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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.
Enhancing Performance Contracts with Monitoring-Based Commissioning (MBCx)
Integrating monitoring-based commissioning (MBCx) software tools into performance contracts is a timely topic given recent developments in MBCx software offerings and the growing number of MBCx deployments nationwide. Many commercial building owners have started to install MBCx software tools that tie in advanced metering infrastructure, building automation systems, and local weather data to enable ongoing commissioning and identify energy conservation measures. To support federal and commercial building owners in understanding, procuring, and implementing MBCx software tools, this report provides an overview of their capabilities, the MBCx process, and how MBCx can be integrated into - and benefit - each phase of a performance contract. This report is intended to spur increased use of MBCx in performance contracts, whether an agency has previously installed or is considering adding MBCx at the time of their project. Additionally, case studies illustrate successful experiences using MBCx within performance contracts at a university campus and across a large number of buildings managed by the General Services Administration.
Performance Assessment of High Efficiency Variable Speed Air-Source Heat Pump in Cold Climate Applications
This project was part of an effort by ComEd's emerging technology program to evaluate the energy saving potential of new energy efficiency technologies. The focus of this technology assessment was to determine energy and peak demand savings potentials of a high efficiency variable speed, air-source, split system heat pump designed for cold climate applications. The results of this technology assessment will be used by CLEAResult to develop a new energy efficiency measure for Commonwealth Edison Company's incentive programs. The project utilized the National Renewable Energy Laboratory's (NREL) Thermal Test Facility to experimentally characterize cooling and heating performance of a high efficiency heat pump split system under varying outdoor climate conditions. The selected climate conditions represented summer and low temperature winter conditions in ComEd's service territory. The laboratory experimentation results were used to develop equipment performance curves required by EnergyPlus hourly simulation engine. Using typical meteorological year 3 weather data for the Chicago O'Hare airport, hourly building simulations (using the EnergyPlus engine) was utilized to estimate the annual energy savings of the high efficiency heat pump in comparison to a standard efficiency unit in the following U.S. Department of Energy (DOE) building codes program energy prototypes: Single-family residence; Strip mall; and Low-rise office.
Workshop Summary: Bridging the Gap Between Atmospheric Science and Grid Integration
The need for dedicated, accurate, expertly curated weather data is increasingly important as the share of variable renewable energy increases on the power system. Projections for futures with very high (50+% annual energy) shares of variable generation require ongoing assessment of data requirements from industry stakeholders in their power system operation and planning contexts. In March 2024, NREL organized a workshop entitled "Bridging the Gap Between Atmospheric Science and Grid Integration Workshop", which brought atmospheric scientists and power system experts together to refine the requirements of atmospheric datasets for grid integration, and to describe a holistic approach to creating new and regularly updated national scale wind datasets for power system planning and operations. The results of this workshop are being used to inform the near-term development and a longer-term strategy for DOE to produce relevant wind resource datasets and inform wider use of wind/solar/load data sets in power system planning. This presentation provides an overview of a preworkshop survey, an assessment of current state of the art of national-scale datasets for wind resource assessment and grid integration, insights on appropriate uses of the WTK-LED, power system perspectives on data needs, as well as recommended next steps as discussed in the workshop and how these steps support longer-term strategies.
Highly Resolved Reference Projections of Building Energy Use for the Contiguous United States: Building Sector Energy Baselines, Projection Methods, and Results
This report describes one methodology of projecting energy consumption of the US residential and commercial building sectors using NREL's ResStock™ and ComStock™ as well as growth rates derived from EIA's Annual Energy Outlook (AEO). The impetus for this work is to provide an intermediate method for compiling demand-side sectoral energy projections that is suitable for grid-scale analysis, such as NREL's Standard Scenarios. ResStock and ComStock are physics-based and statistically representative building stock models of the US residential and commercial sector, respectively. Using the 2012 actual meteorological year (AMY) weather data, the sectoral energy baselines are simulated and then segmented along key dimensions (e.g., geography, dwelling/building type). The segmented results are then scaled using the corresponding annual growth rates derived from the 2021 AEO reference case to produce energy projections out to 2050. The compiled result is a demand-side grid model (dsgrid) data set suitable for use in NREL's large-scale grid models, such as the Regional Energy Deployment System (ReEDS). This simple projection method does not endogenously represent how the building stock could evolve through time. Most notably, it does not reflect large-scale electrification, for example, the conversion of space heating, water heating, clothes drying, and cooking from primary fossil fuels to electricity, as this is not part of AEO's reference case assumptions. Nonetheless this approach is more resolved and potentially extensible compared to the current method used by Standard Scenarios's reference case, which augments a sector's total load based on a single growth rate from AEO.
