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A fuzzy long-term investment planning model for a GenCo in a hybrid electricity market considering climate change impacts

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Abstract

We study the long-term generation capacity investment problem of an independent power generation company (GenCo) that functions in an environment where GenCos perform business with both bilateral contracts (BC) and transactions in the day-ahead market (DAM). A fuzzy mixed integer linear programming model with a fuzzy objective and fuzzy constraints is developed to incorporate the impacts of imprecision/uncertainty in the economic environment on the calculation of the optimal value of the GenCo’s objective function. In formulating the fuzzy objective function we also include the potential impacts of climate change on the energy output of hydroelectric power plants. In addition to formulating and solving the capacity planning/investment problem, we also performed scenario-based (sensitivity) analysis to explore how investment decisions of the GenCos change when fuzziness (tolerance) in the maximum energy output of hydroelectric units and/or drought expectation increases. The proposed model is novel and investigates the effects of factors like drought expectations of climate changes, hydroelectric power plant investments, and other power generation technology investment options.

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Authors and Affiliations

  1. Department of MIS, Uludag University, Inegol, Bursa, 16400, Turkey

    Berna Tektas Sivrikaya

  2. Faculty of Management, Istanbul Technical University, Macka, 34367, Istanbul, Turkey

    Ferhan Cebi

  3. Department of Mechanical and Industrial Engineering, Qatar University, Doha, 2713, Qatar

    Hasan Hüseyin Turan

  4. School of Management, Sabanci University, 34956, Tuzla, Istanbul, Turkey

    Nihat Kasap

  5. Spears School of Business, Oklahoma State University, Stillwater, OK, 74078, USA

    Dursun Delen

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  1. Berna Tektas Sivrikaya
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  5. Dursun Delen
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Sivrikaya, B.T., Cebi, F., Turan, H.H. et al. A fuzzy long-term investment planning model for a GenCo in a hybrid electricity market considering climate change impacts. Inf Syst Front 19, 975–991 (2017). https://doi.org/10.1007/s10796-016-9707-1

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