Päikeseenergia passiivse kasutamise potensiaal erineva geomeetria ja komponentidega hoonetel Eesti kliimas

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PI Parameter Influence on Underfloor Heating Energy Consumption and Setpoint Tracking in nZEBs

In rooms with underfloor heating (UFH), local on–off controllers most often regulate the air temperature with poor accuracy and energy penalties. It is known that proportional–integral (PI) controllers can regulate most processes more precisely. However, hydronic UFH systems have long time constants, especially in low-energy buildings, and PI parameters are not easy to set manually. In this work, several potential PI parameter estimation methods were applied, including optimizing the parameters in GenOpt, calculating the parameters based on simplified models, and tuning the parameters automatically in Matlab. For all found parameter combinations, the energy consumption and control precision were evaluated. Simpler methods were compared to the optimal solutions to find similar parameters. Compared with an on–off controller with a 0.5 K dead-band, the best PI parameter combination found was with a proportional gain of 18 and an integration time of 2300 s, which could decrease the energy consumption for heating by 9% and by 5% compared with default PI parameters. Moreover, while GenOpt was the best method to find the optimal parameters, it was also possible with a simple automatic test and calculation within a weekend. The test can be, for example, 6-h setbacks applied during the nights or weekend-long pseudo-random changes in the setpoint signal. The parameters can be calculated based on the simplified model from these tests using any well-known simple method. Results revealed that the UFH PI controller with the correct parameters started to work in a predictive fashion and the resulting room temperature curves were practically ideal

PI parameter influence on underfloor heating energy consumption and setpoint tracking in NZEBs

In rooms with underfloor heating (UFH), local on-off controllers most often regulate the air temperature with poor accuracy and energy penalties. It is known that proportional-integral (PI) controllers can regulate most processes more precisely. However, hydronic UFH systems have long time constants, especially in low-energy buildings, and PI parameters are not easy to set manually. In this work, several potential PI parameter estimation methods were applied, including optimizing the parameters in GenOpt, calculating the parameters based on simplified models, and tuning the parameters automatically in Matlab. For all found parameter combinations, the energy consumption and control precision were evaluated. Simpler methods were compared to the optimal solutions to find similar parameters. Compared with an on-off controller with a 0.5 K dead-band, the best PI parameter combination found was with a proportional gain of 18 and an integration time of 2300 s, which could decrease the energy consumption for heating by 9% and by 5% compared with default PI parameters. Moreover, while GenOpt was the best method to find the optimal parameters, it was also possible with a simple automatic test and calculation within a weekend. The test can be, for example, 6-h setbacks applied during the nights or weekend-long pseudo-random changes in the setpoint signal. The parameters can be calculated based on the simplified model from these tests using any well-known simple method. Results revealed that the UFH PI controller with the correct parameters started to work in a predictive fashion and the resulting room temperature curves were practically ideal.Peer reviewe

Estimating time constants for underfloor heating control

Time constants are used for tuning PID control parameters and should be correctly estimated to achieve a well-performing controller. However, the estimation of time constants for a very slowly reacting system such as underfloor heating is not easy in practice. In this work, different methods were used to estimate the time constants for underfloor heating. Graphical estimation and transfer function fitting were the core approaches. Measurement data and simulations on a calibrated model were used for the estimations. The resulting time constant values for the graphical method depended clearly on the setback duration and the values differed up to a factor of 100. For the transfer function method, time constant values did not vary significantly. For light construction, the time constant was around 10 hours and for massive, around 30 hours for the otherwise identical room.Peer reviewe

Optimal PI control parameters for accurate underfloor heating temperature control

In low energy buildings, the effect of internal and solar gains on heat balance of rooms is large. As a result, the heating systems, designed assuming steady-state conditions with no heat gains, are over-dimensioned for most of the heating period. This poses a challenge for room-based control systems, especially for thermostatic valves, but also for PI controllers. Using over-dimensioned room units might result in room temperature fluctuations. For finding solutions to this problem by using simulations, correct modelling of the control system together with the room is crucial. Therefore, the aim of this research was to determine the challenges that occur while matching measured and simulated temperature profiles and test the effect of PI control parameters on the calibrated model control accuracy. The experiments were carried out for the underfloor heating system of a test building. The building was simulated in IDA-ICE software and calibration via minimising root mean square error of energy consumption in GenOpt was carried out. The PI parameters were fit by optimisation with objective to simulate the measured temperatures accurately. The effect of the optimized PI parameters was determined by comparison to IDA-ICE default parameters and parameters from Cohen-Coon method.Peer reviewe

Modelling of Wax Actuators in Underfloor Heating Manifolds

| openaire: EC/H2020/856602/EU//FINEST TWINS Publisher Copyright: © The Authors, published by EDP Sciences, 2021. Copyright: Copyright 2021 Elsevier B.V., All rights reserved.Finding sources for power grid balancing has become increasingly important with more renewables used for production. In buildings, heat pumps could be utilized among other electrical appliances. The heat pumps would work at full power to balance the overproduction in the grid. However, short-term grid flexibility announces the consumption need up to 5 minutes in advance, which can prove a problem to control. When there is no current energy need in the building, all valves are closed. That means that when a heat pump with overridden control starts working at the maximum frequency, its full power heats up the local circuit very fast, especially when there is no storage tank. Whether the heat pump overheats and cannot be used for balancing the grid or the whole system opens for heating depends on the regulating valves and their opening speed. For underfloor heating systems, the valve opening speed is slower than for other systems as wax actuators are used. This paper focuses on how to model these wax actuators and determine the opening time to provide input for further studies on flexibility. A physical and a linear segment model are parameterized and the results show that the wax actuator fully opens the valve in six minutes.Peer reviewe

Influence of time constants on low energy buildings' heating control

This paper estimates the range of time constant values for buildings with different insulation, thermal mass, and heat emitters for efficient temperature control by PI controllers, and comparing heat emission efficiency of the systems. Detailed models of the room, the heat emitter and the control system were used for dynamic simulations. For one case, the results were compared with measurements in a test building. Large variance in time constant values was found depending on the heat emitter, building parameters and the method used for the calculation. Time constant values were in the range of 1.9 to 94 hours. PI control with calculated parameters resulted in up to 8% heating energy difference between the low temperature water radiator and underfloor heating. The measurements showed lower time constant values than the simulationsPeer reviewe

Energy saving potential with smart thermostats in low-energy homes in cold climate

Smart home systems with smart thermostats have been used for years. Although initially mostly installed for improving comfort, their energy saving potential has become a renowned topic. The main potential lies in temperature reduction during the times people are not home, which can be detected by positioning their phones. Even if the locating is precise, the maximum time people are away from home is short in comparison to the buildings' time constants. The gaps are shortened by the smart thermostats, which start to heat up hours before occupancy to ensure comfort temperatures at arrival, and low losses through high insulation and heat-recovery ventilation in new buildings, which slow down the cool-down process additional to the thermal mass. Therefore, it is not clear how high the actual savings can be for smart thermostats in new buildings. In this work, a smart radiator valve was installed for a radiator in a test building. Temperature setback measurements were used to calibrate a simulation model in IDA ICE. A simulation analysis was carried out for estimating the energy saving potential in a cold climate for different usage profiles.Peer reviewe