Expected outcomes include:
Methodological Advance: A GPT-4-based “weather-equipment-grid” coupling framework to reduce short-term generation prediction errors from 8%-12% to below 5%.
Societal Impact: Case studies (e.g., desert PV plants) demonstrating AI can reduce renewable energy curtailment by 15%-25%, accelerating carbon neutrality.
Technical Transparency: Develop interpretability tools (e.g., causality tracing for generation decisions) to address grid operators’ distrust of “black-box” models.
OpenAI Model Insights: Reveal GPT-4’s strengths (e.g., multimodal correlation mining) and limitations (e.g., high-frequency data latency) in energy systems, guiding future model development.
Data-Driven Insights
Advanced analytics harnessing multimodal datasets for optimal performance and decision-making across diverse conditions.
Model Development
Utilizing GPT-4 for advanced time-series adaptation and integration of physical relationships in analytics.
Validation Testing
Comprehensive testing of models under extreme conditions for robust performance and reliability in real-world applications.
Innovative Research Design for Data Solutions
We specialize in multimodal data integration, model development, and validation under extreme conditions, leveraging advanced technologies for enhanced efficiency and performance in various applications.