How Snow Drives the Seasonal Evolution of Land and Sea Surface Albedos in the Alaskan High Arctic: Final Technical Report
The purpose of the project was to observe and quantify temporal variation in snow albedo and snow characteristics across the Arctic coastal landscape as winter transitioned into spring and snowmelt occurred, both on tundra and sea ice. This transition is bounded by fully snow-covered landscapes with broadband albedos of approximately 0.8 and snow-free landscapes with albedos of 0.15 (tundra or ponded sea ice). For these landscapes, we monitored the spring surface characteristics and radiative properties nearly daily at three locations on or near the Department of Energy ARM North Slope of Alaska (NSA) User Facility in Utqiagvik, Alaska: the central NSA Facility (hereafter called ARM), one near NSA-E12 (BEO), and one on the sea ice of Elson Lagoon (ICE) during three melt seasons (2019, 2022, and 2024). The field campaign component of this award was named SALVO ( S now AL bedo E VO lution). Typical field seasons began in mid-April and lasted until mid-June. Main measurements included snow depth (at 1-m intervals), broadband albedo (at 5-m intervals), spectral albedo (at 5- m intervals), and multiple digital images. Orthomosaics were converted into binary images to determine the snow-covered fraction over time across various landscapes. Additional measurements included basic weather data and snow-ground (or ice) interface temperatures. Sky conditions were observed and photographed to help assess albedo values.
Sumner County Field Validation: An Assessment of Thermal Energy Storage in Municipal Buildings in Mixed-Humid Climates
The overall aim of the project was to conduct a full-scale implementation of TES in an operational administrative building in Sumner County, Kansas with a special focus of phase change material (PCM) passive implementation in the ceiling envelope. PCM was used with the intention of increasing the ability of public buildings to shift the peak HVAC energy demand and consumption. The study was conducted during the span of three years in 3 phases, (i) phase I: energy audit (pre-retrofit) (ii) phase II: ceiling tile installation (PCM retrofit), and (iii) phase III: energy evaluation (post-retrofit). Temperature and HVAC energy measurements as well as weather data collected is used for an extensive validation study and further parametric assessment to find (a) annual HVAC energy savings (b) peak period electricity and load savings focusing on cooling dominant months of the year.
Off-grid Persons and Communities
Shows a vision for using global weather data to help off-grid persons and communities make decisions about buildings and power systems (short 10 min presentation)
Plant Engineers Solar Energy Handbook: Southern California Region
Discussed in order after the introduction are solar components and systems (collectors, storage, service hot water systems, space heating with liquid and air systems, space cooling, heat pumps and controls); computer programs for system optimization; local solar and weather data; a description of buildings and plants in Southern California applying solar technology; current Federal and California solar legislation; standards, codes and performance testing information; a listing of manufacturers, distributors, and professional services available in Southern California region; and information access. Finally, solar design check lists for those engineers who wish to design their own systems. The program for the Solar Workshop for the Plant Engineer, March 30, 1978, Los Angeles, California is included.
