This paper presents a model of unsupplied energy reduction achieved by the insulation of specified parts of lines belonging to a radial distribution system. An optimization procedure is developed that defines which network sections should be insulated to obtain the greatest possible reliability enhancement, subject to investment cost limitation, or to achieve a desired level of reliability by the minimum cost. The combination of line insulation with system sectionalizing and alternative supply is considered.

Since reliability indices are very important in customer services, they should be considered when a distribution system is designed. A method of estimating the average time of interruptions and the annual unsupplied energy caused by line failures is proposed in this paper. Radial single-feeder networks, typical for rural regions, are considered. It is shown that the most influential factors in determining system reliability are the area of the region, the angle of the feeder service zone, and the number of customers (load points). In particular, the effect of automatic sectionalizer implementation on unsupplied energy is evaluated using an optimal allocation algorithm which adopts the genetic search technique. The efficiency of the system sectionalizing method is estimated as a function of network structure parameters. A simulation study consisting of extensive computational experimentation was carried out to obtain a data set used to train neural networks. The weight coefficients and the structure of these networks are presented, so that functional dependences can be reproduced using available neural network software.

To ensure a given level of reliability of energy supply, distribution networks should be configured in such a way that each load point may be supplied from alternative sources. The method proposed in this paper is aimed at designing such distribution systems with minimal feeder length, energy losses and load imbalance between transformers, subject to voltage drop and capacity constraints. The method is based on the biologically inspired genetic algorithm (GA). Basic GA procedures adapted to the given problem are presented and five versions of the GA are compared. Test results are reported which demonstrate that the chosen version of the proposed algorithm outperforms a heuristic procedure proposed previously.

A procedure for optimal allocation of sectionalizing switches in radial distribution systems is proposed. This procedure is aimed at minimizing unsupplied energy caused by network failures. Opportunities for alternative source supply made possible by network reconfiguration are considered. Two applications of this procedure are explored: when the allocation of alternative supply tie-lines is given and when the optimal allocation of a specified number of tie-lines. as well as the allocation of sectionalizers, must be determined. The procedure is based upon the genetic algorithm, a search technique motivated by natural evolution. The basic operators of the genetic algorithm are adapted to solve the problems considered. Performance enhancing modifications of the algorithm are suggested when applicable. A medium-scale, practical example is presented to illustrate the validity and effectiveness of the proposed method.

This paper presents an economics based model of sectionalizer allocation in single radial feeder distribution systems. The model considers both cost of energy losses and capital investment in the sectionalizer installation. The cases when sectionalizers are not fully reliable and when they may cause additional short-circuits are investigated. To solve the problem of optimal sectionalizer allocation a genetic algorithm based procedure is developed. An illustrative example is presented.