Energy Science & Engineering最新文献

{"title":"Economic Load Dispatch of A Multi-Area Power System Using Multi-Agent Distributed Optimization Based on Genetic Algorithm","authors":"Seyed Yaser Fakhrmousavi,&nbsp;Seyed Babak Mazafari,&nbsp;Shahram Javadi,&nbsp;Mahmood Hosseini Aliabadi","doi":"10.1002/ese3.2086","DOIUrl":"https://doi.org/10.1002/ese3.2086","url":null,"abstract":"<p>This study presents a new methodology for distributed multi-agent optimization utilizing a genetic algorithm to address Multi-Area Economic Dispatch Problem (MAEDP) in a power system. While numerous studies have been conducted on various optimization methods for distributed multi-agent systems, this paper proposes a model for solving the optimal economic dispatch equations in different areas of the power system in a distributed and coordinated manner. In this model, each area is represented by an agent responsible for coordinating data exchange with other areas and solving the generation dispatch equations within its own area. The coordination model between agents and areas is described in the form of an algorithm, whereby the exchanged data values converge after several iterations, and the final solution to the problem is obtained from the perspective of each agent. The objective of each agent in each area is to minimize generation costs and meet its own area's load demand while maintaining voltage profiles. Each agent sets the power generation values of resources in each area using the genetic algorithm rules and then solves the distributed power flow equations using the proposed method. Upon achieving convergence, each agent evaluates all operational constraints within its designated region, calculates the associated generation cost, and shares the cost value to other agents, thereby facilitating the computation of the total cost for each agent. This process continues until the best possible solution is found. The results of implementing the proposed model and algorithm on several different test networks of power systems demonstrate the capability and effectiveness of the method in decomposing the optimal economic dispatch problem into smaller sub-problems and then finding the final optimal solution through simultaneous solving with agent consensus in coordinated steps.</p>","PeriodicalId":11673,"journal":{"name":"Energy Science & Engineering","volume":"13 4","pages":"1679-1690"},"PeriodicalIF":3.5,"publicationDate":"2025-03-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/ese3.2086","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143852885","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":"An Improved NSGA-III With Hybrid Crossover Operator for Multi-Objective Optimization of Complex Combined Cooling, Heating, and Power Systems","authors":"Lejie Ma,&nbsp;Dexuan Zou","doi":"10.1002/ese3.2039","DOIUrl":"https://doi.org/10.1002/ese3.2039","url":null,"abstract":"<p>Traditional combined cooling, heating, and power (CCHP) systems are highly efficient in energy utilization but face challenges such as high operational costs, CO₂ emissions, and complex scheduling. In traditional CCHP systems, typically used in large commercial settings like hospitals or shopping centers, daily operational costs can exceed $1500, and CO₂ emissions often surpass 1.5 tons, limiting broader adoption. This study introduces an improved CCHP system (CCHP-Plus), which integrates photovoltaic thermal (PV/T) technology and energy storage equipments (ESEs) to mitigate these issues. PV/T collectors generate both electricity and heat, reducing natural gas dependence, while ESE balances energy supply and demand for enhanced management. The effectiveness of CCHP-Plus is assessed using three key indicators: primary energy consumption, operational cost, and CO₂ emissions. NSGAIII-AC-GM delivers a 20% reduction in operational costs and a 10% decrease in CO₂ emissions, outperforming seven other algorithms in optimization efficiency on DTLZ and IMOP problems. Furthermore, the algorithm demonstrates superior performance across four CCHP-Plus scenarios, making it a promising solution for sustainable energy systems. These findings offer valuable numerical insights, showcasing the system's potential for real-world applications.</p>","PeriodicalId":11673,"journal":{"name":"Energy Science & Engineering","volume":"13 4","pages":"1509-1543"},"PeriodicalIF":3.5,"publicationDate":"2025-03-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/ese3.2039","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143852826","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":"An Integrated Approach via Design, Experiment, and Simulation for the Development of a Pot-Type Stove for Energy-Intensive Cooking Tasks","authors":"Delmer Gómez-Heleria,&nbsp;José Núñez,&nbsp;Alberto Beltrán,&nbsp;Víctor M. Berrueta,&nbsp;Carlos A. García,&nbsp;Omar R. Masera","doi":"10.1002/ese3.70008","DOIUrl":"https://doi.org/10.1002/ese3.70008","url":null,"abstract":"<p>This investigation aims to develop a device that meets the specific requirements of energy-intensive household cooking tasks, such as the nixtamalization process. In particular, a pot-type biomass stove is designed and built. A computer-aided design (CAD) model of the stove was created, followed by a metal prototype. Thermal performance was evaluated by means of numerical simulations as well as experimental thermographic images. The numerical and experimental results were compared, and the quantitative correlation was found to be in good agreement. The results show that this stove can handle energy-intensive cooking tasks like nixtamalization of maize. The development of this stove resulted in significant improvements in thermal efficiency and fuel consumption when compared to conventional stoves.