Statistical Assessment of Whale Optimization Algorithm for Sizing and Placement of DG Considering Multi-Objective Function with PSO and CSA Algorithm
J P Sridhar1, R Prakash2

1JP Sridhar*, Professor and HOD, Dept. of Electrical and Electronics Engineering, Acharya Institute of Technology, Bengaluru, Karnataka.
2R. Prakash, Assistant professor in Department of EEE, SJB Institute of Technology, Bengaluru, and Karnataka.
Manuscript received on February 10, 2020. | Revised Manuscript received on February 21, 2020. | Manuscript published on March 10, 2020. | PP: 404-411 | Volume-9 Issue-5, March 2020. | Retrieval Number: E2314039520/2020©BEIESP | DOI: 10.35940/ijitee.E2314.039520
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Abstract: Distributed or decentralized power generation (DGEN) technology is popularized in the 21st century and it emerged has an effective alternative solution to meet the forecasted energy demand for restructured power system by putting restriction on power plants and transmission lines of the of the next decade generation. Modified state policies and increased technological innovation for low-capacity production promotes increased development and investment of DGEN. The use of distributed renewable energy generation has been driven by environmental concerns. DGEN’s incorporation into the distribution side of the network offers critical system advantages such as voltage assistance support, reduction in loss, transmission power increase, strengthened system performance, etc. This paper presents the optimized DG placement (ODGP) and sizing solution in distribution side of the network for the multi objective formulation includes the objective of minimizing the losses, maximization of voltage stability and also includes the cost requirement. The new Meta-heuristic based Approach named as Whale optimization algorithm is used for optimal placement and Sizing of DGEN is considered in this work and the solution of the proposed optimization algorithm is compared with two most popular optimization techniques such as Particle Swarm Optimization (PSOA), Cuckoo Search Algorithm (CSOA). The comparative analysis of these above said optimization techniques is developed and compared for performance comparison can be done with 69 bus IEEE standard radial system to validate the results of the proposed multi objective problem. 
Keywords: Distributed Generation (DGEN), Whale Optimization Algorithm (WHOA), Particle Swarm Optimization (PSOA), Cuckoo Search Algorithm (CSOA).
Scope of the Article: Cross Layer Design and Optimization