SEARCH · Search NASA

Results for “heating, ventilation, and air conditioning”

Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

SourceResearch connectionFrom yearThrough year

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 73 records · Page 4

All sources NASA NTRS DOE OSTI

DOE OSTI2021

Development and validation of a second-order thermal network model for residential buildings

Heating, Ventilation, and Air Conditioning (HVAC) systems can maintain the space air temperature of residential buildings, either directly by heating/cooling the air, or indirectly via heat transfer to and from the building structure that acts as a thermal mass. Hence, HVAC systems can help achieve load shifting, peak load reduction, and/or energy cost saving, thus enabling grid-interactive HVAC operation. A home thermal model that can accurately reflect the dynamics of the space air and interior wall surface temperatures, is therefore valuable. This paper develops such a model using the standard RC (resistance-capacitance) approach. The model contains a virtual envelope node and an internal space node and is thus second-order. A hybrid parameter identification scheme, made up of the least-squares and optimal search methods, is also developed. The proposed model and scheme were validated using data collected from a test home. It was found that a modest amount of training data was sufficient to yield reliable parameter estimates and accurate prediction. It was also found that when making 24-hour-ahead prediction of the space air temperature, both methods had comparable performances when the training data began in a transition season. However, when they began in an HVAC season, the optimal search method performed better. Furthermore, the least-squares method is recommended during a transition season due to its lower computational burden, while the optimal search method is recommended during an HVAC season due to its better estimation performance.

24 POWER TRANSMISSION AND DISTRIBUTION↗

DOE OSTI2024

Advanced Frost Sensor for HVAC Applications

Frost is a common problem in heating, ventilation, and air conditioning (HVAC) systems that can degrade their efficiencies, leading to excessive electricity consumption. Appropriate defrosting is therefore essential for heat pumps and refrigeration systems. However, these systems typically run the defrost cycle based on a predetermined time interval, a method that does not accurately identify the amount of frost and thus consume excessive electricity. To substantially improve defrosting initiation and termination, this paper describes development of a smart sensor based on a capacitive sensing technique that can quantify frost accumulation and difference between frost, ice, and water. The reported sensor adopts interdigitated comb electrodes and can be updated to a potential multifunctional sensor array for the enhancing identification of frost, ice, and water with the integrated measurement of surface temperature, frost capacitance, and resistance. The proposed frost sensor is potentially expected to have widespread applications in HVAC systems, including heat pumps, refrigerators, and commercial refrigeration systems.

Gao, Zhiming↗

DOE OSTI2020

Smart Ventilation Controls Boost Energy Efficiency and Indoor Air Quality

The average American household spends more than $2,200 a year on energy, and heating, ventilating, and air conditioning (HVAC) costs comprise nearly half of the bill. This is one reason why home builders focus on tightening building envelopes to save energy. Yet, limiting the potential for air exchange can negatively impact indoor air quality (IAQ). When outdoor conditions are most extreme during occupied periods, there may be comfort implications from continuing high levels of ventilation during associated weather events. This is true even with heat recovery. To mitigate risks, the Florida Solar Energy Center developed and tested approaches for “smart” ventilation system controls that enable more reliable design, installation, and operation to achieve desired IAQ while also minimizing energy and comfort impacts.

30 DIRECT ENERGY CONVERSION↗

DOE OSTI2021

A first principles framework to predict the transient performance of latent heat thermal energy storage

Thermal energy storage (TES) is increasingly recognized as an essential component of efficient Combined Heat and Power (CHP), Concentrated Solar Power (CSP), Heating Ventilation and Air Conditioning (HVAC), and refrigeration as it reduces peak demand while helping to manage intermittent availability of energy (e.g., from solar or wind). Latent Heat Thermal Energy Storage (LHTES) is a viable option because of its high energy storage density. Parametric analysis of LHTES in terms of dimensionless numbers is highly desired as a tool to model LHTES systems. One approach is to develop a model equation so as to minimize the error between the model and data obtained from experiments or simulations. While this approach can produce an accurate correlation applicable within the range of data used for its creation, it does not provide physical understanding of the rate-limiting process controlling the transient behavior of the device. In this paper we present an alternative approach whereby the potential rate-limiting processes are identified from first principles and then the key process is determined as a function of time as a LHTES device is charged. For example, in a simple geometry, the melt-fraction can be expected to vary linearly in time if the heat transfer rate is limited by natural convection of the phase changing material and we show it scales with the PCM Grashof number as $Gr^1_p$ and PCM Prandtl number as $Pr_p^{(1/3)}$. On the other hand, if surface area of solid PCM limits the heat transfer rate, the melt fraction increases asymptotically to reach full melting. The existence of these linear and asymptotic regions and the $Gr^1_pP r^{1/3}_p$ shape of the melt fraction curve is verified using our database of 64 simulations. Of practical importance in designing LHTES devices is the melt fraction at which the heat transfer rate ceases to be limited by convection, after which the heat storage rate deteriorates. For our geometry, this is found to be about 90%. This test case of our methodology shows the value of our approach, that predicting heat storage rate based on the rate-limiting physical phenomenon as a function of time is an effective approach to modeling LHTES devices.

