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Heating Degree Days at 65°F (HDD65) is still utilized by ASHRAE Standard 169 for determining Climate Zones and in other fundamental HVAC resources, such as Air Conditioning Contractors of America's (ACCA's) Manual J and S calculations. The U.S. Energy Information Administration (EIA) also uses HDD65 and it even occurs within the Passive House Institute US (PHIUS) where heating is not in demand until Outdoor Air Temperatures (OAT) reach 45°F. This paper explores and supports utilization of Heating Degree Days at 55°F (HDD55) for building energy analysis in heating dominant climates. This is supported by EnergyPlus modeling results for a sample of building types. A degree days overview on Energycap states that "The 65-degree balance point standard was developed 75 years ago to help the gas industry predict heating loads in residences. Studies back then showed that when the average daily temperature fell below 65°F, residences began turning on the heat." Today, HDD65 doesn't reflect structures built to modern energy codes, because internal loads are offsetting thermal envelope losses and when combined with the continued tightening of ventilation energy recovery requirements, heating is not necessary until much cooler than 65°F. According to a Regional Technical Forum (RTF) presentation titled "Overview of Updated Commercial EnergyPlus Building Models and Alignment with CBSA Data" dated August 31, 2021, the 'apparent balance point range between 50-60°F' was the reasonable OAT before heating was utilized by occupants. When energy modeling to HDD65, decisions are being made relative to temperature ranges that have minimal impact on building energy use. For example, when the OAT is in the 50-65°F range, this may mean more economizer hours are available without having to reheat the outdoor air or heat exterior spaces/operating zones. This would decrease the amount of energy the building utilizes, allowing for more accurately sized equipment. Similarly, utilizing Cooling Degree Day's at 50°F (CDD50), as ASHRAE Standard 169 does to determine Climate Zones, to predict cooling loads isn't appropriate as most building types don't need cooling starting at 50°F. Economizers are essentially mandatory for larger buildings which might need cooling at 50oF OAT, but smaller buildings will possibly be in heating mode when the OAT is 50oF. Utilizing CDD in the range of 60-70°F would give a more accurate representation of required cooling loads and will also be a minor focus of this technical paper. New HDD and CDD figures should be produced for ASHRAE Standard 169, Technical Resource Manuals (TRM's), and other publications that utilize degree days. With this information, end users can better analyze the weather's impact on actual building energy usage and better determine equipment sizing and other impacts. [ABSTRACT FROM AUTHOR]

This paper, concerned with the low and ultra-low-temperature district heating goals of several countries for decarbonization, reveals the temperature mismatch between existing heating and cooling equipment and the thermal supply. The industry and the energy sector aim to resolve this conflict by total electrification with renewables and heat pumps for temperature peaking and, or equipment oversizing. This study shows that both measures defeat the purposes of decarbonization and quantify the carbon dioxide responsibility in embodiments and during operation according to exergy destructions. It has been concluded that widely available but with low exergy waste and solar energy resources can be mobilized for decarbonization in the building sector only with temperature-compatible heating and cooling terminal units minimizing the temperature mismatches. In this respect, a new panel radiator with heat pipe technology, which can satisfy indoor thermal loads with supply temperatures as low as 35oC (95oF) and sensible cooling loads as high as 19oC (292 K, 66.4oF) with little oversizing, is introduced. Test results from the ASHRAE Standard 138 are discussed. [ABSTRACT FROM AUTHOR]

This paper analyzes the performance uncertainty of heat pump(s) of three different design cases that employ the different number (one unit, two units, three units) and sizing of heat pumps in an office building. Because the thermal behavior of a building is highly stochastic due to uncertain factors such as infiltration/ventilation, heat generation from people, lights and equipment, indoor setpoint temperature, the authors assumed three use scenarios (low/medium/high). Then, the authors used EnergyPlus simulation runs developed by US DOE and evaluated the performance uncertainty in terms of heat removal, energy consumption, PLR, and COP. It was found that the PLR and COP of the heat pump(s) are more influenced by the design cases than the use scenarios. In addition, the ranking of the design cases also varies under different cooling loads. This study suggests that for rational design making of heat pumps for a building, stochastic analysis of the system performance is necessary. [ABSTRACT FROM AUTHOR]

