately two seconds, allowing comparison of a large number of configurations. We applied the model in a test case demonstrating reduced inverter clipping for DC-coupled systems and yielded slightly higher overall value than AC-coupled systems, with an approximately 2 percent increase in internal rate of return or benefit/cost ratio. Our results show that at current estimated prices for lithium-ion battery systems, large-scale PV-plus-battery plants are economically viable under the right conditions, with the configuration playing a role in system flexibility and performance. This model provides the ability for project developers, industry professionals, and researchers to use readily available software to quickly evaluate and design these systems.

    更新日期:2020-01-22
  • Solar Salt – Pushing an old material for energy storage to a new limit
    Appl. Energy (IF 8.426) Pub Date : 2020-01-22
    Alexander Bonk; Markus Braun; Veronika A. Sötz; Thomas Bauer
    更新日期:2020-01-22
  • Assessing the impact of injector included angle and piston geometry on thermally stratified compression ignition with wet ethanol
    Appl. Energy (IF 8.426) Pub Date : 2020-01-22
    Brian Gainey; James Gohn; Deivanayagam Hariharan; Mozhgan Rahimi-Boldaji; Benjamin Lawler

    Recent results have concluded that the efficacy of compression stroke injections in enhancing natural thermal stratification are dependent on the injector’s included angle. Therefore, there is a need to further understand how different hardware affects the efficacy of thermally stratified compression ignition. In this study, three injector included angles are considered: 150°, 118°, and 60°. Compression stroke injection timing sweeps are performed with these three injectors using two distinct piston geometries: a re-entrant bowl piston geometry found in a production, light-duty diesel engine, and a custom-made open, shallow bowl piston geometry, designed to reduce surface-to-volume ratio. Using an equivalence ratio of 0.5 and a split fraction of 80%, it was found that, with the re-entrant bowl piston geometry, the 150° injector displayed high controllability over the burn duration and was able to elongate the burn duration by a factor of 1.8×. The 118° injector displayed slight controllability over the burn duration, while the 60° injector displayed no controllability. With the open bowl piston geometry, the 150° maintained high controllability over the burn duration, albeit with less efficacy. The 60° injector still had no controllability and now the 118° injector had no controllability. The low surface-to-volume ratio of the shallow bowl piston led to less natural thermal stratification than the re-entrant bowl piston geometry, which impacted the compression stroke injection’s ability to control the burn rate. Therefore, the hardware setup that achieves the highest efficacy is a re-entrant bowl-like piston geometry with a wide spray angle injector.

    更新日期:2020-01-22
  • A pixel counting based method for designing shading devices in buildings considering energy efficiency, daylight use and fading protection
    Appl. Energy (IF 8.426) Pub Date : 2020-01-17
    Ana Paula de Almeida Rocha; Gilberto Reynoso-Meza; Ricardo C.L.F. Oliveira; Nathan Mendes

    Multi-criteria design techniques applied to the analysis of shading devices of buildings have arisen as useful tools for architects. Even though several techniques have been applied to shading devices with simple geometries, they usually require numerous simulations to suitably complete the analysis, making the optimization process time-consuming. Since shading devices should prevent damage to furnishings and materials, performance indicators may not be related exclusively to thermal comfort, energy consumption and daylight performance, but also to other important criteria, such as fading protection. To overcome these limitations, this study aims to present a multi-criteria method for the design of shading devices, including fading protection as an evaluation criterion, regardless of geometry complexity. The method is applied to perforated shading devices of a room office, considering as the design objectives the energy savings, daylight availability on the work plane and solar beam incidence on interior surfaces. As a novelty, a more practical approach is proposed based on two main steps: search process, for obtaining a set of non-dominated solutions, and physical programming method, in which the solutions are ranked according to the preferences of decision makers. Besides, the solar beam incidence on interior surfaces is evaluated by using a pixel counting based method, which was emerged as a powerful algorithm due its capacity to simulate any geometry with accuracy and low computational cost. The results have shown that the proposed method is an effective process in designing of the optimal shading devices to reduce energy consumption, and improve the daylight use and the fading protection, regardless of the geometry complexity.

    更新日期:2020-01-21
  • Should I Stay Or Should I Go? The importance of electricity rate design for household defection from the power grid
    Appl. Energy (IF 8.426) Pub Date : 2020-01-18
    Will Gorman; Stephen Jarvis; Duncan Callaway

    The cost declines of solar and storage technologies have led to concerns about customers disconnecting from utility service and self-supplying electricity. Prior research addressing this issue focused on average electricity tariffs, solar profiles, and demand without considering detailed customer heterogeneity. This paper fills the gap by analyzing how electricity tariffs that shift cost recovery away from variable charges towards fixed charges influence a customer’s decision to disconnect from utility service. A linear optimization model is developed to size an off-grid solar/storage system. Technology cost and reliability parameters of the optimization model are then adjusted to calculate a range of off-grid costs. Unique rate structure information for over 2000 utilities in the United States is then used to compare grid costs to off-grid costs. The results show limited ability for solar/storage systems to economically substitute for grid services. However, 1% of households might disconnect from utility service in a scenario that accounts for future off-grid costs and updated tariff designs. We find that 3% of households in the Southwest and California have private economics that favor defection in this scenario, rising to as much as 7% in Hawaii. Grid defection could increase from 1% to 7% of United States households in a slightly reduced reliability scenario. These results indicate that utilities and regulators seeking to limit rooftop solar adoption by lowering variable charges face a significant possibility that the corresponding increase in fixed charges could lead to inefficient grid defection.

    更新日期:2020-01-21
  • A high heat storage capacity form-stable composite phase change material with enhanced flame retardancy
    Appl. Energy (IF 8.426) Pub Date : 2020-01-20
    Yi-Huan Huang; Yi-Xin Cheng; Rui Zhao; Wen-Long Cheng

    A high heat storage capacity form-stable composite phase change material (CPCM) with enhanced flame retardancy that integrated modified glass fibers with form-stable PCM was proposed. The modified glass fibers were wrapped by a composite flame retardant coating. The thermal and flame retardant properties of the CPCM were measured and compared to other CPCM samples. The results of vertical burning test indicated that the glass fibers improved the mechanical properties of the CPCM and prevented it from fracturing during the burning process. The modified glass fibers could further improve the flame retardancy of CPCM, and V-0 burning rating was achieved while the content of paraffin was maintained at 70 wt%, which means the proportion of flame retardants could be reduced. TGA results showed that the modified glass fibers could enhance the thermal stability and retard the degradation process of the CPCM, and the char residue was increased to 15.3%. Thermal cycling results indicated that the CPCM has good thermal reliability. The results of cone calorimeter test indicated that the peak heat release rate (PHRR) of flame retardant form-stable CPCM dropped by 58.8%, and the combustion rate could be greatly slowed down due to the protection of carbon layers formed by modified glass fibers. In addition, the thermal conductivity of CPCMs were greatly enhanced and the CPCM has good thermal reliability.

