2010Unpublished venueRequires access

A simulated annealing algorithm for multi-objective distributed generation planning

Akram I Aly, Yasser G. Hegazy, Metwally A Alsharkawy

Open publisher page 37 citations

Abstract

This paper presents a multi-objective optimization model to determine the optimal solutions for the problem of sizing and locating distributed generation facilities. Cost minimization is achieved through the minimization of system losses; complex power acquired from DG units and the number of connected DG units. A Simulated annealing technique is implemented to optimize the proposed multi-objective model. A typical case study is presented and the results obtained are discussed.

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What this paper is about

This paper presents a multi-objective optimization model to determine the optimal solutions for the problem of sizing and locating distributed generation facilities. Cost minimization is achieved through the minimization of system losses; complex power acquired from DG units and the number of connected DG units. A Simulated annealing technique is implemented to optimize the proposed multi-objective model. A typical case study is presented and the results obtained are discussed.

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OpenAlex reports 37 citations for this work. Citation counts describe recorded attention and do not establish research quality.

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Available abstract

This paper presents a multi-objective optimization model to determine the optimal solutions for the problem of sizing and locating distributed generation facilities. Cost minimization is achieved through the minimization of system losses; complex power acquired from DG units and the number of connected DG units. A Simulated annealing technique is implemented to optimize the proposed multi-objective model. A typical case study is presented and the results obtained are discussed.

Key concepts: Simulated annealing, Minification, Sizing, Computer science, Mathematical optimization, Optimization algorithm, Distributed generation, Minimisation (clinical trials)

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