Application on power system economic dispatch of marine predator algorithm improved by asymmetric information...

Area of Science:

• Optimization algorithms
• Power systems engineering
• Computational intelligence

Background:

• The economic dispatch (ED) problem is crucial for reducing power sector operating costs.
• ED is a complex, nonlinear, and nonconvex optimization challenge requiring advanced algorithms.
• Existing algorithms may struggle with the scale and complexity of modern power systems.

Purpose of the Study:

• To propose an enhanced Marine Predator Algorithm (IMPA) for solving the economic dispatch problem.
• To improve the efficiency and effectiveness of optimization algorithms for power system cost reduction.
• To introduce an asymmetric information exchange (AIE) mechanism for better search performance.

Main Methods:

• Development of the Improved Marine Predator Algorithm (IMPA) incorporating an asymmetric information exchange (AIE) mechanism.
• Validation of IMPA performance on 12 benchmark functions.
• Application of IMPA to solve the economic dispatch problem for power systems with 6, 13, 40, and 140 units.

Main Results:

• IMPA demonstrated superior performance compared to the standard Marine Predator Algorithm (MPA) and NMPA.
• The algorithm achieved significantly lower minimum and average operating costs in large-scale power systems.
• IMPA effectively escaped local optima and enriched search diversity, leading to more competitive solutions.

Conclusions:

• The proposed IMPA offers a more competitive and effective solution for the economic dispatch problem.
• IMPA enhances the performance of the Marine Predator Algorithm for large-scale power system optimization.
• This improved algorithm provides a valuable tool for further cost reduction in the power sector.