This paper validates the optimal operation for a grid-connected double-fed induction generator(DFIG)in an oscillating water column power plant(OWCPP).This study presents a novel optimization technique called the circu...This paper validates the optimal operation for a grid-connected double-fed induction generator(DFIG)in an oscillating water column power plant(OWCPP).This study presents a novel optimization technique called the circulatory system-based optimization(CSBO)approach to develop six adaptive fuzzy logic controllers(AFLCs)with 30 parameters and compare them to chaotic-billiards optimization(C-BO)and genetic algorithm(GA).The proposed controller is also compared with a proportional-integral differential(PID)controller based on a self-adaptive global-best harmony search(SGHS).CSBO-based AFLCs are fully investigated under different scenarios and experimented with using a real-time interface DSP1104.The results of using CSBO-AFLCs revealed a fast time response,fast convergence,less overshoot and minimal error compared with those achieved with C-BO-AFLC,SGHS-PID and GA-AFLC during different case studies.The CSBO-based AFLCs ensure maximum power from the DFIG in an OWCPP and enhance dynamic response with very low errors.The results show that the CSBO shows better power tracking by 25%as compared with C-BO,by 45%when compared with the GA and by 56%when compared with PID.Moreover,the integral absolute errors of six controllers are investigated to demonstrate the feasibility of CSBO-AFLC.The root mean square of the errors of six controllers using CSBO is improved by 68.27%when compared with GA,by 22.57%when compared with C-BO and by 38.42%when compared with PID.These indicators demonstrate the feasibility of CSBO when compared with other algorithms with the same OWCPP.展开更多
文摘This paper validates the optimal operation for a grid-connected double-fed induction generator(DFIG)in an oscillating water column power plant(OWCPP).This study presents a novel optimization technique called the circulatory system-based optimization(CSBO)approach to develop six adaptive fuzzy logic controllers(AFLCs)with 30 parameters and compare them to chaotic-billiards optimization(C-BO)and genetic algorithm(GA).The proposed controller is also compared with a proportional-integral differential(PID)controller based on a self-adaptive global-best harmony search(SGHS).CSBO-based AFLCs are fully investigated under different scenarios and experimented with using a real-time interface DSP1104.The results of using CSBO-AFLCs revealed a fast time response,fast convergence,less overshoot and minimal error compared with those achieved with C-BO-AFLC,SGHS-PID and GA-AFLC during different case studies.The CSBO-based AFLCs ensure maximum power from the DFIG in an OWCPP and enhance dynamic response with very low errors.The results show that the CSBO shows better power tracking by 25%as compared with C-BO,by 45%when compared with the GA and by 56%when compared with PID.Moreover,the integral absolute errors of six controllers are investigated to demonstrate the feasibility of CSBO-AFLC.The root mean square of the errors of six controllers using CSBO is improved by 68.27%when compared with GA,by 22.57%when compared with C-BO and by 38.42%when compared with PID.These indicators demonstrate the feasibility of CSBO when compared with other algorithms with the same OWCPP.