Due to air conditioner (AC)/heat pump unit fault, cooling capacity degradation usually exists in residential buildings. This sometimes makes the heating, ventilation, and air-conditioning (HVAC) system struggle in maintaining thermal comfort when the cooling load is getting higher, especially in extreme weather events (e.g., heat waves). A potential solution to tackle these issues is to pre-cool the house to deal with the limitation of house thermal mass or the HVAC capacity. Adaptive model-predictive control (AMPC) is a promising control strategy that can help mitigate those over-heating risks. It predicts the future system state and makes appropriate actions through optimizations ahead of time, and thus effectively responds to disturbance variations (e.g., weather). Optimization is essential to AMPC, but matrix multiplication and inversion cannot be executed online in most existing building controllers. Therefore, AMPC informed rule extraction is proposed to extract simple operation rules from the results of a large-scale AMPC offline implementation. Then, those computationally efficient simple rules will be online executed in the residential HVAC controller. The goal of rule extraction is to select the minimum sets of inputs and feed them to the rule-based controls (RBC) and maintain the same or close levels of energy consumption and thermal comfort with the AMP simultaneously. The AMPC-informed RBC avoids the online execution of computationally expensive optimization, thus alleviating computation load in building HVAC controllers. It is anticipated that if rules are extracted with large sets of data covering different operation scenarios and climate zone, these heuristic rules can be used by practitioners and homeowners, even without a learning model-based adaptive control framework. This paper implements an AMPC in a virtual testbed of a DOE prototype EnergyPlus residential building model. Classification and Regression Tree (CART) are adopted as the rule extraction algorithm to extract operation rules from the AMPC results. The test case is for RBC with an AC unit cooling capacity degradation under an extreme weather event of heatwaves. A preliminary comparison of the performance of ad-hoc RBC, AMPC, and AMPC-informed RBC strategies will be presented. [ABSTRACT FROM AUTHOR]

In 2016, Kujak presented a current state of how to apply hydrocarbon safely per standards consideration and methodologies for direct expansion air conditioning applications. Refrigerant charge limits at the time were very restrictive and did not allow for larger capacity direct refrigerant expansion systems. In recent years, the HVACR industry has been actively investigating the safety of flammable refrigerants by determining their risks, potential occurrences and severity of events and hydrocarbon refrigerant charges have increased significantly. This paper will provide an updated view of the selection challenges faced by air conditioning product designers and compare the various flammability characteristics of R290 compared to R454B. It will give an updated overview of standards methodology to determine the refrigerant charge and resulting cooling load to compare various flammable refrigerants for ASHRAE 34 Standard Class 2L, 2 and 3 refrigerants. In addition, the authors investigated the optimization of blends using R290, R1270 and RE170 to understand if there are possible optimization of properties and flammability limits to increase refrigerant charges. [ABSTRACT FROM AUTHOR]

Zone minimum airflow set point in a single-duct VAV terminal unit with reheat has a great impact on zone reheat requirement and ventilation efficiency. Lowering the set point reduces the zone reheat requirements but drops the ventilation efficiency and thereby increases the ventilation load. When the economizer is enabled, a large amount of fresh air is introduced into the system, and then the set point can be lowered to reduce reheat requirements without any effect on ventilation load. Thus, this paper introduces a control strategy to reset the minimum airflow set point during partial or full free cooling mode and measure its performance under various conditions through simulations and experiments done in fully instrumented VAV systems located in the HVAC lab at the University of Cincinnati. The experiments were conducted on chilled-water VAV system that serves three controlled zones with hot-water reheat VAV boxes controlled by a typical commercial BACnet web-based building automation system BAS. The simulation studies were conducted using the building energy simulation software EnergyPlus to evaluate the strategy in different locations. The results show that, depending on locations, the minimum airflow rate resetting strategy can reduce the reheat requirement by 12 -32%, fan energy use by 1.5 -6%, and the cooling load by 0.5% to 1%. [ABSTRACT FROM AUTHOR]

