Energy Reports最新文献

{"title":"Optimizing technological configurations in residential energy systems with vehicle-to-home integration and community-level power sharing","authors":"","doi":"10.1016/j.egyr.2024.09.033","DOIUrl":"10.1016/j.egyr.2024.09.033","url":null,"abstract":"<div><div>Distributed energy technologies, such as photovoltaic (PV), stationary storage batteries (SBs), and vehicle-to-home (V2H) systems, are expected to be introduced in pursuit of carbon neutrality in the residential and transportation sectors. This study developed the model of a two-tiered energy system to optimize technological configurations and examined the impacts of installed capacities of PV and SBs, along with various vehicle types, on the economic and environmental performance, stability, and efficiency of residential energy systems. The primary contribution of this research lies in its comprehensive analysis of energy systems that incorporate bidirectional power supply between vehicles and residences, as well as power sharing among multiple households within a community. The simulation results revealed substantial benefits from the incorporation of V2H systems and SBs, which notably reduced annual energy costs by approximately 30 % and CO₂ emissions by approximately 40 % in scenarios leveraging community electricity sharing, compared to scenarios without such flexibility. This integration significantly enhanced the self-consumption and self-sufficiency rates of residential energy systems by approximately 10 %, illustrating the efficacy of community-level electricity sharing combined with the charging and discharging capabilities of vehicles. This strategy not only optimizes resource use but also reduces dependency on external power supplies, thereby enhancing overall energy efficiency.</div></div>","PeriodicalId":11798,"journal":{"name":"Energy Reports","volume":null,"pages":null},"PeriodicalIF":4.7,"publicationDate":"2024-09-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142319222","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Corrigendum to “Load forecasting method based on CNN and extended LSTM”, [Energy Rep., vol. 12, December 2024, Pages 2452–2461]","authors":"Chong Wang, Xiang Li, Yan Shi, Wenshuai Jiang, Qiong Song, Xueling Li","doi":"10.1016/j.egyr.2024.09.004","DOIUrl":"https://doi.org/10.1016/j.egyr.2024.09.004","url":null,"abstract":"","PeriodicalId":11798,"journal":{"name":"Energy Reports","volume":null,"pages":null},"PeriodicalIF":5.2,"publicationDate":"2024-09-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142266029","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Corrigendum to “Design and implementation of an autonomous device with an app to monitor the performance of photovoltaic panels” [Energy Rep. 12 (2024) 2498–2510]","authors":"A. Ordoñez, J. Urbano, F. Mesa, M. Castañeda, S. Zapata, B. Quesada, O. García, A.J. Aristizábal","doi":"10.1016/j.egyr.2024.09.005","DOIUrl":"https://doi.org/10.1016/j.egyr.2024.09.005","url":null,"abstract":"","PeriodicalId":11798,"journal":{"name":"Energy Reports","volume":null,"pages":null},"PeriodicalIF":5.2,"publicationDate":"2024-09-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142266031","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Application of wavelet and seasonal-based emotional ANN (EANN) models to predict solar irradiance","authors":"Vahid Nourani, Nazanin Behfar, Anne Ng, Chunwei Zhang, Fahreddin Sadikoglu","doi":"10.1016/j.egyr.2024.09.011","DOIUrl":"https://doi.org/10.1016/j.egyr.2024.09.011","url":null,"abstract":"This study models solar irradiance at six stations in Iran and the USA on an hourly scale. We explored two seasonal emotional artificial neural networks (EANN): sequence-EANN (SEANN) and wavelet EANN (WEANN). Analyzing ten years of climatic and solar data, we evaluated uncertainty using prediction intervals (PIs) computed via the bootstrap method based on artificial neural networks (ANNs). Unlike standalone EANNs, the proposed seasonal models effectively captured seasonal information and leveraged time series processing advantages. Utilizing Wavelet and Fourier transforms, these models captured long-short autoregressive dependencies in solar irradiance, addressing extended seasonal dependencies. Results showed that the seasonal EANN models outperformed the classic EANN model by approximately 15 % and the classic feed-forward neural network (FFNN) by about 25 % in both training and testing. The WEANN model demonstrated the highest performance in PIs, with an average normalized mean PI width (NMPIW) of 0.8 and an average PI coverage probability (PICP) of 0.96.","PeriodicalId":11798,"journal":{"name":"Energy