Grid Event Energy Muting for Continuous Backup Power
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Solution Overview
Problem
Existing transportation systems lack efficient methods to manage energy consumption during grid-related events, such as power outages, which can lead to disruptions and inefficiencies in energy distribution and usage.
Innovation Solution
A system that determines locations at risk of losing electricity, conserves energy by reducing consumption, stores it in energy storage devices, and utilizes this stored energy during events, utilizing blockchain technology for decentralized management and smart contracts for authorization and compensation.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If energy consumption is maintained at normal levels, then device functionality is preserved, but energy storage is insufficient during grid events
Solution Approach 1:
The system performs preliminary actions by detecting grid events in advance and proactively reducing energy consumption before complete power loss occurs. This allows energy storage devices to be charged during the transition period, ensuring sufficient energy is available when the grid event fully impacts the location.
2Loss of energy
If energy consumption is reduced through muting, then energy storage is improved, but device functionality is degraded
Solution Approach 1:
The system applies local quality by selectively muting specific devices or energy-consuming components based on their criticality and energy consumption patterns. Not all devices are muted uniformly; instead, the system tailors the muting strategy to individual devices, preserving functionality for essential devices while reducing consumption from non-critical devices.
3Adaptability or versatility
If decentralized energy storage is implemented, then energy management flexibility is improved, but system complexity increases
Solution Approach 1:
The system introduces an intermediary energy management layer that coordinates between the grid, multiple energy storage devices, and various energy-consuming devices. This intermediary layer handles the complexity of decentralized management by providing centralized control logic that communicates with individual components, simplifying the overall system architecture while maintaining flexibility.
Data Source
AI summary
An example operation includes one or more of determining a location in an area that may lose electricity during an event related to a grid, conserving energy through a muting of energy consumption at the location, storing the conserved energy in an energy storage device at the location, and using the conserved energy at the location when the event occurs.