THE METHOD OF POWER NETWORKS MODE OPTIMIZATION IN BASIS OF GENETIC ALGORITHM

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7 ноябр 2025

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THE METHOD OF POWER NETWORKS MODE OPTIMIZATION IN BASIS OF GENETIC ALGORITHM

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One of the main tasks solved in planning short-term and managing operational modes of electric power systems (EPS) is the optimization of their network modes on the adjustable parameters. For modern complex EPS, this task is often characterized by the multi-extremality of the objective function, the appearance of discontinuous functions, the presence of initial information of a probabilistic and partially uncertain nature. In such conditions, solving the problem by traditional algorithms using mainly linear and nonlinear programming methods, Lagrange, gradient, etc., is associated with a number of difficulties in simplifying them and bringing them to a convenient form for calculations. Such simplifications lead to a decrease in the expected effect of optimization. In this regard, research is relevant on the development and implementation of algorithms for solving this problem based on the use of artificial intelligence methods, in which a number of the listed difficulties are easily overcome. The current existence of some algorithms for solving the problems of calculating EPS modes using artificial intelligence methods cannot be considered sufficiently perfect. A characteristic drawback is their lack of universality and the impossibility of using them for all cases. This paper proposes a new method for optimizing the electrical grid modes by reactive power and node voltage based on a genetic algorithm that has fast and reliable convergence of the iterative calculation process. It effectively takes into account all types of simple and functional limitations, and overcomes many shortcomings typical for traditional algorithms for solving this problem. The results of a study of the effectiveness of the proposed method are presented using the example of optimizing the electrical grid mode using the 14-node IEEE test scheme.

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# genetic algorithm# optimal control# artificial intelligence# electric networks# reactive power# node voltage

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https://eroi.uz/11.0008/A1125-0010

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Foydalanilgan adabiyotlar

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