HVAC Energy Research Articles

HVAC electricity and natural gas saving potential of a novel switchable window compared to conventional glazing systems: A Canadian house case study in city of Toronto

This paper investigates performance of a novel switchable window to reduce HVAC energy consumption of a typical Canadian house located in city of Toronto. Energy saving potential of the proposed glazing system is compared with highly efficient low emissivity coated double and triple pane static windows with low, medium, and high solar heat gain coefficients. Glazing systems material properties are chosen from LBNL experimentally validated international glazing system data base, (IGDB). EnergyPlus software is used to simulate and predict heating and cooling loads of the house with natural gas furnace and electric coils as the building HVAC system. Considering windows orientation, two operation strategies are developed to enhance performance of the switchable window inter-pane coatings and adjust desired solar heat gain and thermal resistance in winter and summer. Medium and high window to wall ratio effects on glazing systems performance are investigated and the result shows that proposed system significantly reduce building heating and cooling energy consumption. Considering window to wall ratio of 90%, compared to conventional clear single and double pane windows, energy analysis shows that switchable glazing system decreases HVAC annual energy bill by 47% and 33%, respectively.

Quantifying the nationwide HVAC energy savings in large hotels: the role of occupant-centric controls

This paper presents a nationwide simulation study to investigate the HVAC energy savings potential of occupancy sensors and occupant-centric controls (OCCs) in large hotel buildings. Three simulation scenarios were defined to reflect the different levels of occupancy sensing capabilities. Multiple zone-level and system-level occupant-centric HVAC control strategies were extracted from the updated ASHRAE Standard 90.1 – 2016 and 90.1 – 2019 to facilitate the control purpose. 19 climate zones defined in the International Energy Conservation Code and two versions of ASHRAE Standard 90.1 were considered to include the diversities of climates and building vintage. The simulation results showed that the HVAC energy savings ratios varied from 24% to 58% depending on the sensor type, local climate zone, and version of building energy code. It was also found that the occupant counting sensor could achieve an additional 5%–15% HVAC energy savings for the whole building compared with the presence sensors.

Air preheating potential with high Opaque Ventilated Façade under natural and forced convection

Opaque ventilated façades (OVF) are increasingly used in building envelope because of their positive impact on building energy efficiency. Usually, air flow is driven by natural ventilation. Recently, there were some attempts to drive air flow mechanically to preheat or precool air in combination with HVAC, Heat pump or Latent Heat Thermal Energy Storage (LHTES) systems. In this framework, an experimental real-scale module of an OVF was built (1.9 m width and 3.5 m height). In this study, OVF is tested during autumn under natural and under forced convection by means of ventilator placed at cavity outlet. Inlet air flowrate are changed from day to day or during the day. For each test, temperature, air velocity, air flow rate and thermal flux are monitored at different locations of OVF. Their analysis shows that collector efficiency and amount of collected energy depend mainly on cavity air flow rate. The measurements are compared to simulation results obtained from two thermal models describing OVF: Trnsys Type 1230 and home-developed pseudo 2D. A good agreement is found for air temperature at cavity outlet while differences are observed in opaque layers due to modelling assumptions. Last, sensitivity analysis on two design parameters is carried out.

Evaluating heating, ventilation, and air-conditioning systems toward minimizing the airborne transmission risk of Mucormycosis and COVID-19 infections in built environment

This ongoing global pandemic of the COVID-19 has generated a significant international concern for our respiratory health. For instance, the breakout of the COVID-19 pandemic was directly linked to the spread of infectious particles in indoor environments between humans, underlining the significance of rigorous and effective actions to limit the transmission of diseases. Recently, Mucormycosis infections in COVID-19 patients have been identified. This investigation aims to investigate potential infection control HVAC solutions for indoor environments, as well as their core mechanisms for reducing infectious disease risk through simulation models of a valid building in a hot climatic region. Considering recent international recommendations, the investigation relies on a methodology of testing a validated building energy model to several systems in the light of infectious diseases prevention. All proposed models are exposed to cost analysis in line with carbon emissions, and indoor thermal conditions. The analysis outlined through parametric simulations, the effectiveness of the proposed DOAS in supplying 100% fresh ventilation air and enhancing the control of the indoor relative humidity simultaneously. Finally, through an enviro-economic assessment, the study concluded that the DOAS model reduced the CO2 emissions to 691 tons, with a potential of reducing HVAC and whole-building energy use by 37% and 16%, respectively in the hot arid climate, with a return on investment of about 6%.

