通过模糊优化为包含不确定可再生能源的智能电网设计优化的分散式点对点能源交易系统

IF 3.3 3区 工程技术 Q2 ENGINEERING, ELECTRICAL & ELECTRONIC Electric Power Systems Research Pub Date : 2024-10-16 DOI:10.1016/j.epsr.2024.111154
Nesar Uddin , Yingjun Wu , Md Saiful Islam , Khan Md Zakaria
{"title":"通过模糊优化为包含不确定可再生能源的智能电网设计优化的分散式点对点能源交易系统","authors":"Nesar Uddin ,&nbsp;Yingjun Wu ,&nbsp;Md Saiful Islam ,&nbsp;Khan Md Zakaria","doi":"10.1016/j.epsr.2024.111154","DOIUrl":null,"url":null,"abstract":"<div><div>The significant issue in today's world is that the power system is undergoing on account of unafforded power generation and distribution. Consequently, improper utilization of renewable energy, as well as its pricing mechanism of electrical energy, is also a vital issue in transmission and distribution systems (TDS). In addition, in the context of upcoming power systems, ensuring energy stability and effective energy management have become paramount. This paper introduces a novel approach to address these challenges by proposing an optimal demand response grid-connected decentralized peer-to-peer (P2P) energy trading system. This system efficiently manages energy transactions among prosumers, the grid, and renewable energy sources (RES) under uncertain conditions. Fuzzy optimization (FO) is employed to facilitate interconnections between these entities. A fuzzy logic controller with intelligent rules governs the overall strategy and pricing mechanism based on prosumer power deviation (PPD). Inspired by human thinking, these rules prioritize P2P transactions, with surplus energy exported to the main grid (MG) and energy imported from the MG when necessary. Pricing adjusts dynamically with load demand. Simulation results demonstrate the effectiveness of the fuzzy rules across various conditions, ensuring proper system operation. The proposed model also proves that the P2P energy trading system has reduced power consumption by balancing the generated power and the load demand. The proposed system is environmentally friendly, emitting no harmful gases.</div></div>","PeriodicalId":50547,"journal":{"name":"Electric Power Systems Research","volume":"238 ","pages":"Article 111154"},"PeriodicalIF":3.3000,"publicationDate":"2024-10-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"An optimized decentralized peer-to-peer energy trading system for smart grids incorporating uncertain renewable energy sources through fuzzy optimization\",\"authors\":\"Nesar Uddin ,&nbsp;Yingjun Wu ,&nbsp;Md Saiful Islam ,&nbsp;Khan Md Zakaria\",\"doi\":\"10.1016/j.epsr.2024.111154\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><div>The significant issue in today's world is that the power system is undergoing on account of unafforded power generation and distribution. Consequently, improper utilization of renewable energy, as well as its pricing mechanism of electrical energy, is also a vital issue in transmission and distribution systems (TDS). In addition, in the context of upcoming power systems, ensuring energy stability and effective energy management have become paramount. This paper introduces a novel approach to address these challenges by proposing an optimal demand response grid-connected decentralized peer-to-peer (P2P) energy trading system. This system efficiently manages energy transactions among prosumers, the grid, and renewable energy sources (RES) under uncertain conditions. Fuzzy optimization (FO) is employed to facilitate interconnections between these entities. A fuzzy logic controller with intelligent rules governs the overall strategy and pricing mechanism based on prosumer power deviation (PPD). Inspired by human thinking, these rules prioritize P2P transactions, with surplus energy exported to the main grid (MG) and energy imported from the MG when necessary. Pricing adjusts dynamically with load demand. Simulation results demonstrate the effectiveness of the fuzzy rules across various conditions, ensuring proper system operation. The proposed model also proves that the P2P energy trading system has reduced power consumption by balancing the generated power and the load demand. The proposed system is environmentally friendly, emitting no harmful gases.</div></div>\",\"PeriodicalId\":50547,\"journal\":{\"name\":\"Electric Power Systems Research\",\"volume\":\"238 \",\"pages\":\"Article 111154\"},\"PeriodicalIF\":3.3000,\"publicationDate\":\"2024-10-16\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Electric Power Systems Research\",\"FirstCategoryId\":\"5\",\"ListUrlMain\":\"https://www.sciencedirect.com/science/article/pii/S037877962401040X\",\"RegionNum\":3,\"RegionCategory\":\"工程技术\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q2\",\"JCRName\":\"ENGINEERING, ELECTRICAL & ELECTRONIC\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Electric Power Systems Research","FirstCategoryId":"5","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S037877962401040X","RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"ENGINEERING, ELECTRICAL & ELECTRONIC","Score":null,"Total":0}
引用次数: 0

