Abstract
This paper proposes a model based on Fuzzy Genetic Algorithm (FGA) to determine the optimal capacity and location of a DG unit in a radial distribution network. In the FGA, a fuzzy controller is integrated into GA to adjust the crossover and mutation rates dynamically to maintain the proper population diversity during GA's operation. This effectively overcomes the premature convergence problem of the simple genetic algorithm (SGA). The main objective functions considered in this study are maximisation of cost savings arising from energy loss, minimisation of voltage drops across all lines, and maximisation of the transfer capability of the system. The model takes into account the peculiarities of radial distribution networks, such as high R/X ratio, voltage dependency and composite nature of loads. The proposed model is evaluated on three radial test distribution systems, and the results obtained are very impressive, with high computational efficiency, when compared with those of the existing approaches cited in the literature.
Highlights
The term distributed generation Elnashar [5] categorised the impacts of DG on the (DG), known as embedded generation (EG) or de- distribution systems as positive, e.g. voltage profile centralised generation (DG) in some quarters is defined c 2014 ADVANCES IN ELECTRICAL AND ELECTRONIC ENGINEERING
Improvement, and negative, such as increased system loss and short circuit level, and used these to formulate a multi-objective function. This problem formulation is flawed because DG would lead to increase in loss only when it is sited in improper locations, and so its impact cannot be considered negative in all cases
A multi-objective model for optimal allocation of a single DG unit in a radial distribution network has been proposed in this paper
Summary
The aim of the multi-objective function formulated in this study is to maximise the energy loss cost savings, minimise voltage drops across all lines, and to maximise the power transfer capability of the system. Each of these is treated in the literature. Minimising the voltage drop on a line is synonymous to maximising the difference between the voltage drop on the line before and after DG connection to the network This can be formulated in percentage form as in Eq (6). These weights are allocated by the system planner to indicate the relative importance of each objective
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