Energy Distribution System with E-Cloud Resiliency
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Solution Overview
Problem
Conventional systems for storing and distributing utility energy from distributed energy resources like solar panels are inefficient, lack resiliency and redundancy, fail to optimize energy value, and result in excessive overhead costs and environmental impact, while not effectively addressing service disruptions or allowing utilities to utilize consumer surplus energy at peak value times.
Innovation Solution
An energy distribution system comprising an energy generation source, energy storage unit, e-cloud, and processor that controls energy distribution, allowing for efficient storage and distribution of utility energy, minimizing asset use and losses, and enabling utilities to utilize consumer surplus energy during peak demand periods.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If conventional systems store and distribute energy from distributed energy resources, then energy storage and distribution is provided, but the systems are inefficient and do not effectively address service disruptions and outages
Solution Approach 1:
The system segments energy storage into distributed storage units located at consumer premises rather than centralized storage. Each storage unit operates semi-independently, providing local resiliency during service disruptions while maintaining overall system efficiency through coordinated control via the energy management system.
Solution Approach 2:
An energy management system acts as an intermediary between distributed energy resources, storage units, and consumers. This intermediary coordinates energy flows, optimizes charging/discharging cycles, and manages load balancing, thereby simultaneously improving efficiency and reliability during outages.
2Adaptability or versatility
If conventional systems distribute DER to utility consumers, then energy distribution is provided, but sufficient resiliency, redundancy, or flexibility is not provided
Solution Approach 1:
The energy storage units and energy management system serve multiple functions: they provide backup power during outages, optimize energy distribution efficiency, enable consumer participation in utility programs, and provide demand response capabilities. This multi-functionality increases system flexibility without proportionally increasing complexity.
Solution Approach 2:
The system dynamically adjusts energy distribution based on real-time conditions including consumer demand, DER availability, utility pricing signals, and grid status. The energy management system continuously optimizes operational parameters, providing adaptability and redundancy while managing complexity through automated control algorithms.
3Loss of energy
If conventional systems use utility assets for energy storage and distribution, then energy supply is maintained, but excessive overhead costs and wear and tear on system component parts result
Solution Approach 1:
The system enables consumers to self-manage their energy storage and distribution needs through locally deployed storage units and intelligent energy management. This reduces reliance on extensive utility infrastructure assets, minimizing utility overhead costs and wear and tear while maintaining energy supply reliability.
Solution Approach 2:
The system utilizes distributed, modular storage units that can be deployed at consumer premises rather than requiring expensive, large-scale centralized utility storage infrastructure. These distributed units reduce overall system implementation costs and utility asset requirements while effectively minimizing energy losses through localized storage and distribution.
4Use of energy by moving object
If conventional systems operate without consumer surplus energy utilization, then simple operation is maintained, but utilities cannot use consumer excess energy during periods when it is most valuable
Solution Approach 1:
The energy management system implements feedback loops that monitor consumer surplus energy production, utility pricing signals, and grid demand conditions. Based on this feedback, the system automatically optimizes the timing and amount of surplus energy utilization, maximizing energy value for utilities while maintaining operational simplicity through automated decision-making algorithms.
Data Source
AI summary
A system and method for distributing energy including an energy generation source that is adapted to generate a generation source portion of energy, energy consumers that each have a demand level, an e-cloud that is adapted to receive a portion of the generation source portion of energy and distribute an e-cloud portion of energy, a processor that is adapted to control the distribution of energy, and a utility that is adapted to communicate with the system. The processor causes the energy generation source to transmit an energy consumer generation source portion substantially equal to or less than an individual energy consumer demand to each of the energy consumers and an e-cloud energy portion to the e-cloud. The processor also causes the e-cloud to transmit an energy consumer e-cloud amount of energy substantially equal to or less than each of the individual energy consumer demands to each of the energy consumers.