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Contract No. DE-AC36-08GO28308

Laboratory Resources and 

Techniques to Evaluate Smart

Home Technology

Preprint

Bethany Sparn 

National Renewable Energy Laboratory 

Presented at the 2018 Summer Study on Energy Efficiency in 

Buildings

Pacific Grove, California

August 12-17, 2018

Suggested Citation

Sparn, Bethany. 2018. “Laboratory Resources and Techniques to Evaluate 

Smart Home Technology: Preprint.” Golden, CO: National Renewable 

Energy Laboratory. NREL/CP-5500-71696.

https://www.nrel.gov/docs/fy18osti/71696.pdf

Conference Paper

NREL/CP-5500-71696

August 2018
NOTICE

This work was authored by the National Renewable Energy Laboratory, operated by Alliance for Sustainable 

Energy, LLC, for the U.S. Department of Energy (DOE) under Contract No. DE-AC36-08GO28308. Funding 

provided by USDOE Office of Energy Efficiency and Renewable Energy Building Technologies Office. This 

research was performed using computational resources sponsored by the Department of Energy's Office of 

Energy Efficiency and Renewable Energy and located at the National Renewable Energy Laboratory. The views 

expressed in the article do not necessarily represent the views of the DOE or the U.S. Government. The U.S. 

Government retains and the publisher, by accepting the article for publication, acknowledges that the U.S. 

Government retains a nonexclusive, paid-up, irrevocable, worldwide license to publish or reproduce the published 

form of this work, or allow others to do so, for U.S. Government purposes.

This report is available at no cost from the National Renewable 

Energy Laboratory (NREL) at www.nrel.gov/publications. 

U.S. Department of Energy (DOE) reports produced after 1991 

and a growing number of pre-1991 documents are available 

free via www.OSTI.gov. 

Cover Photos by Dennis Schroeder: (left to right) NREL 26173, NREL 18302, NREL 19758, NREL 29642, NREL 19795.

NREL prints on paper that contains recycled content.
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Laboratory Resources and Techniques to Evaluate Smart Home Technology

Bethany Sparn, National Renewable Energy Laboratory 

ABSTRACT

Smart home technologies promise to make residential buildings more comfortable, less 

costly to operate, more energy efficient, and more integrated with the grid, but these systems are 

difficult to evaluate in traditional laboratory spaces. To aid in the development and evaluation of 

new home energy management systems, the National Renewable Energy Laboratory (NREL) 

built the Systems Performance Laboratory (SPL) within the Energy Systems Integration Facility.

The SPL has electrical infrastructure for three residential buildings, complete with smart meters, 

breaker panels, and a full complement of major and minor appliances in each “home.” Cord and 

plug power connections mean that appliances can easily be swapped for different models. 

Distributed energy resources, such as residential photovoltaic inverters and home batteries, are 

also available for integration. Sensors monitor the power consumption of all loads, and 

controllers can simulate occupancy to drive the appliances in realistic ways. A novel hardwarein-the-loop (HIL) application was developed to drive air-conditioner cycling by combining a 

building simulation with a physical air conditioner and a thermostat. This system allows us to 

simulate air conditioner performance in any climate with any building construction. Another 

application of the HIL technique uses a grid simulation to model the grid impact for different 

control strategies related to smart home technologies. This laboratory is a powerful, flexible tool 

that can be employed to evaluate the effect that home energy management and other smart home 

technologies will have at the appliance, whole-home, and distribution feeder levels—all of which 

are important perspectives for different stakeholders. 

Introduction

The advent of the Internet of Things brings potential for homes to be filled with smarter, 

more responsive devices and appliances. The capabilities that these new technologies enable 

range from improved comfort and convenience, to increased energy efficiency, to reliable 

demand response and grid services, but many questions remain. There are basic questions about 

interoperability among all the appliances. There are questions related to the impact of a home 

potentially using more energy to take advantage of cheaper electricity when more renewables are 

available. The ability to more easily and reliably participate in grid service programs, such as 

demand response or peak load reduction, opens the door to a multitude of other uses for smart 

appliances in the home, but how do we characterize the response of smart devices to different 

grid service requests? How can we ensure that consumers receive the desired comfort and 

performance from their homes in a cost-effective manner while also providing useful services to 

the local utility grid?

This field of research is still in its infancy, so it is difficult to know which research 

questions will be the most important and relevant going forward. To accommodate the different 

directions that might come with the adoption of smart homes and smart device technologies, 

researchers at the National Renewable Energy Laboratory (NREL) designed and built a 

laboratory focused on studying how residential buildings might interact with the grid of the 

future. The Energy Systems Integration Facility (ESIF) was built in 2013 to provide a research 
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space dedicated to optimizing the nation’s energy system (Van Becelaere 2017). The ESIF 

includes electrical, water, and fuel infrastructure. On the electrical side, the facility has 

capabilities to test or simulate megawatt-scale components or look at the energy consumption of 

residential-scale plug loads and everything in between. One laboratory in the ESIF is the 

Systems Performance Laboratory (SPL), a space designed for research focused on residential 

buildings and their integration with the electric utility grid. The SPL is intended to be a flexible 

resource that can be used to evaluate a wide range of smart home technologies—from studying

innovative power sensors, to testing smart appliances, developing algorithms for home energy 

management systems (HEMS), and evaluating how different control strategies implemented 

across many homes will impact the utility grid (NREL 2016).

