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Turkish Journal of Electrical Engineering and Computer Sciences

DOI

10.3906/elk-1812-54

Abstract

In deregulation, growth in electrical loads necessitates improving power delivery, while nondiscriminatory access to transmission grid is a requirement. Deregulation causes a significant rise in transactions, which requires adequate transfer capability to secure economic transactions. In sustainable power delivery, FACTS devices are deployed to enhance available transfer capability (ATC). However, the high investment cost of FACTS makes the problem formulation a multiobjective optimization: power transfer maximization and minimization of FACTS sizes. Furthermore, due to the complexity in optimizing the control variables of voltage source converter types of FACTS, often the solution results in local optima and high computational time. This paper proposes a hybrid of real power flow performance index sensitivity ($\partial PI$) and particle swarm optimization (PI-PSO) to solve the multiobjective optimization of ATC maximization with minimum FACTS sizes using continuation power flow. $\partial PI$ identifies some high-potential locations with enhanced ATC at minimum FACTS size to constitute the PSO's reduced search space. As $\partial PI$ may exhibit masking effects, iterative $n$-$exponent$ and Newton's divided difference approaches are proposed to reduce masking. The proposed PI-PSO is implemented with a thyristor control series compensator and static synchronous series compensator for both bilateral and multilateral transactions. Results show the effectiveness of the proposed PI-PSO over PSO regarding convergence characteristics, avoidance of local optima, and superior ATC values.

First Page

2881

Last Page

2897

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