As more buildings are connected to cloud-based large data systems, there is an opportunity to learn from the data. Predictive load and energy modeling calculations, which have long been performed based on assumptions, can be validated, or adjusted based on accrued data from in-service buildings. This paper publishes zone sensible cooling loads, based on historical data. The results should serve as a guideline to cooling load and energy modeling calculations in future designs. The data assessed includes room temperature, supply temperature, and airflow, collected on 5-minute intervals for one year of operation. Data assessed is limited to the cooling hours between 8 AM to 6 PM, May through October. Sensible load was calculated for each hour using the difference in temperature, multiplied by the airflow. Zones are classified into Zone Type, based on the room name where the thermostat resides. Loads are normalized to zone area. The results include (1) cooling loads for the 75%, 50%, 25%, 2%, and 0.4% exceedance values, and (2) diversity factors indicating the maximum simultaneously occurring load in multiple zones of the same type. [ABSTRACT FROM AUTHOR]

District Cooling is an energy-efficient technology that can satisfy the cooling demands of regions with extremely hot climates such as the middle east. Designing and operating these plants requires accurate modeling of the existing cooling load created by the building stock connected to the central plant. During the design stage, building archetype models can be used for sizing district cooling load, whereas both the input and output uncertainties of these models have not been well addressed. This paper conducts a comparative analysis of two methodologies of building archetype development, develops an importance ranking for the input parameters of these models, and tries to quantify the uncertainty of the cooling energy output due to input value uncertainty. It develops a region-specific highrise residential archetype and compares it to the US DOE Prototype models. It also develops the parameter ranking using a global sensitivity analysis methodology. It is found that the most practical approach towards the development of building archetypes for a specific region is the development of region-specific models adapted to local practices rather than converting standard models for accuracy and computational cost considerations. It was also concluded that a set number of parameters are responsible for most of the model's output variability. Finally, this study demonstrated the usability of the building archetype models for the hot and arid climate. [ABSTRACT FROM AUTHOR]

The requisite amount of ventilation air of the HVAC system depends on heating/cooling load. The load on HVAC system varies with the condition of outdoor ventilation air that may requires additional heating, cooling and humidification or dehumidification. In most of the cases, outdoor air is more economical to use than recycled return air. The heat transfer in an exterior rectangular duct is a function of solar irradiation, air gap width, mass flow rate and pressure, wall and air temperatures. The significance of analysis of an outdoor HVAC rectangular duct is important, for example, in modeling photovoltaic solar wall structures. The complete duct design is based on complete information for the given design conditions and limitations of operation results. The design of an outdoor duct is either based on a velocity method, an equal friction method or a static pressure recovery method. The design of mass flow rate through the duct is based on heating/cooling load on the ventilation system. The aim of the paper is to present an improved method for design, ventilation and noise assessment of an outdoor duct for pre-heating of fresh air through an example of an outdoor duct [2.5 mm aluminum rectangular duct with a size of (0.25 m (H) X 1.0 m (W) X 3.0 m (L))]. The given outdoor duct is exposed to a steady solar heat flux and is installed on a well insulated building façade. The sensitivity analysis for an outdoor duct is conducted for critical design of ventilation requirements and materials with supply of varying outdoor mass flow rate to a single building zone. The improved method is useful for accurately predicting ventilation air requirements through an outdoor duct. Noise, defined as 'a sensation of unwanted intensity of a wave', is perception of a pollutant and a type of environmental stressor. An environmental stressor such as noise may have detrimental effects on various aspects of health. The unwanted intensity of a wave is a propagation of noise due to transmission of waves (viz. physical agents) such as sun, light, sound, heat, electricity, fluid and fire. The noise scales/charts are calculated from the newly devised noise measurement equations and their units by the author. Furthermore, based on these newly devised noise measurement equations, noise assessment calculations of an outdoor HVAC duct exposed to solar radiation are also presented. [ABSTRACT FROM AUTHOR]

