Parameter-free hybrid RAO algorithm for reactive power optimization

Area of Science:

• Optimization Techniques
• Swarm Intelligence
• Evolutionary Algorithms

Background:

• Rao algorithms are novel parameter-free optimization techniques gaining traction in intelligent optimization.
• Their effectiveness stems from swarm intelligence and survival of the fittest principles, similar to evolutionary algorithms.
• Wide applicability in engineering is noted, yet comprehensive summaries are limited.

Purpose of the Study:

• To provide an up-to-date summary of Rao algorithms for researchers.
• To introduce a hybrid Rao algorithm to address limitations of traditional methods.
• To evaluate the hybrid algorithm's performance on power system optimization problems.

Main Methods:

• A comprehensive review of existing Rao optimization algorithms.
• Development of a novel hybrid Rao algorithm.
• Implementation of the hybrid algorithm for the Optimal VAR Dispatch Problem in IEEE 30-bus and IEEE 57-bus systems.

Main Results:

• The hybrid Rao algorithm demonstrated superior performance in solving the Optimal VAR Dispatch Problem.
• It achieved higher quality solutions within a reasonable timeframe compared to existing literature.
• The algorithm proved effective in complex power system test cases.

Conclusions:

• The developed hybrid Rao algorithm offers an effective enhancement over traditional Rao algorithms.
• This approach provides a valuable tool for solving complex optimization problems in engineering, particularly in power systems.
• Future research should focus on further improvements to the Rao algorithm's performance.