    更新日期:2020-01-21
  • 更新日期:2020-01-21
  • Mechanically durable thermoelectric power generation module made of Ni-based alloy as a reference for reliable testing
    Appl. Energy (IF 8.426) Pub Date : 2020-01-17
    Raju Chetty; Kazuo Nagase; Makoto Aihara; Priyanka Jood; Hiroyuki Takazawa; Michihiro Ohta; Atsushi Yamamoto
    更新日期:2020-01-21
  • Lignin degradation and detoxification of eucalyptus wastes by on-site manufacturing fungal enzymes to enhance second-generation ethanol yield
    Appl. Energy (IF 8.426) Pub Date : 2020-01-16
    Willian Daniel Hahn Schneider; Roselei Claudete Fontana; Henrique Macedo Baudel; Félix Gonçalves de Siqueira; Jorge Rencoret; Ana Gutiérrez; Laura Isabel de Eugenio; Alicia Prieto; María Jesús Martínez; Ángel T. Martínez; Aldo José Pinheiro Dillon; Marli Camassola
    更新日期:2020-01-17
  • Machine-learning based hybrid demand-side controller for high-rise office buildings with high energy flexibilities
    Appl. Energy (IF 8.426) Pub Date : 2020-01-17
    Yuekuan Zhou; Siqian Zheng

    The accurate demand prediction with high efficiency and advanced demand-side controller are essential for the enhancement of energy flexibility provided by buildings, whereas the current literature fails to present the mechanism on modelling development and demand-side control. This paper aims to deal with the complexity of building demand prediction with supervised machine learning method, including the multiple linear regression, the support vector regression and the backpropagation neural network. The regularization, adding the sum of the weights to the learning function, is utilized to improve the training speed and to solve the overfitting by eliminating the unnecessary connections with small weights. The configuration of the artificial neural network was presented, and sensitivity analysis has been conducted on the learning performance regarding different training times. Energy flexibilities of sophisticated building energy systems (including renewable system, electric and thermal demands and building services systems) were quantitatively characterised with a series of quantifiable indicators. Moreover, several advanced controllers have been developed and contrasted, in regard to the flexibility utilisation of building energy systems. Results showed that, the developed hybrid controller with short-term prediction through the cross-entropy function is more technically competitive than other controllers. With the implementation of the developed hybrid controller, the peak power of the grid importation can be reduced from 500.3 to 195 kW by 61%. This study formulates a data-driven model with an advanced machine learning algorithm for the accurate building demand prediction and a hybrid advanced controller with short-term prediction for the energy management, which are critical for the promotion of energy flexible buildings.

    更新日期:2020-01-17
  • Multi-objective economic dispatch of a microgrid considering electric vehicle and transferable load
    Appl. Energy (IF 8.426) Pub Date : 2020-01-16
    Hui Hou; Mengya Xue; Yan Xu; Zhenfeng Xiao; Xiangtian Deng; Tao Xu; Peng Liu; Rongjian Cui

    In order to investigate the impact of electric vehicles’ charging-discharging behaviour and demand side response resources on the economic operation of photovoltaic grid-connected microgrid system, a multi-objective model of microgrid economic dispatching with electric vehicles, transferable load and other distributed generations (diesel engines and energy storage unit) is proposed in this paper. The model takes the comprehensive operating cost of microgrid, the utilization rate of photovoltaic energy and the power fluctuation between the microgrid and main grid as objectives. Moreover, four different cases of microgrid economic dispatch considering electric vehicles and transferable load are put forward, which are electric vehicles’ orderly charging and discharging and transferable load participating in demand response in Case 1, electric vehicles’ charging randomly and the transferable load participating in demand response in Case 2, electric vehicles orderly charging and discharging and transferable load not participating in demand response in Case 3, electric vehicles’ charging randomly and the transferable load not participating in the demand response in Case 4. Multi-objective Seeker Optimization Algorithm and the method of fuzzy membership function are applied in this study to obtain the optimal results. The simulation analysis shows that the orderly charging-discharging behaviour of electric vehicles and the participation of transferable load can effectively improve the economic costs, efficiency and security of microgrid economic operation.

    更新日期:2020-01-17
  • 更新日期:2020-01-17
  • A concentrating solar power system integrated photovoltaic and mid-temperature solar thermochemical processes
    Appl. Energy (IF 8.426) Pub Date : 2020-01-16
    Wanjun Qu; Xueli Xing; Yali Cao; Taixiu Liu; Hui Hong; Hongguang Jin

    The approach of cascading solar energy utilization provides access to reliable and ample supplies of energy and has thus attracted widespread attention. Currently, the hybridization of a concentrating solar photovoltaic process and a solar thermochemical process is a promising approach. This paper describes and investigates a concentrating solar power system to harvest solar energy. Co-producing photovoltaic electricity and solar thermal fuel is its attractive distinction. The visible spectrum is cast onto concentrating photovoltaics to generate electricity, and the ultraviolet and infrared spectra are used to drive methanol decomposition at approximately 250 °C. A spectral splitting parabolic trough concentrator is developed in which incident solar radiation is first split and then concentrated. Based on the measured optical data of concentrators, photovoltaics and reactor, the solar-to-electricity performance is evaluated in the proposed system. The results show that a satisfied solar-to-electricity efficiency of approximately 31.8% would be realized if monocrystalline silicon photovoltaics is adopted. In comparison to individual systems, the efficiency enhancements of about 15.3% and 6.3% are obtained. The solar-to-electricity efficiency can reach approximately 35.1% by adopting gallium arsenide. Meanwhile, the improved optical performance proves that the approach of first splitting and then concentrating sunlight is feasible and promising. Finally, the results are anticipated to lead to a new approach for improving full-spectrum solar energy utilization and guiding the establishment of a prototype in the near future.

