Energy Conversion and Economics最新文献_第7页

Allocation of ancillary service costs to diverse consumers in China: A comprehensive survey and mechanism design 中国不同消费者的辅助服务成本分配：综合调查与机制设计

Energy Conversion and Economics Pub Date : 2025-06-27 Epub Date: 2025-06-11 DOI: 10.1049/enc2.70014

Nan Shang, Chao Guo, Zheng Chen, Zhilin Lu

{"title":"Allocation of ancillary service costs to diverse consumers in China: A comprehensive survey and mechanism design","authors":"Nan Shang, Chao Guo, Zheng Chen, Zhilin Lu","doi":"10.1049/enc2.70014","DOIUrl":"10.1049/enc2.70014","url":null,"abstract":"Ancillary services are crucial for supporting the reliable operation of power systems and constitute an integral part of the power market. The increasing integration of volatile renewable energy sources has introduced new challenges into China's traditional ancillary service markets, such as escalating ancillary service costs. Historically, the ancillary service cost-sharing approach in China has been a redistribution of revenue among generators, resulting in increasing cost-sharing pressure on the supply side. Therefore, based on the basic market logic of ‘who causes the demand, who pays,’ sharing the ancillary service costs with power consumers becomes urgent. This paper presents an overview of the latest research and practical experiences in China and other countries, and proposes an ancillary service cost allocation mechanism considering the participation of consumers. First, the ancillary service cost allocation mechanisms in China and other countries are summarized, including common rules and individual characteristics. Subsequently, a framework for the rights and responsibilities associated with ancillary services is systematically outlined from a market design perspective. Moreover, an ancillary service cost allocation mechanism was introduced based on the principle of ‘common but differentiated responsibilities (CBDR).’ Finally, the construction path of the ancillary service cost allocation mechanism under the new round of power industry reforms was proposed. The findings summarized in this study can promote the reasonable allocation of ancillary service costs and improve the flexibility of power systems and the consumption of renewable energy.","PeriodicalId":100467,"journal":{"name":"Energy Conversion and Economics","volume":"6 3","pages":"141-154"},"PeriodicalIF":0.0,"publicationDate":"2025-06-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1049/enc2.70014","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144492772","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Performance analysis of DC microgrids with output resistance shaping in presence of constant power loads 恒功率负载下具有输出电阻整形的直流微电网性能分析

Energy Conversion and Economics Pub Date : 2025-06-27 Epub Date: 2025-06-12 DOI: 10.1049/enc2.70013

Jitendra Prajapati, A. S. Vijay, Amod C. Umarikar

{"title":"Performance analysis of DC microgrids with output resistance shaping in presence of constant power loads","authors":"Jitendra Prajapati, A. S. Vijay, Amod C. Umarikar","doi":"10.1049/enc2.70013","DOIUrl":"10.1049/enc2.70013","url":null,"abstract":"Constant power loads (CPLs) introduce negative impedance in direct current microgrids (DCMGs), which is a major challenge. This negative impedance can significantly reduce the overall damping of the system, making it less stable and harder to control. To address this issue, output virtual resistance (VR) shaping is commonly employed to enhance system damping and improve power-sharing amongst distributed generators (DGs). The technique proposed in this work involves an adaptive variation of the DG virtual output resistance (<math>\u0000 <semantics>\u0000 <msub>\u0000 <mi>R</mi>\u0000 <mi>V</mi>\u0000 </msub>\u0000 <annotation>$R_{V}$</annotation>\u0000 </semantics></math>) linearly with the output current. This shows improved power sharing between sources. The work compares the small signal stability criteria and the minor loop gain methods for linear, non-linear, and inverse droop controllers to determine the controller parameters with constant power loads. The control scheme is extensively tested through simulations for four different droop control schemes. The work also validates the DCMG performance when the DERs work with different droop controllers (heterogenous of controllers) to assess constant power load penetration, performance in meshed configurations, and DG plug-and-play operations. Additionally, improved power sharing performance was validated through a controller hardware in the loop (CHIL) based implementation.","PeriodicalId":100467,"journal":{"name":"Energy Conversion and Economics","volume":"6 3","pages":"196-212"},"PeriodicalIF":0.0,"publicationDate":"2025-06-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1049/enc2.70013","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144492576","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Federated duelling deep Q-network based collaborative energy scheduling for a power distribution network 基于联合决斗深度q网络的配电网协同能源调度

