Optimal Allocation of Wind DG with Time Varying Voltage Dependent Loads Using Bio-Inspired: Salp Swarm Algorithm

Abstract

Increased energy demand puts burden on power system operations and fossils fuel depletion. Renewable Distributed Generation (DG) integration in the existing network is an effective way to fulfill the increasing load demand. Optimal allocation of DG critically depends on uncertainty in power generation and time varying voltage dependent (TVVD) load models. This paper presents optimal allocation of wind DG in the distribution system considering probabilistic generation and TVVD load models. Salp Swarm Algorithm (SSA) is implemented for minimization of Multi-objective function comprised of voltage deviation, real and reactive losses and voltage stability indices. The effectiveness of proposed approach is tested on IEEE 69-bus and 33-bus systems. Results show that TVVD load models and time varying generation plays an imperative part in DG planning. Further, results also demonstrate the advantage of SSA in terms of better convergence characteristics and less computation time.