Optimisation of controller parameters for grid-tied photovoltaic system at faulty network using artificial neural network-based cuckoo search algorithm

• Published in: IET renewable power generation Vol. 11; no. 12; pp. 1517 - 1526
• Main Authors: Kalaam, Rahila N, Muyeen, S.M, Al-Durra, Ahmed, Hasanien, Hany M, Al-Wahedi, Khaled
• Format: Journal Article
• Language: English
• Published: The Institution of Engineering and Technology 18.10.2017
• Subjects: artificial neural network; control system synthesis; controller parameter optimisation; CSA; cuckoo search algorithm; dynamic performances; faulty network; grid fault conditions; grid‐connected distributed generation system; grid‐tied photovoltaic system; grid‐tied PV system; mathematical design; mathematical model; neurocontrollers; nonlinear control systems; nonlinear system; optimisation algorithm; optimum design procedure; optimum parameters extraction; photovoltaic power systems; PI control; PI controllers; power convertors; power electronic converters; power generation control; power generation faults; power grids; power system applications; power system transients; proportional integral controllers; PSCAD/EMTDC model; Research Article; response surface methodology; RSM; search problems; transient performances; grid-connected distributed generation system; power system applications; artificial neural network; power generation control; response surface methodology; nonlinear system; proportional integral controllers; grid-tied photovoltaic system; CSA; neurocontrollers; controller parameter optimisation; optimisation algorithm; power generation faults; grid-tied PV system; power grids; power electronic converters; search problems; PI controllers; transient performances; power convertors; PI control; grid fault conditions; photovoltaic power systems; optimum design procedure; optimum parameters extraction; control system synthesis; RSM; dynamic performances; power system transients; PSCAD/EMTDC model; faulty network; cuckoo search algorithm; mathematical design; nonlinear control systems; mathematical model
• ISSN: 1752-1416; 1752-1424; 1752-1424
• DOI: 10.1049/iet-rpg.2017.0040

This study exhibits the optimum design procedure to tune controller parameters for grid-connected distributed generation system based on cuckoo search algorithm (CSA). To investigate the effectiveness of proposed algorithm, a grid-tied photovoltaic (PV) system consisting of two power electronic converters controlled by five proportional integral (PI) controllers is chosen. Setting proper values for all the PI controllers is a complicated task, notably when the system is non-linear. In this study, response surface methodology (RSM) is used to develop the mathematical design of the PV system which is required to apply the optimisation algorithm. To minimise the design efforts of RSM, an alternate approach based on artificial neural network is introduced to develop the mathematical model of the PV system which is another salient feature of this research. Moreover, two modifications in the CSA are proposed to extract optimum parameters for the controllers which are found suitable in power system applications. Both the transient and dynamic performances of the system with the optimum values obtained through CSA are studied for different types of grid fault conditions using PSCAD/EMTDC. The design values are compared with values obtained through genetic algorithm and bacterial foraging optimisation. Experimental validation is also given for the proposed method.