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.

Meeting Name

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)


Document Type

Article - Conference proceedings

Document Version


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© 2020 Institute of Electrical and Electronics Engineers (IEEE), All rights reserved.

Publication Date

23 Apr 2020