Predictive control for heat transfer to fluids
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Solution Overview
Problem
Current methods and systems for operating heat pump systems to heat fluids face limitations in achieving user preferences and energy economic efficiencies, especially with the increasing integration of intermittent renewable energy sources and variable electricity pricing.
Innovation Solution
A predictive controller, specifically a model predictive controller, is used to optimize fluid temperature set-points and compressor settings in a heat pump system. This controller determines optimized settings based on user preferences, energy price information, solar information, and GHG intensity information, and continually adjusts these settings to achieve energy usage optimization and user comfort.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of energy
If a predictive controller is implemented to optimize energy usage and achieve user preferences, then energy economic efficiencies and user comfort are improved, but device complexity increases
Solution Approach 1:
The predictive controller performs preliminary actions by determining optimized fluid temperature set-points and compressor settings in advance based on predicted future conditions (energy prices, solar availability, GHG intensity). This allows the system to proactively adjust operations to optimize energy usage before actual demand occurs, resolving the contradiction by achieving energy efficiency through advance planning rather than reactive control
Solution Approach 2:
The controller continuously receives feedback from multiple sources including energy price information, solar production data, GHG intensity measurements, and actual system performance. This multi-parameter feedback loop enables the predictive controller to dynamically adjust settings to maintain optimal energy efficiency while adapting to changing conditions, thereby achieving energy optimization despite increased system complexity
2Adaptability or versatility
If the predictive controller continuously adjusts settings based on multiple input parameters, then adaptability to varying energy prices and renewable energy availability is improved, but measurement and control difficulty increases
Solution Approach 1:
The predictive controller is designed as a multi-functional device that simultaneously processes diverse input parameters (energy prices, solar production, GHG intensity, fluid temperature, compressor settings) and performs multiple control functions. This universal controller handles all adaptation tasks in a single integrated system, reducing the overall difficulty compared to multiple separate control systems while maintaining high adaptability to varying conditions
Solution Approach 2:
The controller manages adaptability by systematically changing operational parameters (fluid temperature set-points, compressor speed settings) in response to varying external conditions (energy prices, solar availability). This parameter-based control approach allows the system to adapt to different scenarios through standardized parameter adjustments rather than complex structural changes, thereby improving adaptability while keeping measurement and control within manageable limits
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 predictive controller effectively optimizes energy usage and user comfort by continuously determining the most efficient settings for the heat pump system, leading to reduced energy consumption and lower greenhouse gas emissions while meeting user preferences.
Implementation Method 1
heat transfer to a fluid
Implementation Method 2
heat pump system
Data Source
AI summary
Predictive controllers are disclosed which provide, among other things, efficient strategics for controlling heat transfer to or from a liquid. A method and system are disclosed that includes receiving input information including any or all of user preferences, energy price information, solar information, and GHG intensity information, determining with the predictive controller settings information to provide one or both of fluid temperature set points and compressor settings of a heat pump system and heating the fluid in response to the settings information to provide hot fluid according to the user preferences and to achieve the economic efficiencies.