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A multi-objective evolutionary algorithm for reactive power compensation in distribution networks

Author

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  • Antunes, Carlos Henggeler
  • Pires, Dulce Fernão
  • Barrico, Carlos
  • Gomes, Álvaro
  • Martins, António Gomes

Abstract

In this paper, the problem of locating and sizing capacitors for reactive power compensation in electric radial distribution networks is modeled as a multi-objective programming problem. An evolutionary approach consisting of an elitist genetic algorithm with secondary population is used to characterize the Pareto optimal (non-dominated) frontier, namely regarding well-distributed and diverse solutions. Two objective functions of technical and economical nature are explicitly considered in this model: minimization of system losses and minimization of capacitor installation costs. Constraints refer to quality of service, power flow, and technical requirements. The performance of the distribution network before and after the reactive power compensation is exploited.

Suggested Citation

  • Antunes, Carlos Henggeler & Pires, Dulce Fernão & Barrico, Carlos & Gomes, Álvaro & Martins, António Gomes, 2009. "A multi-objective evolutionary algorithm for reactive power compensation in distribution networks," Applied Energy, Elsevier, vol. 86(7-8), pages 977-984, July.
  • Handle: RePEc:eee:appene:v:86:y:2009:i:7-8:p:977-984
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    Cited by:

    1. Dong, Hanjiang & Zhu, Jizhong & Li, Shenglin & Wu, Wanli & Zhu, Haohao & Fan, Junwei, 2023. "Short-term residential household reactive power forecasting considering active power demand via deep Transformer sequence-to-sequence networks," Applied Energy, Elsevier, vol. 329(C).
    2. Martinez-Rojas, Marcela & Sumper, Andreas & Gomis-Bellmunt, Oriol & Sudrià-Andreu, Antoni, 2011. "Reactive power dispatch in wind farms using particle swarm optimization technique and feasible solutions search," Applied Energy, Elsevier, vol. 88(12), pages 4678-4686.
    3. Zhang, Zhengfa & da Silva, Filipe Faria & Guo, Yifei & Bak, Claus Leth & Chen, Zhe, 2021. "Double-layer stochastic model predictive voltage control in active distribution networks with high penetration of renewables," Applied Energy, Elsevier, vol. 302(C).
    4. Dashti, Reza & Afsharnia, Saeed & Ghasemi, Hassan, 2010. "A new long term load management model for asset governance of electrical distribution systems," Applied Energy, Elsevier, vol. 87(12), pages 3661-3667, December.
    5. Muhammad, Yasir & Khan, Nusrat & Awan, Saeed Ehsan & Raja, Muhammad Asif Zahoor & Chaudhary, Naveed Ishtiaq & Kiani, Adiqa Kausar & Ullah, Farman & Shu, Chi-Min, 2022. "Fractional memetic computing paradigm for reactive power management involving wind-load chaos and uncertainties," Chaos, Solitons & Fractals, Elsevier, vol. 161(C).
    6. Biswas (Raha), Syamasree & Mandal, Kamal Krishna & Chakraborty, Niladri, 2016. "Pareto-efficient double auction power transactions for economic reactive power dispatch," Applied Energy, Elsevier, vol. 168(C), pages 610-627.
    7. Gandhi, Oktoviano & Rodríguez-Gallegos, Carlos D. & Zhang, Wenjie & Srinivasan, Dipti & Reindl, Thomas, 2018. "Economic and technical analysis of reactive power provision from distributed energy resources in microgrids," Applied Energy, Elsevier, vol. 210(C), pages 827-841.
    8. Srikanth, R. & Nemani, Pavan & Balaji, C., 2015. "Multi-objective geometric optimization of a PCM based matrix type composite heat sink," Applied Energy, Elsevier, vol. 156(C), pages 703-714.
    9. Jerzy Andruszkiewicz & Józef Lorenc & Agnieszka Weychan, 2023. "Determination of the Optimal Level of Reactive Power Compensation That Minimizes the Costs of Losses in Distribution Networks," Energies, MDPI, vol. 17(1), pages 1-24, December.
    10. Ahmadimanesh, A. & Kalantar, M., 2017. "A novel cost reducing reactive power market structure for modifying mandatory generation regions of producers," Energy Policy, Elsevier, vol. 108(C), pages 702-711.
    11. Zhang, Lu & Shen, Chen & Chen, Ying & Huang, Shaowei & Tang, Wei, 2018. "Coordinated allocation of distributed generation, capacitor banks and soft open points in active distribution networks considering dispatching results," Applied Energy, Elsevier, vol. 231(C), pages 1122-1131.

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