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AI for Good Innovate for Impact
Use Case 15: AI Enables New Energy Meteorological Power
Forecast Change 4.2-Climate
Organization: China Huadian Corporation LTD. & Huawei Technologies Co., Ltd.
Country: China
Contact Person:
Primary: Fang Peng, fang -peng@ chd .com .cn
Secondary: Hao Wen, wenhao23@ huawei .com
1 Use Case Summary Table
Item Details
Category Climate Change/Natural Disaster
Problem Addressed Under the overarching goal of global sustainable development, the
installed capacity of renewable energy has been experiencing rapid
expansion worldwide. Both regulatory assessments and electricity
market operations now require renewable energy operators to achieve
significantly enhanced forecasting accuracy and operational efficiency.
Nevertheless, the inherent characteristics of renewable sources, includ-
ing the randomness, volatility, and intermittency of wind and solar power
generation, pose substantial challenges to power grid dispatching
systems. These challenges simultaneously create pressing demands for
the advancement of traditional numerical weather prediction models to
better accommodate the integration of renewable energy into modern
power systems.
Traditional numerical weather forecasting predicts changes in wind
speed and irradiance. This model, based on atmospheric dynamics,
is complex and has not seen new breakthroughs in the past decade. It
takes 6 to 10 hours to complete a prediction, which is time-consuming
and has poor timeliness. The limited improvement in mechanism models
and poor computational timeliness both affect the final prediction accu-
racy.
Key Aspects of Solu- 1) AI Large Model for meteorological forecasting.
tion 2) Cloud-edge collaboration architecture (Group meteorological
model, regional micro meteorological engine, site edge power
prediction service).
Technology Keywords AI Large Model, Cloud-Edge Collaboration, Meteorological Forecast-
ing, Renewable Energy, Power Grid Optimization, Electricity Trading
Data Availability Private
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