Abstract
ABSTRACT Optimal power flow (OPF) is one of the complex optimization problems in the power system domain. The OPF problem becomes much more challenging when renewable energy sources are added to the power system grid, which is unpredictable and volatile. Also, FACTS (flexible AC transmission system) devices are becoming more common in modern power systems to help ease network congestion and minimize demand. This paper aims to solve the single and multi-objective OPF by combining stochastic wind power with various types of FACTS devices such as static VAR compensator, thyristor-controlled series compensator, and thyristor-controlled phase shifter. To model stochastic wind energy, Weibull probability density functions have been used. The locations and ratings of the FACTS devices are also designed to reduce the system’s total generation cost. A non-dominated multi-objective moth flame optimization technique is used for the optimization issue. The fuzzy decision-making approach is applied to the best compromise solution. The results are validated through a modified IEEE-30 bus test system and compared with three newly developed algorithms.
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