Congestion Control by Optimal Engagement of Distribution Generation using Hybrid Evolutionary Algorithm
Kaushik Paul1, Niranjan Kumar2, Poulami Dalapati3

1Kaushik Paul*, Electrical Engineering, National Institute of Technology Jamshedpur, Jamshedpur, India.
2Niranjan Kumar, Electrical Engineering, National Institute of Technology Jamshedpur, Jharkhand, India.
3Poulami Dalapati, Computer Science and Engineering, BIT Sindri, Dhanbad, India. 

Manuscript received on September 17, 2019. | Revised Manuscript received on 25 September, 2019. | Manuscript published on October 10, 2019. | PP: 3329-3336 | Volume-8 Issue-12, October 2019. | Retrieval Number: L28281081219/2019©BEIESP | DOI: 10.35940/ijitee.L2828.1081219
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Abstract: The power system congestion is treated as a vital issue in the restructured topology of the power system. The analysis of appropriate technique to control congestion is of preeminent interest. This paper proposes a congestion controlling scheme with the optimal placement and sizing of the Distributed Generation (DG) so as to ensure an optimal power flow in the power system network. A multi-objective framework is formulated for the proposed approach considering the operating cost, Voltage Stability Index (VSI) and the system losses. A hybrid optimization technique is proposed involving Improved Genetic Algorithm (IGA) and Bat Algorithm (BA) to optimize the objectives proposed in this research. The efficiency of the proposed methodology is verified using IEEE 33 and 69 bus systems. A comparative analysis is established between the outcomes obtained with hybrid IGA-BA and Particle Swarm Optimization (PSO) technique. The output obtained clarifies that by combining IGA and BA, greater efficiency is achieved compared to the PSO algorithm output.
Keywords: Cost Minimization, Congestion Management, Distribution Generation, Optimization.
Scope of the Article: Design Optimization of Structures