Abstract
Smart secondary substations (S/S) play a vital role in advanced Distribution automation system (ADAS) in order to achieve self-healing grid and improve the reliability level of medium voltage (MV) distribution networks. However, the main challenges with ADAS is the determination of the optimal automation level. This is a non-linear discrete optimization problem with multi-dimensions. Thus, it is not possible to apply numerical algorithms for direct searching of all possible solutions. In this paper, a methodology to determine the optimal automation level of MV distribution network based on a heuristic combinatorial search technique is proposed. In addition, a substation-centralized-based ADAS is implemented on a real, urban, underground MV distribution network. The existing distribution network is used to show the validity and efficiency of the proposed methodology. Finally, a reliability assessment study is applied for the proposed automated network to examine the improvement of reliability level. The results indicate clearly the reduction in system reliability indices SAIDI and EENS.
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