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Intelligent Industrial Systems
Published in: Intelligent Industrial Systems 3/2015

01-10-2015 | Original Paper

A Modified Genetic Algorithm for Optimal Allocation of Capacitor Banks in MV Distribution Networks

Authors: Antonino Augugliaro, Luigi Dusonchet, Salvatore Favuzza, Mariano Giuseppe Ippolito, Stefano Mangione, Eleonora Riva Sanseverino

Published in: Intelligent Industrial Systems | Issue 3/2015

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Abstract

In this paper, a genetic algorithm is developed in which each individual is represented not by a string but by a matrix: in this way the entire population is represented by a 3-D matrix. Such a representation is particularly useful for solving optimization problems with many discrete variables: such as, for example, the optimal allocation and sizing of distributed generation systems or the optimal compensation in a distribution system through the installation, in a prefixed number of nodes, of batteries of fixed or modulated capacitors, having different sizes. In these cases, the unknowns of the optimization process are the nodes where the apparatus can be installed and their rated sizes to be chosen in a discrete set of values. The adopted representation allows setting up a group of new operators whose application implies a strong increase of the search space size and consequently the number of algorithm parameters increases as well. The primary objective of this paper is that of evaluating the algorithm’s performance and, with this aim, it has been applied to the problem of the compensation of electrical distribution networks.
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Footnotes
1
The optimization made in the first step determines, for each node, a value of the capacitive reactive power that is the same for all load levels; this value is therefore influenced by the values assumed by the load in all the periods and the length of these periods. The optimization made only for the period of maximum load, not considering the influence of the periods with lower load, gives a value of capacitive power that is surely higher. Similarly, for the period of minimum load, the capacitive power determined on the basis of the levels at higher load, is higher than the optimum and it is therefore necessary to reduce it. Obviously, the final decision to increase (for high loads) or reduce (for low loads) the capacitive power to be installed also depends on the sizes of the existing banks and the cost parameters.
 
2
The economic convenience of switchable bank depends on the possibility to limit the energy losses; it is thus fundamental to verify whether such reduction is connected to an increase or to a decrease of the power of the banks installed; of course the final choice depends on the cost parameters.
 
3
The operation executed on the matrices of the parents consists in the identification of a horizontal row relevant to a given number of modules. Each of the two offspring is attained building a matrix starting from one of the parents and putting in a sequence, in the missing parts of the columns, the modules that are in the other row; if the two parents show a number of compensated nodes equal to the maximum number, the two offsprings will therefore have a number of nodes that is equal or smaller; if one or both parents have a number of compensated nodes that is lower than the maximum, the two offsprings have a number of nodes that is smaller or equal to the maximum.
 
4
The minimum losses compensation is equivalent to consider null the cost of capacitor banks; the value of losses in this condition may serve as a useful point of comparison to assess the quality of the solutions found when considering nonzero costs of compensation.
 
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Metadata
Title
A Modified Genetic Algorithm for Optimal Allocation of Capacitor Banks in MV Distribution Networks
Authors
Antonino Augugliaro
Luigi Dusonchet
Salvatore Favuzza
Mariano Giuseppe Ippolito
Stefano Mangione
Eleonora Riva Sanseverino
Publication date
01-10-2015
Publisher
Springer Singapore
Published in
Intelligent Industrial Systems / Issue 3/2015
Print ISSN: 2363-6912
Electronic ISSN: 2199-854X
DOI
https://doi.org/10.1007/s40903-015-0019-4

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