Building Heating Requirement Estimation from Flow-Return Heat Data
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Solution Overview
Problem
Current methods for determining the heating requirement of buildings, such as consumption energy certificates, are influenced by user behavior and require extensive data collection, making them impractical and inaccurate, especially for older buildings with unclear wall constructions where heat loss is estimated, leading to potential falsification of energy requirement certificates.
Innovation Solution
A method involving continuous measurement of the temperature difference between the heating circuit's flow and return, multiplied by the volume flow, to determine the heating output, which is then related to room and outside temperatures using polynomial averaging and parameter identification to calculate the typical heating requirement, independent of user behavior and accounting for thermal inertia.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of manufacture
If consumption energy certificates are used, then the certificate creation is easier and cheaper, but the results are influenced by user behavior and cannot provide accurate heating requirement data
Solution Approach 1:
The patent replaces manual data collection and estimation methods with automated sensor-based measurement systems. Temperature sensors, flow sensors, and weather data are automatically processed by a control unit to calculate heating requirements, eliminating the need for manual consumption data analysis and providing objective, behavior-independent results.
Solution Approach 2:
The heating system performs self-measurement and self-evaluation of its performance. The control unit automatically collects data from sensors, processes it according to the patent method, and generates heating requirement certificates without external intervention, making the system both the subject and object of measurement.
2Reliability
If required energy certificates are calculated based on building envelope structure, then user behavior influence is eliminated, but heat loss estimation in older buildings leads to falsification of energy requirement certificates
Solution Approach 1:
The patent replaces theoretical heat loss calculations based on building envelope assumptions with actual measured data from temperature and flow sensors. The control unit processes real operational data to determine actual heating requirements, eliminating estimation errors in older buildings with unclear wall constructions.
Solution Approach 2:
The patent transitions from static building parameter analysis (envelope structure, U-values) to dynamic operational parameter measurement (actual temperatures, flow rates, weather conditions). This allows the system to adapt to the actual performance of the building regardless of its construction characteristics.
3Quantity of substance
If consumption data is collected over three years, then sufficient data for certificate issuance is obtained, but energy savings from renovation measures cannot be detected until three years after renovation
Solution Approach 1:
The patent establishes a continuous measurement system that collects and processes data in real-time, maintaining a rolling database of heating performance. This allows the system to have sufficient data available at any point in time, enabling immediate assessment of renovation effects without waiting for a fixed three-year period to elapse.
Solution Approach 2:
The patent implements a dynamic data collection and processing system that continuously updates heating requirement calculations as new data becomes available. The control unit processes measurements in real-time and can generate updated certificates at any time, allowing flexible and immediate detection of energy savings rather than being constrained by fixed time intervals.
4Measurement precision
If continuous measurement of temperature difference and volume flow is performed, then accurate heating output determination is achieved, but measurement uncertainties and thermal inertia delays affect parameter identification
Solution Approach 1:
The patent implements feedback mechanisms where the control unit continuously monitors measurements and adjusts parameter identification based on observed deviations. The system uses the actual measured data to refine its understanding of building thermal characteristics, compensating for measurement uncertainties and thermal inertia effects through iterative optimization.
Solution Approach 2:
The patent employs parameter identification methods that adaptively adjust model parameters based on measured data. The control unit processes the relationship between temperature differences, flow rates, and actual heating output to optimize thermal model parameters, accounting for thermal inertia and measurement uncertainties through statistical and signal processing techniques.
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 method allows for accurate, user-behavior-independent determination of the heating requirement using existing sensors, enabling immediate detection of energy savings from renovation measures and providing detailed, building-specific recommendations for energy certificates without requiring new data collection.
Implementation Method 1
the temperature difference between the flow and the return of the heating circuit is continuously measured. This can be done, for example, using two temperature sensors whose measured values are subtracted from one another
Implementation Method 2
The temperature difference obtained in this way is multiplied by the volume flow, which is recorded by a volume flow sensor
Implementation Method 3
The averaged parameters of a polynomial, which describes the relationship between the temperature difference and heat output in terms of a formula, are determined from the values that are now measured
Implementation Method 4
the parameters are determined using parameter identification methods that are fundamentally known from statistics and digital signal processing, for example on the basis of the mean square deviation, averaged over a longer period of time
Data Source
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Figure 3
AI summary
The invention relates to a method for determining the typical heat requirement for a residential building (1) covered by a heater (2). For this purpose, according to the invention, the heat output of the heater (2) is related to the difference between the room temperature and the outside temperature. The averaged parameters of a polynomial are identified and a heating requirement of the building per year and per square meter is calculated.