Application of a genetic algorithm in the reduction of loss and control of the voltage of distribution networks using the real optimization of fixed and switched capacitors

Abstract

SUMMARYFor a long time, reduction of the loss and control of the voltage of electric distribution networks have been considered to be some of the most important problems of such networks. The importance of these two features arises from the fact that they are directly related to the loss of electric energy. One of the essential and effective methods in solving these two problems is the use of fixed and switched capacitors.In this paper, a new method has been presented on the basis of a genetic algorithm aimed at reducing the loss and controlling the network voltage by using fixed and switched capacitors in the form of real optimization. By real optimization in this method, we mean the use of the range of low-and medium-voltage capacitors available in the market with their real prices and by modelling the load at its different levels, the real model of the network is also taken into consideration. With due regard to the above facts and considering the large number of variables of optimization, the use of the genetic algorithm is an important factor in finding the real optimal method in the application of capacitors.

Optimal stochastic capacitor placement problem from the reliability and cost views using firefly algorithm

“…In recent years, a wide range of researches have been implemented to see different features of optimal capacitor placement and sizing. The solutions of optimal capacitor placement problem can be divided into four main categories [2]: (i) analytical techniques [3], (ii) heuristics methods [4,5], (iii) numerical programming based methods [6] and (iv) artificial techniques [7]. In the above works, the main focuses have been paid to traditional objectives.…”

Interactive Pareto‐optimal with advantage programming for solving bi‐objective capacitor planning

“…It consists of determining the locations, types (fixed or switched), and sizes of capacitors to be installed in the planning period, and also the ON-OFF status of each installed capacitor for a whole year in the operating period, such that the cost profits and quality conditions of the system are improved considering the operating and expansion constraints. Some previous studies [1][2][3] formulated the problem with a single objective. Generally, cost is employed as the objective function and the other possible objective, such as voltage deviation, are treated as constraints.…”

“…In the past decade, several searching techniques, such as linear programming [8,9], dynamic programming [10], sensitivity analysis [11], genetic algorithm [1,12], tabu search [6], and neural networks [13], have been used to address capacitor planning issues with promising results. Especially, three multiobjective evolutionary algorithms have been implemented and applied to the economic dispatch problem with impressive success [14].…”

Reactive power and voltage control in grid-connected wind farms: an online optimization based fast model predictive control approach

“…The problem of RPVC has been well studied in the literature. Various types of evolutionary optimization algorithm like Genetic Algorithm(GA) [18], [28], [35], shuffled frogleaping algorithm [41], Particle Swarm Optimization (PSO) [11], various variants of Genetic algorithms [38], PSO [1], [24], [42], [48], [29], Ant colony optimization [21], [43], Differential Evolution (DE) [40], [20], Cuckoo Search (CS) [4], Harmony Search (HS) [3], [16], [9] etc. have been used.…”