4.5 Article

Salp swarm algorithm-based optimal control scheme for LVRT capability improvement of grid-connected photovoltaic power plants: design and experimental validation

期刊

IET RENEWABLE POWER GENERATION
卷 14, 期 4, 页码 591-599

出版社

INST ENGINEERING TECHNOLOGY-IET
DOI: 10.1049/iet-rpg.2019.0726

关键词

power grids; PI control; maximum power point trackers; optimal control; invertors; response surface methodology; voltage control; power generation control; photovoltaic power systems; control system synthesis; Salp swarm algorithm-based optimal control scheme; LVRT capability improvement; grid-connected photovoltaic power plants; photovoltaic systems; PV controllers; abnormal operational conditions; grid-connected PV systems; voltage response; DC-DC converter; maximum power point tracking operation; proportional-integral-based open fractional voltage control; grid side inverter controls; point of common coupling voltage; DC link voltage; fitness function; optimum design; conventional optimisation-based PI controllers; SSA-based PI control scheme; PSCAD; EMTDC environment

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Contribution of Photovoltaic (PV) systems is rapidly growing and great attention is given to the design of PV controllers to enhance both the performance of PV systems and the low voltage ride through (LVRT) capability during abnormal operational conditions. This article presents a novel application of the salp swarm algorithm (SSA) in order to optimally tune the PV controllers to enhance the LVRT of grid-connected PV systems. Enhancement of LVRT is indicated in percentage undershoots or overshoots, settling time and steady-state error of voltage response. A control strategy is applied to the DC-DC converter to obtain a maximum power point tracking operation through a proportional-integral (PI)-based open fractional voltage control. The grid side inverter controls both the point of common coupling voltage and the DC-link voltage through PI-based cascaded-voltage control. To get PI controller parameters that guarantee the optimum design of the controllers, the fitness function is optimized by using the SSA. The proposed optimal control scheme is tested under various fault scenarios and compared with other conventional optimization-based PI controllers to examine its validity under PSCAD environment. The effectiveness of the optimal control scheme is verified by comparing the simulation results with the practical results of the PV system.

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