Mohamed Goda, Mazen Abdel-Salam, Mohamed-Tharwat EL-Mohandes, Ahmed Elnozahy
{"title":"自愈智能配电系统的供电恢复研究进展","authors":"Mohamed Goda, Mazen Abdel-Salam, Mohamed-Tharwat EL-Mohandes, Ahmed Elnozahy","doi":"10.1186/s42162-025-00541-5","DOIUrl":null,"url":null,"abstract":"<div><p>System restoration is aimed at ensuring continuity of the electric supply to all loads in a distribution system under abnormal conditions without violating electrical-constraints. This adds the feature of “self-healing” to the distribution system to make it as smart system. This paper presents a literature survey of published research techniques on electric supply restoration over the period 1981–2024. Four categories of distribution systems with different attributes are proposed by the present authors to compare fairly among these techniques through implementation and running the necessary codes for each restoration technique. Comparisons are concerned with contribution, adopted technique, test model, advantages and disadvantages as well as utilization of renewables. To meet the electrical-constraints on electric supply restoration, fifteen challenges are selected, reviewed and discussed within the comparisons. The algorithms based on graph theory showed better performance regarding the challenges related to minimizing the energy-not-supplied, achieving self-healing dream, preventing feeder overloading and maintaining the voltage profile within limits when compared with other algorithms. The algorithms based on linear and nonlinear programming showed better performance concerning the challenges related to minimizing restoration time and preventing in-supply load shedding when compared with other algorithms. The algorithms based on heuristics and metaheuristics showed better performance concerning the challenges related to system configuration, generating optimal sequence of switches, minimizing the number of ordered switches and reducing the restoration cost when compared with other algorithms. The future trends of the supply restoration in smart distribution systems are also discussed. The present survey is concluded with a summary of the findings from the literature survey and outlines potential directions for future research. It highlights the key opportunities to support researchers in advancing more intelligent restoration strategies for electric supply in smart distribution systems.</p></div>","PeriodicalId":538,"journal":{"name":"Energy Informatics","volume":"8 1","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2025-09-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://energyinformatics.springeropen.com/counter/pdf/10.1186/s42162-025-00541-5","citationCount":"0","resultStr":"{\"title\":\"Electric supply restoration in self-healed smart distribution systems: a review\",\"authors\":\"Mohamed Goda, Mazen Abdel-Salam, Mohamed-Tharwat EL-Mohandes, Ahmed Elnozahy\",\"doi\":\"10.1186/s42162-025-00541-5\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><p>System restoration is aimed at ensuring continuity of the electric supply to all loads in a distribution system under abnormal conditions without violating electrical-constraints. This adds the feature of “self-healing” to the distribution system to make it as smart system. This paper presents a literature survey of published research techniques on electric supply restoration over the period 1981–2024. Four categories of distribution systems with different attributes are proposed by the present authors to compare fairly among these techniques through implementation and running the necessary codes for each restoration technique. Comparisons are concerned with contribution, adopted technique, test model, advantages and disadvantages as well as utilization of renewables. To meet the electrical-constraints on electric supply restoration, fifteen challenges are selected, reviewed and discussed within the comparisons. The algorithms based on graph theory showed better performance regarding the challenges related to minimizing the energy-not-supplied, achieving self-healing dream, preventing feeder overloading and maintaining the voltage profile within limits when compared with other algorithms. The algorithms based on linear and nonlinear programming showed better performance concerning the challenges related to minimizing restoration time and preventing in-supply load shedding when compared with other algorithms. The algorithms based on heuristics and metaheuristics showed better performance concerning the challenges related to system configuration, generating optimal sequence of switches, minimizing the number of ordered switches and reducing the restoration cost when compared with other algorithms. The future trends of the supply restoration in smart distribution systems are also discussed. The present survey is concluded with a summary of the findings from the literature survey and outlines potential directions for future research. It highlights the key opportunities to support researchers in advancing more intelligent restoration strategies for electric supply in smart distribution systems.</p></div>\",\"PeriodicalId\":538,\"journal\":{\"name\":\"Energy Informatics\",\"volume\":\"8 1\",\"pages\":\"\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2025-09-15\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://energyinformatics.springeropen.com/counter/pdf/10.1186/s42162-025-00541-5\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Energy Informatics\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://link.springer.com/article/10.1186/s42162-025-00541-5\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q2\",\"JCRName\":\"Energy\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Energy Informatics","FirstCategoryId":"1085","ListUrlMain":"https://link.springer.com/article/10.1186/s42162-025-00541-5","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"Energy","Score":null,"Total":0}
Electric supply restoration in self-healed smart distribution systems: a review
System restoration is aimed at ensuring continuity of the electric supply to all loads in a distribution system under abnormal conditions without violating electrical-constraints. This adds the feature of “self-healing” to the distribution system to make it as smart system. This paper presents a literature survey of published research techniques on electric supply restoration over the period 1981–2024. Four categories of distribution systems with different attributes are proposed by the present authors to compare fairly among these techniques through implementation and running the necessary codes for each restoration technique. Comparisons are concerned with contribution, adopted technique, test model, advantages and disadvantages as well as utilization of renewables. To meet the electrical-constraints on electric supply restoration, fifteen challenges are selected, reviewed and discussed within the comparisons. The algorithms based on graph theory showed better performance regarding the challenges related to minimizing the energy-not-supplied, achieving self-healing dream, preventing feeder overloading and maintaining the voltage profile within limits when compared with other algorithms. The algorithms based on linear and nonlinear programming showed better performance concerning the challenges related to minimizing restoration time and preventing in-supply load shedding when compared with other algorithms. The algorithms based on heuristics and metaheuristics showed better performance concerning the challenges related to system configuration, generating optimal sequence of switches, minimizing the number of ordered switches and reducing the restoration cost when compared with other algorithms. The future trends of the supply restoration in smart distribution systems are also discussed. The present survey is concluded with a summary of the findings from the literature survey and outlines potential directions for future research. It highlights the key opportunities to support researchers in advancing more intelligent restoration strategies for electric supply in smart distribution systems.