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Long-term price guidance mechanism of flexible energy service providers based on stochastic differential methods

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  • Yin, Linfei
  • Qiu, Yao

Abstract

With the increasing generation of renewable energy in power markets, the mismatch between power production and power demand in the power market is becoming more serious. Power prices in the short term guided the balance of load and demand. Although short-term power price guidance can provide certain benefits, short-term power price guidance disrupts the potential long-term market balance and provides sustainable development challenges. This paper adopts a stochastic differential method to guide flexible energy service providers for long-term price guidance with addressing the challenges of long-term market imbalances. After knowing power production, the stochastic differentiation method guides load power demand to follow changes in power production by a reasonable power price. The stochastic differential method utilizes energy flexibility for long-term price guidance with cost minimization in a long-term market environment. The power demand results of Zhaoqing considering the water tower model show that the long-term price guidance mechanism based on the stochastic differential method saves 12.39% of the operating cost with RMB 782.6987 million each year. The long-term price guidance based on the stochastic differential method mobilizes the energy flexibility by indirectly control the demand of flexible energy systems through reasonable price signals.

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  • Yin, Linfei & Qiu, Yao, 2022. "Long-term price guidance mechanism of flexible energy service providers based on stochastic differential methods," Energy, Elsevier, vol. 238(PB).
    • Handle: RePEc:eee:energy:v:238:y:2022:i:pb:s0360544221020661
    DOI: 10.1016/j.energy.2021.121818
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    Cited by:

    1. Sabarathinam Srinivasan & Suresh Kumarasamy & Zacharias E. Andreadakis & Pedro G. Lind, 2023. "Artificial Intelligence and Mathematical Models of Power Grids Driven by Renewable Energy Sources: A Survey," Energies, MDPI, vol. 16(14), pages 1-56, July.
    2. Yin, Linfei & Qiu, Yao, 2022. "Neural network dynamic differential control for long-term price guidance mechanism of flexible energy service providers," Energy, Elsevier, vol. 255(C).
    3. Olena Borysiak & Tomasz Wołowiec & Grzegorz Gliszczyński & Vasyl Brych & Oleksandr Dluhopolskyi, 2022. "Smart Transition to Climate Management of the Green Energy Transmission Chain," Sustainability, MDPI, vol. 14(18), pages 1-11, September.

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