25 ENERGY STORAGE↗

DOE OSTI2023

Integration of a Smart Outlet-Based Plug Load Management System with a Building Automation System

The growth of and reliance on renewable energy necessitate a multi-pronged approach to achieve grid reliability and economics. As they represent a notable portion of U.S. energy consumption, commercial buildings must play an active role in this effort. Conserving energy and responding to grid conditions through demand flexibility can be achieved through the integration of major building systems. Integration of plug and process loads with lighting and heating, ventilation, and air conditioning systems maximizes the effectiveness of integrated building energy management. In this research, we demonstrate the integration of smart outlets into a building automation system. We cover the installation process as well as the architecture required for smart outlets to communicate data to the building automation system and to receive commands back. After recording power measurements for one week as a baseline, we configured the building automation system to turn the smart outlets on and off according to a set schedule. This resulted in energy savings of 66% during 1 week on 25 plug loads. This work demonstrates that grid-interactive efficient buildings are achievable through building system integration.

building automation system↗

NASA NTRS2010

Effects of Solar Photovoltaic Panels on Roof Heat Transfer

Building Heating, Ventilation and Air Conditioning (HVAC) is a major contributor to urban energy use. In single story buildings with large surface area such as warehouses most of the heat enters through the roof. A rooftop modification that has not been examined experimentally is solar photovoltaic (PV) arrays. In California alone, several GW in residential and commercial rooftop PV are approved or in the planning stages. With the PV solar conversion efficiency ranging from 5-20% and a typical installed PV solar reflectance of 16-27%, 53-79% of the solar energy heats the panel. Most of this heat is then either transferred to the atmosphere or the building underneath. Consequently solar PV has indirect effects on roof heat transfer. The effect of rooftop PV systems on the building roof and indoor energy balance as well as their economic impacts on building HVAC costs have not been investigated. Roof calculator models currently do not account for rooftop modifications such as PV arrays. In this study, we report extensive measurements of a building containing a flush mount and a tilted solar PV array as well as exposed reference roof. Exterior air and surface temperature, wind speed, and solar radiation were measured and thermal infrared (TIR) images of the interior ceiling were taken. We found that in daytime the ceiling surface temperature under the PV arrays was significantly cooler than under the exposed roof. The maximum difference of 2.5 C was observed at around 1800h, close to typical time of peak energy demand. Conversely at night, the ceiling temperature under the PV arrays was warmer, especially for the array mounted flat onto the roof. A one dimensional conductive heat flux model was used to calculate the temperature profile through the roof. The heat flux into the bottom layer was used as an estimate of the heat flux into the building. The mean daytime heat flux (1200-2000 PST) under the exposed roof in the model was 14.0 Watts per square meter larger than under the tilted PV array. The maximum downward heat flux was 18.7 Watts per square meters for the exposed roof and 7.0 Watts per square meters under the tilted PV array, a 63% reduction due to the PV array. This study is unique as the impact of tilted and flush PV arrays could be compared against a typical exposed roof at the same roof for a commercial uninhabited building with exposed ceiling and consisting only of the building envelope. Our results indicate a more comfortable indoor environment in PV covered buildings without HVAC both in hotter and cooler seasons.