A multi-scale time-series dataset of anthropogenic heat from buildings in Los Angeles County
The dataset contains hourly Anthropogenic heat (AH) from buildings in Los Angeles County, based on weather data from 2018. The hourly AH is aggregated at three spatial resolutions: 450m x 450m grid, 12km x 12km grid, and census tract. The AH is broken down into three components: building envelope surface convection, heating, ventilation, and air conditioning (HVAC) system heat release, and zone exfiltration and exhaust air heat loss. The dataset is created with the physics-based EnergyPlus building energy models to calculate individual buildings' AH considering WRF-UCM simulated microclimate conditions. Please refer to the paper "A multi-scale time-series dataset of anthropogenic heat from buildings in Los Angeles County" for more information about the data generation workflow and the data validation procedure. The data set contains two folders: the "output_data" folder holds the simulation results (EP_output and EP_output_csv), building metadata (building_metadata.geojson and building_metadata.csv), aggregated heat emission and energy consumption time-series data (hourly_heat_energy), and geographical data (geo_data) associated with the GEOID referenced in heat and energy consumption data. The "input_data" folder contains the raw data used to generate files in the "output_data" folder as well as data sets used in the validation. The code repository (https://github.com/IMMM-SFA/xu_etal_2022_sdata) holds the processing scripts for data curation, validation, and visualization.
Advancing Concentrating Solar Thermal Modeling Using System Advisor Model (SAM)
Concentrating solar thermal (CST) technologies play a critical role in enabling dispatchable power and high-temperature industrial heat applications. Accurate and flexible modeling tools are essential for evaluating system performance, guiding technology research and development, and informing investment decisions. The National Laboratory of the Rockies's System Advisor Model (SAM) is a widely used techno-economic simulation platform for CST systems, providing detailed performance and financial modeling capabilities for multiple CST system configurations. SAM integrates physics-based performance models with financial analysis to simulate the behavior of complex energy systems under realistic operating conditions. For CST technologies (including tower, parabolic trough, and linear Fresnel), SAM enables hourly simulations using site-specific weather data that ensure feasible operating conditions and convergence of mass and energy between core system components (i.e., solar field, receiver, thermal energy storage, and power cycle). These capabilities allow researchers and developers to evaluate annual energy production, capacity factors, levelized cost of energy (LCOE), and system dispatch strategies. A key advantage of SAM lies in its flexibility for parametric analysis and large-scale computational studies. Users can vary system design parameters such as heliostat field layout, receiver dimensions, thermal energy storage capacity, power block sizing, and installation cost assumptions to investigate their impact on system performance and financial metrics. When combined with automated scripting through LK, SDKTool, or Python interfaces, SAM enables high-throughput simulation workflows that support sensitivity analysis, technology benchmarking, and optimization studies. These approaches are particularly valuable for next-generation CST concepts, where design spaces are large and system interactions are complex. Another important capability of SAM is its support for dispatch optimization and thermal energy storage modeling, which are central to the value proposition of CST technologies. The ability to simulate integrated storage and flexible power generation allows researchers to explore strategies that maximize grid value, improve capacity utilization, and enhance integration with variable resources such as photovoltaic and wind generation. This poster will present an overview of SAM's thermal system modeling capabilities including concentrating solar. Additionally, we will highlight new feature developments including: 1) implementing Google's OR-Tools optimization platform for faster and more robust dispatch optimization, 2) developing a new power load following controller for modeling behind-the-meter applications, 3) enabling direct modeling of CSP-PV hybrid systems with the inclusion of battery storage, and 4) developing a multi-receiver falling particle Gen3 system model.
