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Using Piecewise Linearization Method to PCS Input/Output-Efficiency Curve for a Stand-Alone Microgrid Unit Commitment

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  • Ha-Lim Lee

    (Smart Distribution Research Center, Advanced Power Grid Research Division, Korea Electrotechnology Research Institute, bulmosan-ro 10beon-gil, Seongsan-gu, Changwonsi, Gyeongsangnam-do 51543, Korea)

  • Yeong-Han Chun

    (Power System Lab, Electronic & Electrical Enginerring School, Hong-Ik University, 94, Wauson-ro, Mapo-gu, Seoul 04066, Korea)

Abstract

When operating a stand-alone micro grid, the battery energy storage system (BESS) and a diesel generator are key components needed in order to maintain demand-supply balance. Using Unit Commitment (UC) to calculate the optimal operation schedule of a BESS and diesel generator helps minimize the operation cost of the micro grid. While calculating the optimal operation schedule for the microgrid, it is important that it reflects the actual characteristics of the implanted devices, in order to increase the schedule result accuracy. In this paper, a piecewise linearization, on the actual power conditioning system (PCS) input/output-efficiency characteristic curve, has been considered while calculating the optimal operation schedule using UC. The optimal schedule result calculated by the proposed method has been examined by comparing the schedule calculated by a fixed input/output-efficiency case, which is conventionally used while solving UC for a stand-alone microgrid.

Suggested Citation

  • Ha-Lim Lee & Yeong-Han Chun, 2018. "Using Piecewise Linearization Method to PCS Input/Output-Efficiency Curve for a Stand-Alone Microgrid Unit Commitment," Energies, MDPI, vol. 11(9), pages 1-13, September.
    • Handle: RePEc:gam:jeners:v:11:y:2018:i:9:p:2468-:d:170280
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    References listed on IDEAS

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    1. Changbin Hu & Shanna Luo & Zhengxi Li & Xin Wang & Li Sun, 2015. "Energy Coordinative Optimization of Wind-Storage-Load Microgrids Based on Short-Term Prediction," Energies, MDPI, vol. 8(2), pages 1-24, February.
    2. Nemati, Mohsen & Braun, Martin & Tenbohlen, Stefan, 2018. "Optimization of unit commitment and economic dispatch in microgrids based on genetic algorithm and mixed integer linear programming," Applied Energy, Elsevier, vol. 210(C), pages 944-963.
    3. Hawkes, A.D. & Leach, M.A., 2009. "Modelling high level system design and unit commitment for a microgrid," Applied Energy, Elsevier, vol. 86(7-8), pages 1253-1265, July.
    4. Wouters, Carmen & Fraga, Eric S. & James, Adrian M., 2015. "An energy integrated, multi-microgrid, MILP (mixed-integer linear programming) approach for residential distributed energy system planning – A South Australian case-study," Energy, Elsevier, vol. 85(C), pages 30-44.
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    Cited by:

    1. Woan-Ho Park & Hamza Abunima & Mark B. Glick & Yun-Su Kim, 2021. "Energy Curtailment Scheduling MILP Formulation for an Islanded Microgrid with High Penetration of Renewable Energy," Energies, MDPI, vol. 14(19), pages 1-15, September.
    2. Francisco G. Montoya & Raúl Baños & Alfredo Alcayde & Francisco Manzano-Agugliaro, 2019. "Optimization Methods Applied to Power Systems," Energies, MDPI, vol. 12(12), pages 1-8, June.

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