Dominguez, A.↗

DOE OSTI2020

Development and Evaluation of Occupancy-Aware HVAC Control for Residential Building Energy Efficiency and Occupant Comfort

Occupancy-aware heating, ventilation, and air conditioning (HVAC) control offers the opportunity to reduce energy use without sacrificing thermal comfort. Residential HVAC systems often use manually-adjusted or constant setpoint temperatures, which heat and cool the house regardless of whether it is needed. By incorporating occupancy-awareness into HVAC control, heating and cooling can be used for only those time periods it is needed. Yet, bringing this technology to fruition is dependent on accurately predicting occupancy. Non-probabilistic prediction models offer an opportunity to use collected occupancy data to predict future occupancy profiles. Smart devices, such as a connected thermostat, which already include occupancy sensors, can be used to provide a continually growing collection of data that can then be harnessed for short-term occupancy prediction by compiling and creating a binary occupancy prediction. Real occupancy data from six homes located in Colorado is analyzed and investigated using this occupancy prediction model. Results show that non-probabilistic occupancy models in combination with occupancy sensors can be combined to provide a hybrid HVAC control with savings on average of 5.0% and without degradation of thermal comfort. Model predictive control provides further opportunities, with the ability to adjust the relative importance between thermal comfort and energy savings to achieve savings between 1% and 13.3% depending on the relative weighting between thermal comfort and energy savings. In all cases, occupancy prediction allows the opportunity for a more intelligent and optimized strategy to residential HVAC control.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

DOE OSTI2020

Accuracy of HVAC Load Predictions: Validation of EnergyPlus and DOE-2 using FLEXLAB Measurements

The aim of the project reported here was to better understand the level of accuracy of three building energy simulation (BES) engines (‘engines’) — EnergyPlus™, DOE-2.1e, and DOE-2.2 — by identifying and investigating significant deviations between the performance predicted by these engines and actual performance as measured in the FLEXLAB® test facility at Lawrence Berkeley National Laboratory (LBNL). The specific test conditions included some of those prescribed in ANSI/ASHRAE Standard 140 - Standard Method of Test for the Evaluation of Building Energy Analysis Computer Programs. Detailed measurements of FLEXLAB performance, including indoor temperatures and heat fluxes and air-flow and water flow rates and temperatures in the Heating, Ventilating and Air Conditioning (HVAC) system, together with hourly weather data, were recorded and used in analyzing the simulation results from EnergyPlus v8.8, DOE-2.2 v3.65 and DOE-2.1e v127. These engines are commonly used in the United States for building energy code compliance, federal, state, and utility incentives programs, as well as energy efficient design of new buildings and energy retrofit of existing buildings. Seven conventional overhead mixing ventilation scenarios were tested and each engine was found to have a similar level of agreement with the measurements of space-level heating and sensible cooling loads. These results provide useful information regarding the accuracy of these engines in predicting the cooling and heating load elements of whole building energy performance. This information is intended for practitioners who are concerned about transitioning between simulation tools with different engines and for managers of utility programs leveraging these tools for evaluating and/or projecting measure savings to be incentivized under their programs. The results of the comparisons of simulated and measured performance indicate that the predictions from all three engines are not significantly different. The 24-hour average value of the absolute mean bias indicates the likely magnitude of the error in any particular case. The average mean bias is reduced by cancelation of overprediction in one case by underprediction in another. The daytime absolute mean biases, which may be more important for both energy performance and occupant comfort, are ~6%, presumably because of the greater complexity involved in simulating in the presence of solar radiation. EnergyPlus typically overpredicts the cooling load and/or underpredicts the heating load by ~1.5% and the DOE-2 engines typically underpredict the cooling load by approximately the same amount. The Root Mean Square Error is relatively more sensitive to shorter term variations in the difference between predicted and measured loads; the three engines have similar values, ~10%, suggesting that the uncertainties in their predictions of peak loads may also be similar in magnitude. The implication of these results is that users, both designers and program analysts, can use EnergyPlus, DOE-2.1e, or DOE-2.2 to model conventional commercial buildings equipped with overhead mixing ventilation with a similar level of confidence. Further work is required to better understand the variability in the level of agreement between the engine predictions and FLEXLAB measurements, where a particular engine will agree well with FLEXLAB in some cases and not so well in others and another engine will agree or disagree in different cases. As the sources of this variability are identified and eliminated or reduced significantly, it is recommended that the experimental capabilities and methods developed in the study reported here should be applied to validating heating and cooling load calculations for spaces with different types of furniture and miscellaneous loads. These methods should then be applied to low energy space conditioning systems in EnergyPlus including, in particular, radiant slab and radiant ceiling panel cooling and heating systems and ‘mixed mode’ systems that combine mechanical cooling and natural ventilation systems, focusing on controls, including control of thermal mass. The work reported here addresses the conventional method of heating and cooling occupied spaces; other methods, such as the use of radiant heating and cooling systems have the potential to provide equivalent occupant comfort, or better, with lower energy consumption. These systems are addressed more explicitly in EnergyPlus but there is a need for empirical validation to give users the same level of confidence in modeling these systems that they have, or should have, in modeling conventional systems, based on the results presented here.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

