Optimal Allocation of DG using Hybrid Optimization Technique for Minimizing the Power Loss
Banka Jyothsna Rani1, Ankireddipalli Srinivasula Reddy2
1Banka Jyothsna Rani, Department of Technical Education, Government model residential polytechnic, Madanapalle, (Andhra Pradesh), India.
2Dr. Ankireddipalli Srinivasula Reddy, CMR Engineering College, Hyderabad, (Telangana), India.
Manuscript received on 23 March 2019 | Revised Manuscript received on 30 March 2019 | Manuscript published on 30 March 2019 | PP: 1583-1591 | Volume-7 Issue-6, March 2019 | Retrieval Number: F2357037619/19©BEIESP
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Abstract: In recent days, the utility grids (renewable resources) facing critical issues in the power generation system due to continuous load development. The traditional power grids are incapable of generating necessary power supply with respect to the load demand. The other issue in the distribution network is power loss during the transmission of generated power. In order to overcome these issues, the Distributed Generation (DG) is utilized in power generation system to maintain the system steadiness, and reject the distribution system bottleneck to satisfy the load demand. This research paper proposed a methodology for placing the DG in appropriate location and fixe the issue of the size of DG units in the distribution system to minimize the power loss and enhance the voltage profile. Additionally, Hybrid optimization methodology is employed for optimal DG reconfiguration. This proposed hybrid methodology is the combination of Binary Particle Swarm Optimization (BPSO) and Kinetic Gas Molecule Optimization (KGMO). The proposed BPSO-KGMO computes the optimal DG placement and size, based on the various control parameters like voltage profile, power loss and cost are considered in the fitness function to find the appropriate placement of DG. which helps to minimize the power losses and enhance the voltage steadiness. The proposed BPSO-KGMO methodology is simulated in IEEE 69 bus system and the efficiency of the proposed BPSO-KGMO methodology is evaluated and compared with the Genetic algorithm, Stud Krill Herd algorithm BPSO algorithm in terms of four test cases.
Keywords: Binary Particle Swarm Optimization (BPSO), and Kinetic Gas Molecule Optimization, Distributed Generation (DG), Optimal Placement, Power loss, Voltage Profile.
Scope of the Article: Optimal Design of Structures