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Fuzzy linear programming for DSS in energy planning

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  • T. Canz

Abstract

Energy system planning requires the use of planning tools that help to design the energy systems under consideration. The mathematical models of real world energy systems are usually multi-period linear optimisation (LP) programs. In these models, the objective function describes the total discounted costs of covering the demand for final energy or energy services. The demand for various forms of energy or energy services is the driving force of the models. By using such LP formulations, decision makers can elaborate suitable strategies to solve their planning problems such as the development of emission reduction strategies. Uncertainties that affect the process of energy system planning can be divided in parameter and in decision uncertainties. Data or parameter uncertainties can be addressed either by stochastic optimisation or by the methodology of fuzzy linear programming (flp). In addition, fuzzy linear programming allows the explicit incorporation of decision uncertainties in a mathematical model. Employing the parallels between multi-objective linear programming (MOLP) and FLP, problems of FLP in DSS-applications are pointed out and solutions are offered. The proposed interactive procedure for solving FLP problems is based on the methodology of aspiration-reservation based decision support and still enables modelling of uncertainties in a fuzzy sense.

Suggested Citation

  • T. Canz, 1999. "Fuzzy linear programming for DSS in energy planning," International Journal of Global Energy Issues, Inderscience Enterprises Ltd, vol. 12(1/2/3/4/5), pages 138-151.
    • Handle: RePEc:ids:ijgeni:v:12:y:1999:i:1/2/3/4/5/6:p:138-151
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    Cited by:

    1. Jeroen Beliën & Jan Colpaert & Liesje De Boeck & Johan Eyckmans & Wouter Leirens, 2013. "Teaching Integer Programming Starting From an Energy Supply Game," INFORMS Transactions on Education, INFORMS, vol. 13(3), pages 129-137, May.

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