Comparison of Convexificated SQCQP and PSO for the Optimal Transmission System Operation based on Incremental In-Phase and Quadrature Voltage Controlled Transformers

The optimal operation of electrical energy systems by solving a security constrained optimal power flow (SCOPF) problem is still a challenging research aspect. Especially, for conventional optimization methods like sequential quadratic constrained quadratic programming (SQCQP) the formulation of the incremental control variables like in-phase and quadrature voltage controlled transformers in a solver suitable way is complex. Compared to this, the implementation of these control variables within heuristic approaches like the particle swarm optimization (PSO) is simple but problem specific adaptations of the classic PSO algorithm are necessary to avoid an unfortunate swarm behavior and local convergence in bad results. The objective of this paper is to introduce a SQCQP and a modified PSO approach in detail to solve the SCOPF problem adequately under consideration of flexible incremental in-phase and quadrature transformers tap sets and to compare and benchmark the results of both approaches for an adapted IEEE 118-bus system. The casestudy shows that both approaches lead to suitable results of the SCOPF with individual advantages of the SQCQP concerning the quality and the reproducibility of the results while the PSO lead to faster solutions when the complexity of the investigation scenario increases.