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Reactive energy scheduling using bi-objective programming with modified particle swarm optimization

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  • Kuo, Cheng-Chien

Abstract

Interactive Bi-objective with Valuable Trade-off programming, together with a modified particle swarm optimization for the daily scheduling of switched capacitors is presented. The two main contradictory concerns of line loss reduction and minimum number of switching operations are considered for realistic request. Both the operating and load constraints for distribution feeders are formulated for practical operation. The proposed approach can provide a set of flexible and valuable trade-off solutions as dictated by decision makers of electric utilities. Quantitative measures can also be provided to aid the decision-making process. To demonstrate the effectiveness and feasibility of the proposed approach, comparative studies were systematically conducted on an actual feeder. The experiment showed encouraging results suggesting that the proposed approach was capable of efficiently determining better quality solutions.

Suggested Citation

  • Kuo, Cheng-Chien, 2009. "Reactive energy scheduling using bi-objective programming with modified particle swarm optimization," Energy, Elsevier, vol. 34(6), pages 804-815.
  • Handle: RePEc:eee:energy:v:34:y:2009:i:6:p:804-815
    DOI: 10.1016/j.energy.2009.03.002
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    References listed on IDEAS

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    1. Arcuri, P. & Florio, G. & Fragiacomo, P., 2007. "A mixed integer programming model for optimal design of trigeneration in a hospital complex," Energy, Elsevier, vol. 32(8), pages 1430-1447.
    2. Yuan, Xiaohui & Su, Anjun & Yuan, Yanbin & Nie, Hao & Wang, Liang, 2009. "An improved PSO for dynamic load dispatch of generators with valve-point effects," Energy, Elsevier, vol. 34(1), pages 67-74.
    3. Mossolly, M. & Ghali, K. & Ghaddar, N., 2009. "Optimal control strategy for a multi-zone air conditioning system using a genetic algorithm," Energy, Elsevier, vol. 34(1), pages 58-66.
    4. Dimopoulos, George G. & Frangopoulos, Christos A., 2008. "Optimization of energy systems based on Evolutionary and Social metaphors," Energy, Elsevier, vol. 33(2), pages 171-179.
    5. Chang, Yung-Chung, 2006. "An innovative approach for demand side management—optimal chiller loading by simulated annealing," Energy, Elsevier, vol. 31(12), pages 1883-1896.
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    Cited by:

    1. Narang, Nitin & Dhillon, J.S. & Kothari, D.P., 2012. "Multiobjective fixed head hydrothermal scheduling using integrated predator-prey optimization and Powell search method," Energy, Elsevier, vol. 47(1), pages 237-252.
    2. Kusiak, Andrew & Li, Mingyang, 2010. "Reheat optimization of the variable-air-volume box," Energy, Elsevier, vol. 35(5), pages 1997-2005.
    3. Lin, Q.G. & Huang, G.H., 2010. "An inexact two-stage stochastic energy systems planning model for managing greenhouse gas emission at a municipal level," Energy, Elsevier, vol. 35(5), pages 2270-2280.

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