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Optimal active and reactive power allocation in distribution networks using a novel heuristic approach

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  • Bayat, A.
  • Bagheri, A.

Abstract

A wide range of solution methodologies has been presented in the literature for the siting and sizing of active and reactive power sources in radial distribution systems. The solution techniques are mainly classified into mathematical programming algorithms, heuristics, meta-heuristic methods, and the analytical approaches. This paper proposes a novel heuristic method for optimal allocation of distributed generation (DG) and capacitor banks. The conducted approach is easy for implementation and does not suffer from the complicacy of the other methods. Based on some mathematical calculations, two main formulations are derived. Then, the resulting formulations are employed to site and size capacitor bank and DG unit in the 33-bus distribution network to verify its performance by comparing the obtained results with those of global search method. Afterward, the proposed method is used to allocate a specified number of DGs and capacitors in the 33 and 69-bus systems. Finally, the conducted approach is employed to allocate multiple DGs and capacitors, and also multiple DGs with optimal power factor in the 119-bus distribution network. The recently presented methodologies including particle swarm optimization (PSO), improved analytical (IA), hybrid analytical-PSO, Teaching Learning Based Optimization (TLBO), Quasi-Oppositional Teaching Learning based optimization (QOTLBO), Comprehensive Teaching Learning-Based Optimization (CTLBO), and LSF-BFOA algorithms are used for investigating the efficiency of the developed method. The simulation results demonstrate that the presented heuristic approach is robust in finding the optimal results, very fast and easy to implement, applicable to large distribution systems and it give better results than the algorithms presented so far.

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  • Bayat, A. & Bagheri, A., 2019. "Optimal active and reactive power allocation in distribution networks using a novel heuristic approach," Applied Energy, Elsevier, vol. 233, pages 71-85.
    • Handle: RePEc:eee:appene:v:233-234:y:2019:i::p:71-85
    DOI: 10.1016/j.apenergy.2018.10.030
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