    更新日期:2020-01-17
  • Cycle life test optimization for different Li-ion power battery formulations using a hybrid remaining-useful-life prediction method
    Appl. Energy (IF 8.426) Pub Date : 2020-01-16
    Jian Ma; Shu Xu; Pengchao Shang; Yu ding; Weili Qin; Yujie Cheng; Chen Lu; Yuzhuan Su; Jin Chong; Haizu Jin; Yongshou Lin
    更新日期:2020-01-17
  • Seeking for a climate change mitigation and adaptation nexus: Analysis of a long-term power system expansion
    Appl. Energy (IF 8.426) Pub Date : 2020-01-16
    Kamia Handayani; Tatiana Filatova; Yoram Krozer; Pinto Anugrah

    Reductions in carbon emissions have been a focus of the power sector. However, the sector itself is vulnerable to the impacts of global warming. Extreme weather events and gradual changes in climate variables can affect the reliability, cost, and environmental impacts of the energy supply. This paper analyzed the interplay between CO2 mitigation attempts and adaptations to climate change in the power sector using the Long-range Energy Alternative Planning System (LEAP) model. This paper presented a novel methodology to integrate both CO2 mitigation goals and the impacts of climate change into simulations of a power system expansion. The impacts on electricity supply and demand were quantified, based on historical climate-related impacts revealed during fieldwork and existing literature. The quantified effects, together with climate mitigation targets, were then integrated into the LEAP modeling architecture. The results showed a substantial alteration in technology composition and an increase in installed capacities driven by the joint climate mitigation–adaptation efforts when compared with the scenario without mitigation and adaptation (reference). Furthermore, an increase in CO2 emissions was observed under the mitigation-adaptation scenario compared with the mitigation only scenario, indicating that the power sector’s adaptations for climate change are likely to hinder CO2 mitigation efforts. Therefore, a nexus between mitigation and adaptation should be exploited in the policy development for a low-carbon and climate-resilient power system.

    更新日期:2020-01-17
  • Multiple group search optimization based on decomposition for multi-objective dispatch with electric vehicle and wind power uncertainties
    Appl. Energy (IF 8.426) Pub Date : 2020-01-17
    Xian Zhang; Ka Wing Chan; Huaizhi Wang; Bin Zhou; Guibin Wang; Jing Qiu

    While the number of plug-in electric vehicles (PEVs) increases rapidly, the application potential of PEVs should be accounted in electric power dispatch with several conflicting and competing objectives such as providing vehicle-to-grid (V2G) service or coordinating with wind power. To solve this highly constrained multi-objective optimization problem (MOOP), a multiple group search optimization based on decomposition (MGSO/D) is proposed considering the uncertainties of PEVs and wind power. Specifically, the decomposition approach effectively reduces the computational complexity, and the innovatively incorporated producer-scrounger model effectively improves the diversity and spanning of the Pareto-optimal front (PF). Meanwhile, the estimation error punishment is utilized to take into account of uncertainties. The performance of MGSO/D and the effectiveness of the uncertainty model are investigated on the IEEE 30-bus and 118-bus system with wind farms and PEV aggregators. Simulation results demonstrate the superiority of MGSO/D to solve this MOOP with practical uncertainties by comparing with well-established Pareto heuristic methods.

    更新日期:2020-01-17
  • Multiphysical field measurement and fusion for battery electric-thermal-contour performance analysis
    Appl. Energy (IF 8.426) Pub Date : 2020-01-17
    Xiaoyu Li; Zuguang Zhang; Wenhui Wang; Yong Tian; Dong Li; Jindong Tian

    A battery often exhibits a coupling change in electric, thermal and battery surface topography during operation, especially under abuse conditions. Analysis of the coupling relationship among the multiphysical field parameters is necessary for battery physical structure optimization, failure mechanism analysis and fault prognostics method design. However, there are few multiphysical data acquisition and analysis systems for batteries at present. In this context, a novel battery multiphysical field measurement system with a data fusion model for battery performance analysis is proposed in this paper. The measurement system consists of a three-dimensional scanner, an infrared thermal imager, and an integrated battery charger and discharger. In order to accurately acquire the relationship between the battery surface topography and the battery surface temperature, a data fusion model is proposed, and a joint calibration method is accordingly introduced for the parameter identification of the data fusion model. The results show that the multiphysical measurement system can achieve the position matching deviation of 0.19 mm with high resolution and high data acquisition speed. The functionality of the multiphysical measurement system and the data fusion model are verified by the experimental results of different tests, including a 1 C rate charging/discharging test, a high rate charging/discharging test, and two battery abuse operation tests. It will provide key tools for battery thermal runaway mechanism analysis and battery fault diagnosis method design.

    更新日期:2020-01-17
  • Model development and performance investigation of staggered tube-bundle heat exchanger for seawater source heat pump
    Appl. Energy (IF 8.426) Pub Date : 2020-01-16
    Zhenjing Wu; Shijun You; Huan Zhang; Wandong Zheng

    Seawater heat pump system exhibits merits of reducing building energy consumption, while enhancing the heat transfer of seawater heat exchangers is the key to improve the system performance. The effect of seawater flow behavior on the thermal performance of seawater heat exchanger immersed in oscillating flow is significant but often neglected. An unsteady mathematical model was firstly developed to describe heat transfer of oscillating flow around the staggered tube-bundle heat exchanger and verified by experimental results. Effects of the structural and operational parameters, such as the tube length, heat transfer fluid velocity, wave parameters and sinking depth on the thermal performance were analyzed. It was shown that the thermal efficiency of seawater heat exchanger ascended with the increase of wave amplitude and decrease of the heat exchanger sinking depth. Additionally, the tube length and heat transfer fluid velocity could be reasonably designed to achieve the optimum value between cost and performance. The heat transfer mechanism in seawater side was predominated by forced convection to natural convection with the increasing sinking depth under various wave parameters. The proposed model is favorable to delicately characterize the heat transfer of seawater heat exchanger with the consideration of seawater flow. The results in this paper is helpful to guide the optimization on designing the staggered tube-bundle heat exchanger in oscillating flow and to promote the application of ocean thermal energy.

