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Generation Expansion Planning with Energy Storage Systems Considering Renewable Energy Generation Profiles and Full-Year Hourly Power Balance Constraints

Author

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  • Radhanon Diewvilai

    (Department of Electrical Engineering, Chulalongkorn University, Bangkok 10330, Thailand)

  • Kulyos Audomvongseree

    (Department of Electrical Engineering, Chulalongkorn University, Bangkok 10330, Thailand
    Energy Research Institute, Chulalongkorn University, Bangkok 10330, Thailand)

Abstract

This paper proposes a methodology to develop generation expansion plans considering energy storage systems (ESSs), individual generation unit characteristics, and full-year hourly power balance constraints. Generation expansion planning (GEP) is a complex optimization problem. To get a realistic plan with the lowest cost, acceptable system reliability, and satisfactory CO 2 emissions for the coming decades, a complex multi-period mixed integer linear programming (MILP) model needs to be formulated and solved with individual unit characteristics along with hourly power balance constraints. This problem requires huge computational effort since there are thousands of possible scenarios with millions of variables in a single calculation. However, in this paper, instead of finding the globally optimal solutions of such MILPs directly, a simplification process is proposed, breaking it down into multiple LP subproblems, which are easier to solve. In each subproblem, constraints relating to renewable energy generation profiles, charge-discharge patterns of ESSs, and system reliability can be included. The proposed process is tested against Thailand’s power development plan. The obtained solution is almost identical to that of the actual plan, but with less computational effort. The impacts of uncertainties as well as ESSs on GEP, e.g., system reliability, electricity cost, and CO 2 emission, are also discussed.

Suggested Citation

  • Radhanon Diewvilai & Kulyos Audomvongseree, 2021. "Generation Expansion Planning with Energy Storage Systems Considering Renewable Energy Generation Profiles and Full-Year Hourly Power Balance Constraints," Energies, MDPI, vol. 14(18), pages 1-25, September.
    • Handle: RePEc:gam:jeners:v:14:y:2021:i:18:p:5733-:d:633681
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    References listed on IDEAS

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    Cited by:

    1. Tomonobu Senjyu & Mahdi Khosravy, 2022. "Power System Planning and Quality Control," Energies, MDPI, vol. 15(14), pages 1-2, July.
    2. Seyed Hamed Jalalzad Mahvizani & Hossein Yektamoghadam & Rouzbeh Haghighi & Majid Dehghani & Amirhossein Nikoofard & Mahdi Khosravy & Tomonobu Senjyu, 2022. "A Game Theory Approach Using the TLBO Algorithm for Generation Expansion Planning by Applying Carbon Curtailment Policy," Energies, MDPI, vol. 15(3), pages 1-16, February.
    3. Radhanon Diewvilai & Kulyos Audomvongseree, 2022. "Optimal Loss of Load Expectation for Generation Expansion Planning Considering Fuel Unavailability," Energies, MDPI, vol. 15(21), pages 1-17, October.
    4. Radhanon Diewvilai & Kulyos Audomvongseree, 2022. "Possible Pathways toward Carbon Neutrality in Thailand’s Electricity Sector by 2050 through the Introduction of H 2 Blending in Natural Gas and Solar PV with BESS," Energies, MDPI, vol. 15(11), pages 1-26, May.
    5. Majid Dehghani & Mohammad Taghipour & Saleh Sadeghi Gougheri & Amirhossein Nikoofard & Gevork B. Gharehpetian & Mahdi Khosravy, 2021. "A Deep Learning-Based Approach for Generation Expansion Planning Considering Power Plants Lifetime," Energies, MDPI, vol. 14(23), pages 1-21, December.
    6. Siripha Junlakarn & Radhanon Diewvilai & Kulyos Audomvongseree, 2022. "Stochastic Modeling of Renewable Energy Sources for Capacity Credit Evaluation," Energies, MDPI, vol. 15(14), pages 1-27, July.

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