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A Dynamic Game Approach for Demand-Side Management: Scheduling Energy Storage with Forecasting Errors

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  • Matthias Pilz

    (Kingston University London)

  • Luluwah Al-Fagih

    (Kingston University London)

Abstract

Smart metering infrastructure allows for two-way communication and power transfer. Based on this promising technology, we propose a demand-side management (DSM) scheme for a residential neighbourhood of prosumers. Its core is a discrete time dynamic game to schedule individually owned home energy storage. The system model includes an advanced battery model, local generation of renewable energy, and forecasting errors for demand and generation. We derive a closed-form solution for the best response problem of a player and construct an iterative algorithm to solve the game. Empirical analysis shows exponential convergence towards the Nash equilibrium. A comparison of a DSM scheme with a static game reveals the advantages of the dynamic game approach. We provide an extensive analysis on the influence of the forecasting error on the outcome of the game. A key result demonstrates that our approach is robust even in the worst-case scenario. This grants considerable gains for the utility company organising the DSM scheme and its participants.

Suggested Citation

  • Matthias Pilz & Luluwah Al-Fagih, 2020. "A Dynamic Game Approach for Demand-Side Management: Scheduling Energy Storage with Forecasting Errors," Dynamic Games and Applications, Springer, vol. 10(4), pages 897-929, December.
    • Handle: RePEc:spr:dyngam:v:10:y:2020:i:4:d:10.1007_s13235-019-00309-z
    DOI: 10.1007/s13235-019-00309-z
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    References listed on IDEAS

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    2. Bilal Masood & Song Guobing & Jamel Nebhen & Ateeq Ur Rehman & Muhammad Naveed Iqbal & Iftikhar Rasheed & Mohit Bajaj & Muhammad Shafiq & Habib Hamam, 2022. "Investigation and Field Measurements for Demand Side Management Control Technique of Smart Air Conditioners located at Residential, Commercial, and Industrial Sites," Energies, MDPI, vol. 15(7), pages 1-23, March.

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