Optimal switch placement considering costs and annual reliability improvement during the regulatory period. (17th November 2016)

• Record Type: Journal Article
• Authors: Conti, Stefania; Rizzo, Santi A.; Zeineldin, Hatem Hussein
• Is Part Of: International transactions on electrical energy systems. Volume 27:Number 5(2017:Jul.)
• Page Start: n/a
• Page End: n/a
• Publication Date: 2016-11-17
• Subjects: genetic algorithms -- optimal scheduling -- Pareto optimization -- power system planning -- power system reliability -- regulatory period; Electric power -- Periodicals; Electric power systems -- Periodicals; Electrical engineering -- Periodicals; 621.3
• DOI: 10.1002/etep.2309
• Languages: English
• ISSNs: 2050-7038

Abstract

Summary: The introduction of reward/penalty mechanisms by the national regulation authorities has strongly increased the utilities' interest in distribution systems reliability improvement. Usually, the regulator correlates such mechanisms with the annual number and/or duration of interruptions per customer, requiring the utilities to reach a target value for these reliability indicators each year for a given regulatory period. Installing switches along the distribution network positively affects reliability but does involve utility costs. Therefore, utilities need a method to schedule annually the switches' placement to obtain the required annual reliability improvement in a cost‐effective manner. This paper proposes a simple and effective model of the optimization problem that enables the distribution network operator to try to achieve uniform levels of improvement in distribution system reliability indices during the regulatory period. In this perspective, the paper presents a way to provide the optimal number, type, and position of the switches that must be installed each year to achieve both the targeted annual reliability improvement and the cheapest investment cost during the overall regulatory period. The proposed approach is formulated as a multiobjective optimization problem and is solved using a genetic algorithm. The proposed approach is useful for the distribution network operator since it is able to provide the overall minimum investment cost required for each desired reliability level to be reached annually over the regulatory period, as well as the maximum annual reliability that can be achieved for each overall economic investment by performing only one single optimization.