Energy performance and indoor airflow analysis of a healthcare ward designed with resource conservation objectives

With the outbreak of COVID-19, the urgency of wide-scale healthcare infrastructure development has been felt globally for human survival. To accommodate a large infected population, copious wards are to be built within the prevalent constraints of land, power and material availability. This study designs a two-bed modular healthcare ward which is shrunk in size to minimize the requirement of space and other construction commodities such as materials, labour and power. Additionally, HVAC energy usage is accounted for conservation. The health safety and thermal comfort of occupants are regulated by monitoring indoor environment attributes while pushing towards a resource-efficient structure. Two popular envelope thermal retrofits viz. phase change material and thermal insulation are tested to conceive gains in terms of improved energy performance of the ward. Various ward designs contest with their energy performance and occupant's health safety and comfort characteristics in a multicriteria decision making process for delivering the most favourable solution. Subsequently, the most suitable solution is offered by a design involving thermal insulation retrofit with 8 ACH fresh air supply rate and 26°C inlet air temperature. The proposed design can support developing nations to contrive quick response to pandemic outbreaks with reduced construction (cost, time) and energy loads.

HVAC Energy Saving Strategies for Public Buildings Based on Heat Pumps and Demand Controlled Ventilation

The paper analyzes and compares the perspectives for reducing the energy consumption associated to the operation of Heating Ventilation and Air Conditioning system for climatic control of large-size non-residential buildings. Three different control strategies are considered comparing the use of boiler and heat pumps as heating systems and analyzing the use of demand-controlled ventilation, operating on the effective occupancy of the building. The control strategies are applied to two different educational buildings with shapes representative of typical educational structures. The results of the analysis show how the energy consumption can be reduced up to 70%, shifting from the actual values of the energy intensity of over 300 kWh/m2 for year to values of less than 100 kWh/m2 per year. The significance of the energy savings achieved in such different buildings has led to the identification of a possible benchmark for HVAC systems in the next future years which could help reach the environmental targets in this sector.

Usefulness of loading PCM into envelopes in arid climate based on Köppen–Geiger classification - Annual assessment of energy saving and GHG emission reduction

A share of 22% for residential buildings along with 18% for commercial ones has caused the share of buildings in energy consumption to reach 40% in 2020. Focusing on energy demand reduction, this numerical study examined the effectiveness of installing PCM into building envelopes in arid climate zones based on the Köppen–Geiger classification. For this purpose, four climate zones of Dubai, Jeddah, Kuwait City and Lahore City were selected and then a 20 mm PCM layer (SP-21EK) was incorporated into envelopes to examine the effects of PCM on HVAC energy usage defining two scenarios. In the first scenario, for Dubai, Jeddah, Kuwait City and Lahore City the incorporation of PCM into the envelopes reduced the annual HVAC power usage by 55.47, 53.89, 58.86 and 53.57%, respectively. In the second scenario, HVAC power usage reduced by 2.6, 2.03, 1.99 and 5.6%. Under the best conditions and owing to using SP-21EK, CO2 emission reduced by 56.27, 44.81, 45.27 and 58.5%. Due to the PCM phase change inside the envelopes, energy consumption is reduced if PCM is selected correctly. As a preliminary choice, the apparent PCM melting temperature for Lahore City is 21–23 °C, while for Dubai this figure is 23–25 °C and PCM with melting temperature within 25–27 °C can be a good choice for Jeddah and Kuwait City.

