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

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  • Peesapati, Rajagopal
  • Yadav, Vinod Kumar
  • Kumar, Niranjan

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.

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  • Peesapati, Rajagopal & Yadav, Vinod Kumar & Kumar, Niranjan, 2018. "Flower pollination algorithm based multi-objective congestion management considering optimal capacities of distributed generations," Energy, Elsevier, vol. 147(C), pages 980-994.
    • Handle: RePEc:eee:energy:v:147:y:2018:i:c:p:980-994
    DOI: 10.1016/j.energy.2018.01.077
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    Cited by:

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    3. Sadhan Gope & A. K. Goswami & P. K. Tiwari, 2020. "Transmission congestion management with integration of wind farm: a possible solution methodology for deregulated power market," International Journal of System Assurance Engineering and Management, Springer;The Society for Reliability, Engineering Quality and Operations Management (SREQOM),India, and Division of Operation and Maintenance, Lulea University of Technology, Sweden, vol. 11(2), pages 287-296, April.
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    6. Panda, Mitali & Nayak, Yogesh Kumar, 2022. "Impact analysis of renewable energy Distributed Generation in deregulated electricity markets: A Context of Transmission Congestion Problem," Energy, Elsevier, vol. 254(PC).
    7. Hadidian Moghaddam, Mohammad Jafar & Kalam, Akhtar & Nowdeh, Saber Arabi & Ahmadi, Abdollah & Babanezhad, Manoochehr & Saha, Sajeeb, 2019. "Optimal sizing and energy management of stand-alone hybrid photovoltaic/wind system based on hydrogen storage considering LOEE and LOLE reliability indices using flower pollination algorithm," Renewable Energy, Elsevier, vol. 135(C), pages 1412-1434.

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