    更新日期:2020-01-16
  • Evaluating the climate sensitivity of coupled electricity-natural gas demand using a multivariate framework
    Appl. Energy (IF 8.426) Pub Date : 2020-01-16
    Renee Obringer; Sayanti Mukherjee; Roshanak Nateghi

    Projected climate change will significantly influence the shape of the end-use energy demand profiles for space conditioning—leading to a likely increase in cooling needs and a subsequent decrease in heating needs. This shift will put pressure on existing infrastructure and utility companies to meet a demand that was not accounted for in the initial design of the systems. Furthermore, the traditional linear models typically used to predict energy demand focus on isolating either the electricity or natural gas demand, even though the two demands are highly interconnected. This practice often leads to less accurate predictions for both demand profiles. Here, we propose a multivariate, multi-sector (i.e., residential, commercial, industrial) framework to model the climate sensitivity of the coupled electricity and natural gas demand simultaneously, leveraging advanced statistical learning algorithms. Our results indicate that the season-to-date heating and cooling degree-days, as well as the dew point temperature are the key predictors for both the electricity and natural gas demand. We also found that the energy sector is most sensitive to climate during the autumn and spring (intermediate) seasons, followed by the summer and winter seasons. Moreover, the proposed model outperforms a similar univariate model in terms of predictive accuracy, indicating the importance of accounting for the interdependence within the energy sectors. By providing accurate predictions of the electricity and natural gas demand, the proposed framework can help infrastructure planners and operators make informed decisions towards ensuring balanced energy delivery and minimizing supply inadequacy risks under future climate variability and change.

    更新日期:2020-01-16
  • Impact of climatic, technical and economic uncertainties on the optimal design of a coupled fossil-free electricity, heating and cooling system in Europe
    Appl. Energy (IF 8.426) Pub Date : 2020-01-16
    K. Zhu; M. Victoria; G.B. Andresen; M. Greiner

    To limit the global temperature increase to 1.5 °C, fossil-free energy systems will be required eventually. To understand how such systems can be designed, the current state-of-the-art is to apply techno-economical optimisation modelling with high spatial and temporal resolution. This approach relies on a number of climatic, technical and economic predictions that reach multiple decades into the future. In this paper, we investigate how the design of a fossil-free energy system for Europe is affected by changes in these assumptions. In particular, the synergy among renewable generators, power-to-heat converters, storage units, synthetic gas and transmission manage to deliver an affordable net-zero emissions system. We find that levelised cost of energy decreases due to heat savings, but not for global temperature increases. In both cases, heat pumps become less favourable as surplus electricity is more abundant for heating. Demand-side management through buildings’ thermal inertia could shape the heating demand, yet has modest impact on the system configuration. Cost reductions of heat pumps impact resistive heaters substantially, but not the opposite. Cheaper power-to-gas could lower the need for thermal energy storage.

    更新日期:2020-01-16
  • Real-time realization of Dynamic Programming using machine learning methods for IC engine waste heat recovery system power optimization
    Appl. Energy (IF 8.426) Pub Date : 2020-01-16
    Bin Xu; Dhruvang Rathod; Adamu Yebi; Zoran Filipi

    This study aims to present a method for real-time realization of Dynamic Programming algorithm for power optimization in an organic Rankine Cycle waste heat recovery system. Different from existing studies, for the first time machine learning algorithms are utilized to extract the rules from offline Dynamic Programming results for optimal power generation. In addition, for the first time a single state Proper Orthogonal Decomposition and Galerkin Projection based reduced order model is combined with Dynamic Programming for its high accuracy and low computation cost. For a transient driving cycle, Dynamic Programming algorithm is utilized to generate the optimal working fluid pump speed. A total of eleven state-of-art machine learning algorithms are screened to predict this pump speed. Random Forest algorithm is then selected for its best pump speed prediction accuracy. A rule-based method is added to the Random Forest model to improve energy recovery. As one of the main discoveries in this study, in the rule extraction process, the Random Forest model reveals that the time delayed exhaust gas mass flow rate and exhaust temperature improve the rule extraction accuracy. This observation points out the difference between steady state and transient optimization and that the steady state optimization results do not necessarily hold true in transient conditions. Another key observation is that Random Forest – rule-based method retrieves 97.2% of the energy recovered by offline Dynamic Programming in a validation driving cycle. In addition, the inclusion of rule-based method significantly increases the Random Forest model’s energy recovery from 66.5% to 97.2%. This high accuracy means that the machine learning models can be used to extract Dynamic Programming rules for real-time application.

    更新日期:2020-01-16
  • 更新日期:2020-01-16
  • Battery energy storage sizing optimisation for different ownership structures in a peer-to-peer energy sharing community
    Appl. Energy (IF 8.426) Pub Date : 2020-01-14
    Daniel L. Rodrigues; Xianming Ye; Xiaohua Xia; Bing Zhu

    Existing studies have shown the benefits of battery energy storage systems (BESS) inclusion, but do not consider optimal BESS sizing and operation in a peer-to-peer (P2P) energy sharing network under different BESS ownership structures. Under the P2P framework, two different BESS ownership structures, namely the ESP owned structure and the user owned structure are investigated in this study, which are compared to the traditional user owned BESS under the peer-to-grid (P2G) framework. It is found that in campus buildings with a P2P energy sharing network, the user owned BESS exhibits the highest NPV comparing to the other two BESS ownership structures. The ESP owned structure is economically less beneficial, but provided the opportunity for the prosumers to engage in P2P energy sharing and reduce their energy costs without a BESS investment cost.

    更新日期:2020-01-14
  • Day-ahead high-resolution forecasting of natural gas demand and supply in Germany with a hybrid model
    Appl. Energy (IF 8.426) Pub Date : 2020-01-13
    Ying Chen; Xiuqin Xu; Thorsten Koch

    As the natural gas market is moving towards short-term planning, accurate and robust short-term forecasts of the demand and supply of natural gas is of fundamental importance for a stable energy supply, a natural gas control schedule, and transport operation on a daily basis. We propose a hybrid forecast model, Functional AutoRegressive and Convolutional Neural Network model, based on state-of-the-art statistical modeling and artificial neural networks. We conduct short-term forecasting of the hourly natural gas flows of 92 distribution nodes in the German high-pressure gas pipeline network, showing that the proposed model provides nice and stable accuracy for different types of nodes. It outperforms all the alternative models, with an improved relative accuracy up to twofold for plant nodes and up to fourfold for municipal nodes. For the border nodes with rather flat gas flows, it has an accuracy that is comparable to the best performing alternative model.

