Abstract
In order to assess the reliability of distribution systems, more and more researchers are directing their attention to the artificial intelligent method, and several reliability indices have been proposed, such as basic load point indices and system performance indices. Artificial neural network is recently established as a useful and much promising too, applied to variety of power systems engineering. This paper presents ANN version for evaluating the reliability of distribution power systems (DPSs), in the proposed algorithm, the ANN used to predicted (RPS) using historical data method constructed according to the backpropagation learning rule. At the same time, System indices such as SAIFI and SAIDI of real distribution system are computed and compared with results generated by network method. The result obtained by proposed method gives acceptable reliability indices and can also found that the deviation of computed values by the proposed method is less than 1% and needs running time on ASUN network environment of less than 2 s. The ANN approach demonstrates advantage over the network method.
Highlights
Speaking, electrical power distribution systems include all parts of electrical utility systems between bulk power sources and the consumers’ service-entrance equipment
The main function of distribution network is to supply electrical power generated from large sources to consumers at desired voltage level and with a degree of appropriate reliability [1]
Distribution networks operating at several voltage levels including the networks of local or municipal unities are the primary parts of view; distribution system reliability evaluation is major preoccupation of the power company, in particular, in face of emergency and necessary reconfiguration
Summary
Electrical power distribution systems include all parts of electrical utility systems between bulk power sources and the consumers’ service-entrance equipment. Several methods [1,2,3,4,5] have been presented in literature for evaluating distribution system reliability; They have been divided in two abroad groups, firstly based on solution of logic networks and secondly on the solution of state-space models. Between them, these methods can accommodate most practical systems. The paper organized as follows: section proposed methodology includes ANN approach Section 3 test systems for the case study and Section 4 where result and discussion and Section 5 are concludes the paper
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