Multiobjective Optimisation Problem

In an open electricity market environment, dispersed generation is predicted to play an important position. A high level of penetration and dispersion with distributed generators of an electric network imposes some additional problems; among them, of significant importance is the reconfiguration. The problem of reconfiguration has become more difficult because the customers ask more and more quality in power supply and reliability. The paper presents an original algorithm, aiming to find out the optimal open-looped points of electrical distribution networks with dispersed generation in order to obtain optimal radial configurations using Pareto optimality and evolution strategies.

Most popular evolutionary algorithms for multiobjective optimisation maintain a population of solutions from which individuals are selected for reproduction. In this paper, we introduce a simpler evolution scheme for multiobjective problems, called the Pareto archived evolution strategy (PAES). We argue that PAES may represent the simplest possible non-trivial algorithm capable of generating diverse solutions in the Pareto optimal set. The algorithm is identified as being a (1+ 1) evolution strategy, using local search from ...

A systematic framework is presented for optimum sensor selection for control and fault tolerance subject to complex system requirements. The framework combines the well known robust control via loop-shaping design, the fault tolerance control concept and multiobjective optimisation. The framework is tested via realistic simulations on an Electro Magnetic Suspension system which is a non-linear, unstable and safety-critical system with a set of non-trivial requirements.

Abstract: - This paper presents an educational approach based on computer simulation for teaching on emission pollution constraints concerning the use of fossil fuel in power systems plants, burning coal, oil or gas to convert into electric energy. Particularly, the paper addresses the short-...

This study proposes and applies an evolutionary-based approach for multiobjective reconfiguration in electrical power distribution networks. In this model, two types of indicators of power quality are minimised: (i) power system's losses and (ii) reliability indices. Four types of reliability indices are considered. A microgenetic algorithm ('GA) is used to handle the reconfiguration problem as a multiobjective optimisation problem with competing and non-commensurable objectives. In this context, experiments have been conducted on two standard test systems and a real network. Such problems characterise typical distribution systems taking into consideration several factors associated with the practical operation of medium voltage electrical power networks. The results show the ability of the proposed approach to generate well-distributed Pareto optimal solutions to the multiobjective reconfiguration problem. In the systems adopted for assessment purposes, our proposed approach was able to find the entire Pareto front. Furthermore, better performance indexes were found in comparison to the Pareto envelope-based selection algorithm 2 (PESA 2) technique, which is another well-known multiobjective evolutionary algorithm available in the specialised literature. From a practical point of view, the results established, in general, that a compact trade-off region exists between the power losses and the reliability indices. This means that the proposed approach can recommend to the decision maker a small set of possible solutions in order to select from them the most suitable radial topology.

The research area of evolutionary multiobjective optimization (EMO) is reaching better understandings of the properties and capabilities of EMO algorithms, and accumulating much evidence of their worth in practical scenarios. An urgent emerging issue is that the favoured EMO algorithms scale poorly when problems have" many"(eg five or more) objectives. One of the chief reasons for this is believed to be that, in many-objective EMO search, populations are likely to be largely composed of nondominated solutions. In ...

Although great progress has been made in the last 40 years, efficient operation of water reservoir systems still remains a very active research area. The combination of multiple water uses, non-linearities in the model and in the objectives, strong uncertainties in inputs and high dimensional state make the problem challenging and intriguing. The purpose of this paper is to review, in