Energy Conversion and Economics Pub Date : 2025-06-27 Epub Date: 2025-06-08 DOI: 10.1049/enc2.70012

Yanhong Yang, Wei Pei, Tianyi Xu, Dawei Wang, Abdelbari Redouane

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Adjustable robust optimization with decision-dependent uncertainty for power system problems: A review 具有决策依赖不确定性的电力系统问题可调鲁棒优化：综述

Energy Conversion and Economics Pub Date : 2025-06-27 Epub Date: 2025-05-20 DOI: 10.1049/enc2.70010

Tao Tan, Meng Yang, Rui Xie, Yuji Cao, Yue Chen

{"title":"Adjustable robust optimization with decision-dependent uncertainty for power system problems: A review","authors":"Tao Tan, Meng Yang, Rui Xie, Yuji Cao, Yue Chen","doi":"10.1049/enc2.70010","DOIUrl":"10.1049/enc2.70010","url":null,"abstract":"The increasing uncertainty caused by volatile renewable generation and random electricity demand has always been a critical challenge in power system operations. Robust optimization (RO) is a powerful tool for effectively addressing this uncertainty. As the interplay between uncertain factors and decision-making becomes more prevalent, RO with decision-dependent uncertainty (DDU) has attracted increasing attention. DDU significantly changes how the uncertainty set in RO is modelled and how the problems are solved. This study provides a comprehensive overview of the recent developments in RO with DDU for power system problems. We begin by introducing various models of DDU, classified according to their underlying causes. Next, we summarize the state-of-the-art solution algorithms for RO with DDU, such as variants of the column-and-constraint generation (C&CG) algorithm, variants of Benders decomposition, and multiparametric programming. Furthermore, we explore the application of RO with DDU in power systems. Based on our findings, we propose several research directions that may be valuable for future studies.","PeriodicalId":100467,"journal":{"name":"Energy Conversion and Economics","volume":"6 3","pages":"155-169"},"PeriodicalIF":0.0,"publicationDate":"2025-06-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1049/enc2.70010","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144493013","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Affinely adjustable robust optimal scheduling of a power system considering the flexibility of supply and demand 考虑供需灵活性的电力系统仿射可调鲁棒最优调度

Energy Conversion and Economics Pub Date : 2025-06-27 Epub Date: 2025-06-12 DOI: 10.1049/enc2.70011

Yumin Zhang, Yongchen Zhang, Xizhen Xue, Xingquan Ji, Yunqi Wang, Pingfeng Ye

{"title":"Affinely adjustable robust optimal scheduling of a power system considering the flexibility of supply and demand","authors":"Yumin Zhang, Yongchen Zhang, Xizhen Xue, Xingquan Ji, Yunqi Wang, Pingfeng Ye","doi":"10.1049/enc2.70011","DOIUrl":"10.1049/enc2.70011","url":null,"abstract":"As the integration of renewable energy sources, such as wind power and photovoltaics, continues, the issue of system uncertainty has become more pronounced. This paper proposes a stochastic power system dispatch method based on affinely adjustable robust optimization (AARO) with a generalized linear polyhedron (GLP) uncertainty set that can accurately quantify the flexibility of the power system supply and demand as well as enhance the optimality of dispatch strategies. First, a GLP uncertainty set was established to characterize both the temporal stochasticity and spatial correlation of multiple renewable energy outputs. A correlation envelope was employed to reflect renewable energy outputs from historical data, and a polyhedral set was proposed to accurately describe the uncertainty for model formulation, which can effectively reduce model conservatism by minimizing empty regions. Furthermore, the range of net load variations was analysed to build a demand flexibility quantification model for the power system. Next, based on the expected operational value, a robust optimization dispatch model that considers the flexible supply and demand balance is developed within the affine strategy framework. Finally, simulations of a modified 6-bus system and modified IEEE 57-bus system validate the effectiveness of the proposed GLP-AARO method for power system flexibility quantification and dispatch strategy optimization.","PeriodicalId":100467,"journal":{"name":"Energy Conversion and Economics","volume":"6 3","pages":"170-186"},"PeriodicalIF":0.0,"publicationDate":"2025-06-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1049/enc2.70011","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144492575","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

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Energy Conversion and Economics Pub Date : 2025-06-12

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Energy Conversion and Economics Pub Date : 2025-06-12

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Energy Conversion and Economics Pub Date : 2025-06-11

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Energy Conversion and Economics Pub Date : 2025-06-08

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Energy Conversion and Economics Pub Date : 2025-05-20

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