Optimization of power network states by voltage using genetic algorithm

Abstract

Relevance: Determining the permissible operating states of modern complex electric networks and selecting the optimal one for implementation is one of the pressing issues. Currently, in developed countries, it has been established that the use of genetic algorithms, taking into account real characteristics, ensures a reduction in fuel consumption. In particular, special attention is given to the use of genetic algorithms for calculating and optimizing stable states of electric networks. Today, numerous optimization methods are known for solving various problems in the energy sector. The current stage of electric power development is characterized by significant limitations on allocated resources and increasing demands for their efficient use. This highlights the urgency of developing and implementing new optimization technologies.

Aim: To analyze and substantiate mathematical models and methods for the problem of optimizing the states of electric networks based on node voltages using genetic algorithms.

Methods: Theories of calculation and optimization of steady states of electric networks, linear and nonlinear programming, artificial intelligence methods, genetic algorithms, and system analysis methods were used.

Results: The possibilities of effective use of genetic algorithms in optimizing the states of electric networks have been investigated. The applied genetic algorithm provides faster and more reliable results compared to traditional optimization methods. The genetic algorithm is recommended as an effective tool for increasing energy efficiency and ensuring system stability in the optimization of electric network states.