Optimal Allocation of Wind DG with Time Varying Voltage Dependent Loads using Bio-Inspired: Salp Swarm Algorithm
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.
A. Ahmed et al., "Optimal Allocation of Wind DG with Time Varying Voltage Dependent Loads using Bio-Inspired: Salp Swarm Algorithm," Proceedings of the 3rd International Conference on Computing, Mathematics and Engineering Technologies: Idea to Innovation for Building the Knowledge Economy (2020, Sindh, Pakistan), Institute of Electrical and Electronics Engineers (IEEE), Apr 2020.
The definitive version is available at https://doi.org/10.1109/iCoMET48670.2020.9074118
3rd International Conference on Computing, Mathematics and Engineering Technologies, iCoMET 2020 (2020: Jan. 29-30, Sindh, Pakistan)
Electrical and Computer Engineering
Keywords and Phrases
Distributed Generation; Multi-Objective Index; Salp Swarm Algorithm; Time Varying And Voltage Dependent Loads
International Standard Book Number (ISBN)
Article - Conference proceedings
© 2020 Institute of Electrical and Electronics Engineers (IEEE), All rights reserved.
23 Apr 2020