System and method for power optimizing control of multi-zone heat pumps
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Solution Overview
Problem
Conventional vapor compression systems face challenges in minimizing power consumption due to slow convergence rates of extremum-seeking controllers and the need for sensor measurements, which limits real-time optimization and robustness against disturbances.
Innovation Solution
A control system with a cascade configuration, featuring an inner feedback loop for zone temperature regulation and an outer power-optimizing feedback loop that uses a modified mathematical model to compute the gradient of power consumption analytically, allowing for exponential convergence to minimal power consumption without time-scale separation or sensor measurements.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Use of energy by moving object
If conventional extremum-seeking controllers are used to minimize power consumption, then power optimization is achieved, but convergence rate is slow
Solution Approach 1:
The patent implements a feedback mechanism where the estimated power consumption is continuously monitored and used to adjust control inputs. The gradient estimation feedback loop enables the system to converge to optimal power consumption faster by using real-time performance metric information rather than relying on slow perturbation-based methods.
Solution Approach 2:
The patent replaces the mechanical perturbation-based extremum-seeking approach with a computational gradient estimation method. Instead of physically perturbing system inputs and measuring resulting power changes, the system uses a mathematical model to estimate the gradient of power consumption with respect to control inputs, enabling faster convergence without physical experimentation.
2Use of energy by moving object
If perturbation-based extremum seeking controllers are used, then optimal operating point is found, but time-scale separation is required
Solution Approach 1:
The patent introduces a mathematical model of power consumption as an intermediary between the control inputs and the actual power measurement. This model enables gradient estimation without requiring direct measurement of power consumption or time-scale separation, simplifying the control system architecture while maintaining optimization capability.
3Use of energy by moving object
If sensor measurements are used to measure power consumption, then accurate optimization is achieved, but additional sensors and complexity are required
Solution Approach 1:
The patent creates a computational copy or model of the power consumption characteristic rather than directly measuring it with sensors. This mathematical representation allows the system to estimate power consumption and its gradient using existing sensor data and system state information, eliminating the need for additional power measurement sensors.
4Use of energy by moving object
If set-point schedules are used to minimize power, then power reduction is achieved, but calibration is time-consuming and expensive
Solution Approach 1:
The patent enables the control system to automatically determine optimal operating conditions through real-time gradient estimation and feedback, eliminating the need for manual calibration. The system self-adjusts to minimize power consumption based on current operating conditions without requiring time-consuming calibration procedures or expert intervention.
Solution Approach 2:
The patent transitions from static set-point schedules to dynamic optimization where control inputs are continuously adjusted based on real-time gradient estimation. This dynamic approach allows the system to adapt to changing operating conditions automatically, eliminating the need for pre-calibrated static schedules and enabling real-time power optimization.
5Use of energy by moving object
If conventional set-point schedules are used, then power minimization is attempted, but robustness against disturbances is poor
Solution Approach 1:
The patent implements continuous feedback based on real-time gradient estimation of power consumption. This feedback mechanism enables the system to respond to disturbances and changing operating conditions dynamically, maintaining robustness and reliability while minimizing power consumption, unlike open-loop set-point schedules that lack adaptive capability.
Data Source
AI summary
Systems and methods for a vapor compression system including primary actuators, secondary actuators, primary sensors that provide a primary set of system outputs, and secondary sensors that provide a secondary set of system outputs. A primary controller receives the primary set of system outputs, and produces a primary set of control inputs for the primary actuators, to regulate one or more zone temperatures to set-points and to regulate one or more critical process variables to set-points. A secondary controller receives the secondary set of system outputs, and produces a secondary set of control inputs, to minimize an overall system power consumption. The secondary inputs may include set-points to the primary controller. The primary outputs may include estimates of critical process variables that are used as inputs to the secondary controller.