Sensitivity Effects of High Temperature Overhead Conductors to Line Rating Variables
For traditional overhead transmission lines, the maximum allowable conductor operating temperature on ASCR, AAC, or AAAC lines for determining the static line ratings can be quite low, typically well under 100 C. At these low temperatures, the primary driver for determining static line ratings are assumptions made about the wind speed and direction and the ambient temperature. Assumptions for solar loading and emitted thermal radiation, driven by line emissivity and absorptivity, are secondary factors, and only provide small changes to the static ratings. However, when considering newer high temperature conductors such as ACSS, ACCR, ZTACIR, and ACCC® the maximum allowable conductor temperatures can be significantly higher, up to 250° C. This higher temperature shifts the importance of the emissivity assumptions of the overhead transmission line, due to the nature of the T4 dependence of the radiative heat loss compared to the T1 dependence of the convective heat loss, as well as shifting the dependency on local wind conditions. Typical assumptions in the United States for the emissivity/absorptivity of overhead transmission lines in determining the static ratings are to use a value of 0.5 for both parameters or set a value in the range of 0.7 to 0.9. Recent experimental tests at EPRI have shown that higher emissivity aging assumptions may not be valid in some regions of the US, and that actual values may be much lower (0.25-0.45) than older studies have predicted (0.8-0.9). Here, the assumptions of different US Regional Transmission Operators (RTOs) and different utilities within RTOs are examined for the static ratings for traditional lower operating temperatures up to 100° C as well as with the higher maximum temperature conductors associated with newer conductor designs at 250° C. The sensitivity of the static ratings is examined at both lower and higher temperature conductors with respect to overhead line emissivity and absorptivity, wind speed, wind direction, and solar loading, and ambient temperature. It is shown that the effects of the conductor absorptivity, solar flux and ambient temperature on the static rating are increased when the transmission line has a lower maximum conductor temperature. The effects of the conductor emissivity, wind direction and wind speed have increased effects on the static rating when the transmission line has a higher maximum conductor temperature. In addition, example weather data is used to calculate the conductor temperature with different line emissivity and absorptivity assumptions. This shows the effect of assumptions made for emissivity only has a minor impact for low temperature lines, but for high temperature transmission lines can cause a 150-200° C temperature swing.
Analysis of Residential Time-of-Use Utility Rate Structures and Economic Implications for Thermal Energy Storage
Thermal energy storage (TES) is an increasingly popular tool to level out the daily electrical demand and add stability to the electrical grid as more intermittent renewable energy sources are installed. TES systems can locally decouple high thermal loads from the operation of a heat pump or reduce the electrical energy demand of the heat pump by providing a more favorable temperature gradient. In addition, many policy makers and utility providers have introduced time-of-use (TOU) rate schedules for residential customers to better reflect the price of electricity generation and demand for specific times. TOU rate schedules price grid-provided electricity differently throughout the day depending on the region’s climate, time of year, and electrical production. Large differences between on-peak and off-peak electrical prices may create an economic advantage for a residential customer to install a TES system. In this work, the economic and energy savings are calculated for a modeled 2,400 square foot residential building with water/ice-based TES using a TOU rate structure. The weather data is from Fresno County, CA, ASHRAE climate zone 3B, and a representative residential TOU utility rate structure from Pacific Gas and Electric (PG&E) was used. The results showed that total energy consumption could be reduced by 14.5% with an 87.5% reduction in on-peak energy usage when the TES is installed. The cost of operating this system for space cooling was reduced by nearly 20% using the sample utility rate plan.
A Modeling Tool to Analyze the Performance of Industrial Cooling Towers
Energy efficiency and energy savings have become an important factor as industries look for ways to save energy and minimize their energy consumption while reducing their carbon footprint. Cooling towers are utilized significantly in industries for either serving chillers or process cooling. Depending on the size of the cooling tower, it can use a surprising amount of energy and water, which is why it is crucial to make sure that the facility has optimized their cooling tower.A modeling tool has been developed to perform a thorough analysis of a cooling tower and its various operations to ensure that the facility has optimized its cooling tower. This model analyzes an annual base case in comparison with the revised case of a cooling tower operation. This modeling tool simulates 8,760 hourly calculations for fan power for various fan controls, water consumption, and pumping energy consumption and demand based on the user’s location and its corresponding Typical Meteorological Year 3 (TMY3) weather data. This model is capable to simulate up to five cooling tower cells as one large tower utilizing one pump or parallel pumping. The successful validated cooling tower model should assist industry to save energy at their facility through their cooling tower, whether they use it for process cooling or heating, ventilation and air conditioning (HVAC) applications. The entering/leaving water temperatures based on a monthly operating schedule or a wet-bulb temperature schedule will be used as inputs, and the model can calculate savings in energy for various conditions including variable-frequency drive (VFD) on the fan/pump, drift eliminators, number of cycles of concentration, reduced water flow rate, etc.
