Distributed Heat Pump Control with Shadow Device Fault Tolerance
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Solution Overview
Problem
Existing heat pump systems lack integrated smart algorithms that can efficiently condition spaces based on real-time and future conditions, often operate suboptimally due to lack of integrated control over multiple indoor units, and do not account for energy pricing or user comfort settings, leading to inefficiencies and user burden.
Innovation Solution
A distributed control system with a main control device and shadow control system that monitors health status and dynamically adjusts operation of multiple heat pumps, using model predictive control to optimize energy use, humidity, and comfort based on real-time and predicted conditions.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If a distributed control system with multiple control devices is implemented, then system reliability and fault tolerance are improved, but device complexity increases
Solution Approach 1:
The patent implements shadow control devices that create copies of the main control device's functionality. These shadow control devices monitor and stand ready to take over if the main control device fails, providing fault tolerance without requiring complete system redesign. The shadow control devices are essentially copies that can activate when needed.
Solution Approach 2:
The control system is divided into multiple independent control devices (main control device and shadow control devices) rather than relying on a single centralized controller. This segmentation distributes the control functionality across multiple units, improving reliability while allowing each individual device to remain relatively simple in design.
2Use of energy by moving object
If model predictive control algorithms are used to optimize energy use and comfort, then energy efficiency improves, but computational complexity and control system complexity increase
Solution Approach 1:
The model predictive control algorithm performs preliminary computations to determine optimal control sequences in advance. By calculating ahead what the optimal control actions should be based on predicted future conditions, the system can make efficient energy use decisions without requiring complex real-time computations during operation.
Solution Approach 2:
The control system continuously receives feedback from sensors about actual system state and compares it with predicted values. This feedback loop allows the model predictive control to adjust and refine its predictions, improving energy efficiency while managing computational complexity through iterative optimization rather than exhaustive calculation.
3Productivity
If integrated control over multiple indoor units is implemented, then system productivity and energy efficiency improve, but device complexity and control difficulty increase
Solution Approach 1:
The patent merges the control of multiple indoor units under a unified distributed control system. The main control device and shadow control devices coordinate multiple indoor units together, allowing them to operate as an integrated system rather than independent units, thereby improving overall productivity and energy efficiency.
Solution Approach 2:
The control devices are designed with multi-functionality, serving as both main control devices and shadow control devices at different times. This universal design allows the same hardware to perform multiple roles, reducing the need for specialized complex control circuits for each function while still achieving integrated control over multiple indoor units.
4Reliability
If shadow control system with monitoring is implemented, then system reliability improves, but loss of energy and computational overhead increase
Solution Approach 1:
The shadow control devices perform monitoring and standby functions partially - they continuously monitor system state and maintain readiness to take over, but they do not fully execute control operations unless needed. This partial action provides fault tolerance while minimizing the computational overhead and energy consumption that would result from full continuous operation of all control devices.
Data Source
AI summary
Heat pump systems, control systems for heat pumps, and methods of controlling heat pumps utilizing distributed control techniques are described herein. In one example, a heat pump system includes: a set of heat pumps; multiple sensors; and a control system including multiple control devices communicatively coupled with one another, the set of heat pumps, and the sensors. A first of the control devices is configured as a main control device for computing a control input for the set of heat pumps at each of multiple time steps. A subset of the control devices is configured to: monitor health status information of the first control device; and at each time step: determine whether the health status information at the current time step indicates a fault or failure of the first control device; and if so, elect a second of the control devices to be configured as the main control device.