The primary objective of Economic Load Dispatch (ELD) is to determine the most efficient distribution of power among generating units while considering various constraints, such as minimum and maximum power output, transmission line capacity, and reserve requirements. By solving the ELD problem, power system operators can minimize the overall operating cost of the power system and enhance its efficiency, which has far-reaching implications for sustainable energy management and resource allocation. However, because of the non-convex nature of the ELD problem, finding the global optimum solution poses a significant challenge. Consequently, several optimization techniques, such as metaheuristics, have been developed in order to address this type of problems. By iteratively exploring the solution space, metaheuristics offer a higher likelihood of finding near- optimal solutions, even in the presence of multiple local optima. This research introduces an enhanced social network search (ESNS) algorithm as an improvement over the existing social network search (SNS) algorithm, aiming to achieve the aforementioned objectives. The core of the SNS algorithm is driven by the social network users’ dialogue, imitation, creativity, and disputation moods. The proposed ESNS algorithm builds upon the SNS approach by enhancing its search capability, particularly around the best potential solution. The primary goal is to improve the algorithm’s ability to explore global search possibilities while avoiding being trapped in locally optimal solutions. The performance of ESNS has been tested in the 23 benchmark test suits, and its superiority against SNS and other recent algorithms has been verified. Moreover, To evaluate the effectiveness of the proposed ESNS algorithm, it is applied to four standard test systems comprising 11-, 15-, 40-, and 110-unit test systems. The results demonstrate that the ESNS algorithm outperforms other optimization algorithms in terms of solution quality and convergence speed. These findings suggest that the ESNS algorithm holds significant promise as a valuable tool for researchers and power system operators in addressing the economic dispatch problem. Overall, the ESNS technique presents a promising result to this complex challenges. Its capability to handle multiple constraints and its superior performance compared to other recent algorithms make it a valuable addition to the existing set of tools available for solving ELD.

Global optimization of economic load dispatch in large scale power systems using an enhanced social network search algorithm

Desideri U.
2024-01-01

Abstract

The primary objective of Economic Load Dispatch (ELD) is to determine the most efficient distribution of power among generating units while considering various constraints, such as minimum and maximum power output, transmission line capacity, and reserve requirements. By solving the ELD problem, power system operators can minimize the overall operating cost of the power system and enhance its efficiency, which has far-reaching implications for sustainable energy management and resource allocation. However, because of the non-convex nature of the ELD problem, finding the global optimum solution poses a significant challenge. Consequently, several optimization techniques, such as metaheuristics, have been developed in order to address this type of problems. By iteratively exploring the solution space, metaheuristics offer a higher likelihood of finding near- optimal solutions, even in the presence of multiple local optima. This research introduces an enhanced social network search (ESNS) algorithm as an improvement over the existing social network search (SNS) algorithm, aiming to achieve the aforementioned objectives. The core of the SNS algorithm is driven by the social network users’ dialogue, imitation, creativity, and disputation moods. The proposed ESNS algorithm builds upon the SNS approach by enhancing its search capability, particularly around the best potential solution. The primary goal is to improve the algorithm’s ability to explore global search possibilities while avoiding being trapped in locally optimal solutions. The performance of ESNS has been tested in the 23 benchmark test suits, and its superiority against SNS and other recent algorithms has been verified. Moreover, To evaluate the effectiveness of the proposed ESNS algorithm, it is applied to four standard test systems comprising 11-, 15-, 40-, and 110-unit test systems. The results demonstrate that the ESNS algorithm outperforms other optimization algorithms in terms of solution quality and convergence speed. These findings suggest that the ESNS algorithm holds significant promise as a valuable tool for researchers and power system operators in addressing the economic dispatch problem. Overall, the ESNS technique presents a promising result to this complex challenges. Its capability to handle multiple constraints and its superior performance compared to other recent algorithms make it a valuable addition to the existing set of tools available for solving ELD.
2024
Hassan, M. H.; Kamel, S.; Jurado, F.; Desideri, U.
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11568/1217207
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