</p>","PeriodicalId":11673,"journal":{"name":"Energy Science & Engineering","volume":"13 4","pages":"1798-1806"},"PeriodicalIF":3.5,"publicationDate":"2025-03-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/ese3.70008","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143852828","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":"Dispatchable Potential Analysis of FCHEV Aggregator Considering Uncertainty of Charging Scheduling","authors":"Guanhui Liu,&nbsp;Akram M. Abdurraqeeb,&nbsp;Abdulaziz Alkuhayli,&nbsp;Andres Annuk,&nbsp;Mohamed A. Mohamed","doi":"10.1002/ese3.70021","DOIUrl":"https://doi.org/10.1002/ese3.70021","url":null,"abstract":"<p>The analysis of the dispatchable potential of fuel-cell hybrid electric vehicle (FCHEV) is particularly important to ensure the stable operation of the power system, but the uncertainty of vehicle owners' charging scheduling brings challenges to the analysis of the dispatchable potential of FCHEV aggregators. Therefore, this paper comprehensively considers the influence of vehicle charging scheduling uncertainty on the dispatchable potential of FCHEV aggregators, and proposes an analysis method for the dispatchable potential of FCHEV aggregators. In the context of urban transportation networks, the charging behavior of FCHEV is analyzed and modeled. From the subjective and objective perspectives, the evaluation index of the owner's charging scheduling was established. According to the relevant theories of behavioral psychology, the willingness of vehicle owners to participate in the dispatch of the power system is calculated, and the dispatchable potential of FCHEV aggregators is analyzed. Through the verification of examples, the analysis method proposed in this paper can effectively describe the uncertainty of vehicle owners' charging scheduling and ensure the validity of the evaluation results of dispatchable potential.</p>","PeriodicalId":11673,"journal":{"name":"Energy Science & Engineering","volume":"13 4","pages":"1983-1994"},"PeriodicalIF":3.5,"publicationDate":"2025-03-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/ese3.70021","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143852886","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":"Comparative Performance and Emission Analysis of Soybean and Algae Biodiesels in Low Heat Rejection Engines","authors":"Ratchagaraja Dhairiyasamy,&nbsp;Wasurat Bunpheng,&nbsp;Chan Choon kit,&nbsp;Nasim Hasan","doi":"10.1002/ese3.2090","DOIUrl":"https://doi.org/10.1002/ese3.2090","url":null,"abstract":"<p>The quest for sustainable energy solutions has driven extensive research into biodiesel derived from renewable sources such as soybean oil and algae. This study aims to optimize biodiesel production from soybean oil and algae using transesterification and pyrolysis processes. Additionally, it evaluates the performance and emission characteristics of these biodiesels in conventional and low heat rejection (LHR) engines to enhance the understanding of biodiesel production processes and their impact on engine performance and emissions. Soybean oil and algae were used as feedstocks for biodiesel production via transesterification and pyrolysis. The produced biodiesels, specifically soybean methyl ester (SBME), algae methyl ester (ALME), and soybean pyrolytic oil (SBPO), were tested in both conventional and LHR engines. Performance metrics such as brake-specific fuel consumption (BSFC), brake thermal efficiency (BTE), exhaust gas temperature (EGT), and emissions (CO, HC, NOx) were analyzed. SBME20 blend demonstrated superior performance with lower BSFC, higher BTE, and reduced CO and HC emissions compared to ALME20 and SBPO20 blends. However, NOx emissions were higher in LHR engines due to increased combustion temperatures. The LHR engine's enhanced thermal environment improved fuel combustion efficiency, particularly for SBME20, which exhibited the best overall performance and emission profile. The study concludes that SBME20 is the most efficient and environmentally friendly biodiesel blend for LHR engines, highlighting the potential of soybean oil as a viable feedstock for sustainable biodiesel production. Further optimization is required for ALME20 and SBPO20 to achieve comparable performance levels.</p>","PeriodicalId":11673,"journal":{"name":"Energy Science & Engineering","volume":"13 4","pages":"1732-1748"},"PeriodicalIF":3.5,"publicationDate":"2025-03-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/ese3.2090","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143852821","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":"Machine Learning-Based Solar Photovoltaic Power Forecasting for Nigerian Regions","authors":"Christian Idogho,&nbsp;Emmanuel Owoicho Abah,&nbsp;Joy Ojodunwene Onuhc,&nbsp;Catur Harsito,&nbsp;Kenneth Omenkaf,&nbsp;Akeghiosi Samuel,&nbsp;Abel Ejila,&nbsp;Idoko Peter Idoko,&nbsp;Ummi Ene Ali","doi":"10.1002/ese3.70013","DOIUrl":"https://doi.org/10.1002/ese3.70013","url":null,"abstract":"<p>This study explores machine learning-based forecasting of solar photovoltaic (PV) power generation across distinct climatic regions in Nigeria. Machine learning techniques, particularly support vector