Power Distribution Control System with Peer-to-Peer Asset Negotiation
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Solution Overview
Problem
Current power distribution systems face challenges in managing peak demand, grid stability, and energy efficiency due to intermittency in clean energy sources, infrastructure constraints, and latency in centralized control systems, leading to increased costs and energy waste.
Innovation Solution
A power distribution control system comprising a string of power assets (sources, stores, and responsive loads) with local routers and a server that communicates peer-to-peer to negotiate power transfer times and quantities, anticipating peak activity and dynamically adjusting energy production and consumption to balance the grid.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If centralized control systems are used to manage power distribution, then coordination between power assets is achieved, but latency in response to peak demand and grid instability occurs
Solution Approach 1:
The system divides power assets into decentralized groups, each with local control capabilities. Instead of a single centralized controller managing all assets, multiple local controllers autonomously manage their respective groups, enabling faster local responses to grid conditions while maintaining overall system coordination through peer-to-peer communication.
Solution Approach 2:
Power assets proactively prepare for anticipated peak demand periods by pre-charging energy storage systems, pre-cooling or pre-heating buildings, and pre-positioning resources before grid stress occurs. This anticipatory approach allows the system to respond to peak demand without waiting for centralized detection and command, reducing response latency.
2Loss of energy
If clean energy sources like wind and solar are used, then energy efficiency and environmental sustainability are improved, but rapid intermittency causes grid instability
Solution Approach 1:
Energy storage systems are charged in advance during periods of high renewable generation, and responsive loads are pre-conditioned (e.g., pre-cooling buildings) before renewable output fluctuates. This allows the system to buffer against rapid intermittency and maintain grid stability without sacrificing the use of clean energy sources.
Solution Approach 2:
The system implements real-time monitoring and feedback loops where power assets continuously report their status and respond to grid conditions. Local controllers adjust asset operation based on feedback from peer assets and grid status, enabling rapid compensation for renewable intermittency while maintaining overall system stability.
3Speed
If pumped-water energy storage facilities are deployed, then rapid response to peak demand is achieved, but infrastructure cost and environmental impact increase
Solution Approach 1:
The system replaces large-scale centralized pumped-water facilities with numerous smaller, distributed energy storage systems and responsive loads. Each local asset provides incremental response capability, collectively achieving system-wide rapid response without requiring complex centralized infrastructure.
Solution Approach 2:
Local power assets autonomously manage their own operation and response to grid conditions without requiring centralized control infrastructure. This self-service approach eliminates the need for complex communication and control systems while enabling rapid local responses that aggregate to system-level stability.
4Productivity
If local battery storage is used in smart meter schemes, then peak demand reduction is achieved, but the grid operator still experiences peaks requiring expensive capacity provision
Solution Approach 1:
The system merges multiple local battery storage systems and responsive loads into coordinated groups that collectively manage peak demand. By combining the capabilities of distributed assets, the system achieves greater peak reduction effectiveness than individual systems while sharing control complexity across multiple autonomous units.
Solution Approach 2:
Distributed battery storage systems are charged in advance during off-peak periods and discharge during anticipated peak demand periods. Responsive loads are pre-conditioned before peak periods to reduce or eliminate their peak consumption. This proactive approach reduces overall peak demand without requiring complex real-time centralized control.
Data Source
AI summary
A power distribution control system having a string of power assets comprising at least two different power assets selected from sources, stores and responsive loads is disclosed. The assets and associated local routers communicate with a central server and attempt to fulfil high level aims of the server by negotiating times and quantities of power transfer between themselves. Preferably a database stores parameters in relation to the power assets. Preferably a control system at the server anticipates future activity, such as future peaks in demand or supply, in the grid, and local power assets prepare in response. Preferably the power assets communicate between themselves on a peer-to-peer basis and collectively confirm to the server their ability to modify their collective behavior in response to an event in the grid.