    更新日期:2020-01-13
  • Statistical investigations of transfer learning-based methodology for short-term building energy predictions
    Appl. Energy (IF 8.426) Pub Date : 2020-01-11
    Cheng Fan; Yongjun Sun; Fu Xiao; Jie Ma; Dasheng Lee; Jiayuan Wang; Yen Chieh Tseng

    The wide availability of massive building operational data has motivated the development of advanced data-driven methods for building energy predictions. Existing data-driven prediction methods are typically customized for individual buildings and their performance are highly influenced by the training data amount and quality. In practice, buildings may only possess limited measurements due to the lack of advanced monitoring systems or data accumulation time. As a result, existing data-driven approaches may not present sufficient values for practical applications. A novel solution can be developed based on transfer learning, which utilizes the knowledge learnt from well-measured buildings to facilitate prediction tasks in other buildings. However, the potentials of transfer learning-based methods for building energy predictions have not been systematically examined. To address this research gap, a transfer learning-based methodology is proposed for 24-h ahead building energy demand predictions. Experiments have been designed to investigate the potentials of transfer learning in different scenarios with different implementation strategies. Statistical assessments have been performed to validate the value of transfer learning in short-term building energy predictions. Compared with standalone models, the transfer learning-based methodology could reduce approximately 15% to 78% of prediction errors. The research outcomes are useful for developing advanced transfer learning-based methods for typical tasks in building energy management. The insights obtained can help the building industry to fully realize the value of existing building data resources and advanced data analytics.

    更新日期:2020-01-13
  • Efficient simulation and auto-calibration of soot particle processes in Diesel engines
    Appl. Energy (IF 8.426) Pub Date : 2020-01-11
    Shaohua Wu; Jethro Akroyd; Sebastian Mosbach; George Brownbridge; Owen Parry; Vivian Page; Wenming Yang; Markus Kraft
    更新日期:2020-01-13
  • A particle-scale reduction model of copper iron manganese oxide with CO for chemical looping combustion
    Appl. Energy (IF 8.426) Pub Date : 2020-01-13
    William Benincosa; Ranjani Siriwardane; Hanjing Tian; Jarrett Riley; James Poston

    Chemical looping combustion is a promising power generation technology that produces sequestration-ready CO2 and heat/power from the combustion of fossil fuels with oxygen provided by an oxygen carrier, or metal oxide, rather than air. Successful implementation of chemical looping combustion depends highly on the choice of oxygen carrier and the development of reaction rate parameters for process design and scale-up of the multi-reactor system. In this work, the reaction profile of a promising trimetallic oxygen carrier, copper iron manganese oxide with CO, a component of coal-derived synthesis gas was characterized using differential scanning calorimetry/thermogravimetric analysis and in-situ X-Ray diffraction. A unique phase formation with reactivities different from that with single metal components and phase changes during the reaction with CO were identified. Three major reactions were identified from the phase changes to use for reaction modelling. A particle-scale reaction model was selected which best described the experimental thermogravimetric analysis data to determine the valuable intrinsic reaction values for reactor design and scale-up. A particle-scale reaction model based on nucleation and growth and 1-D phase boundary behavior exhibited the most accurate correlation with the experimental data and provided intrinsic rate constants which were validated with the conventional mass transport analysis.

    更新日期:2020-01-13
  • Chinese electricity demand and electricity consumption efficiency: Do the structural changes matter?
    Appl. Energy (IF 8.426) Pub Date : 2020-01-13
    Boqiang Lin; Junpeng Zhu

    Electricity plays an important role in economic and social development. China’s coal-based power generation structure emits a large quantity of greenhouse gases. Improving electricity consumption efficiency is an important measure for energy conservation and emission mitigation. With this in mind, this study analyzes the influencing factors of electricity consumption and estimates the electricity consumption efficiency by considering the role of structural changes in China’s 30 provinces over the period 2006–2015. The following findings are obtained: (1) Per capita income, urbanization, population, the proportion of secondary industry, and electricity price have significant impacts on electricity consumption. (2) The optimization of industrial structure is conducive for improving the electricity consumption efficiency and has a significant impact, while the improvement in electrification level will lead to a decrease in efficiency score during the study period. (3) There are significant differences in electricity consumption efficiency with a range from 0.372 to 1.000, depending on different model specifications, regions, and years. This paper sheds new light on the electricity demand and its efficiency. Based on these findings, this paper proposes some targeted policy recommendations.

    更新日期:2020-01-13
  • Wind turbine fault detection based on expanded linguistic terms and rules using non-singleton fuzzy logic
    Appl. Energy (IF 8.426) Pub Date : 2020-01-09
    Fuming Qu; Jinhai Liu; Hongfei Zhu; Bowen Zhou

    Wind power generation efficiency has been negatively affected by wind turbine (WT) faults, which makes fault detection a very important task in WT maintenance. In fault detection studies, fuzzy inference is a commonly-used method. However, it can hardly detect early faults or measure fault severities due to the singleton input and the limited linguistic terms and rules. To solve this problem, this paper proposes a WT fault detection method based on expanded linguistic terms and rules using non-singleton fuzzy logic. Firstly, a generation method of non-singleton fuzzy input is proposed. Using the generated fuzzy inputs, non-singleton fuzzy inference system (FIS) can be applied in WT fault detection. Secondly, a mechanism of expanding linguistic terms and rules is presented, so that the expanded terms and rules can provide more fault information and help to detect early faults. Thirdly, the consequent of FIS is designed by the expanded consequent terms. The defuzzified result, which is defined as the fault factor, can measure fault severities. Finally, four groups of experiments were conducted using the real WT data collected from a wind farm in northern China. Experiment results show that the proposed method is effective in detecting WT faults.

    更新日期:2020-01-11
  • Predicting onset conditions of a free piston Stirling engine
    Appl. Energy (IF 8.426) Pub Date : 2020-01-10
    Shahryar Zare; A.R. Tavakolpour-Saleh

    This research predicts the onset conditions of the free piston Stirling engines using analytical solution of the governing equations and averaging-based Lyapunov technique. In this regard, firstly, the linear dynamic equations of the free piston Stirling engines are extracted. Then, the analytical solutions of the motion equations of the displacer and the power pistons are obtained. Afterwards, these analytical solutions are put into the mean value of the time derivative of Lyapunov function to obtain a convenient relation which provides meaningful information regarding the onset condition of free piston Stirling engines. The mentioned procedure has been verified by the results of multiple numerical simulations and the experimental data (B10-B and SUTech-SR-1). In addition, the results of this method have been validated by the outcomes obtained from the state-space technique. Lastly, by comparing the results of the simulation works and the experiments, it has been confirmed that this method is capable of precisely predicting the onset condition of free piston Stirling engines. Besides, the proposed approach could be used as a powerful tool to predict the behavior of various free piston Stirling engines regardless of whether they meet the onset condition or not.