machines (SVM) and artificial neural networks (ANN), were employed to predict solar PV output, utilizing a comprehensive data set spanning 12 years of climatic parameters, including solar irradiation, cloud cover, temperature, and humidity. Model training, validation, and testing were conducted in MATLAB using the ANN approach, with results indicating a notable improvement in prediction accuracy with the addition of hidden layers. The model achieved optimal performance with 1000 hidden layers, achieving a low mean squared error (MSE) and high correlation coefficient (<i>R</i>) values across all regions. Forecasted power generation values revealed region-specific insights, with the Northern region exhibiting the highest solar potential, attributable to its hot, dry climate and minimal cloud cover. Conversely, regions with high humidity and frequent cloud cover, such as the Southern region, showed reduced PV output. These findings highlight the critical role of machine learning in enhancing solar PV forecasting accuracy across diverse environments. The study's insights provide a foundation for policymakers and stakeholders to make informed decisions, promote sustainable energy initiatives, and optimize solar energy resource management in Nigeria.</p>","PeriodicalId":11673,"journal":{"name":"Energy Science & Engineering","volume":"13 4","pages":"1922-1934"},"PeriodicalIF":3.5,"publicationDate":"2025-03-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/ese3.70013","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143852824","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":"Dynamic Calculation Method of Interwell Connectivity Based on the Attention Mechanism","authors":"Wei Li,&nbsp;Feng Wei,&nbsp;Xiaoquan Chen,&nbsp;Zhigang Yu,&nbsp;Zhenyu Zhou,&nbsp;Yuli Zhang,&nbsp;Shuai Ma,&nbsp;Qingjun Meng,&nbsp;Chunyi Yang","doi":"10.1002/ese3.70011","DOIUrl":"https://doi.org/10.1002/ese3.70011","url":null,"abstract":"<p>The analysis of interwell connectivity plays a pivotal role in the optimization of the injection-production relationship, the formulation of an oilfield development plan and the description of the remaining oil distribution. Nevertheless, conventional techniques for determining interwell connectivity, such as tracer analysis, interference well testing, and numerical simulation, are characterized by high costs and low efficiency. To address this challenge, an increasing number of artificial intelligence methods have been proposed. However, these methods often necessitate the availability of a substantial quantity of labeled data to facilitate model training, and sensitivity analysis is required to ascertain the interwell connectivity of the model training results. Furthermore, the majority of existing methods are unable to perform dynamic analysis of interwell connectivity. This paper proposes a dynamic calculation method of interwell connectivity based on an attention mechanism to address the aforementioned issues. The interwell connectivity is taken as the intermediate parameter of the neural network, with the interwell connectivity between each injection well and the current production well in the well group inverted by predicting the daily fluid production of each production well in the well group. The experimental results demonstrate that the interwell connectivity calculations presented in this paper are in accordance with the actual operational conditions observed in the oil field and the reservoir expertize of industry professionals. This indicates that our approch can effectively support dynamic decision-making in the production process of oil reservoirs.</p>","PeriodicalId":11673,"journal":{"name":"Energy Science & Engineering","volume":"13 4","pages":"1807-1818"},"PeriodicalIF":3.5,"publicationDate":"2025-03-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/ese3.70011","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143852823","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":"Alkali Modification and Pyrolysis of Rice Husks for Bioenergy Potential: A Kinetics Study","authors":"Vianney Andrew Yiga,&nbsp;Michael Lubwama,&nbsp;Peter Wilberforce Olupot","doi":"10.1002/ese3.2084","DOIUrl":"https://doi.org/10.1002/ese3.2084","url":null,"abstract":"<p>Rice husks are significantly creating environmental challenges in terms of air pollution because of their unsustainable disposal methods. In this study, pyrolysis of sodium hydroxide (NaOH) alkali-modified rice husks using thermogravimetric analysis (TGA) was carried out to determine combustion and kinetic parameters at three different heating rates of 20, 40, and 50°C/min for application in biofuels. Combustion performance was analyzed from the results of ignition temperature, burn-out temperature, combustion rates, flammability index, and combustion characteristic index. The increase in heating rate from 20°C to 40°C and further to 50°C/min increased the onset of degradation, burnout, and peak temperatures as observed by curve shifts to the right. This was likely due to a shorter reaction time when a higher heating rate was utilized, increasing the temperature required for degradation. Flammability and combustion characteristic index ranged between 0.8 × 10⁻⁵–1.1 × 10⁻⁵%/min.