AI Energy Edge Platform for Coordinating Decentralized Resources
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Solution Overview
Problem
The energy market is transitioning from a centralized model to a decentralized one, requiring a platform that manages and improves legacy infrastructure while coordinating with distributed systems, leveraging AI and IoT technologies for efficient energy management and transaction enablement.
Innovation Solution
An AI-based energy edge platform that integrates with distributed energy resources (DERs) and IoT devices for intelligent orchestration, optimization, and automation, utilizing AI systems, intelligent data layers, smart contracts, and energy transaction enablement to manage energy generation, storage, and consumption across various environments.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If the energy market transitions to a decentralized model with distributed systems, then adaptability and energy management efficiency are improved, but system complexity and coordination difficulty increase
Solution Approach 1:
The platform segments the decentralized energy system into manageable components including energy generation units, storage systems, consumption points, and transaction modules. Each component operates semi-autonomously while being coordinated through the central platform, reducing overall system complexity through modular organization
Solution Approach 2:
The AI-based energy edge platform acts as an intermediary that coordinates between distributed energy resources, legacy infrastructure, and consumption points. The platform manages complexity by centralizing coordination functions while allowing distributed operation, resolving the contradiction between decentralization benefits and coordination difficulty
2Extent of automation
If AI and IoT technologies are integrated for intelligent orchestration, then energy management efficiency and automation are improved, but device complexity and implementation difficulty increase
Solution Approach 1:
The platform implements a universal AI-based orchestration layer that handles multiple functions including demand forecasting, resource optimization, transaction management, and legacy system integration. This multi-functional approach reduces implementation difficulty by providing a single comprehensive solution rather than multiple separate systems
Solution Approach 2:
The system employs self-service mechanisms where the AI automatically optimizes energy allocation, forecasts demand, and manages transactions without requiring manual intervention. The platform self-configures and self-adjusts based on real-time data, reducing implementation and operational complexity despite high automation levels
3Reliability
If the platform coordinates legacy infrastructure with distributed systems, then energy system reliability is improved, but integration complexity and management difficulty increase
Solution Approach 1:
The platform serves as an intermediary layer between legacy infrastructure and distributed energy systems, providing standardized interfaces and protocols that simplify integration. This mediator approach maintains reliability by ensuring coordinated operation while reducing integration complexity through abstraction
Solution Approach 2:
The system implements prior cushioning by pre-configuring integration protocols, establishing backup coordination mechanisms, and preparing transition pathways before integrating legacy systems with distributed resources. This proactive approach ensures reliability during integration while managing complexity through advance planning
Data Source
AI summary
An AI-based platform for enabling intelligent orchestration and management of power and energy is disclosed. The platform includes a system configured to perform automated and coordinated governance of a set of energy entities that are operationally coupled within an energy grid and a set of distributed edge energy resources. At least one of the distributed edge energy resources is operationally independent of the energy grid.