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Joint economic and emission dispatch in energy markets: A multiobjective mathematical programming approach

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  • Vahidinasab, V.
  • Jadid, S.

Abstract

Economic load dispatch is the method of determining the most efficient, low-cost and reliable operation of a power system by dispatching the available electricity generation resources to supply the load on the system. Environmental concerns that arise due to the operation of fossil fuel fired electric generators, change the classical problem into multiobjective emission/economic dispatch (MEED) which is formulated as a constrained nonlinear multiobjective mathematical programming (MMP). The proposed MEED formulation includes emission minimization objective, AC load flow constraints and security constraints of the power system which usually are found simultaneously in real-world power systems. The proposed model has a more accurate evaluation of transmission losses obtained from the load flow equations. The MMP approach based on ɛ-constraint algorithm has been proposed for generating Pareto-optimal solutions of power systems MEED problem. Moreover, fuzzy decision making process is employed to extract one of the Pareto-optimal solutions as the best compromise nondominated solution. The proposed approach is simulated on the IEEE 30-bus six-generator test system and obtained results have been comprehensively compared with some of the most recently published research in the area (from the both aspects of precision and execution tome) which confirms the potential and effectiveness of the proposed approach.

Suggested Citation

  • Vahidinasab, V. & Jadid, S., 2010. "Joint economic and emission dispatch in energy markets: A multiobjective mathematical programming approach," Energy, Elsevier, vol. 35(3), pages 1497-1504.
    • Handle: RePEc:eee:energy:v:35:y:2010:i:3:p:1497-1504
    DOI: 10.1016/j.energy.2009.12.007
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    References listed on IDEAS

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    1. Jonathan F. Bard, 1988. "Short-Term Scheduling of Thermal-Electric Generators Using Lagrangian Relaxation," Operations Research, INFORMS, vol. 36(5), pages 756-766, October.
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