New modified algorithm: θ-turbulent flow of water-based optimization.

Area of Science:

• Electrical Engineering
• Power Systems Optimization
• Computational Intelligence

Background:

• Reactive power control is crucial for power system stability and efficiency.
• Optimization problems in power systems often involve mixed continuous and discrete variables.
• Existing methods may face challenges in efficiently solving complex optimal reactive power distribution (ORPD) problems.

Purpose of the Study:

• To propose a novel and effective optimization algorithm for the ORPD problem.
• To introduce an improved version of the proposed algorithm, θ-TFWO.
• To reduce power system losses through optimal reactive power distribution.

Main Methods:

• Development of the Turbulent Flow of Water-based Optimization (TFWO) algorithm.
• Implementation of an enhanced version, θ-TFWO.
• Application and testing on large-scale IEEE 57-bus systems.
• Comparative analysis against Biogeography-Based Optimization (BBO), Social Spider Algorithm (SSA), and Optics Inspired Optimization (OIO).

Main Results:

• The proposed TFWO and θ-TFWO algorithms demonstrated superior performance in solving the ORPD problem.
• Significant reduction in power system losses was achieved.
• The algorithms proved robust and effective in handling mixed-integer optimization challenges.
• TFWO outperformed other tested algorithms in terms of solution quality and convergence.

Conclusions:

• The TFWO algorithm is a powerful and effective tool for optimal reactive power distribution.
• The proposed method offers a robust solution for reducing losses in large-scale power systems.
• TFWO provides a competitive alternative to existing optimization techniques for power system applications.