Research on Two-Stage Regulation Method for Source–Load Flexibility Transformation in Power Systems

Under the premise of continuously increasing the grid-connected capacity of new energy, the fluctuation and anti-peak shaving characteristics of wind power have always constrained the development of green power systems. Considering the characteristics of power system flexibility resources, this pape...

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Veröffentlicht in:Sustainability 2023-09, Vol.15 (18), p.13918
Hauptverfasser: Hao, Chunyang, Wang, Yibo, Liu, Chuang, Zhang, Guanglie, Yu, Hao, Wang, Dongzhe, Shang, Jingru
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Sprache:eng
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Zusammenfassung:Under the premise of continuously increasing the grid-connected capacity of new energy, the fluctuation and anti-peak shaving characteristics of wind power have always constrained the development of green power systems. Considering the characteristics of power system flexibility resources, this paper introduces a two-stage regulation approach for power systems with enhanced source–load flexibility. In the day-ahead stage, an advanced peak regulation transformation is employed, leveraging the combined heat storage device of conventional thermal power units to enhance their peak regulation capability. Additionally, the Energy Intensive Load (EIL) is integrated into the regulation system. A two-level coordinated optimization model is developed, incorporating wind power integration and dispatching power allocation, with the aim of optimizing wind power integration and achieving the optimal allocation of dispatching power. In the intra-day stage, the connection of wind plants and energy storage devices is utilized to minimize the wind power fluctuations and improve the control ability over wind power variations. Compared with traditional methods, the wind power consumption in Scenario 1 and Scenario 2 increases by 2741.1 MW/h and 2478.5 MW/h respectively. Furthermore, the inclusion of an energy storage device in the intra-day stage significantly reduces the wind power fluctuations, maintaining a stable fluctuation rate within ±1%. Therefore, this method can effectively improve the level of wind power consumption and reduce the impact of real-time fluctuations on the power system.
ISSN:2071-1050
2071-1050
DOI:10.3390/su151813918