SOLARMAN's Virtual Power Plant (VPP) VPP leverages advanced technologies such as loT (internet of Things),.Al, and big data to ihtegrate and consolidate a wide range of distributed energy resources, such as solar systems, energy storage systems, charging stations, heat pumps, and other adjustable loads. By integrating these resourceswith corresponding electricity market mechanisms, it forms a system capable of responding to grid operational adiustments. This enables households and C&l users to participate in electricity markets and grid ancillary servicesadds value and optimization to the assets of end-users with aggregated resources, and enhances grid companies' power system stability.
Leveraging AI algorithms to analyze vast amounts of energy data enables high-accuracy forecasting of load, power generation, and electricity prices.
Edge node performs lightning-fast response of distributed energy resource output and energy storage system charging/discharging states in response to commands from the control center.
Edge computing system analyzes device response outcomes to optimize subsequent dispatch command strategies and identify anomaly alerts.
Support multiple protocol types including Modbus, MQTT, DL/T 645, IEC 61850, IEC 61499, OpenADR, and OCPP, ensuring compatibility across device access, data transmission, and application interaction layers.
SOLARMAN's core VPP deeply integrates real-time electricity price signals and market trends, transforming energy storage systems from passive responders to proactive decision-makers-charging decisively during low-price periodsand discharging accurately during peak times, automatically seizing the best opportunities in every market fluctuation. This is the standardized future of intelligent energy storage operations: where success is measured not by scale, but by efficiency and returns.
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SOLARMAN's core VPP deeply integrates real-time electricity price signals and market trends, transforming energy storage systems from passive responders to proactive decision-makers-charging decisively during low-price periodsand discharging accurately during peak times, automatically seizing the best opportunities in every market fluctuation. This is the standardized future of intelligent energy storage operations: where success is measured not by scale, but by efficiency and returns.