An Enhanced Evolutionary Algorithm for Providing Energy Management Schedule in the Smart Distribution Network

HTML
  • Hossein Lotfi1,
  • Amir Nikooei1,
  • Ali Shojaei1,
  • Reza Ghazi2,
  • Mohammad Bagher Naghibi Sistani3,
  1. Department of Electrical Engineering, Neyshabur Branch, Islamic Azad University, Neyshabur, Iran.
  2. Department of Electrical Engineering, Ferdowsi University of Mashhad, Mashhad, Iran.
  3. Department of Electrical Engineering, Ferdowsi University of Mashhad, Mashhad, Iran

Published in Issue 2024-02-15

How to Cite

Lotfi, H., Nikooei, A., Shojaei, A., Ghazi, R., & Naghibi Sistani, M. B. (2024). An Enhanced Evolutionary Algorithm for Providing Energy Management Schedule in the Smart Distribution Network. Majlesi Journal of Electrical Engineering, 14(2). https://oiccpress.com/mjee/article/view/4864

HTML views: 9

Abstract

Penetration of distributed generation resources including wind power and solar photovoltaic units in distribution system has been increased, and it is important to examine their impact on the distribution systemsâ operation in term of reliability. In this paper, the multi-objective dynamic feeder reconfiguration is introduced as an efficient approach for providing an energy management schedule in the distribution grid considering energy loss and energy not supplied as the objective functions in the presence of renewable energy sources and capacitor units. In addition, the effect of uncertainty related to power demand is considered in the evaluations. To this end, an enhanced particle swarm optimization algorithm is provided in this paper, the proposed approach is applied to the 33-node testing system.

Keywords

  • distributed generators (DGs),
  • Dynamic Distribution Feeder Reconfiguration (DDFR),
  • Enhanced Particle Swarm Optimization Algorithm (EPSO),
  • Lyapunov Stability,
  • Multi-Objective Optimization
HTML