Space-time fusion photovoltaic power generation prediction method, system, equipment and medium
By employing a spatiotemporal fusion photovoltaic power generation prediction method, utilizing spatiotemporal attention layers and cluster representations, and dynamically weighted expert networks, the problem of insufficient accuracy in photovoltaic power generation prediction in existing technologies is solved, thereby achieving efficient dispatch and stable operation of the power system.
Patent Information
- Application Number
- CN202610484561.6
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- Filing Date
- 2026-04-14
- Publication Date
- 2026-05-12
- Estimated Expiration
- 2046-04-14
AI Technical Summary
Existing photovoltaic power generation and load forecasting methods mainly rely on single time series modeling, resulting in insufficient accuracy of photovoltaic power generation forecasts, which affects the quality of power system dispatch and stable operation.
A spatiotemporal fusion prediction method is adopted. By performing spatiotemporal and temporal transformation on photovoltaic power generation data, a fused embedded representation is generated. Feature extraction is performed using a spatiotemporal attention layer. Combined with cluster representation and expert gating network, the prediction results are dynamically allocated and fused to generate the optimal power generation plan.
It significantly improves the accuracy and robustness of photovoltaic power generation forecasting, ensuring the safe operation and efficient dispatch of the power grid.