Optimization Techniques Enhance Renewable Energy Performance in Distribution Systems

Strategic Insights -

Fresh data on Energy - Renewable Energy was presented in a recent report, highlighting the use of optimization techniques to improve various electric power systems. According to the research, various algorithms help system operators determine the optimal location and capacity of renewable energy sources, enabling them to achieve specific goals and improve performance. The study employed 20 famous metaheuristic optimization techniques, evaluating them based on 10 performance measures, including power loss indices and voltage profile indices.

Key Takeaways:

  • 7 algorithms (AEO, GWO, JS, PSO, MVO, BO, and GNDO) were ranked as excellent, accounting for less than 25% of the total score.
  • 6 algorithms (ALO, DA, FPA, SSA, YAYA, and SPO) were categorized as very good, with rankings ranging from 25 to 50%.
  • 2 algorithms (SMA and CGO) were classified as good, with rankings between 50 and 75%.
  • 5 algorithms (CStA, HHO, AOA, GOA, and AOS) were positioned in the lowest group, each achieving rankings beyond 75%.
  • The proposed algorithms achieved a power loss of 71.644 kW for the 69-bus system, which is less than or equal to the published work.
  • The research concluded that using the appropriate algorithms with distribution systems saves time and effort for the system operator, enhances performance, and increases the usability of optimization algorithms.
  • The study involved 10 distribution systems of varying sizes to ensure an equitable comparison of the algorithm.
  • The Friedman Ranking method evaluated algorithms based on performance metrics, yielding a specific score.

Statistics:

  • 20 metaheuristic optimization techniques were evaluated in the study.
  • 10 performance measures were used to evaluate the algorithms, including power loss indices, voltage profile indices, load flow calling frequency, and execution time.
  • The AEO, GWO, JS, PSO, MVO, BO, and GNDO algorithms achieved rankings below 25%, placing them in the highest category.
  • The ALO, DA, FPA, SSA, YAYA, and SPO algorithms fell into the second category, with rankings ranging from 25 to 50%.
  • The SMA and CGO algorithms were classified in the third group, with rankings between 50 and 75%.
  • The algorithms CStA, HHO, AOA, GOA, and AOS achieved rankings beyond 75%, positioning them in the lowest group.

Sources:

  • Multi-criteria assessment of optimization methods for controlling renewable energy sources in distribution systems. Scientific Reports, 2025;15(1):36438.
  • Qassim University, Dept. of Electrical Engineering, College of Engineering, Buraidah, 52571, Saudi Arabia.