Numerical Simulation and Design of Economic Load Dispatch of IEEE-40 Generator Test System Using Improved Cuckoo Search Optimization
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Abstract
This paper presents a novel approach for minimizing fuel costs in the IEEE-40 Generator Test System through the application of an Improved Cuckoo Search Algorithm (ICSA). The optimal operation of power systems is of critical concern due to the escalating demand for electricity and the necessity to minimize operational costs and environmental impacts. In this study, the IEEE-40 Generator Test System, which represents a complex power generation scenario, is utilized as the testbed.
The proposed Improved Cuckoo Search Algorithm builds upon the traditional Cuckoo Search Algorithm, incorporating enhanced strategies for population diversity, exploration, and exploitation. The algorithm aims to effectively balance exploration of the search space and exploitation of promising solutions to achieve optimal or near-optimal solutions for minimizing fuel costs.
The optimization process involves formulating a cost function that considers the fuel costs of generators in the power system, subject to various operational constraints such as generator limits and load demand. The ICSA is employed to iteratively adjust the control settings of generators to find the configuration that minimizes the overall fuel cost while satisfying these constraints.
Simulation results on the IEEE-40 Generator Test System demonstrate the efficacy of the proposed approach. Comparative analysis against other metaheuristic optimization algorithms showcases the superiority of the Improved Cuckoo Search Algorithm in terms of convergence speed and solution quality. This method offers a promising avenue for addressing fuel cost optimization in large-scale power systems, contributing to efficient and cost-effective energy generation