Single-Axis Tracker Control Optimization Potential for the Contiguous United States: Preprint
Conventional tracker control algorithms maximize collection of direct irradiance with no regard for collection of diffuse irradiance. Therefore, a tracker control algorithm that optimizes for maximal total irradiance, not just direct, might realize improved insolation collection. Using weather data gridded at 0.25° by 0.25° latitude/longitude spacing covering the contiguous United States, we evaluate the insolation gain of two alternative control algorithms optimized for improved total irradiance collection in monofacial arrays and present annual and monthly geographic heatmaps showing the gains across the contiguous United States. Certain locations show potential annual insolation gains approaching 1.0%, but most locations with recently-built tracker systems show annual gains between 0.1% and 0.4%. We also demonstrate a relationship between a climate's annualized diffuse insolation fraction and its potential tracker optimization insolation gain.
Hybrid Heat Pump Controls: Conventional Dual Fuel versus Seamlessly Fuel Flexible Heat Pump
This paper compares the performance of a novel seamlessly fuel flexible heat pump (SFFHP) and conventional dual fuel heat pump (DFHP) for space heating. The conventional dual fuel systems either run on the gas furnace or electric heat pump at any given moment, as a comparison, the proposed seamlessly fuel flexible heat pump simultaneously consumes gas and electricity by continuously optimizing the proportion of each. The process air flows across the heat pump condenser first and then flows across the furnace coil, therefore, the heat pump temperature lift is reduced. SFFHP delivers energy savings by allowing each subsystem, i.e., gas furnace and electric heat pump, to operate where it performs best.For DFHP, two operation control strategies, i.e., non-restricted control and restricted control, are available on market. For the non-restricted mode, the thermostat has a switching temperature-programmed according to the balancing point of heating load and capacity curve. Heat pump operates above the switching temperature, while the furnace takes over under the switching temperature. For the restricted control, the compressor of a heat pump is disabled below a predefined lockout outdoor temperature to let the furnace take over. For SFFHP, a model predictive control strategy is developed to continuously adjust the capacities of the electric heat pump and gas furnace based on the foreseen weather data, utility price signals, and marginal grid emission signals with the goal of minimizing the utility cost and CO2 emission while guaranteeing comfort requirements.In this paper, DFHP and SFFHP are simulated using high-fidelity heat pump performance curves generated from DOE/ORNL heat pump design model. Performance comparison of DFHP and SFFHP during 2019-2020 heating season in Los Angeles shows that SFFHP with model predictive control achieves 23% utility cost reduction and 17 % CO2 emission reduction. Case studies demonstrate that SFFHP can deliver significant reductions in peak demand, utility cost, and CO2 emission. As a result, SFFHP can deliver superior benefits for utility cost reduction and CO2 emission reduction over conventional dual fuel heat pump.
Rear-Side Irradiance Simulation of Field PV Modules: Preprint
Assessing the durability of photovoltaic (PV) module backsheet is critical to increasing module lifetime. Historically, laboratory-based accelerated testing has insufficient in predicting large-scale failures of commercial polymeric materials. Additionally, there is growing concern that standard condition tests do not reflect non-uniformities in field exposure, and that certain modules experience more severe degradation due to their location. Anisotropy in field exposures is installation dependent and reflects different levels of exposure to irradiance due to mounting geometry, ground surface albedo, and climatic zone. "Bificial Radiance" [1], simulates the amount of reflected irradiance on the Polyethylene Naphthalate (PEN) backsheet of a PV array located in Maryland. In our work, site specific weather data are gathered for the entire length of exposure for the modules. The total full-spectrum dose for the incident irradiance on the backsheet was then determined. The simulation results are integrated with historical field survey data to better understand realworld outdoor degradation.