Energy storage micro-grid cooperative scheduling method based on photovoltaic prediction and related equipment
By fusing historical photovoltaic power generation data with meteorological sensor data and applying photovoltaic output prediction models, combined with energy storage system status assessment, and dynamically adjusting scheduling decision parameters, the problem of insufficient transmission of uncertain photovoltaic output information in energy storage microgrids was solved, and the energy flow coordination balance and stable operation of microgrids were achieved.
Patent Information
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- HENGKAI ELECTRIC CO LTD
- Filing Date
- 2026-06-22
- Publication Date
- 2026-07-24
AI Technical Summary
Existing energy storage microgrid dispatching methods cannot effectively transmit the uncertainty information of photovoltaic output prediction, resulting in frequent over-limits of energy storage systems or power imbalances in grid interaction under scenarios with large fluctuations in photovoltaic output, making it difficult to ensure the stable operation of the microgrid.
By fusing historical photovoltaic power generation data with meteorological sensor data, a feature dataset is generated. A pre-trained photovoltaic power output prediction model is used to predict photovoltaic power output, resulting in a result that includes the predicted value and confidence interval. The result is then combined with the energy storage state of charge, grid interaction margin, and load demand for comprehensive evaluation. The scheduling decision parameters are dynamically adjusted to achieve coordinated energy flow allocation among photovoltaic arrays, energy storage systems, local loads, and the grid.
In scenarios with fluctuating photovoltaic output, it ensures the coordinated balance and stable operation of microgrid energy flow, avoids the disconnect between prediction results and scheduling decisions, and realizes adaptive adjustment of scheduling schemes.
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