An efficient control strategy for optimal power flow management from a renewable energy source to a generalized three-phase microgrid system: A hybrid squirrel search algorithm with whale optimization algorithm approach. (July 2020)

• Record Type: Journal Article
• Authors: Durairasan, M; Balasubramanian, Divya
• Is Part Of: Transactions of the Institute of Measurement and Control. Volume 42:Number 11(2020)
• Page Start: 1960
• Page End: 1976
• Publication Date: 2020-07
• Subjects: Power flow control (PFC) -- photovoltaic (PV) -- wind turbine (WT) -- fuel cells (FC) -- squirrel search algorithm (SSA) -- whale optimization algorithm (WOA) -- power controller; Automatic control -- Periodicals; Measuring instruments -- Periodicals; Commande automatique -- Périodiques; Mesure -- Instruments -- Périodiques; 681.2
• DOI: 10.1177/0142331220901628
• Languages: English
• ISSNs: 0142-3312

Abstract

This paper introduces a hybrid approach for power flow management (PFM) of the hybrid renewable energy source (HRES) connected microgrid (MG) system. Here, the proposed approach is the combination of both the squirrel search algorithm (SSA) with whale optimization algorithm (WOA) named as SSAWO. Here, the SSA is developing the control signals of the voltage source inverter subject to the difference of power exchange between the source side and load side. The multi-objective function is shaped by the grid required active and reactive power varieties generated based on the accessible source power. The WOA procedures guarantee to locate the online control signals by utilizing the parallel execution against the active and reactive power varieties. The proposed technique-based control model enhances the control parameters of the power controller in light of the power flow varieties. By using the proposed methodology, the PFM of the MG system is controlled based on the source side and load side parameters variations. In order to render the power demand by the grid, the present system is accountable for dominating the energy sources using, optimally, both renewable energy sources and energy storage devices. Finally, the proposed model is implemented in MATLAB/Simulink working platform and the execution equates with the existing techniques.