IDEAS home Printed from https://ideas.repec.org/a/gam/jeners/v15y2022i9p3176-d803008.html
   My bibliography  Save this article

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
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/1996-1073/15/9/3176/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/1996-1073/15/9/3176/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. R. E. Bellman & L. A. Zadeh, 1970. "Decision-Making in a Fuzzy Environment," Management Science, INFORMS, vol. 17(4), pages 141-164, December.
    2. Heejung Park, 2020. "Generation Capacity Expansion Planning Considering Hourly Dynamics of Renewable Resources," Energies, MDPI, vol. 13(21), pages 1-15, October.
    3. Rajesh, K. & Bhuvanesh, A. & Kannan, S. & Thangaraj, C., 2016. "Least cost generation expansion planning with solar power plant using Differential Evolution algorithm," Renewable Energy, Elsevier, vol. 85(C), pages 677-686.
    4. Almeida Prado, Fernando & Athayde, Simone & Mossa, Joann & Bohlman, Stephanie & Leite, Flavia & Oliver-Smith, Anthony, 2016. "How much is enough? An integrated examination of energy security, economic growth and climate change related to hydropower expansion in Brazil," Renewable and Sustainable Energy Reviews, Elsevier, vol. 53(C), pages 1132-1136.
    5. Jang-yeop Kim & Kyung Sup Kim, 2018. "Integrated Model of Economic Generation System Expansion Plan for the Stable Operation of a Power Plant and the Response of Future Electricity Power Demand," Sustainability, MDPI, vol. 10(7), pages 1-27, July.
    6. Hemmati, Reza & Hooshmand, Rahmat-Allah & Khodabakhshian, Amin, 2016. "Coordinated generation and transmission expansion planning in deregulated electricity market considering wind farms," Renewable Energy, Elsevier, vol. 85(C), pages 620-630.
    7. Abdulaziz Almalaq & Khalid Alqunun & Mohamed M. Refaat & Anouar Farah & Fares Benabdallah & Ziad M. Ali & Shady H. E. Abdel Aleem, 2022. "Towards Increasing Hosting Capacity of Modern Power Systems through Generation and Transmission Expansion Planning," Sustainability, MDPI, vol. 14(5), pages 1-26, March.
    8. Hanif D. Sherali & Konstantin Staschus & Jorge M. Huacuz, 1987. "An Integer Programming Approach and Implementation for an Electric Utility Capacity Planning Problem with Renewable Energy Sources," Management Science, INFORMS, vol. 33(7), pages 831-847, July.
    9. Pereira, Adelino J.C. & Saraiva, João Tomé, 2011. "Generation expansion planning (GEP) – A long-term approach using system dynamics and genetic algorithms (GAs)," Energy, Elsevier, vol. 36(8), pages 5180-5199.
    10. Pohekar, S. D. & Ramachandran, M., 2004. "Application of multi-criteria decision making to sustainable energy planning--A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 8(4), pages 365-381, August.
    11. Nissan Levin & Asher Tishler & Jacob Zahavi, 1983. "Time Step vs. Dynamic Optimization of Generation-Capacity-Expansion Programs of Power Systems," Operations Research, INFORMS, vol. 31(5), pages 891-914, October.
    12. Berna Tektas Sivrikaya & Ferhan Cebi, 2016. "Long-termed investment planning model for a generation company operating in both bilateral contract and day-ahead markets," International Journal of Information and Decision Sciences, Inderscience Enterprises Ltd, vol. 8(1), pages 24-52.
    13. Rommelfanger, Heinrich, 1996. "Fuzzy linear programming and applications," European Journal of Operational Research, Elsevier, vol. 92(3), pages 512-527, August.
    14. Olsina, Fernando & Garces, Francisco & Haubrich, H.-J., 2006. "Modeling long-term dynamics of electricity markets," Energy Policy, Elsevier, vol. 34(12), pages 1411-1433, August.
    15. Byman Hamududu & Aanund Killingtveit, 2012. "Assessing Climate Change Impacts on Global Hydropower," Energies, MDPI, vol. 5(2), pages 1-18, February.
    16. Borges, Ana Rosa & Antunes, Carlos Henggeler, 2003. "A fuzzy multiple objective decision support model for energy-economy planning," European Journal of Operational Research, Elsevier, vol. 145(2), pages 304-316, March.
    17. Dennis Anderson, 1972. "Models for Determining Least-Cost Investments in Electricity Supply," Bell Journal of Economics, The RAND Corporation, vol. 3(1), pages 267-299, Spring.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Berna Tektas Sivrikaya & Ferhan Cebi & Hasan Hüseyin Turan & Nihat Kasap & Dursun Delen, 2017. "A fuzzy long-term investment planning model for a GenCo in a hybrid electricity market considering climate change impacts," Information Systems Frontiers, Springer, vol. 19(5), pages 975-991, October.