Reports","volume":null,"pages":null},"PeriodicalIF":5.2,"publicationDate":"2024-09-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142266030","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Biogas generation from food waste through anaerobic digestion technology with emphasis on enhancing circular economy in Sub-Saharan Africa – A review","authors":"Jovine Kamuhabwa Emmanuel, Maroa Julias Juma, Stephano Hanolo Mlozi","doi":"10.1016/j.egyr.2024.09.008","DOIUrl":"https://doi.org/10.1016/j.egyr.2024.09.008","url":null,"abstract":"Globally, 2.2 billion tons of municipal solid waste (MSW) are generated, primarily being disposed of as landfills and couple with fossil fuels (FFs) in polluting the environment resulting in the loss of over 600,000 human life in Sub-Saharan Africa (SSA). Besides, MSW particularly food waste (FW) is a potential alternative clean energy source and is abundant in urban and rural areas. The impact and challenges of FW on biogas production particularly in Sub-Saharan Africa, are not well understood. Still, there exists a large gap of access to clean energy in SSA compared to the rest of the world, especially G20. Therefore, this review explores the impact and challenges of utilizing FW for retrieving biogas for use as clean energy source in urban and rural areas in SSA towards attainment of sustainable development goal 7 (SDG7) and reduce human loss of life resulting from the use of harmful energy sources. The findings reveal that the impact of energy retrieved from FW alone through anaerobic digestion (AD) process is minimal and faces feedstock, structural and AD technology associated challenges. Anaerobic co-digestion of FW with animal manure and the integration of pyrolysis and AD process can significantly address these challenges. Based on the amount of FW availability, a significant impact of biogas from FW can be as high as 57 % and 43 % in urban and rural areas, respectively, if such challenges are timely addressed. This can greatly reduce human loss of life and increase access to clean energy, promote circular economy, protect the environment, and accelerate achievement of SDG7.","PeriodicalId":11798,"journal":{"name":"Energy Reports","volume":null,"pages":null},"PeriodicalIF":5.2,"publicationDate":"2024-09-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142266032","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Empowering E-mobility: Day-ahead dynamic time of use tariff for electric vehicle charging","authors":"Tafsir Ahmed Khan, Syed Abdullah-Al-Nahid, Silvia Tasnim, Md. Abu Taseen, Taskin Jamal, Tareq Aziz","doi":"10.1016/j.egyr.2024.08.086","DOIUrl":"https://doi.org/10.1016/j.egyr.2024.08.086","url":null,"abstract":"The greenhouse gases and preservation of the environment have been the most prioritized concern in many countries and international organizations, leading to set aims and initiatives for lowering the dependency on fossil fuels and minimizing carbon emissions. As a part of many initiatives, great emphasis is given to promoting electric vehicles (EVs) over their traditional carbon fuel-based counterpart. To support large-scale EV adoption, a dynamic tariff scheme is required that addresses complex issues like user comfort, savings, and utility revenue. In this research work, a dynamic pricing scheme is modeled for the centralized EV charging stations (EVCS) on a residential feeder. This pricing scheme integrates the existing static time of use (ToU) pricing to an hourly dynamic ToU tariff that varies according to the demand level in the residential feeder. The proposed tariff plan provides a day-ahead dynamic structure with a probable price variation range to aid the EV owners and the day-ahead charging mechanism to schedule the EVs beforehand. The developed scheme calculates the returns and adjusts the tariff including the demand charge and the recovery component on a daily, monthly, and yearly basis for the unsatisfactory investment revenue. Also, user convenience is ensured by setting the minimum possible tariff as well as satisfying the minimum revenue target with the integration of particle swarm optimization (PSO) in designing the pricing structure. The simulation results demonstrate the effectiveness of the proposed dynamic pricing scheme maintaining a trade-off between the interests of all parties involved. Moreover, the simulation outcome of the test case indicates that EV owners can save more than 32 % on charging bills if they plan correctly. On the other hand, the utility can earn more than 2.4 times the existing rate during the peak time of the residential feeder.","PeriodicalId":11798,"journal":{"name":"Energy