Cloud-edge collaboration + AI empowerment: Digital intelligence platform solves the "four difficulties" of virtual power plants

Recently, the National Development and Reform Commission and the National Energy Administration jointly issued the "Guiding Opinions on Accelerating the Development of Virtual Power Plants". The document clearly states that by 2027, the construction and operation management mechanisms of virtual power plants in China will become mature and standardized, and the mechanisms for participating in the electricity market will be improved. By then, the regulating capacity of virtual power plants nationwide is expected to reach over 20 million kilowatts. Looking ahead to 2030, the application scenarios of virtual power plants will be further expanded, various business models will achieve innovative development, and the regulating capacity of virtual power plants nationwide is expected to reach over 50 million kilowatts.

JGE has launched the "One-Stop Solution for New Energy Digital and Intelligent Platform". Based on the "Cloud-Edge Collaboration + AI Empowerment" technical architecture, this solution integrates multi-dimensional data streams such as photovoltaic, energy storage, and charging, enabling unified management and control of virtual power plants, microgrids, and V2G platforms. It builds a smart energy system covering the entire chain from "source to network to load to storage", providing panoramic digital support for the construction of new power systems.

The current electricity market faces issues such as low compensation standards for ancillary services and limited incentives for peak-valley price differences, making it difficult to cover the aggregation costs of dispersed resources through existing revenue mechanisms. Especially for user-side resources, the barriers to participating in the market are high, and the definition of resource rights and responsibilities is unclear, severely restricting the progress of marketization.

JGE innovatively connects carbon asset management with electricity trading channels, quantifying the behavior of charging new energy vehicles with green electricity into carbon credits. Leveraging the carbon inclusive platform, it realizes the dual value monetization of "green electricity consumption revenue + carbon asset trading". On the operational side, the platform supports a dynamic billing strategy across 48 time segments, combining AI algorithms to predict load and electricity price fluctuations, helping operators maximize peak-valley arbitrage opportunities.

Addressing the pain points of fragmented protocols, weak security protection, and low response efficiency in distributed energy equipment, a three-level collaborative architecture of "terminal-edge-cloud" is established: the terminal side utilizes a stake-level edge computing gateway to accommodate multiple brand protocols, collecting over 200 items of equipment data in real time; the edge side integrates environmental monitoring and V2G control modules with station-level servers to achieve millisecond-level response; the cloud side integrates multiple data streams and establishes an energy dynamic model relying on digital twin technology. Combined with 20 AI algorithms (including charging prediction and equipment health management), resource aggregation efficiency is increased by 40%, and scheduling accuracy exceeds 95%. Furthermore, a triple protection system consisting of battery safety monitoring, environmental early warning, and blockchain certification ensures data security and the credibility of carbon assets. This solution addresses the challenge of heterogeneous terminal collaboration and provides a standardized technical path for large-scale operations.

The poor integration between virtual power plants and grid dispatching systems, coupled with the lack of unified cross-provincial trading rules, hinders the optimal allocation of resources across the entire region. Traditional management models struggle to adapt to the dynamic interaction needs of "source-grid-load-storage", necessitating the establishment of a new collaborative mechanism. Our innovatively integrated "city-level energy collaboration platform" utilizes digital twin technology to construct a dynamic model of grid topology, simulating microgrid operation status and energy flow in real time, providing visual support for dispatching decisions. The platform is deeply integrated with the State Grid data platform, establishing a three-tier response mechanism of "provincial dispatching instructions - municipal resource allocation - precise control at stations". At the ecological level, data connectivity has been achieved with transportation networks and carbon trading platforms, successfully piloting cross-domain collaboration scenarios such as "charging demand forecasting + traffic congestion mitigation + green power dispatching" in places like Nanjing city.