Power flow management of hybrid system in smart grid requirements using ITSA-MOAT approach. (1st August 2022) - Logeswaran, T.; Senthil Raja, M.; Beevi Sahul Hameed, Jennathu; Abdulrahim, Mahabuba
Highlights: A power flow management (PFM) concept of photovoltaic/fuel cell/battery/super capacitor in smart grid (SG) system is proposed in this paper. The proposed system controls the photovoltaic (PV) system, battery storage, fuel cell (FC) and super capacitor (SC). The proposed control system is the combination of Improved Tunicate Swarm Optimization (ITSA) and Multi Objective Artificial Tree (MOAT), hence it is called ITSA-MOAT method. Abstract: A power flow management (PFM) concept of Photovoltaic/Fuel Cell/Battery/Super capacitor in smart grid (SG) system is proposed in this paper. The proposed system controls the photovoltaic (PV) system, battery storage, fuel cell (FC) and super capacitor (SC). The proposed control system is the combination of Improved Tunicate Swarm Optimization (ITSA) and Multi Objective Artificial Tree (MOAT), hence it is called ITSA-MOAT method. Here, ITSA is building up the control pulses of the inverter using the energy exchange assortment between the source and load side. Here, the composition of multi-objective function is considered according to the obtainable source power and several specified grid produced by the active power and reactive power. To acquire the online control pulses, MOAT is utilized based on the variants of power. Moreover, the global state of charge (SoC) of energy storages and load demand are considered. The ITSA-MOAT method is implemented in MATLAB/Simulink platform. By then, the experimental results of the proposed method are analyzed with the existing methods.