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A Fuzzy Prescriptive Analytics Approach to Power Generation Capacity Planning

Author

Listed:
  • Berna Tektaş

    (Faculty of Business Administration, Izmir Katip Celebi University, Cigli, Izmir 35620, Turkey)

  • Hasan Hüseyin Turan

    (School of Engineering and Information Technology, University of New South Wales, Canberra, ACT 2612, Australia)

  • Nihat Kasap

    (Sabanci Business School, Sabanci University, Tuzla, Istanbul 34956, Turkey)

  • Ferhan Çebi

    (Management Faculty, Istanbul Technical University, Maçka, Istanbul 34367, Turkey)

  • Dursun Delen

    (Spears School of Business, Oklahoma State University, Stillwater, OK 74078, USA
    Faculty of Engineering and Natural Sciences, Istinye University, Istanbul 34396, Turkey)

Abstract

This study examines the long-term energy capacity investment problem of a power generation company (GenCo), considering the drought threat posed by climate change in hydropower resources in Turkey. The mid-term planning decisions such as maintenance and refurbishment scheduling of power plants are also considered in the studied investment planning problem. In the modeled electricity market, it is assumed that GenCos conduct business in uncertain market conditions with both bilateral contracts (BIC) and day-ahead market (DAM) transactions. The problem is modeled as a fuzzy mixed-integer linear programming model with a fuzzy objective and fuzzy constraints to handle the imprecisions regarding both the electricity market (e.g., prices) and environmental factors (e.g., hydroelectric output due to drought). Bellman and Zadeh’s max-min criteria are used to transform the fuzzy capacity investment model into a model with a crisp objective and constraints. The applicability of methodology is illustrated by a case study on the Turkish electric market in which GenCo tries to find the optimal power generation investment portfolio that contains five various generation technologies alternatives, namely, hydropower, wind, conventional and advanced combined-cycle natural gas, and steam (lignite) turbines. The results show that wind turbines with low marginal costs and steam turbines with high energy conversion efficiency are preferable, compared with hydroelectric power plant investments when the fuzziness in hydroelectric output exists (i.e., the expectation of increasing drought conditions as a result of climate change). Furthermore, the results indicate that the gas turbine investments were found to be the least preferable due to high gas prices in all scenarios.

Suggested Citation

  • Berna Tektaş & Hasan Hüseyin Turan & Nihat Kasap & Ferhan Çebi & Dursun Delen, 2022. "A Fuzzy Prescriptive Analytics Approach to Power Generation Capacity Planning," Energies, MDPI, vol. 15(9), pages 1-26, April.
    • Handle: RePEc:gam:jeners:v:15:y:2022:i:9:p:3176-:d:803008
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    References listed on IDEAS

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