By forecasting and analysing energy flows our technology enables utilities, VPPs and distributed energy resource owners to optimise behind-the-meter energy generation, storage, usage and trading. Each Energy AI agent acts both independently and cooperatively to ensure maximum utilisation of the distributed energy resources.
To achieve high performance, scalability, and resiliency of the system, Energy AI is built in a hybrid Fog architecture. This approach uses a combination of centralized computing capability for forecasting grid and prosumer behavior together with decentralized and autonomous agents for local optimization.
Collects data from various sources, extrapolates missing consumption data if needed, and forecasts consumption, renewable production, and energy prices for both traditional and distributed grids with full bottom-up architecture.
Optimizes the setup of Distributed Energy Resources (DER), and their real-time operations, based on various inputs such as prediction data, constraints, prosumers, and ecosystem objectives.
Automatically executes Local pool trading decisions. Maximal energy revenues and minimal costs are achieved through an autonomous agent executing trading decisions based on the PREDICT and OPTIMIZE results.
Energy AI can be deployed through several applications:
Single asset optimization - Learns and profile the behaviour of each prosumer in the gird and chooses automatically and in real time the most cost effective strategies for using, storing, buying and selling energy back to the grid.
Community - When multiple agents are connected in a local grid, collaboration through local trading brings local balancing to the grid, reduces energy and grid costs, prevents congestions and increases renewable energy penetration.
VPP - When assets are spread over multiple areas, a VPP aggregation service optimizes available flexibility to maximise the value for DER asset owners in various flexibility markets.
Fog based architecture utilizes a fully decentralized management system based on distributed AI agents. Scalable big data architecture allows optimizing single C&I sites , communities and larger prosumer based grids. Utilizing Fog architecture ensures that management system continues works both ongrid and in Island mode.