Longyuan Power Applies Power Prediction Optimization Technology, First time in the Industry

On August 30, based on the R&D results of the “Research and Application of Renewable Energy Forecasting System for New Power System Targeting the Goal of Carbon Peaking and Carbon Neutrality” project, Zhongneng Company of Longyuan Power under China Energy successfully applied remote online optimization technology for new energy power forecasting to achieve real-time adjustment and optimization of the prediction model on the field station side. This was the first such attempt in China and achieved good results.

Prediction model is the core part of the renewable energy forecasting system, and its continuous adjustment and optimization is directly related to the prediction accuracy. For a long time in the past, as the renewable energy power prediction system operated in the safety zone of grid dispatching, the prediction model parameter tuning purely relied on manual operation, which proved inefficient and error-prone, leaving shortcomings in security, versatility and automation degree.

To address this problem, the company established a technical research team which, based on the principles of independent innovation, overcoming difficulties, and safety compliance, gradually conquered technical difficulties such as optimized measurement of model parameters on the main station side, file format compatibility of isolating devices on the field side, and real time file transmission of isolating devices. By achieving integrated model parameter filing on the main station side, optimized measurement of model parameters, configuration file generation and application, and synchronous transmission of isolating devices on the field side, the company is now able to remotely optimize the power prediction model for renewable energy stations across the country in a safe, active and efficient way.

Since its commissioning, the technology has been operating stably. While improving the accuracy of new energy power forecasting, it helps reduce maintenance costs, enhance system security and protection capabilities, cement the company’s technological leadership, and set an industry benchmark for new energy power forecasting.