    2. Berna Tektas Sivrikaya & Ferhan Cebi & Hasan Hüseyin Turan & Nihat Kasap & Dursun Delen, 0. "A fuzzy long-term investment planning model for a GenCo in a hybrid electricity market considering climate change impacts," Information Systems Frontiers, Springer, vol. 0, pages 1-17.
    3. Fitiwi, Desta Z. & Lynch, Muireann & Bertsch, Valentin, 2020. "Enhanced network effects and stochastic modelling in generation expansion planning: Insights from an insular power system," Socio-Economic Planning Sciences, Elsevier, vol. 71(C).
    4. Sadeghi, Hadi & Rashidinejad, Masoud & Abdollahi, Amir, 2017. "A comprehensive sequential review study through the generation expansion planning," Renewable and Sustainable Energy Reviews, Elsevier, vol. 67(C), pages 1369-1394.
    5. Mikhailov, L., 2004. "A fuzzy approach to deriving priorities from interval pairwise comparison judgements," European Journal of Operational Research, Elsevier, vol. 159(3), pages 687-704, December.
    6. Tong Koecklin, Manuel & Fitiwi, Desta & de Carolis, Joseph F. & Curtis, John, 2020. "Renewable electricity generation and transmission network developments in light of public opposition: Insights from Ireland," Papers WP653, Economic and Social Research Institute (ESRI).
    7. Yong Zeng & Yanpeng Cai & Guohe Huang & Jing Dai, 2011. "A Review on Optimization Modeling of Energy Systems Planning and GHG Emission Mitigation under Uncertainty," Energies, MDPI, vol. 4(10), pages 1-33, October.
    8. Tien-Fu Liang & Tien-Shou Huang & Ming-Feng Yang, 2012. "Application of fuzzy mathematical programming to imprecise project management decisions," Quality & Quantity: International Journal of Methodology, Springer, vol. 46(5), pages 1451-1470, August.
    9. Chen, Shih-Pin & Tsai, Ming-Jiun, 2011. "Time-cost trade-off analysis of project networks in fuzzy environments," European Journal of Operational Research, Elsevier, vol. 212(2), pages 386-397, July.
    10. Aikaterini Papapostolou & Charikleia Karakosta & Kalliopi-Anastasia Kourti & Haris Doukas & John Psarras, 2019. "Supporting Europe’s Energy Policy Towards a Decarbonised Energy System: A Comparative Assessment," Sustainability, MDPI, vol. 11(15), pages 1-26, July.
    11. Sakawa, Masatoshi & Kato, Kosuke & Nishizaki, Ichiro, 2003. "An interactive fuzzy satisficing method for multiobjective stochastic linear programming problems through an expectation model," European Journal of Operational Research, Elsevier, vol. 145(3), pages 665-672, March.
    12. Sarid, A. & Tzur, M., 2018. "The multi-scale generation and transmission expansion model," Energy, Elsevier, vol. 148(C), pages 977-991.
    13. Dong, C. & Huang, G.H. & Cai, Y.P. & Liu, Y., 2012. "An inexact optimization modeling approach for supporting energy systems planning and air pollution mitigation in Beijing city," Energy, Elsevier, vol. 37(1), pages 673-688.
    14. Teufel, Felix & Miller, Michael & Genoese, Massimo & Fichtner, Wolf, 2013. "Review of System Dynamics models for electricity market simulations," Working Paper Series in Production and Energy 2, Karlsruhe Institute of Technology (KIT), Institute for Industrial Production (IIP).
    15. Güner, Yusuf Emre, 2018. "The improved screening curve method regarding existing units," European Journal of Operational Research, Elsevier, vol. 264(1), pages 310-326.
    16. Ahmad, Salman & Mat Tahar, Razman & Muhammad-Sukki, Firdaus & Munir, Abu Bakar & Abdul Rahim, Ruzairi, 2016. "Application of system dynamics approach in electricity sector modelling: A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 56(C), pages 29-37.
    17. Ioannou, Anastasia & Angus, Andrew & Brennan, Feargal, 2017. "Risk-based methods for sustainable energy system planning: A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 74(C), pages 602-615.
    18. Hsiao, Chih-Tung & Liu, Chung-Shu & Chang, Dong-Shang & Chen, Chun-Cheng, 2018. "Dynamic modeling of the policy effect and development of electric power systems: A case in Taiwan," Energy Policy, Elsevier, vol. 122(C), pages 377-387.
    19. Figueroa–García, Juan Carlos & Hernández, Germán & Franco, Carlos, 2022. "A review on history, trends and perspectives of fuzzy linear programming," Operations Research Perspectives, Elsevier, vol. 9(C).
    20. Luhandjula, M.K., 2006. "Fuzzy stochastic linear programming: Survey and future research directions," European Journal of Operational Research, Elsevier, vol. 174(3), pages 1353-1367, November.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:gam:jeners:v:15:y:2022:i:9:p:3176-:d:803008. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.