    更新日期:2020-01-11
  • Experimental study on a double-stage absorption solar thermal storage system with enhanced energy storage density
    Appl. Energy (IF 8.426) Pub Date : 2020-01-09
    J.T. Gao; Z.Y. Xu; R.Z. Wang

    The solar energy utilization has great significance regarding the ever-increasing environment pollution and energy shortage issues. To overcome the instability and intermittency of solar energy, various solar thermal storage technologies have been proposed, and absorption thermal storage is promising for its high energy storage density and long-term storage. However, past researches focused more on working pair and neglected the potential of cycle enhancement. In this paper, an absorption solar thermal storage system with enhanced energy storage density from double-stage output is studied experimentally. A prototype with water-LiBr working pair was designed, manufactured, and tested. The long-term heat storage and short-term heat/cold storage were both tested and evaluated for the double-stage and single-stage working modes. Hot water at 75–85 °C was used as heat source in the charging process to simulate the solar energy from non-concentrated collector, and the prototype was able to provide heating output/cooling output at 50/11 °C in discharging process. Energy storage density of 233 kJ/kg (103 kWh/m3) was achieved for heating output with temperature lift of 30–46 °C, which was 2.51 times higher than that of the single-stage system (93 kJ/kg). The proposed system with large temperature lift, multi-function output, and enhanced energy density has proved its effectiveness in solar thermal storage and conversion, which also provides a feasible option for the large-scale utilization of solar energy.

    更新日期:2020-01-11
  • Robust chance-constrained programming approach for the planning of fast-charging stations in electrified transportation networks
    Appl. Energy (IF 8.426) Pub Date : 2020-01-10
    Bo Zhou; Guo Chen; Qiankun Song; Zhao Yang Dong

    In this paper, a bi-level programming model is established to address the planning issues of fast-charging stations in electrified transportation networks with the consideration of uncertain charging demands. The capacitated flow refueling location model is considered in the upper level to minimize the planning cost of fast-charging stations while the traffic assignment model is utilized in the lower level to determine the spatial and temporal distribution of plug-in electric vehicle flows over entire transportation networks. Such bi-level model unveils the inherent relationship among charging demands, electrical demands and the spatial and temporal distribution of plug-in electric vehicle flows. Robust chance constraints are formulated to characterize the service abilities of fast-charging stations under distribution-free uncertain charging demands, where the ambiguity set is constructed to estimate the potential values of the uncertainties based on their moment-based information, such that the robust chance constraints can exactly be reduced to mixed integer linear constraints. By introducing new variables, the bi-level model is then reformulated into a single-level mixed integer second-order cone programming model so as to be solved via off-the-shelf solvers, which guarantee the optimality of the solution. A case study is conducted to illustrate the effectiveness of the proposed planning model, which reveals three critical factors that significantly impact the planning outcomes.

    更新日期:2020-01-11
  • Hydrogen production from steam gasification of polyethylene using a two-stage gasifier and active carbon
    Appl. Energy (IF 8.426) Pub Date : 2020-01-10
    Yong-Seong Jeong; Ki-Bum Park; Joo-Sik Kim

    Steam gasification of polyethylene was conducted using a two-stage gasifier consisting of a fluidized bed gasifier and a tar-cracking reactor filled with active carbon. The main aim of the work was to produce H2-rich syngas and simultaneously reduce tar. The main reaction variable was the steam-to-fuel ratio. The possibility of gasification without using an electrostatic precipitator was also examined in the study. In addition, the effect of the type of distributor (hook-type and mesh-type distributor) located between the fluidized bed gasifier and tar-cracking reactor on coke formation was investigated. Finally, the possibility of in situ regeneration of active carbon with steam was explored. As a result, the syngas from the two-stage gasifier contained a maximum 66 vol% hydrogen and a minimum 0 mg/Nm3 tar. The syngas produced without using an electrostatic precipitator had similar quality to that obtained with an electrostatic precipitator, providing a positive indication for the implementation of the two-stage gasifier in commercial applications. Additionally, the mesh-type distributor was found to be excellent against coke formation. The in situ regeneration of active carbon with steam significantly recovered the textural properties of the original active carbon, yielding a surface area recovery rate of approximately 63%. A long-term gasification for 4 h with repetitive in situ regeneration of active carbon with steam produced a syngas having 55 vol% H2 on average and toluene as a tar component.

    更新日期:2020-01-11
  • Design and optimization of a hydrogen supply chain using a centralized storage model
    Appl. Energy (IF 8.426) Pub Date : 2020-01-10
    Seung-Kwon Seo; Dong-Yeol Yun; Chul-Jin Lee

    This study involves the construction of a hydrogen supply chain optimization model using a centralized storage model that combines and consolidates flows of hydrogen from different production sites into integrated bulk storage. To supply hydrogen to a fuel cell electric vehicle station, various hydrogen supply pathways and storage configurations for different types of production technologies and transportation modes are considered. In terms of the topological structure, the centralized storage model requires fewer storage areas than the decentralized storage model. The results show that a hydrogen supply chain with a centralized storage structure advances the phase transition of central hydrogen production plants and reduces the total annual cost of the entire supply chain. The optimal hydrogen pathway is on-site steam methane reforming production in the early markets for fuel-cell electric vehicles. However, in matured markets, hydrogen is liquefied in central production plants and stored in bulk storages equipped with vaporizers. Then, the hydrogen is distributed from the central storage areas to local refueling stations via pipelines. The role of central storage areas is predicted to become important as market shares of fuel cell electric vehicle reach 15–30%; in other words, 0.28–0.56 million tonne/year of hydrogen will be demanded in 20 cities of South Korea.

