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

Berna Tektas Sivrikaya, Ferhan Cebi, Hasan Hüseyin Turan, Nihat Kasap, Dursun Delen

Research output: Contribution to journalArticle

3 Scopus citations


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.

Original languageEnglish
Pages (from-to)975-991
Number of pages17
JournalInformation Systems Frontiers
Issue number5
StatePublished - 1 Oct 2017
Externally publishedYes



  • bilateral contracts market
  • climate change
  • day-ahead market
  • energy generation
  • fuzzy programming
  • hydroelectric power
  • Long-term capacity planning

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