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Policy-driven planning of distribution automation, using mixed integer non-linear programming

Feeder automation (FA) is a major function of distribution automation (DA) and according to economic analysis is the most beneficial one. Since implementing FA is an expensive time-consuming process, it is important to find a way to recognize the most economic timing schedule to start FA implementation on. In this paper a novel method is proposed that uses mixed integer non-linear programming to evaluate the economic aspects of FA on feeders and to find the optimal schedule to implement FA. In addition to Energy Not Served (ENS) index that shows supplier's financial loss, we will consider Customer Energy Interrupted (CEI) index that represents financial loss of different types of customers (industrial, commercial or residential). Since reducing CEI index brings an indirect profit for suppliers, different scenarios are introduced to take CEI index into account. These scenarios are based on policies and administration of distribution companies. The method is tested on a three feeder test network using sbb solver of GAMS and improved results are presented.