Heat Pump Defrost Prediction for Continuous Hot Water Supply
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Solution Overview
Problem
Heat pumps used for providing heated water are disruptive due to their slow startup and defrost cycles, which can interrupt the continuous supply of heated water, and existing strategies for energy and water conservation are not adaptable to individual household needs.
Innovation Solution
A computer-implemented method that uses machine learning algorithms to predict the start time of a heat pump's defrost cycle, allowing the system to pre-charge the thermal energy storage medium and adjust the indoor temperature, thereby minimizing disruptions during defrost cycles and optimizing energy usage based on user patterns and weather data.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Use of energy by moving object
If a heat pump is used to provide heated water, then energy efficiency is improved, but the system becomes disruptive due to slow startup and defrost cycles
Solution Approach 1:
The system performs preliminary actions by predicting defrost cycle start times using machine learning algorithms and pre-charging the thermal energy storage medium before defrost cycles begin. This allows the heat pump to maintain continuous heated water supply despite the inherent disruptions of defrost cycles, resolving the contradiction between energy efficiency and reliable continuous operation
2Reliability
If the heat pump operates continuously to maintain heated water supply, then reliability is improved, but energy consumption increases during peak tariff periods
Solution Approach 1:
The system operates the heat pump in advance during off-peak tariff periods to pre-charge the thermal energy storage medium, then relies on stored thermal energy during peak periods. This timing strategy reduces energy consumption costs while maintaining continuous heated water supply reliability
Solution Approach 2:
The system uses machine learning algorithms that analyze historical data and weather forecasts to predict future heated water demands and defrost cycle timing. This feedback mechanism optimizes when to operate the heat pump versus when to rely on stored thermal energy, balancing reliability with energy cost efficiency
3Reliability
If the thermal energy storage medium is pre-charged before defrost cycles, then disruption is reduced, but the system complexity increases
Solution Approach 1:
The system employs machine learning algorithms that automatically learn and predict defrost cycle patterns and heated water demand without requiring manual intervention or complex control mechanisms. The system self-optimizes the pre-charging strategy based on predicted defrost timing and user patterns, reducing the effective complexity while maintaining reliability
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 approach enables heat pumps to provide consistent heated water with reduced disruption during defrost cycles, promoting energy efficiency and water conservation by anticipating and preparing for energy demands, thus making heat pumps a more practical alternative to electrical heaters.
Implementation Method 1
a heat pump configured to transfer thermal energy from outside the building to a thermal energy storage medium inside the building
Implementation Method 2
The now higher energy refrigerant is compressed, causing it to raise temperature considerably
Implementation Method 3
where this now hot refrigerant exchanges thermal energy via a heat exchanger to a heating water loop
Implementation Method 4
heat extracted by the heat pump can be transferred to a water in an insulated tank that acts as a thermal energy storage
Data Source
AI summary
The present disclosure provides a computer-implemented method of defrosting a heat pump of a water provision system installed in a building, the water provision system comprising the heat pump configured to transfer thermal energy from outside the building to a thermal energy storage medium inside the building and a control module configured to control operation of the heat pump, the water provision system being configured to provide water heated by the thermal energy storage medium to an occupant of the building at one or more water outlets, the method being performed by the control module and comprising: determining, based on performance of the heat pump, an expected start time of a next defrost cycle; and preparing the water provision system before the expected start time of the next defrost cycle.