{"title":"基于混合非洲秃鹫优化算法和模式搜索调谐模糊PID控制器的电动汽车电力系统频率控制","authors":"P M Dash, A K Baliarsingh, Sangram K Mohapatra","doi":"10.4108/ew.135","DOIUrl":null,"url":null,"abstract":"This work suggests a hybrid African Vultures Optimization Algorithm (AVOA) and Pattern search (hAVOA-PS) based Fuzzy PID (FPID) structure for frequency control of a nonlinear power system with Electric Vehicles (EVs). To illustrate the dominance of the projected hAVOA-PS algorithm, initially PI controllers are considered and results are compared with AVOA, Genetic Algorithm (GA) and Particle Swarm Optimization (PSO) methods. To further enhance the dynamic performance, PID and FPID controllers are considered. The dominance of FPID over PID and PI controllers is shown. In the next step, EVs are incorporated in the test system and a comparative analysis of hAVOA-PS based PI/PID/FPID and FPID+EV is presented. To exhibit the superiority of projected frequency control scheme in maintaining the stability of system under different disturbance conditions like load increase in area-1 only, load decrease/increase in all areas, and large load increase in all areas are considered. It is noticed that the suggested hAVOA-PS based FPID controller n presence of EV is able to maintain system stability for all the considered cases where as other compared approaches fail to maintain stability in some cases.","PeriodicalId":53458,"journal":{"name":"EAI Endorsed Transactions on Energy Web","volume":"178 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2023-10-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Frequency control of power system with electric vehicles using hybrid african vultures optimization algorithm and pattern search tuned fuzzy PID controller\",\"authors\":\"P M Dash, A K Baliarsingh, Sangram K Mohapatra\",\"doi\":\"10.4108/ew.135\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This work suggests a hybrid African Vultures Optimization Algorithm (AVOA) and Pattern search (hAVOA-PS) based Fuzzy PID (FPID) structure for frequency control of a nonlinear power system with Electric Vehicles (EVs). To illustrate the dominance of the projected hAVOA-PS algorithm, initially PI controllers are considered and results are compared with AVOA, Genetic Algorithm (GA) and Particle Swarm Optimization (PSO) methods. To further enhance the dynamic performance, PID and FPID controllers are considered. The dominance of FPID over PID and PI controllers is shown. In the next step, EVs are incorporated in the test system and a comparative analysis of hAVOA-PS based PI/PID/FPID and FPID+EV is presented. To exhibit the superiority of projected frequency control scheme in maintaining the stability of system under different disturbance conditions like load increase in area-1 only, load decrease/increase in all areas, and large load increase in all areas are considered. It is noticed that the suggested hAVOA-PS based FPID controller n presence of EV is able to maintain system stability for all the considered cases where as other compared approaches fail to maintain stability in some cases.\",\"PeriodicalId\":53458,\"journal\":{\"name\":\"EAI Endorsed Transactions on Energy Web\",\"volume\":\"178 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2023-10-30\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"EAI Endorsed Transactions on Energy Web\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.4108/ew.135\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q3\",\"JCRName\":\"Engineering\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"EAI Endorsed Transactions on Energy Web","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.4108/ew.135","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"Engineering","Score":null,"Total":0}
Frequency control of power system with electric vehicles using hybrid african vultures optimization algorithm and pattern search tuned fuzzy PID controller
This work suggests a hybrid African Vultures Optimization Algorithm (AVOA) and Pattern search (hAVOA-PS) based Fuzzy PID (FPID) structure for frequency control of a nonlinear power system with Electric Vehicles (EVs). To illustrate the dominance of the projected hAVOA-PS algorithm, initially PI controllers are considered and results are compared with AVOA, Genetic Algorithm (GA) and Particle Swarm Optimization (PSO) methods. To further enhance the dynamic performance, PID and FPID controllers are considered. The dominance of FPID over PID and PI controllers is shown. In the next step, EVs are incorporated in the test system and a comparative analysis of hAVOA-PS based PI/PID/FPID and FPID+EV is presented. To exhibit the superiority of projected frequency control scheme in maintaining the stability of system under different disturbance conditions like load increase in area-1 only, load decrease/increase in all areas, and large load increase in all areas are considered. It is noticed that the suggested hAVOA-PS based FPID controller n presence of EV is able to maintain system stability for all the considered cases where as other compared approaches fail to maintain stability in some cases.
期刊介绍:
With ICT pervading everyday objects and infrastructures, the ‘Future Internet’ is envisioned to undergo a radical transformation from how we know it today (a mere communication highway) into a vast hybrid network seamlessly integrating knowledge, people and machines into techno-social ecosystems whose behaviour transcends the boundaries of today’s engineering science. As the internet of things continues to grow, billions and trillions of data bytes need to be moved, stored and shared. The energy thus consumed and the climate impact of data centers are increasing dramatically, thereby becoming significant contributors to global warming and climate change. As reported recently, the combined electricity consumption of the world’s data centers has already exceeded that of some of the world''s top ten economies. In the ensuing process of integrating traditional and renewable energy, monitoring and managing various energy sources, and processing and transferring technological information through various channels, IT will undoubtedly play an ever-increasing and central role. Several technologies are currently racing to production to meet this challenge, from ‘smart dust’ to hybrid networks capable of controlling the emergence of dependable and reliable green and energy-efficient ecosystems – which we generically term the ‘energy web’ – calling for major paradigm shifts highly disruptive of the ways the energy sector functions today. The EAI Transactions on Energy Web are positioned at the forefront of these efforts and provide a forum for the most forward-looking, state-of-the-art research bringing together the cross section of IT and Energy communities. The journal will publish original works reporting on prominent advances that challenge traditional thinking.