    更新日期:2020-01-11
  • Understanding the impact of non-synchronous wind and solar generation on grid stability and identifying mitigation pathways
    Appl. Energy (IF 8.426) Pub Date : 2020-01-09
    Samuel C. Johnson; Joshua D. Rhodes; Michael E. Webber

    High penetrations of non-synchronous renewable energy generation can decrease overall grid stability because these units do not provide rotational inertia in the same way as traditional synchronously-connected generators. Many recent studies have investigated 100% renewable energy generation scenarios, but few have explored the trade-offs associated with an electricity grid dominated by non-synchronous generation (i.e. wind and solar). Fast frequency response from grid-forming inverters—along with other technology changes—could help mitigate low system inertia levels, but the impact of this response is unknown. An inertia-constrained unit commitment and dispatch model was used to study the stability of future grid scenarios with high penetrations of non-synchronous renewable energy generation under a variety of technology scenarios. The Texas grid (the Electric Reliability Council of Texas – ERCOT) was used as a test case and instances when the system inertia fell below 100 GW·s (the grid’s current minimum level) were recorded. When the modeled critical inertia limit was reduced to 80 GW·s to represent changes in grid operation, no critical inertia hours occurred for renewable energy penetrations up to 93% of annual energy. The critical inertia limit could drop to 60 GW·s if the largest generators in ERCOT (two co-located nuclear plants) were retired, but emissions increased by ~25% in these scenarios. If the critical inertia limit was kept the same (100 GW·s), adding 525 MW of fast frequency response from wind, solar, and energy storage could reduce the number of critical inertia hours by up to 95%. These results show that changes to grid operating practices and generator retirements reduced critical inertia hours more than fast frequency response from inverter-connected resources. Each of these mitigation pathways has associated trade-offs, so the transition to a grid dominated by non-synchronous energy generation should be handled with care, but high renewable energy penetrations (i.e. >80%) might be feasible in Texas.

    更新日期:2020-01-11
  • Agent-based distributed demand response in district heating systems
    Appl. Energy (IF 8.426) Pub Date : 2020-01-10
    Hanmin Cai; Shi You; Jianzhong Wu

    Current district heating systems are moving towards 4th generation district heating in which end-users play an active role in system operation. Research has shown that optimising buildings' heating demands can release network congestion and contribute to reducing primary energy usages. Coupled with end-user privacy concerns, an approach in which buildings jointly optimise their heating demands while preserving privacy needs to be investigated. In view of this need, we have developed a distributed demand response approach based on exchange ADMM to support distributed agent-based heating demand optimisation for the district heating system with minimal private information exchanges. This paper summarises mathematical derivation, simulation and implementation of the proposed approach. The results show that the proposed approach obtained the same results as its centralised counterpart proposed in the existing literature and the sensible information exchanges were substantially reduced. An implementation at multiple spatial scales and time scales on micro-controllers and a communication system validates the proposed approach in a practical context. In conclusion, the proposed approach is suitable for real-world implementation in a large-scale district heating system.

    更新日期:2020-01-11
  • Coupling of piezo- and pyro-electric effects in miniature thermal energy harvesters
    Appl. Energy (IF 8.426) Pub Date : 2020-01-10
    Miwon Kang; Eric M. Yeatman

    Thermal energy harvesting from ambient heat into electricity is of interest due to its wide potential applicability. This paper demonstrates a moving beam thermal energy harvesting mechanism exploiting both pyro- and piezo-electric effects simultaneously, for use adjacent to a heat source with small temperature variations at low frequency (below 0.1 Hz). For the first time, the relative contributions of these two mechanisms in such a device is established both theoretically and experimentally, and a dynamic model is provided. The relative phase of the contributed currents is shown to be a critical factor, and methods are introduced to optimise this phase relationship, particularly by selection of the mechanical configuration. The reported prototype achieves around 0.4 μW for a temperature difference of around 15 K at frequency 0.02 Hz with an optimal condition in the fixed-fixed configuration about 90% above the fixed-free end configuration.

    更新日期:2020-01-11
  • A two-stage evaluation and optimization method for renewable energy development based on data envelopment analysis
    Appl. Energy (IF 8.426) Pub Date : 2020-01-10
    Yuan Zeng; Waiying Guo; Hongmei Wang; Fengbin Zhang

    Different kinds of renewable energy resources have developed rapidly. For renewable energy planning, it is meaningful to assess the comprehensive performances of different schemes and then to determine the optimal design of the energy structure. This paper presents a two-stage method for the comprehensive evaluation and structure optimization of renewable energy plans. First, in the evaluation stage, multiple indexes from different aspects are taken into consideration, of which each qualitative index will be converted quantitatively, using the intuitionistic fuzzy number to describe the fuzziness and ambiguity in a qualitative index. Then, the superefficiency data envelopment analysis model is used to determine the comprehensive performances of different plans based on the concept of relative efficiency. Next, in the optimization stage, an optimal model combining multiple renewable energy resources is established based on the relative efficiency results of the evaluation process. This model aims at the maximum efficiency as a whole and can be used to optimize the proportions of different renewable energy resources. Finally, a real case of renewable energy development from a province in China is given to demonstrate the feasibility and effectiveness of the proposed method in this paper. The results show that it can overcome the shortcomings of the traditional basic model, obtain more objective evaluation results and provide beneficial references for the strategy making of renewable energy development.

    更新日期:2020-01-11
  • Synthesis and optimization of work and heat exchange networks using an MINLP model with a reduced number of decision variables
    Appl. Energy (IF 8.426) Pub Date : 2020-01-08
    Lucas F. Santos; Caliane B.B. Costa; José A. Caballero; Mauro A.S.S. Ravagnani

    Integrating the energy available in industrial processes in the form of heat and work is fundamental to achieve higher energy efficiencies as well as to reduce process costs and environmental impacts. To perform this integration, a new framework for the optimal synthesis of work and heat exchange networks (WHEN) aiming to reduce capital and operating costs is presented. The main contribution of this paper is the elaboration of a new WHEN superstructure and mixed-integer nonlinear programming (MINLP) derived model. Strategies of changing variables are applied to reduce the number of decision variables from the model. The MINLP problem with a reduced number of decision variables is solved with a two-level meta-heuristic optimization approach, using Simulated Annealing in the combinatorial problem and Particle Swarm Optimization in the nonlinear programming problem. For the sake of validation, this methodology is applied to three case studies comprising two, five, and six process streams. Economic savings achieved outperform results reported in the literature from 1.0 to 7.2%. Also, the solutions obtained present non-intuitive WHENs that shows the importance of using superstructure-based mathematical programming for such a difficult decision-making task.

    更新日期:2020-01-09
  • Unique applications and improvements of reverse electrodialysis: A review and outlook
    Appl. Energy (IF 8.426) Pub Date : 2020-01-09
    Hailong Tian; Ying Wang; Yuansheng Pei; John C. Crittenden

    Reverse electrodialysis (RED) is a promising technology for extracting energy from salinity gradients. However, there are still barriers to the realization of its commercial application. Developing flexible methods of RED application is a feasible scheme. In this paper, we review and summarize unique RED applications in recent years. The review summarizes RED applications related to energy conversion, desalination technology, and water treatment and some improvements to standard RED. The electricity generated by RED or combined RED can be converted to hydrogen or other energy forms and stored in a battery for access at any time. RED heat engine expands RED application with conversion of waste heat to electricity. RED can be coupled with one or more desalination technologies to improve the power density of RED and minimize the influence of brine discharge from desalination technology on the environment. RED or combined RED can also be used for water treatment by direct or indirect reactions. The review also summarizes the improvements of electrodes, feed solutions, membranes and operation of membrane cell for RED. With the development of related technologies, RED will play an important role in an increasing number of fields.

