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Evolutionary hybrid approaches for a power system scheduling problem

Dahal, K. and Aldridge, C. and Galloway, S.J. (2007) Evolutionary hybrid approaches for a power system scheduling problem. European Journal of Operational Research, 177 (3). pp. 2050-2068. ISSN 0377-2217

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Abstract

Generation scheduling (GS) in power systems is a tough optimisation problem which continues to present a challenge for efficient solution techniques. The solution is to define on/off decisions and generation levels for each electricity generator of a power system for each scheduling interval. The solution procedure requires simultaneous consideration of binary decision and continuous variables. In recent years researchers have focused much attention on developing new hybrid approaches using evolutionary and traditional exact methods for this type of mixed-integer problems. This paper investigates how the optimum or near optimum solution for the GS problem may be quickly identified. A design is proposed which uses a variety of metaheuristic, heuristics and mathematical programming techniques within a hybrid framework. The results obtained for two case studies are promising and show that the hybrid approach offers an effective alternative for solving the GS problems within a realistic timeframe.

Item type: Article
ID code: 11351
Keywords: evolutionary computations, genetic algorithms, knowledge-based systems, power systems, scheduling, Electrical engineering. Electronics Nuclear engineering, Modelling and Simulation, Management Science and Operations Research, Information Systems and Management
Subjects: Technology > Electrical engineering. Electronics Nuclear engineering
Department: Faculty of Engineering > Electronic and Electrical Engineering
Faculty of Science > Mathematics and Statistics > Mathematics
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    Depositing user: Strathprints Administrator
    Date Deposited: 24 Nov 2011 17:41
    Last modified: 04 Sep 2014 20:47
    URI: http://strathprints.strath.ac.uk/id/eprint/11351

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