{"title":"基于蜂群智能的电热协调控制,实现零通信负担的电压稳定","authors":"Qi Qi, Haobo Guo, Xueying Yang, Deying Zhang, Xin Ai, Bing Qi, Yu Fu, Yue Li","doi":"10.1049/gtd2.13230","DOIUrl":null,"url":null,"abstract":"<p>The movement towards electrification is entailing deep changes in power systems. On the demand side, the adoption of electric heating (EH) has grown rapidly in recent years. To eliminate the voltage fluctuations caused by the random switching-on/-off behaviors of EHs in some application scenes with special-power-line in low voltage distribution networks (LVDNs), a swarm-intelligence-based coordinated control approach of EHs for voltage stabilization with zero communication burden while guaranteeing the users’ thermal comforts is researched. A novel bird-perch-on-branch (BPB) -based swarm intelligence theory is proposed, which reveals the mapping relation between local observations and global states. On this theoretical basis, a multi-agent reinforcement learning (MARL) framework is developed for the coordinated dispatch of EHs, where the deep-Q-network (DQN) algorithm is adopted to learn and generate the optimal control policy for each EH. The implementation of the proposed MADQN-BPB approach is described based on the principle of centralized-training and decentralized-execution. Comparative control performances of MADQN-BPB with a commercially available approach, and the global optimal solution are evaluated. Simulation results verify the capability of MADQN-BPB in voltage stabilization with zero communication burden. Its control performance is close to that of the global optimal solution, and is scalable to the variations of environment.</p>","PeriodicalId":13261,"journal":{"name":"Iet Generation Transmission & Distribution","volume":null,"pages":null},"PeriodicalIF":2.0000,"publicationDate":"2024-08-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1049/gtd2.13230","citationCount":"0","resultStr":"{\"title\":\"Swarm-intelligence-based coordinated control of electric heatings for voltage stabilization with zero communication burden\",\"authors\":\"Qi Qi, Haobo Guo, Xueying Yang, Deying Zhang, Xin Ai, Bing Qi, Yu Fu, Yue Li\",\"doi\":\"10.1049/gtd2.13230\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p>The movement towards electrification is entailing deep changes in power systems. On the demand side, the adoption of electric heating (EH) has grown rapidly in recent years. To eliminate the voltage fluctuations caused by the random switching-on/-off behaviors of EHs in some application scenes with special-power-line in low voltage distribution networks (LVDNs), a swarm-intelligence-based coordinated control approach of EHs for voltage stabilization with zero communication burden while guaranteeing the users’ thermal comforts is researched. A novel bird-perch-on-branch (BPB) -based swarm intelligence theory is proposed, which reveals the mapping relation between local observations and global states. On this theoretical basis, a multi-agent reinforcement learning (MARL) framework is developed for the coordinated dispatch of EHs, where the deep-Q-network (DQN) algorithm is adopted to learn and generate the optimal control policy for each EH. The implementation of the proposed MADQN-BPB approach is described based on the principle of centralized-training and decentralized-execution. Comparative control performances of MADQN-BPB with a commercially available approach, and the global optimal solution are evaluated. Simulation results verify the capability of MADQN-BPB in voltage stabilization with zero communication burden. Its control performance is close to that of the global optimal solution, and is scalable to the variations of environment.</p>\",\"PeriodicalId\":13261,\"journal\":{\"name\":\"Iet Generation Transmission & Distribution\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":2.0000,\"publicationDate\":\"2024-08-09\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://onlinelibrary.wiley.com/doi/epdf/10.1049/gtd2.13230\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Iet Generation Transmission & Distribution\",\"FirstCategoryId\":\"5\",\"ListUrlMain\":\"https://onlinelibrary.wiley.com/doi/10.1049/gtd2.13230\",\"RegionNum\":4,\"RegionCategory\":\"工程技术\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q3\",\"JCRName\":\"ENGINEERING, ELECTRICAL & ELECTRONIC\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Iet Generation Transmission & Distribution","FirstCategoryId":"5","ListUrlMain":"https://onlinelibrary.wiley.com/doi/10.1049/gtd2.13230","RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"ENGINEERING, ELECTRICAL & ELECTRONIC","Score":null,"Total":0}
Swarm-intelligence-based coordinated control of electric heatings for voltage stabilization with zero communication burden
The movement towards electrification is entailing deep changes in power systems. On the demand side, the adoption of electric heating (EH) has grown rapidly in recent years. To eliminate the voltage fluctuations caused by the random switching-on/-off behaviors of EHs in some application scenes with special-power-line in low voltage distribution networks (LVDNs), a swarm-intelligence-based coordinated control approach of EHs for voltage stabilization with zero communication burden while guaranteeing the users’ thermal comforts is researched. A novel bird-perch-on-branch (BPB) -based swarm intelligence theory is proposed, which reveals the mapping relation between local observations and global states. On this theoretical basis, a multi-agent reinforcement learning (MARL) framework is developed for the coordinated dispatch of EHs, where the deep-Q-network (DQN) algorithm is adopted to learn and generate the optimal control policy for each EH. The implementation of the proposed MADQN-BPB approach is described based on the principle of centralized-training and decentralized-execution. Comparative control performances of MADQN-BPB with a commercially available approach, and the global optimal solution are evaluated. Simulation results verify the capability of MADQN-BPB in voltage stabilization with zero communication burden. Its control performance is close to that of the global optimal solution, and is scalable to the variations of environment.
期刊介绍:
IET Generation, Transmission & Distribution is intended as a forum for the publication and discussion of current practice and future developments in electric power generation, transmission and distribution. Practical papers in which examples of good present practice can be described and disseminated are particularly sought. Papers of high technical merit relying on mathematical arguments and computation will be considered, but authors are asked to relegate, as far as possible, the details of analysis to an appendix.
The scope of IET Generation, Transmission & Distribution includes the following:
Design of transmission and distribution systems
Operation and control of power generation
Power system management, planning and economics
Power system operation, protection and control
Power system measurement and modelling
Computer applications and computational intelligence in power flexible AC or DC transmission systems
Special Issues. Current Call for papers:
Next Generation of Synchrophasor-based Power System Monitoring, Operation and Control - https://digital-library.theiet.org/files/IET_GTD_CFP_NGSPSMOC.pdf