Flower pollination algorithm based multi-objective congestion management considering optimal capacities of distributed generations

Rajagopal Peesapati, Vinod Kumar Yadav and Niranjan Kumar

Energy, 2018, vol. 147, issue C, 980-994

Abstract: Transmission Congestion creates hindrance that limit the most economical supply to reach demands. Hence, it is relieved at the earliest to make optimum utilization of available transmission network in order to achieve maximum profits. In this work, optimal capacities of distributed generation (DG) units are inserted to remove the congestion in the transmission lines of bulk power system. Multi-objectives like real power losses, investment costs, voltage deviations and line capacities are converted into single objective and is minimized to obtain the optimal capacities of the DG units. Flower Pollination Algorithm (FPA) is implemented to achieve the best capacities of the DGs that are operating at unity (UPF) and 0.9 lagging power factors. The capacities of DGs are obtained at multiple locations instead of single optimal or sub-optimal location in order to improve the practical feasibility while connecting the DGs. The proposed methodology is practiced on IEEE 30 and 118 bus system to check the effectiveness. Further, the result obtained by FPA are compared with Genetic algorithm (GA) and Particle Swarm Optimization (PSO) approaches in terms of real power losses (RPL) and line flows. Results conveyed that the proposed algorithm had superior features, stable convergence characteristics and good computational efficiency.

Keywords: Transmission congestion; Distributed generation; Flower pollination algorithm (search for similar items in EconPapers)
Date: 2018
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (7)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:energy:v:147:y:2018:i:c:p:980-994

DOI: 10.1016/j.energy.2018.01.077

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