分布式光伏功率智能预测方法及装置
By training a prediction model for photovoltaic power plants and using target training data of different weather types, the impact of weather conditions on photovoltaic power parameters is reduced, the accuracy of photovoltaic power prediction is improved, and the timely dispatch of the power grid and the stability of users' electricity consumption are ensured.
Patent Information
- Authority / Receiving Office
- CN · China
- Patent Type
- Patents(China)
- Current Assignee / Owner
- SHENZHEN COMTOP INFORMATION TECH
- Filing Date
- 2022-12-16
- Publication Date
- 2026-07-17
AI Technical Summary
Existing photovoltaic power forecasting technologies are easily affected by weather conditions, resulting in low forecast accuracy and difficulty in timely grid dispatching, which affects the normal operation of the grid and users' electricity consumption.
By identifying target training data for different weather types, a prediction model is trained. This model uses the current weather type of the photovoltaic power station to predict future photovoltaic power parameters, reducing the impact of weather conditions on photovoltaic power parameters and improving prediction accuracy.
It improves the accuracy of photovoltaic power prediction, enables timely adjustments to grid dispatch, and ensures normal grid operation and normal power consumption for users.
Smart Images
Figure CN116247651B_ABST