Application on power system economic dispatch of marine predator algorithm improved by asymmetric information exchange
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View abstract on PubMed
Summary
This summary is machine-generated.This study introduces an improved Marine Predator Algorithm (IMPA) to efficiently solve the complex economic dispatch (ED) problem in power systems. IMPA significantly reduces operating costs by enhancing search diversity and escaping local optima, outperforming existing methods.
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.
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