This paper solves a novel multi-objective optimal power flow (MO-OPF) problem for a hybrid power system consisting the thermal generators, wind energy generators (WEGs) and solar photovoltaic (PV) units with battery energy storage (BES) system. In this paper, three objective functions, i.e., total generation cost, transmission losses and voltage stability enhancement index are considered to be optimized simultaneously. The total generation cost minimization objective include the cost of conventional thermal generators, wind and solar power purchasing from the private owners and to reduce the risk due to the wind and solar power uncertainties. Here, the power output from the wind and solar power outputs are determined based on the Weibull probability distribution function. This paper utilizes a particle swarm optimization (PSO) based fuzzy satisfaction maximization technique to solve the proposed MO-OPF problem of a hybrid power system. Here, a modified IEEE 30 bus system is used to demonstrate the effectiveness of the proposed approach. The proposed technique is robust and faster which modifies the control variables effectively. The proposed approach can be useful to the system operator as the decision supportive tool to handle the hybrid power systems.
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