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Real-Time Demand Side Management Algorithm Using Stochastic Optimization

Author

Listed:
  • Moses Amoasi Acquah

    (Department of Electrical Engineering, Kyungpook National University, 80 Daehak-ro, Sangyeok-dong, Buk-gu, Daegu 41566, Korea)

  • Daisuke Kodaira

    (Department of Electrical Engineering, Kyungpook National University, 80 Daehak-ro, Sangyeok-dong, Buk-gu, Daegu 41566, Korea)

  • Sekyung Han

    (Department of Electrical Engineering, Kyungpook National University, 80 Daehak-ro, Sangyeok-dong, Buk-gu, Daegu 41566, Korea)

Abstract

A demand side management technique is deployed along with battery energy-storage systems (BESS) to lower the electricity cost by mitigating the peak load of a building. Most of the existing methods rely on manual operation of the BESS, or even an elaborate building energy-management system resorting to a deterministic method that is susceptible to unforeseen growth in demand. In this study, we propose a real-time optimal operating strategy for BESS based on density demand forecast and stochastic optimization. This method takes into consideration uncertainties in demand when accounting for an optimal BESS schedule, making it robust compared to the deterministic case. The proposed method is verified and tested against existing algorithms. Data obtained from a real site in South Korea is used for verification and testing. The results show that the proposed method is effective, even for the cases where the forecasted demand deviates from the observed demand.

Suggested Citation

  • Moses Amoasi Acquah & Daisuke Kodaira & Sekyung Han, 2018. "Real-Time Demand Side Management Algorithm Using Stochastic Optimization," Energies, MDPI, vol. 11(5), pages 1-14, May.
    • Handle: RePEc:gam:jeners:v:11:y:2018:i:5:p:1166-:d:144935
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    References listed on IDEAS

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    1. Chao Lu & Hanchen Xu & Xin Pan & Jie Song, 2014. "Optimal Sizing and Control of Battery Energy Storage System for Peak Load Shaving," Energies, MDPI, vol. 7(12), pages 1-15, December.
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    Cited by:

    1. Mayank Singh & Rakesh Chandra Jha, 2019. "Object-Oriented Usability Indices for Multi-Objective Demand Side Management Using Teaching-Learning Based Optimization," Energies, MDPI, vol. 12(3), pages 1-25, January.
    2. Moses Amoasi Acquah & Sekyung Han, 2019. "Online Building Load Management Control with Plugged-in Electric Vehicles Considering Uncertainties," Energies, MDPI, vol. 12(8), pages 1-19, April.
    3. Jérôme Buire & Frédéric Colas & Jean-Yves Dieulot & Xavier Guillaud, 2019. "Stochastic Optimization of PQ Powers at the Interface between Distribution and Transmission Grids," Energies, MDPI, vol. 12(21), pages 1-16, October.
    4. Gi-Ho Lee & Jae-Young Park & Seung-Jun Ham & Young-Jin Kim, 2020. "Comparative Study on Optimization Solvers for Implementation of a Two-Stage Economic Dispatch Strategy in a Microgrid Energy Management System," Energies, MDPI, vol. 13(5), pages 1-21, March.
    5. van der Meer, Dennis & Wang, Guang Chao & Munkhammar, Joakim, 2021. "An alternative optimal strategy for stochastic model predictive control of a residential battery energy management system with solar photovoltaic," Applied Energy, Elsevier, vol. 283(C).
    6. Jingyeong Park & Jeonghyeon Choi & Hyeondeok Jo & Daisuke Kodaira & Sekyung Han & Moses Amoasi Acquah, 2022. "Life Evaluation of Battery Energy System for Frequency Regulation Using Wear Density Function," Energies, MDPI, vol. 15(21), pages 1-16, October.

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