Application of vision-based occupancy counting method using deep learning and performance analysis

Recently, several researchers have attempted to detect occupancy information and use it to reduce building energy. Although occupancy counting using a camera and deep learning is a very effective method that has recently emerged, there are few cases in which the experimental performance and utilization have been comprehensively evaluated. The purpose of this study is to comprehensively evaluate the applicability of vision-based occupancy counting using the latest deep learning model. First, this study experimentally evaluated the performance of the vision-based occupancy-counting method in two offices and investigated the user's acceptance of this method using a questionnaire. Second, the energy-saving performance of various occupancy-centric control strategies applied to HVAC and lighting was analyzed. Experimental results showed high performance for a small office of fewer than five people (NRMSE: 0.0435) and lower performance in a larger office (NRMSE: 0.0918). In addition, despite several occupants feeling privacy invasion by the camera, they responded that the system could be accommodated to reduce building energy. Simulation results indicated that occupancy-centric control using the number of occupants could reduce annual HVAC and lighting energy in small offices by 10.2%. In addition, among several occupancy-centric control strategies, modulating the outdoor airflow rate was found to be the most effective in saving energy.

Potential Analysis of the Attention-Based LSTM Model in Ultra-Short-Term Forecasting of Building HVAC Energy Consumption

Predicting system energy consumption accurately and adjusting dynamic operating parameters of the HVAC system in advance is the basis of realizing the model predictive control (MPC). In recent years, the LSTM network had made remarkable achievements in the field of load forecasting. This paper aimed to evaluate the potential of using an attentional-based LSTM network (A-LSTM) to predict HVAC energy consumption in practical applications. To evaluate the application potential of the A-LSTM model in real cases, the training set and test set used in experiments are the real energy consumption data collected by Kitakyushu Science Research Park in Japan. Pearce analysis was first carried out on the source data set and built the target database. Then five baseline models (A-LSTM, LSTM, RNN, DNN, and SVR) were built. Besides, to optimize the super parameters of the model, the Tree-structured of Parzen Estimators (TPE) algorithm was introduced. Finally, the applications are performed on the target database, and the results are analyzed from multiple perspectives, including model comparisons on different sizes of the training set, model comparisons on different system operation modes, graphical examination, etc. The results showed that the performance of the A-LSTM model was better than other baseline models, it could provide accurate and reliable hourly forecasting for HVAC energy consumption.

Discussion on HVAC Energy Saving Technology and HVAC Engineering Management

Discussion on HVAC Energy Saving Technology and HVAC Engineering Management

A user-interactive system for smart thermal environment control in office buildings

In this paper, our goal is to develop user-interactive thermal environment control systems that aim to increase energy efficiency and occupant satisfaction in office buildings. Towards this goal, we present a new modeling approach of occupant interactions with a temperature control and energy use interface based on utility theory that reveals causal effects in the human decision-making process. The model is a utility function that quantifies occupants’ preference over temperature setpoints incorporating their comfort and energy use considerations. We demonstrate our approach by implementing the user-interactive system in actual office spaces with an energy efficient model predictive HVAC controller. The results show that with the developed interactive system occupants achieved the same level of overall satisfaction with selected setpoints that are closer to temperatures determined by the model-predictive control (MPC) strategy to reduce energy use. Also, occupants often accept the default MPC setpoints when a significant improvement in the thermal environment conditions is not needed to satisfy their preference. Our results show that the HVAC energy consumption with MPC can be underestimated by up to 55% without considering occupants’ overrides. The prototype user-interactive system recovered 36% of this additional energy consumption while achieving the same overall occupant satisfaction level. Based on these findings, we propose that the utility model can become a generalized approach to evaluate the design of similar user-interactive systems for different office layouts and building operation scenarios.