DOE OSTI2020

Smart Ventilation Controls Boost Energy Efficiency and Indoor Air Quality

Building America↗

DOE OSTI2025

Refrigerants for a Sustainable Future

Worldwide use of high global warming potential (GWP) hydrofluorocarbon (HFC) refrigerants for space conditioning and food storage results in significant equivalent greenhouse gas (GHG) emissions. This is further exacerbated in developed countries by the current transition from hydrochlorofluorocarbon (HCFC) refrigerants to HFC refrigerants. Under the Kigali amendment to the Montreal Protocol, the proposed phase-out of currently used HFC and HCFC refrigerants has initiated a re-evaluation of some pre-existing refrigerants as well as the development and evaluation of new refrigerants. Making the ideal refrigerant selections for heating, ventilation, air-conditioning, and refrigeration (HVAC&R) applications is thereby difficult in an already overabundant refrigerants market. In this paper, a study of key parameters required of a good refrigerant is conducted, followed by the analysis of refrigerants desired and refrigerants used in two major sectors of the HVAC&R industry, namely commercial refrigeration and residential air-conditioning and heat pumps. Finally, keeping in consideration the global environmental regulations and safety standards, a recommendation of the most suitable refrigerants in both sectors has been made.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2022

Long-term trends in connected thermostat performance

Internet-connected thermostats (CTs) control heating and cooling systems in about 30% of North American homes, and capture half of annual thermostat sales. In 2017 the U.S. Environmental Protection Agency created a program to certify the performance of ENERGY STAR® Connected Thermostats. To demonstrate compliance with energy-saving criteria, thermostat vendors must submit performance summaries for a representative sample of up to 1250 homes. Vendors must then re-submit results from a new, representative sample every six months in order to maintain their ENERGY STAR certification. This procedure has created a unique record of each thermostat’s long-term performance in response to changes in weather, customer demographics, building stock, and algorithms. Our analysis covers submissions from 13 different vendors, who submitted data up to 7 times over four years. We found that these semi-annual samples generated relatively stable trends for comfort temperatures and Heating, Ventilating and Air Conditioning (HVAC) runtimes over the study period. However, some vendors achieved consistently more energy-conserving comfort temperatures and shorter HVAC runtimes than others. The most recent submission runtimes averaged 700 hours for heating and 1,300 hours for cooling, but some vendors achieved runtimes as much as 17% below the mean. This implies lower energy consumption is due in large part to more successful algorithms and control strategies used by those vendors.

Meier, Alan↗

NASA NTRS1996

Fungal colonization of fiberglass insulation in the air distribution system of a multi-story office building: VOC production and possible relationship to a sick building syndrome

Complaints characteristic of those for sick building syndrome prompted mycological investigations of a modern multi-story office building on the Gulf coast in the Southeastern United States (Houston-Galveston area). The air handling units and fiberglass duct liner of the heating, ventilating and air conditioning system of the building, without a history of catastrophic or chronic water damage, demonstrated extensive colonization with Penicillium spp and Cladosporium herbarum. Although dense fungal growth was observed on surfaces within the heating-cooling system, most air samples yielded fewer than 200 CFU m-3. Several volatile compounds found in the building air were released also from colonized fiberglass. Removal of colonized insulation from the floor receiving the majority of complaints of mouldy air and continuous operation of the units supplying this floor resulted in a reduction in the number of complaints.

NASA Program Environmental Health↗

DOE OSTI2020

Intelligent multi-zone residential HVAC control strategy based on deep reinforcement learning

Residential heating, ventilation, and air conditioning (HVAC) has been considered as an important demand response resource. However, the optimization of residential HVAC control is no trivial task due to the complexity of the thermal dynamic models of buildings and uncertainty associated with both occupant-driven heat loads and weather forecasts. In this paper, we apply a novel model-free deep reinforcement learning (RL) method, known as the deep deterministic policy gradient (DDPG), to generate an optimal control strategy for a multi-zone residential HVAC system with the goal of minimizing energy consumption cost while maintaining the users’ comfort. Here, the applied deep RL-based method learns through continuous interaction with a simulated building environment and without referring to any prior model knowledge. Simulation results show that compared with the state-of-art deep Q network (DQN), the DDPG-based HVAC control strategy can reduce the energy consumption cost by 15% and reduce the comfort violation by 79%; and when compared with a rule-based HVAC control strategy, the comfort violation can be reduced by 98%. In addition, experiments with different building models and retail price models demonstrate that the well-trained DDPG-based HVAC control strategy has high generalization and adaptability to unseen environments, which indicates its practicability for real-world implementation.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

