Abeer Mohammed Alazab, Hamdy Kanaan, Mohammed I. Elsayed
{"title":"采用puma优化算法优化配电网的规模和配置,提高电压稳定指标,降低功率损耗","authors":"Abeer Mohammed Alazab, Hamdy Kanaan, Mohammed I. Elsayed","doi":"10.1016/j.sciaf.2025.e02920","DOIUrl":null,"url":null,"abstract":"<div><div>The incorporation of Distributed Generation (DG) units into radial distribution networks (RDNs) is a proven strategy to mitigate power losses and enhance voltage stability. However, the efficacy of DG integration heavily depends on optimal placement and sizing, which remains a complex optimization challenge. This study introduces the novel Puma Optimization Algorithm (POA) to address the optimal location of three DG types—Type-1 (active power), Type-2 (reactive power), and Type-3 (active and reactive power)—in IEEE 33 and 69-buses RDNs. POA, drawing inspiration from the foraging behavior of pumas, dynamically balances exploration and exploitation to reduce power losses and enhance the Voltage Stability Index (VSI). Results demonstrate POA’s superior performance compared to established algorithms like BSOA, CSFS, GA, and hybrid techniques. For the IEEE 33-bus, POA achieved a 48.77 % loss reduction with Type-1 DG (single unit), 65.83 % with multiple Type-1 units, and 94.45 % with Type-3 units, alongside significant VSI improvements (up to 0.9705 pu). In the IEEE 69-bus, POA reduced losses by 80.11 % (Type-1) and 80.05 % (Type-3), with VSI reaching 0.9772 pu. Type-3 DG consistently outperformed other types, underscoring its dual-power capability for stability enhancement. The study validates POA as a robust tool for DG location, offering utilities a scalable solution to enhance grid efficiency and reliability. Key contributions include a comparative analysis of DG types, a novel metaheuristic approach, and actionable insights for real-world deployment.</div></div>","PeriodicalId":21690,"journal":{"name":"Scientific African","volume":"29 ","pages":"Article e02920"},"PeriodicalIF":3.3000,"publicationDate":"2025-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Enhancing voltage stability index and reducing power loss through optimal sizing and placing of distribution generation types using puma optimization algorithm\",\"authors\":\"Abeer Mohammed Alazab, Hamdy Kanaan, Mohammed I. Elsayed\",\"doi\":\"10.1016/j.sciaf.2025.e02920\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><div>The incorporation of Distributed Generation (DG) units into radial distribution networks (RDNs) is a proven strategy to mitigate power losses and enhance voltage stability. However, the efficacy of DG integration heavily depends on optimal placement and sizing, which remains a complex optimization challenge. This study introduces the novel Puma Optimization Algorithm (POA) to address the optimal location of three DG types—Type-1 (active power), Type-2 (reactive power), and Type-3 (active and reactive power)—in IEEE 33 and 69-buses RDNs. POA, drawing inspiration from the foraging behavior of pumas, dynamically balances exploration and exploitation to reduce power losses and enhance the Voltage Stability Index (VSI). Results demonstrate POA’s superior performance compared to established algorithms like BSOA, CSFS, GA, and hybrid techniques. For the IEEE 33-bus, POA achieved a 48.77 % loss reduction with Type-1 DG (single unit), 65.83 % with multiple Type-1 units, and 94.45 % with Type-3 units, alongside significant VSI improvements (up to 0.9705 pu). In the IEEE 69-bus, POA reduced losses by 80.11 % (Type-1) and 80.05 % (Type-3), with VSI reaching 0.9772 pu. Type-3 DG consistently outperformed other types, underscoring its dual-power capability for stability enhancement. The study validates POA as a robust tool for DG location, offering utilities a scalable solution to enhance grid efficiency and reliability. Key contributions include a comparative analysis of DG types, a novel metaheuristic approach, and actionable insights for real-world deployment.</div></div>\",\"PeriodicalId\":21690,\"journal\":{\"name\":\"Scientific African\",\"volume\":\"29 \",\"pages\":\"Article e02920\"},\"PeriodicalIF\":3.3000,\"publicationDate\":\"2025-09-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Scientific African\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://www.sciencedirect.com/science/article/pii/S2468227625003904\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q2\",\"JCRName\":\"MULTIDISCIPLINARY SCIENCES\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Scientific African","FirstCategoryId":"1085","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S2468227625003904","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"MULTIDISCIPLINARY SCIENCES","Score":null,"Total":0}
Enhancing voltage stability index and reducing power loss through optimal sizing and placing of distribution generation types using puma optimization algorithm
The incorporation of Distributed Generation (DG) units into radial distribution networks (RDNs) is a proven strategy to mitigate power losses and enhance voltage stability. However, the efficacy of DG integration heavily depends on optimal placement and sizing, which remains a complex optimization challenge. This study introduces the novel Puma Optimization Algorithm (POA) to address the optimal location of three DG types—Type-1 (active power), Type-2 (reactive power), and Type-3 (active and reactive power)—in IEEE 33 and 69-buses RDNs. POA, drawing inspiration from the foraging behavior of pumas, dynamically balances exploration and exploitation to reduce power losses and enhance the Voltage Stability Index (VSI). Results demonstrate POA’s superior performance compared to established algorithms like BSOA, CSFS, GA, and hybrid techniques. For the IEEE 33-bus, POA achieved a 48.77 % loss reduction with Type-1 DG (single unit), 65.83 % with multiple Type-1 units, and 94.45 % with Type-3 units, alongside significant VSI improvements (up to 0.9705 pu). In the IEEE 69-bus, POA reduced losses by 80.11 % (Type-1) and 80.05 % (Type-3), with VSI reaching 0.9772 pu. Type-3 DG consistently outperformed other types, underscoring its dual-power capability for stability enhancement. The study validates POA as a robust tool for DG location, offering utilities a scalable solution to enhance grid efficiency and reliability. Key contributions include a comparative analysis of DG types, a novel metaheuristic approach, and actionable insights for real-world deployment.