Analysis of HVAC Energy Saving Technology in Construction Engineering

Analysis of HVAC Energy Saving Technology in Construction Engineering

Community-scale interaction of energy efficiency and demand flexibility in residential buildings

Demand-side management (DSM) strategies, including energy efficiency (EE) and demand flexibility (DF), contribute to cost-effective operation of the electricity grid. From a system-level perspective, such programs reduce costs, enhance reliability, and reduce network issues. Similarly, DSM programs help participating customers reduce utility bills while maintaining occupant comfort. Understanding the relationship between EE and DF is key to realizing the full potential of DSM programs. In this study, we modeled an all-electric residential community based on a 498-home community that is planned for construction in Fort Collins, Colorado in the United States. We used this community model to study the relationship between different EE measures, including building envelope upgrades and smart appliances, and DF enabled by a home energy management system (HEMS) responding to a time-varying tariff. Various EE levels in the homes – code-minimum, zero energy ready, and even higher levels of envelope efficiency – were simulated. DF is enabled by the HEMS, which coordinates behind-the-meter resources, including flexible building loads, PV, and home battery systems, to minimize utility bills while maintaining occupant comfort. When comparing to the code-minimum homes, EE upgrades alone reduce HVAC energy use during peak hours by up to 50% and the HVAC utility bill by up to $312/year. With the addition of HEMS, the average daily peak demand can be reduced by up to 0.58 MW or 1.2 kW/home in the higher envelope efficiency homes. The combination of EE upgrades, HEMS, and home battery systems is expected to save homeowners up to $590/year while increasing community load flexibility. However, HEMS and home battery systems are less effective in increasing the DF in the more efficient homes due to the lower load.

Research on Electric Control Device of Hybrid Energy in Household Air Conditioning

Hvac energy consumption is the construction of large energy consumption, in order to realize building energy conservation to reduce the energy consumption of hvac operation, through the research by a thin film solar battery, connecting wires, charge and discharge controller, the electric control board outdoor, indoor machine electric control box, electronic circuit control board, switch and battery of household air conditioning hybrid energy electrical control devices, When it is sunny, the direct current generated by the solar cell group is directly supplied to the indoor unit. When it is cloudy, it is switched to the power supply to the indoor unit, forming a hybrid power supply mode for complementary use, which can effectively reduce the electric energy consumed by the operation of HVAC and realize energy saving in the operation of HVAC.

Use of Artificial Intelligence in Optimizing HVAC Energy Consumption

Use of Artificial Intelligence in Optimizing HVAC Energy Consumption

Generation of Typical Meteorological Year Data for a City in South-Western Nigeria

Weather data is essential in determination of the performance of energy systems such as HVAC and solar energy systems. Weather data therefore, can be employed in designing more energy-efficient systems. This work focuses on the generation of a Typical Meteorological Year (TMY) Data for Abeokuta (7°7′1″ N, 3°22′13″E), a state in South-Western Nigeria by the use of a modified Sandia method. It makes use of seven weather parameters obtained over 29 years (1984 - 2012) in the construction of the TMY. Sandia method is highly affected by solar radiation even if its weight is reduced by half. The weights of other parameters such as temperature, wind, and relative humidity have less impact on the selection of TMY. The results of this study show that the weather pattern of Abeokuta follows the general diurnal variation of dry/harmattan season and wet/rainy season, typical to Nigeria. In this work also, the effect of general rise in temperature and solar radiation, indicative of global warming, is highlighted. Higher solar radiation values are majorly typical of a low cloud cover, and high clearness index. Suggestions were also made as to the preferable type of sustainable energy system to make use of in this location, as well as in the development of energy systems and data collection in Nigeria. The relevance of this work is that it would help to strengthen building energy standards, understand the local climate of Abeokuta and hence facilitate building energy system performance.

