Advancing Economic Load Dispatch in Power Systems: A Hybrid Cuckoo Search Algorithm with Adaptive Parameter Control and Linear Regression

The Economic Load Dispatch (ELD) problem is a critical facet of power system optimization, tasked with determining the optimal allocation of power generation among various units to minimize operational costs. This research introduces a novel hybrid algorithm to address the ELD problem, combining the strengths of the Cuckoo Search algorithm with adaptive parameter control and linear regression. The proposed approach aims to enhance the algorithm's convergence and solution quality, particularly variability and complexity into power systems. This paper evaluates the effectiveness of the hybrid algorithm using two test systems: the IEEE 30-bus system and the IEEE 14-bus system. These widely recognized test cases provide diverse and realistic scenarios for assessing the proposed algorithm's performance under different operational conditions. The integration of adaptive parameter control allows the algorithm to dynamically adjust its parameters during optimization, ensuring adaptability to the changing characteristics of the ELD problem. Furthermore, the inclusion of linear regression provides insights into the underlying patterns of the ELD problem, aiding in the modeling of relationships between variables. The research conducts a comprehensive analysis, comparing the proposed hybrid algorithm with existing techniques. Through extensive simulations and performance evaluations, the study demonstrates the algorithm's superiority in achieving optimal economic load dispatch, particularly when faced with the challenges posed by renewable energy sources. This paper contributes to the ongoing efforts to enhance the economic operation of power systems, addressing the evolving landscape of energy resources and fostering sustainability in the face of increasing renewable energy integration.