Design and implementation of Legendre-based neural network controller in grid-connected PV systems

• Published in: IET renewable power generation Vol. 13; no. 15; pp. 2783 - 2792
• Main Authors: Arora, Ankita, Singh, Alka
• Format: Journal Article
• Language: English
• Published: The Institution of Engineering and Technology 18.11.2019
• Subjects: adaptive control; backpropagation; backpropagation multilayer perceptron neural network; compensation; control system synthesis; controller design; current control mode; distorted grid; electric current control; grid‐connected PV systems; Legendre polynomials; Legendre‐based functional neural network algorithm; Legendre‐based neural network controller; load current; multilayer perceptrons; neurocontrollers; nonlinear functional Legendre expansion; photovoltaic power systems; photovoltaic‐based grid‐connected system; power factor; power factor improvement; power grids; power quality; power supply quality; PQ problems; PV source; reactive power; reactive power control; recurrent neural nets; recurrent neural network; Research Article; shunt compensation; solar irradiation; synchronous reference frame theory; current control mode; load current; controller design; shunt compensation; electric current control; nonlinear functional Legendre expansion; photovoltaic-based grid-connected system; neurocontrollers; power factor improvement; synchronous reference frame theory; power grids; Legendre polynomials; multilayer perceptrons; recurrent neural network; recurrent neural nets; photovoltaic power systems; Legendre-based functional neural network algorithm; control system synthesis; adaptive control; PV source; distorted grid; power factor; power supply quality; Legendre-based neural network controller; solar irradiation; power quality; reactive power; backpropagation; backpropagation multilayer perceptron neural network; compensation; reactive power control; grid-connected PV systems; PQ problems
• ISSN: 1752-1416; 1752-1424; 1752-1424
• DOI: 10.1049/iet-rpg.2019.0269

This study presents the development of Legendre-based functional neural network algorithm for shunt compensation in photovoltaic (PV)-based grid-connected system. The controller is developed for improving power quality (PQ) and the compensator is controlled to work in current control mode. It injects the requisite compensating current depending on the nature of the load current. The compensator is also interfaced with PV source and the controller design incorporates its contribution too. Some of the PQ problems studied include curtailment of harmonics, providing necessary reactive power, power factor improvement and so on. Results under distorted grid, varying solar irradiation and variety of loads have been presented. The proposed algorithm is designed using non-linear functional Legendre expansion of load current and has not been used for compensation or PQ problem alleviation till date. Both simulation and experimental results verify that the proposed algorithm performs far better than the adaptive popular backpropagation multilayer perceptron neural network, recurrent neural network and non-adaptive conventional synchronous reference frame theory based techniques.