°C² and 0.3 × 10⁻⁸–0.4 × 10⁻⁸%/min/°C respectively, and their values decreased with increasing heating rates since it takes longer to transfer heat from the external environment to the interior of the rice husks, thereby creating a hysteresis effect. The average activation energies for modified K85 (<i>kaiso</i>) and modified K98 (<i>supa</i>) rice husks using the Kissinger–Akahira–Sunose (KAS) method were 104.5 kJ/mol and 105.4 kJ/mol as well as 109.4 kJ/mol and 110.3 kJ/mol using the Ozawa–Flynn–Wall (OFW) method. Enthalpy, Gibbs free energy, and Entropy changes were in ranges 103.9–105.0 kJ/mol, 160.8–167.5 kJ/mol, and 0.09 kJ/mol.K, respectively. The low energy barrier (≤ 7.0 kJ/mol) between activation energy and enthalpy changes indicated that modified rice husk initiation occurs easily and can easily be transformed into biofuels. In general, the findings from this work have confirmed the feasibility of modified rice husks as a potential source of bioenergy.</p>","PeriodicalId":11673,"journal":{"name":"Energy Science & Engineering","volume":"13 4","pages":"1638-1652"},"PeriodicalIF":3.5,"publicationDate":"2025-03-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/ese3.2084","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143852735","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":"Simulation of Natural Gas Pipeline Networks Based on Roughness Optimization Algorithm and Global Mesh Refinement","authors":"Yi Yang","doi":"10.1002/ese3.2058","DOIUrl":"https://doi.org/10.1002/ese3.2058","url":null,"abstract":"<p>Natural gas pipeline network simulation technology is the fundamental technology of system capacity analysis, pipeline design, operation planning and optimization as well as emergency decision-making for the whole life cycle of a given pipeline network system. There has been an increased demand for the computation efficiency and numeric accuracy of pipeline simulation with the increase of the total mileage of China's pipeline network as well as the centralize mode of one control center operating the entire system. This paper proposes a new numerical simulation method for natural gas pipeline systems based on roughness optimization and global mesh refinement. The numerical model of the natural gas pipeline system, which consists of governing equation of the pipeline fluid flow and characteristic equations of equipment, is firstly obtained by using an implicit finite difference method for discretization. The roughness identification problem is then transformed into an optimization problem by minimizing the error between measured and simulated values. The GA-based algorithm is applied thereafter. Finally, a two-step nonlinear iterative algorithm is proposed, which uses the coarse mesh to obtain the initial solution and the refined mesh to solve the problem to achieve accuracy and efficiency performance. The proposed method was verified by three industrial pipeline network examples. It is found that the average relative errors between the simulated and the measured data of the three cases are reduced by 3.87%, 5.06%, and 6.0%, respectively. The computational costs under 24-h transient simulation conditions were reduced by 39%, 56%, and 65%, respectively. These numeric results show that the developed method has the advantages of stability, computation efficiency, and convergence, which provide a technical basis for the subsequent simulation of the national pipeline network.</p>","PeriodicalId":11673,"journal":{"name":"Energy Science & Engineering","volume":"13 4","pages":"1567-1576"},"PeriodicalIF":3.5,"publicationDate":"2025-03-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/ese3.2058","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143852736","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":"The Dynamics of Energy Poverty in China: Household Level Analysis and Mitigation Strategies","authors":"Junming Feng,&nbsp;Yiyu Chen,&nbsp;Fatima Gulzar,&nbsp;Sanajar Mirzaliev,&nbsp;Hind Alofaysan,&nbsp;Peter Mark","doi":"10.1002/ese3.70023","DOIUrl":"https://doi.org/10.1002/ese3.70023","url":null,"abstract":"<p>Energy poverty poses a significant challenge in the context of stringent environmental policies, particularly in developing economies like China. This study investigates the impact of energy poverty at the household level from 2010 to 2022 using data from the China Family Panel Studies (CFPS). The analysis incorporates information from 49,373 households across 25 regional administrative divisions, excluding regions with insufficient representation. We measure energy poverty using two proxies: the proportion of household energy expenditure to total household income, and a threshold indicator where households spending more than 10% of their budget on energy are classified as energy poor. Covariates include family size, age, and education level of household heads, and regional characteristics (North–South division). Results reveal that households in northern China experience significantly higher energy poverty, exacerbated by stricter environmental policies and climatic conditions. Energy storage systems are emerging as a critical mitigating factor, reducing energy costs and smoothing consumption patterns. Policy implications suggest incentivizing affordable and accessible energy storage technologies to alleviate energy poverty while ensuring environmental sustainability.</p>","PeriodicalId":11673,"journal":{"name":"Energy Science & Engineering","volume":"13 4","pages":"2011-2021"},"PeriodicalIF":3.5,"publicationDate":"2025-03-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/ese3.70023","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143852730","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}