    更新日期:2020-01-09
  • 更新日期:2020-01-08
  • Robust and automatic data cleansing method for short-term load forecasting of distribution feeders
    Appl. Energy (IF 8.426) Pub Date : 2020-01-07
    Nathalie Huyghues-Beaufond; Simon Tindemans; Paola Falugi; Mingyang Sun; Goran Strbac

    Distribution networks are undergoing fundamental changes at medium voltage level. To support growing planning and control decision-making, the need for large numbers of short-term load forecasts has emerged. Data-driven modelling of medium voltage feeders can be affected by (1) data quality issues, namely, large gross errors and missing observations (2) the presence of structural breaks in the data due to occasional network reconfiguration and load transfers. The present work investigates and reports on the effects of advanced data cleansing techniques on forecast accuracy. A hybrid framework to detect and remove outliers in large datasets is proposed; this automatic procedure combines the Tukey labelling rule and the binary segmentation algorithm to cleanse data more efficiently, it is fast and easy to implement. Various approaches for missing value imputation are investigated, including unconditional mean, Hot Deck via k-nearest neighbour and Kalman smoothing. A combination of the automatic detection/removal of outliers and the imputation methods mentioned above are implemented to cleanse time series of 342 medium-voltage feeders. A nested rolling-origin-validation technique is used to evaluate the feed-forward deep neural network models. The proposed data cleansing framework efficiently removes outliers from the data, and the accuracy of forecasts is improved. It is found that Hot Deck (k-NN) imputation performs best in balancing the bias-variance trade-off for short-term forecasting.

    更新日期:2020-01-08
  • Underground solar energy storage via energy piles
    Appl. Energy (IF 8.426) Pub Date : 2020-01-07
    Qijie Ma; Peijun Wang

    Conventional piles embedded with geothermal loops, referred to as energy piles, have been successfully used as heat exchangers for the ground source heat pump system. For heating-dominated regions, it is crucial for the ground source heat pump system to keep the ground thermal balance in the long run. Solar energy is the most feasible source to charge the ground manually. In this study, thermal performance of an energy pile-solar collector coupled system for underground solar energy storage was investigated using numerical modeling. The results suggested that a lower flow rate should be adopted for the energy pile-solar collector coupled system to save the operational cost of the circulation pump. For the case with a pile length of 30 m, the decrease in the rate of solar energy storage was about 2% when the mass flow rate was reduced from 0.3 to 0.05 kg/s. Throughout a year, the maximum daily average rate of solar energy storage reached 150 W/m. It was also found that to increase the length and the diameter of the pile improved the thermal performance of the system by keeping its temperature relatively lower. In addition, the effects of the pile-pile thermal interference on reducing the rate of solar energy storage after a one-year operation were quantified to be within 10 W/m for groups with the pile-pile spacing of 3 times the pile diameter.

    更新日期:2020-01-07
  • Urban form, shrinking cities, and residential carbon emissions: Evidence from Chinese city-regions
    Appl. Energy (IF 8.426) Pub Date : 2020-01-07
    Xingjian Liu; Mingshu Wang; Wei Qiang; Kang Wu; Xiaomi Wang

    This paper analyzes the relationship between urban form, shrinking cities, and residential carbon emissions, based on information collected for prefectural-level and above Chinese cities for the years of 2005, 2010, and 2015. After controlling for a number of urban form and socioeconomic variables (e.g., size, compactness, and polycentricity), this paper pays attention to residential carbon emissions in ‘shrinking cities’, which have experienced population loss and are a recent urban phenomenon in China. Everything else being equal, shrinking cities tend to be associated with less energy efficient than their growing counterparts, suggesting that these cities may not only be ‘battling’ with shrinking populations and economies but also need to consider the environmental issues.

    更新日期:2020-01-07
  • Oxidation efficiency of glucose using viologen mediators for glucose fuel cell applications with non-precious anodes
    Appl. Energy (IF 8.426) Pub Date : 2020-01-07
    Meisam Bahari; Michael A. Malmberg; Daniel M. Brown; S. Hadi Nazari; Randy S. Lewis; Gerald D. Watt; John N. Harb

    Glucose is a potential source of energy for fuel cell applications. However, its complete oxidation has been a challenge. Dimethyl viologen, as an electron mediator, has been shown to promote high levels of glucose oxidation under aerobic conditions. Nevertheless, the efficiency of viologen-mediated glucose oxidation has been low in electrochemical experiments. In this study, viologen-mediated oxidation of glucose was investigated under anaerobic electrochemical conditions to understand the factors that impact the oxidation efficiency. Of particular interest was the improvement of electrochemical oxidation for glucose fuel cell applications. An experimental cell was developed to electrochemically reoxidize the mediator as it was homogeneously reduced by glucose under anaerobic conditions. In contrast, the mediator was reoxidized by direct reaction with oxygen under aerobic conditions. The aerobic oxidation efficiency was 75%, three times larger than the maximum efficiency in the electrochemical cell. 13C-NMR results show that the main product formed under aerobic conditions was formic acid, whereas glycolic acid was the principal product formed in the electrochemical cell. Carbonate was only formed under aerobic conditions. Therefore, the use of oxygen to reoxidize the mediator also directly influenced the glucose oxidation pathway. In the electrochemical cell, the oxidation efficiency depended on the electrochemical reaction rate of the mediator and was higher at faster rates. The efficiency also depended on the initial molar ratio of the mediator to glucose. The maximum oxidation efficiency of glucose in the electrochemical cell was approximately 22%, which is about three times larger than the maximum efficiency for precious-metal-based anodes.

    更新日期:2020-01-07
  • Improved activity of magnetite oxygen carrier for chemical looping steam reforming by ultrasonic treatment
    Appl. Energy (IF 8.426) Pub Date : 2020-01-07
    Chunqiang Lu; Kongzhai Li; Xing Zhu; Yonggang Wei; Lei Li; Min Zheng; Bingbing Fan; Fang He; Hua Wang
    更新日期:2020-01-07
  • 更新日期:2020-01-07
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