ETS Heater Charging Control for Grid-Responsive Thermal Storage
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Solution Overview
Problem
Conventional Electric Thermal Storage (ETS) heaters face inefficiencies in managing electricity usage, leading to prolonged surges during off-peak hours and inability to balance heating demands effectively, especially with increasing levels of non-carbon generation and distribution constraints, while existing grid management techniques struggle with slow response times and interference with customer experience.
Innovation Solution
An energy management system that incorporates a controller responsive to weather data, building data, and electricity prices, optimizing energy charging strategies for ETS systems to balance supply and demand, and interact with grid management systems to handle intermittent energy sources and unpredictable events.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Use of energy by moving object
If conventional ETS heaters charge during off-peak hours, then energy cost is reduced, but prolonged surges occur during off-peak hours causing grid instability
Solution Approach 1:
The system dynamically adjusts charging rates based on real-time grid conditions, weather forecasts, and building thermal models. Instead of fixed off-peak charging schedules, the controller continuously optimizes power absorption to match actual grid capabilities and building heating requirements, preventing prolonged surges while maintaining cost efficiency.
Solution Approach 2:
The system implements closed-loop feedback control by monitoring grid conditions, weather forecasts, and actual building temperature responses. The controller uses this feedback to adjust charging strategies in real-time, balancing energy cost optimization with grid stability requirements through continuous adaptation.
2Productivity
If predictive load management techniques are used, then some load patterns are optimized, but response time remains slow and unpredictable events cannot be compensated
Solution Approach 1:
The system performs preliminary actions by pre-charging thermal energy storage based on forecasted weather conditions and predicted load patterns. Thermal batteries are charged in advance during periods of low grid stress, preparing heating capacity before peak demand occurs, thus optimizing load without waiting for predictive algorithms to detect patterns.
Solution Approach 2:
The system transitions from static predictive modeling to dynamic real-time control. The controller continuously updates charging strategies based on actual grid conditions and weather changes, enabling rapid response to unpredictable events while maintaining the load optimization benefits of predictive approaches.
3Loss of energy
If ETS systems absorb excess nighttime power, then grid burden is reduced, but distribution constraints and simultaneous activation of heaters create new problems
Solution Approach 1:
The system implements localized control at each building level, allowing individual ETS systems to independently manage their charging based on local grid conditions and building requirements. This distributed approach eliminates the need for centralized coordination, reducing distribution constraint complexity while maintaining overall grid burden reduction.
Solution Approach 2:
Each ETS system autonomously determines its charging strategy based on local thermal models, weather forecasts, and real-time grid conditions. The systems self-regulate power absorption without requiring external coordination or complex distribution management, simplifying the overall system while effectively reducing grid burden.
4Ease of operation
If conventional load management techniques are used, then basic load balancing is achieved, but customer experience is interfered with and response time is slow
Solution Approach 1:
The system replaces mechanical load management approaches (timers, circuit breakers) with intelligent control based on thermal modeling and real-time optimization. The controller uses building-specific thermal models to predict heating requirements and proactively manage load, achieving load balancing without interfering with customer comfort or experiencing delays.
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
The system enables ETS heaters to efficiently purchase energy, maintain heating performance, and respond quickly to grid events, optimizing energy usage and reducing grid burden, while providing better performance metrics and stability.
Implementation Method 1
The ETS heater includes electric heating elements for generating heat
Implementation Method 2
The ETS heater has a heat sink surrounded by an insulated housing. The heat sink is often made of some type of brick. The brick for example is a type of ceramic brick that can be heated to a high temperature
Implementation Method 3
The ETS heater may further include at least one duct through the heat sink and housing to allow for surrounding air to be circulated past and heated by the heat sink. The ETS heater includes electric heating elements for generating heat and one or more fans for circulating air through the ducts
Data Source
AI summary
A method and apparatus of controlling the electric power usage of electric thermal storage heaters and systems are based on: 1) current and recorded measurements local to the heater and building; 2) current measurements external to the heater and building; 3) forecasts communicated to the apparatus. The method also includes sending out communications about power use as well as various other local measurements. The apparatus has local controls on the electric thermal storage, including but not limited to the relays that control flow of power into the heating elements, a logic module that integrates the local controls, as well as communication channels that extend outside the building to entities capable of providing automatic forecasts and potentially other types of information not available locally.