David Elmakis

Redundancy optimization for series-parallel multi-state systems

This paper generalizes a redundancy optimization problem to multi-state systems, where the system and its components have a range of performance levels-from perfect functioning to complete failure. The components are: (1) chosen from a list of products available in the market; and (2) characterized by their nominal performance level, availability and cost. System availability is represented by a multi-state availability function, which extends the binary-state availability. To satisfy the required multi-state system availability, the redundancy for each component can be used. A procedure which determines the minimal-cost series-parallel system structure subject to a multi-state availability constraint is proposed. A fast procedure is developed, based on a universal generating function, to evaluate the multi-state system availability. Two important types of systems are considered and special operators for the universal generating function determination are introduced. A genetic algorithm is used as an optimization technique. Examples are given.

Power system structure optimization subject to reliability constraints

Abstract The problem of the optimization of the structure of a power system where redundant elements are included in order to provide a desired level of reliability is considered. A procedure which determines the minimal cost series-parallel system configuration is proposed. In this procedure, system elements are chosen from a list of products available on the market and the number of such elements is determined for each system component. The elements are characterized by their capacity, availability and cost. System reliability is defined as the ability to satisfy consumer demand which is represented as a piecewise cumulative load curve. To evaluate system reliability, a fast procedure is developed which is based on a universal generating function. A genetic algorithm is used as an optimization technique. An example of the redundancy optimization of a power station coal feeding system is presented.

Structure optimization of power system with different redundant elements

Abstract The problem of optimization of the structure of a power system where redundant elements are included in order to provide a desired level of reliability is considered. The elements of the system are characterized by their capacity, availability and cost. A procedure which determines the minimal cost series-parallel system configuration is proposed which allows elements with different parameters to be allocated in parallel. In this procedure, system elements are chosen from a list of products available on the market. System reliability is defined as the ability to satisfy consumer demand which is represented as a piecewise cumulative load curve. To evaluate system reliability, a universal generating function technique is applied. A genetic algorithm (GA) is used as an optimization technique. Basic GA procedures adapted to the given problem are presented, and different versions of the GA are compared to determine the most effective one. An example of the optimal structure determination and optimal extension of a power station coal transportation system are presented.

Optimal sectionalizer allocation in electric distribution systems by genetic algorithm

Abstract 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.

Genetic algorithm for optimal sectionalizing in radial distribution systems with alternative supply

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.

Genetic algorithm for open-loop distribution system design

Abstract 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.

System approach to shunt capacitor allocation in radial distribution systems

Abstract This paper presents a system approach to shunt capacitor placement on distribution systems under capacitor switching constraints. The optimum capacitor allocation solution is found for the system of feeders fed through their transformer and not for any individual feeder. The main benefits due to capacitor installation, such as system capacity release and reduction of overall power and energy losses are considered. The capacitor allocation constraints due to capacitor-switching transients are taken into account. These constraints are extremely important if pole-mounted capacitors are used together with a substation capacitor bank. A genetic algorithm is used as an optimization tool. An illustrative example is presented. The algorithm is currently in use in the Israel Electric Corporation (IECo).

Genetic algorithm and universal generating function technique for solving problems of power system reliability optimization

To provide a required level of power system reliability, redundant elements are included. Usually engineers try to achieve this level with minimal cost. The problem of total investment cost minimization, subject to reliability constraints, is well known as the redundancy optimization problem. When applied to power systems (PS), reliability is considered as a measure of the ability of the system to meet the load demand, i.e. to provide an adequate supply of electrical energy. In this case the outage effect will be essentially different for units with different nominal generating (transmitting) capacity. It will also depend on consumer demand. Therefore the capacities of PS components should be taken into account as well as the consumer load curve. To solve the redundancy optimization problem for a system with different element capacities, a genetic algorithm is used which is a technique inspired by a principle of evolution. A procedure based on the universal generating function method is used for fast reliability estimation of multi-state PS with series-parallel structure. Using the composition of the genetic algorithm and the universal generating function technique provides solutions of the following problems of reliability optimization of series-parallel multi-state PS: structure optimization subject to reliability constraints, optimal expansion, maintenance optimization and optimal multistage modernization.

Life cycle cost analysis: Actual problem in industrial management

The reliability associated costs are the main part of total life cycle cost for any repairable system. The paper presents the history of life cycle cost analysis, its principles and applicable standards. It analyzes the reasons behind the contradiction between the great theoretical achievements and their relatively rare applications in practice. It was shown that incorrect management is the main reason. Measures for management improvement were suggested.

Reliability indices of a radial distribution system with sectionalizing as a function of network structure parameters

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.