Reports","volume":null,"pages":null},"PeriodicalIF":5.2,"publicationDate":"2024-09-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142266056","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"A novel radial air-breathing proton exchange membrane fuel cell for miniaturized applications with effective stacking potentials","authors":"Sura Qahtan Kadhim Alziayree, M.J. Kermani, M.A.R.S. Al-Baghdadi, H. Heidary","doi":"10.1016/j.egyr.2024.08.084","DOIUrl":"https://doi.org/10.1016/j.egyr.2024.08.084","url":null,"abstract":"Increasing volumetric power density in fuel cells can be accomplished by increasing its compactness or output power. This is very crucial for miniaturized applications due to constraints in available spaces. In this study, a three-dimensional, multiphase, and non-isothermal computational fluid dynamics (CFD) tool is used to develop a novel radial air-breathing (AB) PEM fuel cell for miniaturized applications, which has unique stack-ability feature. The noted cell can accommodate multiply higher active area in cathode electrode with respect to planar and tubular AB designs. Increasing the cathode side active area, the electrode with the highest sources of losses for the kinetics of reactions in proton exchange membrane (PEM) fuel cells, has shown to play a significant role in performance enhancement of radial AB cells. For instance, at 0.4 Acm the radial AB PEM fuel cell, can deliver 27.9 % and 10 % more power than the earlier planar and tubular AB ones, respectively. The stack-ability of AB fuel cells usually face severe challenges due to non-uniform air supply to the cells, resulting in imbalance of the cells output power. As opposed to tubular and planar AB cells, one unique feature for the present radial AB stack design is its attack-ability that ensures adequate and uniform supply of air/oxygen to all cells.","PeriodicalId":11798,"journal":{"name":"Energy Reports","volume":null,"pages":null},"PeriodicalIF":5.2,"publicationDate":"2024-09-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142266057","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Network reconfiguration and integration of distributed energy resources in distribution network by novel optimization techniques","authors":"Muhammad Zubair Iftikhar, Kashif Imran","doi":"10.1016/j.egyr.2024.08.067","DOIUrl":"https://doi.org/10.1016/j.egyr.2024.08.067","url":null,"abstract":"Nowadays, electrical load demand in radial distribution networks (RDN) is continuously growing, therefore RDNs are facing some serious challenges like voltage violation and line losses. Since modern RDNs have reconfiguration capabilities, optimal network reconfiguration is preferred over the costly construction of new lines and cables. In addition, the optimal integration of distributed energy resources (DER) helps to decrease above mentioned network challenges. This paper presents an improved version of the radiality maintenance algorithm (IRMA) to solve the optimal reconfiguration problem using a meta-heuristics algorithm. It also proposes two different schemes of algorithms by the blending of a Genetic algorithm (GA) and Teaching learning-based optimization (TLBO) to solve the optimal DER integration problem, where blending enhances the search space of each scheme which helps to find global minima in less iterations and time, while existing algorithms get stuck in local minima with same number of searching agents. The proposed problems are solved by minimizing active power loss by the single objective function and the sum of active power loss, reactive power loss, and voltage deviation index by multi-objective function using the weighted sum method where all objectives are equally dealt with, and their sum is used as single fitness function for the optimization algorithm. Four case studies are simulated using different DER technologies to improve each objective function. The efficiency of the proposed IRMA and two newly developed schemes of optimization algorithms, named GA-TLBO and TLBO-GA, are tested on two IEEE benchmark RDN of 33 and 69 buses. The results validate the efficiency of proposed algorithms that remarkably minimize a single objective from 210.9800 kW in the base case to 58.8768 kW, whereas existing algorithms like GWO and HHO were able to only reduce it to 72.7861 kW and 72.900 kW for IEEE 33 bus RDN, respectively. Similarly, for IEEE 69 bus system, single objective is reduced from base case of 224.9917 kW to 36.2543 kW, while existing algorithms like QOTLBO and QOSIMBO were only able to reduce it to 71.6250 kW and 71 kW, respectively. Furthermore, in multi-objective functions, reactive power losses and voltage deviation are also significantly improved from their base values. After that, the results of improved algorithms