Affiliations: Department of Railroad Electrical Systems Engineering, Woosong University, Daejeon, Republic of Korea
Correspondence:
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Corresponding author. Young Hwan Lho, Department of Railroad Electrical Systems Engineering, Woosong University, Daejeon, Republic of Korea. E-mail: yhlho@wsu.ac.kr.
Abstract: This paper proposes the solution to an optimal scheduling problem of a thermal-wind power system. Here, the power output from a wind energy generator (WEG) is assumed to be schedulable, therefore the wind power penetration limits can be determined by the system operator (SO). The intermittent nature of wind power and speed is modeled using the Weibull density function. Here, 3 objective functions i.e., total operating cost, voltage stability enhancement index and system losses are selected. The total generation cost minimization objective has the cost of power generated from thermal and WEGs, under and over estimation costs of wind power. In the present paper, a multi-objective optimal power flow (MO-OPF) problems are framed by considering different objective functions simultaneously, and they are solved using the multi-objective Glowworm Swarm Optimization (MO-GSO) technique. The proposed optimization problem is solved on a modified IEEE 30 bus test system with two wind farms situated at two different buses in the system. The obtained simulation results show the suitability of proposed MO-OPF method for large scale power systems.