Although EnergyPlus is widely used by researchers and engineers for whole building energy simulations, it is not capable of modeling variable airflow fanpowered terminal units (FPTUs) using build-in modules. Energy Management System (EMS) and user-defined modules in EnergyPlus provide flexibility in modeling customized equipment and systems. In this paper, the performance model of variable airflow series FPTUs was implemented using EMS and user-defined modules. The performance model was also integrated with the rest of HVAC system to investigate the impact of terminal unit fan operation on system energy consumption. A single story, five-zone office building model was created in EnergyPlus as the testbed. Simulations were performed with four different climates and two terminal unit fan operation modes. Compared with the constant airflow series FPTUs, simulation results revealed that the variable airflow series FPTUs can save up to 85% of terminal unit fan energy consumption. It is also shown that the variable airflow series FPTUs can save central supply fan and cooling coil energy consumption by 4% and 6%, respectively, due to decreases in motor heat gains from terminal unit fans and primary air reduction at a given zone cooling load. Although the heating energy is increased due to the reduced heat gain from terminal unit fan motors, the use of variable airflow series FPTUs can lead to 15-35% savings in the annual energy consumption of HVAC system. [ABSTRACT FROM AUTHOR]

Grid-interactive efficient buildings (GEBs) require quick and accurate manipulation of flexible electrical loads. Heating, ventilating, and air conditioning (HVAC) loads are particularly well suited for demand flexibility control by utilizing thermal mass in building structures. The HVAC load and its responding zone temperature (ZT) can be optimized by model predictive control (MPC) to minimize the operation cost with the indoor comfort constraint. However, due to the lack of reliable and affordable energy meters, the current HVAC demand control is implemented using ZT feedback control with the responding ZT optimized by MPC as the setpoint and the HVAC load as the response. Unfortunately, the building thermal mass makes the actual HVAC load significantly different than the optimized HVAC load, which is the on-demand setpoint, with potential demand penalty. Low-cost virtual flow meter technology makes the cooling load measurement at air handling units (AHUs) available, thus energy feedback control can be applied to actively control the cooling load of AHUs at its on-demand setpoint. The objective of the paper is to preliminarily investigate the demand flexibility control performance of the energy feedback control at AHUs. First, the energy feedback control at AHUs is introduced. Then, the performance of a single zone AHU is simulated and compared between the ZT feedback control and energy feedback control. Finally, a field experiment is conducted on a 7-ton single duct variable air volume AHU with these two different controls. Experimental results show that the cooling load with the current ZT feedback control drops to the on-demand setpoint after 25 minutes. On the other hand, the energy feedback control can reduce the cooling load to the on-demand setpoint in less than 3 minutes. Therefore, the active energy feedback control can significantly advance the current ZT feedback control by quickly and accurately controlling the cooling load at AHUs to avoid the demand penalty. [ABSTRACT FROM AUTHOR]

Single-duct variable-air-volume (VAV) systems are widely used to condition buildings in the United States. When such a system serves multiple zones with different load profiles, simultaneous cooling and heating frequently occur. To avoid this inefficient scenario, dual VAV systems, where one VAV system provides cooling and the other provides heating, could be used. This paper proposes a new configuration for dual VAV systems to improve their operation to reduce the loads on cooling and heating equipment and thereby total energy use. The proposed configuration and its sequence of operation can reduce cooling and heating loads by eliminating simultaneous heating and cooling and maximizing the use of outdoor air (OA) for cooling and return air for heating. The performances of both single and dual VAV systems are simulated for given buildings and for different locations to estimate load reductions and fan energy savings achieved by the proposed dual VAV system configuration and control strategies. The simulation results that show significant heating load reductions of up to 89%, great fan savings up to 15%, and minor cooling load reductions of around 1% can be obtained, depending mainly on load variations and locations. [ABSTRACT FROM AUTHOR]

