Maximizing Social Welfare in Double-Sided Auction Market by Placement and Sizing of TCSC Using Coordinated Aggregation-Based Particle Swarm Optimization

摘要

This paper presents a particle swarm optimization (PSO) based algorithm to perform congestion management and maximize social welfare by placement and sizing of one Thyristor-controlled series capacitor (TCSC) device in a double-sided auction market. Simulation results (with line flow constraints, before and after the compensation) are used to analyze the impact of TCSC on the congestion levels of the modified IEEE 14-bus and 30-bus test systems. The algorithm utilizes conventional quadratic smooth and augmented quadratic nonsmooth generator cost curves with sine components to improve the accurate of the model by incorporating the valve loading effects. It also employs quadratic smooth consumer benefit functions. However, consideration of valve point effect presents nondifferentiable and nonconvex regions in the model that introduced additional challenges in most gradient-based optimization algorithms. The proposed approach makes use of the PSO algorithm to allocate the near-optimal GenCos, DisCos and TCSC (location and size) while the Newton-Raphson solution minimizes the mismatch of the power flow equations. Several case studies are investigated to test and validate the consistency of detecting near-global solutions. Simulation results by the proposed PSO algorithm are compared to solutions obtained by sequential quadratic programming (SQP) and Fuzzy based genetic algorithm (Fuzzy-GA) approaches. The main contributions are inclusion of customer benefit in the congestion management objective function, consideration of nonsmooth generator characteristics and the utilization of a coordinated aggregation-based PSO for locating/sizing of TCSC.