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Robust energy storage scheduling for imbalance reduction of strategically formed energy balancing groups

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  • Chakraborty, Shantanu
  • Okabe, Toshiya

Abstract

Imbalance (on-line energy gap between contracted supply and actual demand, and associated cost) reduction is going to be a crucial service for a Power Producer and Supplier (PPS) in the deregulated energy market. PPS requires forward market interactions to procure energy as precisely as possible in order to reduce imbalance energy. This paper presents, 1) (off-line) an effective demand aggregation based strategy for creating a number of balancing groups that leads to higher predictability of group-wise aggregated demand, 2) (on-line) a robust energy storage scheduling that minimizes the imbalance energy and cost of a particular balancing group considering the demand prediction uncertainty. The group formation is performed by a Probabilistic Programming approach using Bayesian Markov Chain Monte Carlo (MCMC) method after applied on the historical demand statistics. Apart from the group formation, the aggregation strategy (with the help of Bayesian Inference) also clears out the upper-limit of the required storage capacity for a formed group, fraction of which is to be utilized in on-line operation. For on-line operation, a robust energy storage scheduling method is proposed that minimizes expected imbalance energy and cost (a non-linear function of imbalance energy) while incorporating the demand uncertainty of a particular group. The proposed methods are applied on the real apartment buildings' demand data in Tokyo, Japan. Simulation results are presented to verify the effectiveness of the proposed methods.

Suggested Citation

  • Chakraborty, Shantanu & Okabe, Toshiya, 2016. "Robust energy storage scheduling for imbalance reduction of strategically formed energy balancing groups," Energy, Elsevier, vol. 114(C), pages 405-417.
    • Handle: RePEc:eee:energy:v:114:y:2016:i:c:p:405-417
    DOI: 10.1016/j.energy.2016.07.170
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    References listed on IDEAS

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    Cited by:

    1. Ryusuke Konishi & Akiko Takeda & Masaki Takahashi, 2018. "Optimal Sizing of Energy Storage Systems for the Energy Procurement Problem in Multi-Period Markets under Uncertainties," Energies, MDPI, vol. 11(1), pages 1-19, January.
    2. Chakraborty, Shantanu & Baarslag, Tim & Kaisers, Michael, 2020. "Automated peer-to-peer negotiation for energy contract settlements in residential cooperatives," Applied Energy, Elsevier, vol. 259(C).
    3. Hojnik, Jana & Ruzzier, Mitja & Fabri, Stephanie & Klopčič, Alenka Lena, 2021. "What you give is what you get: Willingness to pay for green energy," Renewable Energy, Elsevier, vol. 174(C), pages 733-746.
    4. Ondeck, Abigail D. & Edgar, Thomas F. & Baldea, Michael, 2018. "Impact of rooftop photovoltaics and centralized energy storage on the design and operation of a residential CHP system," Applied Energy, Elsevier, vol. 222(C), pages 280-299.

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