{"title":"基于混合粒子群优化和引力搜索算法的最优AGC方案设计","authors":"N. Kouba, M. Menaa, M. Hasni, M. Boudour","doi":"10.1504/IJPEC.2019.10017464","DOIUrl":null,"url":null,"abstract":"In this paper, a novel hybrid particle swarm optimisation and gravitational search algorithm (HPSO-GSA) is proposed to design an optimal automatic generation control (AGC) scheme in interconnected power system. The proposed algorithm combines the advantages of both particle swarm optimisation (PSO) and gravitational search algorithm (GSA). This new meta-heuristic HPSO-GSA is applied to achieve the optimal proportional-integral-derivative (PID) controller parameters. Hence, the optimal PID controller is used to reduce the system fluctuations with the best dynamic performances. The AGC issue is formulated as an optimal load frequency control problem, where the frequency fluctuations and the tie-line power flow deviations are to be minimised in the same time. In order to test the performance of the proposed HPSO-GSA strategy, the integral time multiplied by absolute error (ITAE) is used as an objective function. To evaluate the efficiency of the proposed approach over disturbances, the standard two-area power system is used for the simulation. The obtained simulation results are compared to those yielded using classical and heuristic optimisation techniques surfaced in the recent state-of-the-art literature. The comparative study demonstrates the potential of the proposed strategy and shows its robustness to solve the optimal AGC problem.","PeriodicalId":38524,"journal":{"name":"International Journal of Power and Energy Conversion","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2019-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"3","resultStr":"{\"title\":\"Optimal AGC Scheme Design Using Hybrid Particle Swarm Optimisation and Gravitational Search Algorithm\",\"authors\":\"N. Kouba, M. Menaa, M. Hasni, M. Boudour\",\"doi\":\"10.1504/IJPEC.2019.10017464\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In this paper, a novel hybrid particle swarm optimisation and gravitational search algorithm (HPSO-GSA) is proposed to design an optimal automatic generation control (AGC) scheme in interconnected power system. The proposed algorithm combines the advantages of both particle swarm optimisation (PSO) and gravitational search algorithm (GSA). This new meta-heuristic HPSO-GSA is applied to achieve the optimal proportional-integral-derivative (PID) controller parameters. Hence, the optimal PID controller is used to reduce the system fluctuations with the best dynamic performances. The AGC issue is formulated as an optimal load frequency control problem, where the frequency fluctuations and the tie-line power flow deviations are to be minimised in the same time. In order to test the performance of the proposed HPSO-GSA strategy, the integral time multiplied by absolute error (ITAE) is used as an objective function. To evaluate the efficiency of the proposed approach over disturbances, the standard two-area power system is used for the simulation. The obtained simulation results are compared to those yielded using classical and heuristic optimisation techniques surfaced in the recent state-of-the-art literature. The comparative study demonstrates the potential of the proposed strategy and shows its robustness to solve the optimal AGC problem.\",\"PeriodicalId\":38524,\"journal\":{\"name\":\"International Journal of Power and Energy Conversion\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2019-04-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"3\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"International Journal of Power and Energy Conversion\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1504/IJPEC.2019.10017464\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q3\",\"JCRName\":\"Energy\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"International Journal of Power and Energy Conversion","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1504/IJPEC.2019.10017464","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"Energy","Score":null,"Total":0}
Optimal AGC Scheme Design Using Hybrid Particle Swarm Optimisation and Gravitational Search Algorithm
In this paper, a novel hybrid particle swarm optimisation and gravitational search algorithm (HPSO-GSA) is proposed to design an optimal automatic generation control (AGC) scheme in interconnected power system. The proposed algorithm combines the advantages of both particle swarm optimisation (PSO) and gravitational search algorithm (GSA). This new meta-heuristic HPSO-GSA is applied to achieve the optimal proportional-integral-derivative (PID) controller parameters. Hence, the optimal PID controller is used to reduce the system fluctuations with the best dynamic performances. The AGC issue is formulated as an optimal load frequency control problem, where the frequency fluctuations and the tie-line power flow deviations are to be minimised in the same time. In order to test the performance of the proposed HPSO-GSA strategy, the integral time multiplied by absolute error (ITAE) is used as an objective function. To evaluate the efficiency of the proposed approach over disturbances, the standard two-area power system is used for the simulation. The obtained simulation results are compared to those yielded using classical and heuristic optimisation techniques surfaced in the recent state-of-the-art literature. The comparative study demonstrates the potential of the proposed strategy and shows its robustness to solve the optimal AGC problem.
期刊介绍:
IJPEC highlights the latest trends in research in the field of power generation, transmission and distribution. Currently there exist significant challenges in the power sector, particularly in deregulated/restructured power markets. A key challenge to the operation, control and protection of the power system is the proliferation of power electronic devices within power systems. The main thrust of IJPEC is to disseminate the latest research trends in the power sector as well as in energy conversion technologies. Topics covered include: -Power system modelling and analysis -Computing and economics -FACTS and HVDC -Challenges in restructured energy systems -Power system control, operation, communications, SCADA -Power system relaying/protection -Energy management systems/distribution automation -Applications of power electronics to power systems -Power quality -Distributed generation and renewable energy sources -Electrical machines and drives -Utilisation of electrical energy -Modelling and control of machines -Fault diagnosis in machines and drives -Special machines