DOE OSTI2022

Load Shifting with Space Conditioning Heat Pumps During Heating Season in the Pacific Northwest

Ductless mini- and multi-split heat pumps are commonly deployed in Pacific Northwest residences, which historically have inefficient space heating and no space cooling. Heat pumps provide these residences with more energy-efficient space heating in the winter and space cooling for increasingly warm summer periods. For many of these applications, heat pumps add a new electrical load at the residence, compelling regional utilities to seek to understand their impacts on the electrical grid and opportunities for load management. In coordination with regional utilities, this study examined the winter load-shifting potential of residential multi-split heat pumps with variable capacity technology. The study included nine residential sites with a total of 20 ductless indoor units, which underwent simulated smart grid control. Grid control functionality was provided through the CTA-2045 communication protocol and included offsetting temperature setpoints for individual indoor units in the study. Field data collection included whole-house and heating, ventilation, and air conditioning electrical power consumption; indoor zone temperatures; occupant surveys; and CTA-2045 curtailment data for both baseline and simulated load-shifting events by site. This paper provides an overview of the load-shifting strategies and aggregated results from winter data collection.

ASHRAE, Heat pump, energy effciency, residential b↗

DOE OSTI2023

Performance assessment of a real water source heat pump within a hardware-in-the-loop (HIL) testing environment

Over the last decade, the global fight against climate change through electrification has led to an increase in research on building heating, ventilation, and air conditioning (HVAC) systems that utilize intelligent control algorithms to provide demand-side grid service while also maintaining the thermal comfort of building occupants. As the pivotal point between building electricity consumption and indoor thermal comfort, high-efficiency electrical vapor-compression heat pumps are at the center of these emerging studies, and various grid-interactive and occupant-comfort control algorithms have been developed for them. The impact of these algorithms on heat pump operation and performance when subjected to different weather conditions, building loads, and grid requests calls for investigation and verification via experimental testing with actual heat pumps integrated with real-time building and grid responses. This study introduces a Water-Source Heat Pump (WSHP) Hardware-in-The-Loop (HIL) Test Facility that is the first of its kind. This testbed utilizes a 2-ton variable speed water-to-air heat pump that is capable of interacting with a virtual environment currently comprised of an EnergyPlus (E+) building simulation, an agent-based occupant behavioral model, and a single U-tube ground-loop heat exchanger (GLHE) model. Detailed descriptions of the testbed’s physical design and operation, virtual environment, as well as their mutual communication is provided. An uncertainty analysis is also performed under manufacturer specified heating and cooling design conditions. This analysis shows that the total load across the WSHP’s demand side heat exchanger, i.e., the sum of its latent and sensible components, can be measured with a relative uncertainty of ± 10.4% and ± 3.6% in cooling and heating mode respectively. The WSHP’s coefficient of performance (COP) can be measured with relative uncertainties of ± 10.4% in cooling mode, and ± 3.7% in heating mode. A preliminary 24-h experimental demonstration is then performed utilizing the DOE prototype small commercial office building model in E+. The simulation takes place in Atlanta, GA on the date of 08/26/15 from 12:00 AM to 11:59 PM using TMY3 weather data. Here, the results from this demonstration show that over the course of this experiment the simulated outputs of zone dry-bulb temperature, zone humidity ratio, and WSHP inlet water temperature can be tracked by testbed emulators up to a root mean squared error (RMSE) of ± 0.27 °C, ± 0.376 g/kg, and ± 0.85 °C respectively. The WSHP’s dynamic behavioral characteristics and performance are also captured, and correspond well with the authors’ previous understanding of heat pump efficiency as a function of evaporator and condenser fluid inlet conditions respectively.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

DOE OSTI2022

Impact of Mass Wood Walls on Building Energy Use, Peak Demand, and Thermal Comfort

