Taking into account the constraints in power system mode optimization by genetic algorithms

Abstract

Over the past decades, many publications on the use of genetic algorithms, which offer a new and powerful approach for solving the problem of power system mode optimization, have appeared. Despite this, the issues of effectively taking into account various constraints when solving such problems with genetic algorithms remain opened. In this regard, this article proposes an algorithm for optimizing power system modes by genetic algorithm, taking into account functional constraints in the form of equalities and inequalities by various penalty functions. The results of effectiveness research of the given algorithm in the example of optimization of 8-nodal power system with four thermal power plants and three lines with controlled power flows are presented.

Synthesis of the neuro-fuzzy regulator with genetic algorithm

“…Step 9, we will consider changes in the operating mode (load) of technological units of electric power facilities as a control object. The ranges of input and output parameters of the process are determined on the basis of the technological regulations, on the basis of which the terms of the sets are determined, each of which corresponds to one of the signal levels: Z -zero, PS -positive small, NS -negative small, PL -positive large, NL -negative large Figure 4 [25]- [27]. Figure 4 shows the term-multiples of input Figure 4(a) and output Figure 4(b) parameters of the NFR.…”