{"title":"基于分布式鲁棒优化的互联城市综合能源和输电系统协调调度","authors":"Wei Xu;Yufeng Guo;Tianhui Meng;Yingwei Wang;Jilai Yu","doi":"10.35833/MPCE.2023.000255","DOIUrl":null,"url":null,"abstract":"To improve the economic efficiency of urban integrated energy systems (UIESs) and mitigate day-ahead dispatch uncertainty, this paper presents an interconnected UIES and transmission system (TS) model based on distributed robust optimization. First, interconnections are established between a TS and multiple UIESs, as well as among different UIESs, each incorporating multiple energy forms. The Bregman alternating direction method with multipliers (BADMM) is then applied to multi-block problems, ensuring the privacy of each energy system operator (ESO). Second, robust optimization based on wind probability distribution information is implemented for each ESO to address dispatch uncertainty. The column and constraint generation (C&CG) algorithm is then employed to solve the robust model. Third, to tackle the convergence and practicability issues overlooked in the existing studies, an external C&CG with an internal BADMM and corresponding acceleration strategy is devised. Finally, numerical results demonstrate that the adoption of the proposed model and method for absorbing wind power and managing its uncertainty results in economic benefits.","PeriodicalId":51326,"journal":{"name":"Journal of Modern Power Systems and Clean Energy","volume":"12 3","pages":"840-851"},"PeriodicalIF":5.7000,"publicationDate":"2024-03-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10460469","citationCount":"0","resultStr":"{\"title\":\"Coordinated Dispatch Based on Distributed Robust Optimization for Interconnected Urban Integrated Energy and Transmission Systems\",\"authors\":\"Wei Xu;Yufeng Guo;Tianhui Meng;Yingwei Wang;Jilai Yu\",\"doi\":\"10.35833/MPCE.2023.000255\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"To improve the economic efficiency of urban integrated energy systems (UIESs) and mitigate day-ahead dispatch uncertainty, this paper presents an interconnected UIES and transmission system (TS) model based on distributed robust optimization. First, interconnections are established between a TS and multiple UIESs, as well as among different UIESs, each incorporating multiple energy forms. The Bregman alternating direction method with multipliers (BADMM) is then applied to multi-block problems, ensuring the privacy of each energy system operator (ESO). Second, robust optimization based on wind probability distribution information is implemented for each ESO to address dispatch uncertainty. The column and constraint generation (C&CG) algorithm is then employed to solve the robust model. Third, to tackle the convergence and practicability issues overlooked in the existing studies, an external C&CG with an internal BADMM and corresponding acceleration strategy is devised. Finally, numerical results demonstrate that the adoption of the proposed model and method for absorbing wind power and managing its uncertainty results in economic benefits.\",\"PeriodicalId\":51326,\"journal\":{\"name\":\"Journal of Modern Power Systems and Clean Energy\",\"volume\":\"12 3\",\"pages\":\"840-851\"},\"PeriodicalIF\":5.7000,\"publicationDate\":\"2024-03-05\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10460469\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Journal of Modern Power Systems and Clean Energy\",\"FirstCategoryId\":\"5\",\"ListUrlMain\":\"https://ieeexplore.ieee.org/document/10460469/\",\"RegionNum\":1,\"RegionCategory\":\"工程技术\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"ENGINEERING, ELECTRICAL & ELECTRONIC\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Modern Power Systems and Clean Energy","FirstCategoryId":"5","ListUrlMain":"https://ieeexplore.ieee.org/document/10460469/","RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"ENGINEERING, ELECTRICAL & ELECTRONIC","Score":null,"Total":0}
Coordinated Dispatch Based on Distributed Robust Optimization for Interconnected Urban Integrated Energy and Transmission Systems
To improve the economic efficiency of urban integrated energy systems (UIESs) and mitigate day-ahead dispatch uncertainty, this paper presents an interconnected UIES and transmission system (TS) model based on distributed robust optimization. First, interconnections are established between a TS and multiple UIESs, as well as among different UIESs, each incorporating multiple energy forms. The Bregman alternating direction method with multipliers (BADMM) is then applied to multi-block problems, ensuring the privacy of each energy system operator (ESO). Second, robust optimization based on wind probability distribution information is implemented for each ESO to address dispatch uncertainty. The column and constraint generation (C&CG) algorithm is then employed to solve the robust model. Third, to tackle the convergence and practicability issues overlooked in the existing studies, an external C&CG with an internal BADMM and corresponding acceleration strategy is devised. Finally, numerical results demonstrate that the adoption of the proposed model and method for absorbing wind power and managing its uncertainty results in economic benefits.
期刊介绍:
Journal of Modern Power Systems and Clean Energy (MPCE), commencing from June, 2013, is a newly established, peer-reviewed and quarterly published journal in English. It is the first international power engineering journal originated in mainland China. MPCE publishes original papers, short letters and review articles in the field of modern power systems with focus on smart grid technology and renewable energy integration, etc.