Thermal mass moderates indoor temperatures, allowing the heating, ventilation, and air conditioning (HVAC) system to operate more efficiently during peak hours. Cross-Laminated Timber (CLT) and other mass wood products provide thermal mass to the building envelope in a lighter and more environmentally friendly form than concrete. However, the influence of CLTs on heating and cooling energy, peak energy demand, and the indoor climate is not well-known. This project was formed to find the energy efficiency benefits of mass timber structures. The objectives were to (1) test the thermal performance of insulated mass wall structures in controlled laboratory conditions, (2) validate simulation models to expand performance to natural climatic conditions, (3) isolate the impact of the thermal properties of wood (thermal mass, thermal conductivity, moisture storage) on heating and cooling energy use and peak energy demand, and to optimize the performance. Currently, the designs used for CLT buildings have focused on structural and fire issues, and they do not consider the thermal mass benefits. Therefore, the thermal performance is not necessarily optimized.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

DOE OSTI2022

In Tube Condensation Heat Transfer and Pressure Drop for R454B and R32—Potential Replacements for R410A

The heating, ventilation and air conditioning (HVAC) industry in the United States seeks near-term alternative refrigerants to replace R-410A in unitary equipment. Two potential replacement refrigerants are R-454B and R-32. It is of interest to investigate the capability and accuracy of existing heat exchanger design methods when applied to these replacement refrigerants. To that end, this work presents empirical condensation quasi-local heat transfer coefficient and pressure drop data for R-454B and R-32. These data were obtained in a $\frac{3}{8}$ in. (9.52 mm) outside diameter (OD) smooth copper tube with a wall thickness of 0.032 in. (0.81 mm). The experimental variables and their ranges included refrigerant absolute pressure ( 1960 ≤ P a b s ≤ 3196 kPa), condensation temperature ( 35 ≤ T c o n d ≤ 50 °C), mass flux ( 100 ≤ G ≤ 200 kg m -2 s -1 ), vapor quality ( 0 ≤ x ≤ 1 ), and heat flux ( 32.9 ≤ q ″ ≤ 62.97 kW m -2 ). It was found that the heat transfer correlation developed by Cavallini et al. Cavallini et al. (2006) predicted the experimental condensation heat transfer data, for both R-454B and R-32, with the greatest accuracy. Using the Cavallini et al. correlation, it was found that the mean absolute percentage error (MAPE) was 10.5% and 15.1% for R-454B and R-32, respectively. Additionally, the pressure drop correlation developed by Friedel Friedel (1979) predicted the experimentally determined pressure gradient with a MAPE of 7.7% and 5.5% for R-454B and R-32, respectively. These results will assist the practicing thermal engineer to choose the most appropriate design correlation for these near-term replacement refrigerants.

42 ENGINEERING↗

DOE OSTI2020

Cloud-based implementation of white-box model predictive control for a GEOTABS office building: A field test demonstration

Model predictive control (MPC) has been proven in simulations and pilot case studies to be a superior control strategy for large buildings. MPC can utilize the weather and occupancy schedule forecasts, together with the system model, to predict the future thermal behavior of the building and minimize the overall energy use and maximize thermal comfort. However, these advantages come with the cost of increased modeling effort, computational demands, communication infrastructure, and commissioning efforts. Thus a typical approach is to, often rapidly, simplify the building modeling and MPC optimization problem while paying a price of not reaching the full performance potential. It has been shown that by employing accurate physics-based models, MPC performance can be notably increased closer to its theoretical performance bound. However, implementation of such high-fidelity MPC in real buildings remains a challenge, resulting in a lack of successful field test studies. This work presents the methodology and field test demonstration of a computationally efficient implementation of the white-box MPC in an office building in Belgium. The detailed model of the building is based on first-principle physical equations. The deployment and supervision of MPC operation in a practical setting are supported by an automated cloud-based communication infrastructure. The motivating factor behind the cloud-based architecture is its compatibility with a commercially appealing control as a service concept. The building is equipped with a ground source heat pump (GSHP) and thermally activated building structures (TABS), where the combination of both is also known as GEOTABS. From a control perspective, GEOTABS buildings are particularly challenging systems due to large scale, complex heating, ventilation and air conditioning (HVAC) system, and slow dynamics with time delays. On the other hand, there is an increased potential for energy savings due to the high thermal mass, which acts as thermal storage. The MPC operation is demonstrated during the challenging transient seasons (switching between heating and cooling), and its performance is compared to a traditional rule-based controller (RBC). We provide a proof of concept of real MPC operation for the most difficult seasons with notable GSHP energy use savings equal to 53.5% and thermal comfort improvement by 36.9%. Other MPC applications found in the literature describe tests for only cooling or only heating, and up to now only for a black-box or a grey-box approach.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