This paper proposes the optimum controller for shunt active filter(SAF)to mitigate the harmonics and maintain the power quality in the distribution system.It consists of shunt active filter,Voltage Source Inverter(VSI...This paper proposes the optimum controller for shunt active filter(SAF)to mitigate the harmonics and maintain the power quality in the distribution system.It consists of shunt active filter,Voltage Source Inverter(VSI),series inductor and DC bus and nonlinear load.The proposed hybrid approach is a combination of Particle Swarm Optimization(PSO)and Artificial Neural Network(ANN)termed as PSOANN.The PI controller gain parameters of kp and ki are optimized with the help of PSOANN.The PSOANN improves the accuracy of tuning the gain parameters under steady and dynamic load conditions;thereby it reduces the values of THD within the prescribed limits of IEEE 519.The PSO optimizes the dataset of terminal voltage and DC voltage present in shunt active filter for different load condition.The optimized dataset acts as the input for the controller to predict the optimal gain with minimal error and to generate the optimized control signal for the SAF.The proposed methodology is modelled and simulated with the help of MATLAB/Simulink platform and illustrated the few test cases considered for exhibiting the performance of proposed hybrid controller.The experimental results are measured with developed laboratory prototype and compared with the simulation results to validate the effectiveness of the proposed control methodology.展开更多
The developing populace and industrialization power demand prompted the requirement for power generation from elective sources.The desire for this pursuit is solid due to the ever-present common assets of petroleum de...The developing populace and industrialization power demand prompted the requirement for power generation from elective sources.The desire for this pursuit is solid due to the ever-present common assets of petroleum deri-vatives and their predominant ecological issues.It is generally acknowledged that sustainable power sources are one of the best answers for the energy emergency.Among these,Photovoltaic(PV)sources have many benefits to bestow a very promising future.If integrated into the existing power distribution infrastructure,the solar source will be more successful,requiring efficient Direct Current(DC)-Alternating Current(AC)conversion.This paper mainly aims to improve control-lers’performance between AC/DC Energy sources and the DC loads using the Adaptive Nonlinear Sliding Mode(ANSM)control method.The proposed ANSM method efficiently controls power quality issues,such as transient response,powerflow reliability and Total Harmonics Distortion(THD).The proposed con-troller is applied for both AC/DC and DC/DC converters and the performance of the proposed controller is validated through simulation checking the above para-meters.The simulation results confirm ANSM configuration is more reliable and efficient than the existing fuzzy and sliding mode control methods.展开更多
文摘This paper proposes the optimum controller for shunt active filter(SAF)to mitigate the harmonics and maintain the power quality in the distribution system.It consists of shunt active filter,Voltage Source Inverter(VSI),series inductor and DC bus and nonlinear load.The proposed hybrid approach is a combination of Particle Swarm Optimization(PSO)and Artificial Neural Network(ANN)termed as PSOANN.The PI controller gain parameters of kp and ki are optimized with the help of PSOANN.The PSOANN improves the accuracy of tuning the gain parameters under steady and dynamic load conditions;thereby it reduces the values of THD within the prescribed limits of IEEE 519.The PSO optimizes the dataset of terminal voltage and DC voltage present in shunt active filter for different load condition.The optimized dataset acts as the input for the controller to predict the optimal gain with minimal error and to generate the optimized control signal for the SAF.The proposed methodology is modelled and simulated with the help of MATLAB/Simulink platform and illustrated the few test cases considered for exhibiting the performance of proposed hybrid controller.The experimental results are measured with developed laboratory prototype and compared with the simulation results to validate the effectiveness of the proposed control methodology.
文摘The developing populace and industrialization power demand prompted the requirement for power generation from elective sources.The desire for this pursuit is solid due to the ever-present common assets of petroleum deri-vatives and their predominant ecological issues.It is generally acknowledged that sustainable power sources are one of the best answers for the energy emergency.Among these,Photovoltaic(PV)sources have many benefits to bestow a very promising future.If integrated into the existing power distribution infrastructure,the solar source will be more successful,requiring efficient Direct Current(DC)-Alternating Current(AC)conversion.This paper mainly aims to improve control-lers’performance between AC/DC Energy sources and the DC loads using the Adaptive Nonlinear Sliding Mode(ANSM)control method.The proposed ANSM method efficiently controls power quality issues,such as transient response,powerflow reliability and Total Harmonics Distortion(THD).The proposed con-troller is applied for both AC/DC and DC/DC converters and the performance of the proposed controller is validated through simulation checking the above para-meters.The simulation results confirm ANSM configuration is more reliable and efficient than the existing fuzzy and sliding mode control methods.
