AI-Driven Energy Storage Trading for Power Market Optimization

This document presents a comprehensive solution for modernizing energy storage systems through artificial intelligence and cloud-edge-device architecture. It addresses the pain point of traditional systems lacking intelligent perception, which hinders capturing arbitrage opportunities and grid frequency regulation. The PotisTrader platform enables millisecond-level trading decisions using AI algorithms, supporting multiple scenarios like independent/shared storage, solar-storage integration, and virtual power plants. Key innovations include time-segmented trading, user-friendly interfaces, real-time risk identification, and flexible configuration. The EMS cloud-edge collaboration provides centralized monitoring, online alarms, and intelligent O&M for full lifecycle management. Technical features include support for up to 128 PCS units, ms-level grid frequency monitoring, and protocols like Modbus TCP and IEC 104. The three-level intelligent structure uses federated learning and transfer learning for real-time prediction, optimizing trading strategies and reducing electricity costs. Full-process business decision support services cover data collection, meteorological analysis, electricity price prediction, and market simulation, enabling entities to accurately judge market trends and formulate effective trading strategies.