Evaluating potential benefits of air barriers in commercial buildings using NIST infiltration correlations in EnergyPlus

According to the U. S. Department of Energy (DOE), infiltration accounts for 6% of the energy use and $11 billion in energy cost for U. S. commercial buildings. One strategy to reduce infiltration in commercial buildings is to provide more supply airflow than return and exhaust in order to “pressurize the building”. DOE has developed EnergyPlus models of several prototype buildings which assume that pressurization results in system-on infiltration rates that are 75% less than the system-off rates. However, airflow simulations of these buildings using the CONTAM multizone airflow software showed that pressurization reduced infiltration by an average of 44% only. To improve the infiltration rates calculated by the EnergyPlus models of prototype buildings, CONTAM infiltration rates were used to develop coefficients that can be input into EnergyPlus. CONTAM captures the effects of wind, temperature difference, and system operation on infiltration rates. Coefficients were developed for 11 prototype buildings, eight cities, and two levels of building envelope airtightness. Comparisons of the predicted infiltration rates were made between using the DOE prototype model inputs and the NIST infiltration correlations. Using the NIST correlations resulted in an average HVAC-EUI (HVAC-related energy use intensity) savings of 6% or 1.4 kBtu/ft2 due to airtightening. These results indicate that the effects of infiltration on HVAC energy use are important and that infiltration can and should be better accounted for in whole-building energy modeling.

In-situ application of an ANN algorithm for optimized chilled and condenser water temperatures set-point during cooling operation

In this study, an artificial neural network (ANN) based real-time predictive control and optimization algorithm for a chiller based cooling system was developed and applied to an actual building to analyze its cooling energy saving effects through in-situ application and actual measurements. For this purpose, we set the cooling tower's condenser water outlet temperature and the chiller's chilled water outlet temperature as the system control variables. To evaluate the algorithm performance, we compared and analyzed the electric consumption and the COP when the chilled and condenser water temperatures were controlled conventionally and controlled based on the ANN. As a result, the ANN model's accuracy was high, with a Cv(RMSE) of 4.9%. In addition, the ANN based control algorithm's energy analysis showed that the average energy saving rate for the chiller was 24.7% and that the total average energy saving effect for the chiller and cooling towers was 7.4%. The results confirmed that the proposed MPC algorithm could contribute to improved HVAC energy efficiency in commercial buildings.

HVAC Best Practices in Arctic Climates

Arctic climates provide unique challenges for designers of HVAC, plumbing, and thermal energy systems. The importance of considering the operation outside air temperatures, system reliability, and building resiliency cannot be understated. The paper describes best practice examples of robust and reliable systems with the emphasis on their redundancy, durability, and functionality. The paper also discusses the most common heating and ventilation system approaches used in arctic climate with the emphasis on the importance of a maintenance program that allows building operators to successfully troubleshoot and maintain buildings in the arctic. More detailed discussion of concepts presented in this paper can be found in the Guide [1] where these concepts are illustrated by best practice examples from U.S. military bases in Alaska and Søndre Strømfjord, the international airport of Greenland that previously was used as a U.S. military base. The paper results from experts’ discussions during the Consultation Forum “Thermal Energy Systems Resilience in Cold/Arctic Climates” [2] and research conducted under the IEA EBC Annex 73, the Environmental Security Technology Certification Program (ESTCP) Project “Technologies Integration to Achieve Resilient, Low-Energy Military Installations” and U.S. Army Program project 633734T1500 under Military Engineering Technology Demonstration. The paper is complementary to the ASHRAE Cold Climate Design Guide [3] with a focus on resilience of thermal energy systems.

Flexible Control Strategy for Intelligent Building Air Conditioning System

An improved optimization adjustment strategy for building heating ventilation and air conditioning (Heating Ventilation and Air Conditioning, HVAC) is proposed. The energy consumption model of building heating/refrigeration is established by using the instantaneous energy balance of heat, and then the optimal operation strategy of building HVAC energy based on weather forecast data is constructed in the range of user temperature comfort. Finally, the MATLAB and TRNSYS simulation techniques are used to verify the example. Simulation results show that the optimal operation strategy of building HVAC energy based on weather forecast data can not only significantly reduce the cost of energy use, but also effectively improve the absorption capacity of renewable energy on the building side.