Buildings account for approximately 40% of the nation's total energy demand1. About 39% of total primary building energy consumption can be attributed to losses through building envelope. Therefore, building envelope load reduction plays a key role to minimize building heating and cooling load, and building electricity consumption. Phase change material (PCM)-based thermal energy storages have re-gained increased attention in recent years, in particular, for a peak load shifting of grid-interactive efficient buildings (GEBs). To simulate PCMs and facilitate the performance studies of PCM-based system using the whole building simulation program, EnergyPlus, two PCM modules have been added to EnergyPlus: the single curve model and the dual curve hysteresis model. Different from the single curve model, the dual curve model allows the melting/freezing process to follow different curves. The proposed dual curve model is useful to represent the hysteresis effect better compared with the existing EnergyPlus model. Our study found that the current hysteresis model in EnergyPlus has problems modeling the partial transition process. A static two-phase model is used to replace the current hysteresis model, and this is implemented by modifying EnergyPlus source code. Validation simulations has confirmed that our new model could successfully model the partial transition process. [ABSTRACT FROM AUTHOR]

People spend about 87 - 92% of their overall time of day in some form of indoor environment. It is also well established that buildings consume about 40% of the total electricity generated. Studies have shown that operating windows during HVAC use can increase the heating and cooling load. Until now, fixed window opening and closing schedules have been used in Building Energy Simulation engines (BES) like Energy Plus. We studied the window opening behavior of students living in a residential dorm at Syracuse University for over a year. The window opening behavior changed depending on the location of the window and the time of the year. During summer, the bedroom windows were opened substantially for a longer time and living room windows were opened briefly. During transition seasons, all windows were opened very briefly. We created a specific set of neural network models that could predict the state of the window and the duration of the window opening. We modeled the open/close state change for all three windows in three different zones using Artificial Neural Network (ANN) machine learning architecture. The three model, when trained on individual datasets generated a True Positive Rate (TPR) of 0.97, 0.99, and 0.97. The newly released Python API incorporated the models into Energy Plus. The sensible heating/cooling energy for the living room, north-facing bedroom, and south-facing bedroom were calculated based on the window schedule predicted by the ANN model. Compared to the baseline model of complete mechanical ventilation, the heating energy was reduced by 3.96% and 24.78% for north and south-facing bedrooms, respectively, for October. [ABSTRACT FROM AUTHOR]

As renewable energy resources, such as wind and solar, continue to be added to the US electric grid, the available energy produced will become more variable. Wind and solar energy resources are highly dependent on wind and solar radiation availability, which are highly varied compared to traditional electricity generation sources. With an increase in variable generation, it is beneficial for grid reliability to modulate grid loads to match available generation. This can be accomplished through building load participation in flexibility services (FS). The various primary end-uses such as heating, ventilation, and air conditioning (HVAC) and lighting in commercial buildings can provide Demand Response (DR) services such as regulation, contingency, and ramping. Overall, in the US, HVAC loads, specifically cooling in commercial buildings, account for around 15% of electricity consumption. However, these loads further vary based on the climate zone in which the building is located. To provide load flexibility, HVAC loads can be switched off for a limited time be such that the thermal comfort criterion of predicted mean vote (PMV) remains under 0.5. Overall, this study aims to estimate the amount and duration for HVAC cooling loads that can provide demand flexibility using US Department of Energy (DOE) commercial Reference and Prototype building models for small office buildings. [ABSTRACT FROM AUTHOR]

Building cooling load consumption is heavily influenced by two factors, i.e., spatial correlations such as outside air conditions and temporal relations, which factors the occupancy influence into account. Moreover, the anomalies in cooling consumption patterns are mainly caused by the abnormal behavior of the time-dependency of such temporal networks. A novel framework for building cooling load prediction is proposed to explore these dependencies separately using regression and recurrent neural networks for spatial and temporal relations, respectively, and then combine their outputs using an ensemble approach. The proposed forecasting model provides a 3-4% higher R2 value and 2-3% better CVRMSE accuracy when compared with the traditional machine learning model. [ABSTRACT FROM AUTHOR]