摘要

当今世界的一个重要问题是,电力系统正在因发电和配电成本过高而出现问题。因此,可再生能源的不当利用及其电能定价机制也是输配电系统(TDS)中的一个重要问题。此外,在即将到来的电力系统背景下,确保能源稳定性和有效的能源管理已变得至关重要。本文提出了一种优化需求响应并网分散式点对点(P2P)能源交易系统,从而介绍了一种应对这些挑战的新方法。该系统能在不确定条件下有效管理用户、电网和可再生能源(RES)之间的能源交易。模糊优化(FO)被用来促进这些实体之间的相互联系。一个具有智能规则的模糊逻辑控制器管理着基于消费者电力偏差(PPD)的整体策略和定价机制。受人类思维的启发,这些规则优先考虑 P2P 交易,将多余的能源输出到主电网 (MG),并在必要时从 MG 输入能源。定价随负载需求动态调整。模拟结果证明了模糊规则在各种条件下的有效性,确保了系统的正常运行。提出的模型还证明,P2P 能源交易系统通过平衡发电量和负载需求,减少了电力消耗。建议的系统非常环保,不会排放有害气体。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
An optimized decentralized peer-to-peer energy trading system for smart grids incorporating uncertain renewable energy sources through fuzzy optimization
The significant issue in today's world is that the power system is undergoing on account of unafforded power generation and distribution. Consequently, improper utilization of renewable energy, as well as its pricing mechanism of electrical energy, is also a vital issue in transmission and distribution systems (TDS). In addition, in the context of upcoming power systems, ensuring energy stability and effective energy management have become paramount. This paper introduces a novel approach to address these challenges by proposing an optimal demand response grid-connected decentralized peer-to-peer (P2P) energy trading system. This system efficiently manages energy transactions among prosumers, the grid, and renewable energy sources (RES) under uncertain conditions. Fuzzy optimization (FO) is employed to facilitate interconnections between these entities. A fuzzy logic controller with intelligent rules governs the overall strategy and pricing mechanism based on prosumer power deviation (PPD). Inspired by human thinking, these rules prioritize P2P transactions, with surplus energy exported to the main grid (MG) and energy imported from the MG when necessary. Pricing adjusts dynamically with load demand. Simulation results demonstrate the effectiveness of the fuzzy rules across various conditions, ensuring proper system operation. The proposed model also proves that the P2P energy trading system has reduced power consumption by balancing the generated power and the load demand. The proposed system is environmentally friendly, emitting no harmful gases.
求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
来源期刊
Electric Power Systems Research
Electric Power Systems Research 工程技术-工程:电子与电气
CiteScore
7.50
自引率
17.90%
发文量
963
审稿时长
3.8 months
期刊介绍: Electric Power Systems Research is an international medium for the publication of original papers concerned with the generation, transmission, distribution and utilization of electrical energy. The journal aims at presenting important results of work in this field, whether in the form of applied research, development of new procedures or components, orginal application of existing knowledge or new designapproaches. The scope of Electric Power Systems Research is broad, encompassing all aspects of electric power systems. The following list of topics is not intended to be exhaustive, but rather to indicate topics that fall within the journal purview. • Generation techniques ranging from advances in conventional electromechanical methods, through nuclear power generation, to renewable energy generation. • Transmission, spanning the broad area from UHV (ac and dc) to network operation and protection, line routing and design. • Substation work: equipment design, protection and control systems. • Distribution techniques, equipment development, and smart grids. • The utilization area from energy efficiency to distributed load levelling techniques. • Systems studies including control techniques, planning, optimization methods, stability, security assessment and insulation coordination.
期刊最新文献
Efficient handling of radiality constraints for large-scaled power distribution networks Graph topology-constrained BILP for optimal PMU placements Evaluation of reliability and resilience in wind integrated power systems using 80 meter mast measurements A novel method to enhance partial discharge localization accuracy using sectional winding analysis and a neural network-based learning vector quantization model Evaluating synchrophasor-enabled angle-based differential protection in distribution networks
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 联系我们:info@booksci.cn
Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。
Copyright © 2023 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1