Energy NexusAl RelyEZ AI Agent Platform

Integrates multiple authoritative global weather data sources including ECMWF, NCEI and DWD. In cooperation with the Hong Kong University of Science and Technology, it provides high-precision and high-resolution 1×1 km station-level weather forecast data, 15-minute granular ultra-shor-term weather forecasts and medium- and long-term weather forecast data for up to 45 days, and issues early warnings for extreme weather. It suppors station power forecasting and full-market load forecasting, sering as a strong basis for formulating trading strategies.

Based on high-precision weather data and the RelyEZ OS software ecosystem, it integrates deep neural network models, time-series models and more, with a variety of built-in advanced algorithm modules covering high-precision algorithms such as Wavelet+LSTM+Transformer, as well as transfer learning and reinforcement learning for various forecasting scenarios. It supports multi-dimensional forecasting models including market load forecasting, electricity price forecasting and battery SOH health forecasting, providing full support for energy operation businesses.

Based on multi-model forecasting, the historical accuracy of day-ahead electricity price forecasting (1-MAPE) reaches 82%, real-time electricity price forecasting accuracy 72%, with a peak day-ahead accuracy of 96% and real-time price forecasting trend fitting degree of 74.5%. The average electricity price prediction error in Yunnan Province is 0.011 CNY/kWh, and trading-assisted optimization strategies boost monthly revenue by 20%.

Automatically acquires data and performs electricity price forecasting, recommends trading bidding strategies via optimization algorithm solvers, forecasts and backtests daily strategy returns, compares and evaluates strategy effects, and continuously optimizes and evolves model algorithms to maximize full-lifecycle returns.