Distributed Energy Storage Control for Peak Demand Shifting
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Solution Overview
Problem
Current energy storage control schemes fail to facilitate widespread consumer adoption and ignore the potential of demand shifting, which is crucial for grid resilience and reducing peak energy demand, particularly in regions prone to blackouts and climate-related heatwaves.
Innovation Solution
A computer-implemented method and system that manages energy storage devices through a remote energy management computing system, allowing for the comparison of utility energy prices with user-set prices to trigger discharge commands, enabling energy storage devices to supply power during peak demand times and charge during off-peak times, thereby shifting demand and reducing strain on the grid.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If energy storage devices are deployed at consumer premises, then consumer energy cost savings and grid resilience are improved, but device complexity and infrastructure requirements increase
Solution Approach 1:
The patent introduces an energy management computing system as an intermediary that coordinates between utility companies, energy storage devices, and consumers. This centralized control system manages discharge commands, pricing signals, and device availability without requiring complex peer-to-peer communication between all system components, thereby improving grid resilience while controlling overall system complexity.
Solution Approach 2:
The system segments control functions by separating the energy management computing system (centralized coordination) from the embedded controllers (local device control). This segmentation allows each component to have simplified functionality while the overall system achieves high reliability through coordinated operation of multiple segmented units.
2Productivity
If demand shifting is implemented to reduce peak energy demand, then the need for peaker plants is reduced, but control system complexity increases
Solution Approach 1:
The system implements feedback mechanisms where the energy management computing system receives information about device availability, charge status, and consumer preferences, then sends targeted discharge commands and pricing signals. This feedback loop enables automated demand shifting to reduce peak demand and eliminate the need for peaker plants, while the structured feedback process keeps control complexity manageable through rule-based decision making.
Solution Approach 2:
The system performs preliminary actions by having consumers pre-register their energy storage devices and specify discharge preferences before peak demand events occur. The energy management system maintains a ready list of available devices and can quickly activate them when demand signals are received, enabling proactive demand management without complex real-time decision algorithms.
3Speed
If embedded controllers are used for local management, then response time is improved, but loss of centralized coordination increases
Solution Approach 1:
The patent creates a hierarchical control structure with two dimensions: centralized coordination (energy management computing system) and local execution (embedded controllers). The embedded controllers operate autonomously at the local dimension for immediate response to discharge commands, while the energy management system operates at the centralized dimension for overall coordination. This multi-dimensional approach enables fast local response without losing centralized coordination capabilities.
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
This solution enables consumers to save on energy costs, reduces the need for peaker plants, and enhances grid resilience by decentralizing power sources, avoiding congestion and outages, while providing utilities with cost-effective demand management without the need for additional infrastructure.
Implementation Method 1
the energy storage device delivers power from a battery system to an electrical appliance coupled to the energy storage device
Data Source
AI summary
Systems and methods for shifting energy demand are described herein. An energy management computing system can monitor energy prices and send commands to a residential energy storage device to discharge at periods when energy prices are relatively high. Alternatively, the energy storage device can receive energy prices and determine when to discharge in order to reduce costs when energy prices are relatively high. In yet another alternative, an energy distributor can take advantage of a plurality of energy storage devices to shift energy demand during periods of peak demand.