are compared with those of existing algorithms in the literature review for a comprehensive evaluation, which proves that proposed algorithm schemes are much more efficient and stable for the proposed problem as well as for standard benchmark optimization functions.","PeriodicalId":11798,"journal":{"name":"Energy Reports","volume":null,"pages":null},"PeriodicalIF":5.2,"publicationDate":"2024-09-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142266260","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Optimal low-carbon scheduling of integrated energy systems considering stepped carbon trading and source-load side resources","authors":"Limeng Wang, Xing Ren, Yuze Ma, Ziyu Liu, Wenkai Dong, Longbo Ni","doi":"10.1016/j.egyr.2024.09.002","DOIUrl":"https://doi.org/10.1016/j.egyr.2024.09.002","url":null,"abstract":"Under the dual-carbon goal of achieving carbon peaking and carbon neutrality, the Integrated Energy System (IES) enhances the power sector's environmental sustainability by integrating multiple energy sources. To enhance the low-carbon utilization of IES energy, this paper introduces an economic optimization model that incorporates stepwise carbon trading and both source and load-side resources. Initially, the model integrates a Concentrated Solar Power Plant (CSPP) with a Combined Heating and Power (CHP) unit for bidirectional electricity-heat conversion, and incorporates Power to Gas (P2G) and Carbon Capture System (CCS) for carbon recycling within the IES. On the demand side, demand response optimizes the electricity-heat load curve. Subsequently, a stepped carbon trading mechanism guides the system in controlling carbon emissions and constructing a carbon emission model. Finally, the model minimizes the sum of energy purchase costs, carbon transaction costs, demand response compensation costs, wind curtailment penalties, and equipment maintenance costs to optimize the IES economically. By establishing five scenarios for comparative analysis, incorporating CSPP, P2G-CCS, demand response, and a stepped carbon trading mechanism reduces system costs, carbon emissions, and abandonment rates by 21.1 %, 30.87 %, and 23.78 %, respectively, validating the model's effectiveness in promoting a low-carbon economy.","PeriodicalId":11798,"journal":{"name":"Energy Reports","volume":null,"pages":null},"PeriodicalIF":5.2,"publicationDate":"2024-09-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142266259","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Harnessing machine learning algorithms to unveil energy efficiency investment archetypes","authors":"Diamantis Koutsandreas, Ilkka Keppo","doi":"10.1016/j.egyr.2024.09.009","DOIUrl":"https://doi.org/10.1016/j.egyr.2024.09.009","url":null,"abstract":"Increasing transparency about the performance of different projects is crucial to reducing the heterogeneity in the energy efficiency services market, thereby upscaling investments. In this context, machine learning algorithms could assist in identifying and analyzing energy efficiency project archetypes, although this field has so far been explored with a limited view in the literature. This paper aims to address this gap by identifying energy efficiency investment families and the determinant factors of the classification scheme, using machine learning. In this effort, it hinges on a wide range of indicators from implemented projects around Europe and the USA, including investment profitability, initial investment, risk of failure, intervention type, life measure, region of implementation and building type. The analysis employs two clustering approaches, namely Partitioning Around Medoids (PAM) and K-means, determining the number of clusters based on the Silhouette index and total within–cluster sum of squares. The results indicate that energy efficiency investments can be classified into three categories: (i) “junk investments”, characterized by low–profitability (IRR10%), moderate risk, and extended horizons; (ii) “safe profitability”, distinguished by high profitability (IRR30%) and minimal risk; and (iii) “high stakes”, described by exceptionally high profitability (IRR40%), coupled with a substantial risk. Next to profitability and risk of failure, also energy efficiency intervention and building type (sector) emerge among the most influential factors in the classification scheme. Feature importance shows a significant sensitivity to the chosen classification model.","PeriodicalId":11798,"journal":{"name":"Energy Reports","volume":null,"pages":null},"PeriodicalIF":5.2,"publicationDate":"2024-09-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142266058","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}