Abstract
The paper is concerned with multi-criteria optimization of the placement and selection of the nominal power static capacitor banks in distribution electric networks. The proposed hypothesis is that the use of evolutionary computation, in particular the classical genetic algorithm, allows for the effective overcoming of local extrema in complex combinatorial problems and finding a globally optimal configuration for compensating devices. This simultaneously reduces technical and operational losses and minimizes total economic costs while strictly adhering to regulatory restrictions on power quality. The objective of the study is the development, software implementation and practical testing of an automated method for designing reactive power compensation systems. The primary tool used is a comprehensive mathematical model of the fitness function, integrating discrete and continuous variables. The model takes into account active power losses, voltage deviations at nodal points, the tangent of the reactive power angle as well as capital investments for the equipment purchase and operating costs. The algorithm is specifically adapted to handle nonlinear distribution network characteristics and discrete nominal power ratings. A system of empirically selected weighting coefficients is used to normalize multidirectional criteria. Numerical simulations were performed on a test distribution network using the author's implementation of the algorithm, including discrete chromosome coding, a population of 100 individuals, point crossover and mutation with a 2%probability. The stopping condition was the stabilization of the best solution over 10 generations. Experimental results from a series of 1000 independent runs confirmed the high performance of the proposed approach. The average convergence of the algorithm to the optimal solution was achieved within 372 generations, demonstrating the method high computational efficiency. The developed methodological apparatus is recommended for implementation in the strategic planning of new distribution networks, existing electrical installations modernization, feasibility studies of investment projects, new consumer connection as well as in educational programs in the specialty of electricity supply.
Keywords
reactive power compensation, genetic algorithm, placement optimization, static capacitor banks, power losses, power factor.
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