Other research facilities around the country and the world can also be used to evaluate 

smart home technologies, but they are generally implemented as “lab homes”—homes that have 

been built for residential energy research, are usually unoccupied, and are instrumented with 

many sensors and controllers (Crocker 2017; Ghaffarianhoseini et al. 2013; PNNL 2018). Lab 

homes are a valuable tool that can be used to evaluate many important aspects of smart home 

technologies, particularly those related to interoperability and deployment in real homes. But the 

SPL enables more early-stage research, more flexibility in the connected building systems, and, 

most importantly, integration with resources that can evaluate the grid-level impact of these 

technologies. 

Figure 1. One of the homes in the SPL, including an electric vehicle. Source: Dennis Schroeder, NREL 38890

Laboratory Design

The SPL was designed to accommodate a range of research types and be a flexible, 

evolving space. The initial planning for the SPL focused on investigating the interactions 

between the electrical distribution system and residential communities, developing/evaluating 

new sensors and controls for building control systems, and testing relevant equipment under 

extreme weather or grid conditions. The lab was also intended to be a place for collaboration 
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among researchers in industry, other national labs, and academia. With these goals in mind, the 

following criteria were used to guide the lab design: 

• The lab should include multiple “homes” that can be monitored and controlled 

simultaneously to simulate a community-scale load profile.

• Each home should have the necessary electrical and water infrastructure for a typical 

residential building, but it should be easy to switch out the physical appliances installed.

• Including heating, ventilating, and air-conditioning (HVAC) loads is essential for this 

laboratory space, but some means of driving the equipment in a realistic fashion must be 

developed. 

• The lab should include necessary sensors and controls infrastructure to operate each 

home individually or as a group, and the data acquisition system should accommodate 

additional sensors and controls as necessary. 

With these requirements in mind, the lab was built and became fully operational in 2014. 

The lab contains three separate homes, which allows multiple projects to run concurrently or 

enables more complex projects with multiple homes/occupant profiles. The lab also has the 

capability to interface with other resources in the ESIF, including a high-performance computer

(HPC) and megawatt-scale electrical infrastructure.

Figure 2. Rendering of the SPL showing all three homes as built. Source: Illustration by Josh Bauer, NREL

The SPL includes the electrical infrastructure for three homes, each with an advanced 

metering infrastructure utility meter feeding a 150-A breaker panel, with dedicated power meters 

on each circuit, and a whole-home power meter measuring real and reactive power. A full 

complement of major appliances is installed in each home, though only two of the three homes 

have an HVAC system. The system needed to drive the HVAC equipment (to be discussed 

further) is too large for the laboratory to accommodate three separate versions. In addition to the 
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major appliances, the homes have several outlet banks on separate circuits to accommodate a 

variety of plug loads and small appliances. With the exception of the HVAC equipment, all of 

the appliances have been installed using cord and plug connections to allow the appliances to be 

replaced more easily. Two of three homes currently have photovoltaic (PV) inverters installed 

and can accommodate additional distributed energy resources (DERs), such as stationary 

batteries, natural gas generators, or electric vehicle supply equipment (EVSE). The third home 

can also accommodate DERs, but they have not yet been needed. The homes can also be 

powered from a variety of sources, including facility power (default), a grid simulator (also 

known as a programmable AC power supply), or through the ESIF research electrical 

distribution bus. The homes can also be powered as a group or individually via step-down 

transformers located outside the building. 

In addition to the physical infrastructure, the SPL includes data and network resources 

that can be tailored to individual projects. The lab includes a National Instruments-based data 

acquisition system that enables a wide range of configurability options—a user might need 

sensors related to a single appliance, a whole home, or all three homes, and the data acquisition 

system is able to accommodate this. The data acquisition system collects circuit-level power data

for all appliances, water flow and temperature data for appliances that use water, ambient 

temperature and humidity data, and airflow and temperature data for the HVAC system. 

Additional sensors can be added as needed. 

Many smart appliances or advanced sensors rely on a connection to a manufacturerspecific cloud for data processing or scheduling. Other devices have additional features available 

via mobile applications when connected to the Internet. To accommodate the variety of 

communicating devices, we installed multiple wireless networks with different features and 

security levels. The existing networks can be modified if needed or additional networks can be 

temporarily installed to accommodate different network and security requirements. 

Simulated Occupancy

The homes in the SPL are designed to electrically represent real homes, but the actual 

load profiles depend on how the equipment is operated. We apply simulated occupancy—a 

technique used to establish occupancy-related energy use—to all of the relevant appliances in the 

lab. The details of the project will determine how the simulated occupancy is designed, but it is 

common to start from the appliance schedules in the Building America House Simulation 

Protocols (Wilson et al. 2014). 

Depending on the appliance, the controls needed to impose simulated occupancy vary. 

Appliances that run continuously—the refrigerator, water heater, and HVAC system—can be 

controlled in an autonomous fashion; whereas other appliances—the dishwasher, clothes washer, 

and dryer—require manual interaction and are more difficult to automate. The clothes washer, 

dryer, and dishwasher are operated manually on a schedule. To ensure that the washer and 

dryer’s operation is realistic, we use a load of white T-shirts and laundry detergent. Once the Tshirts have been washed, they are moved to the dryer. The dishwasher is loaded with dishes, and, 

when possible, a cycle is chosen that does not rely on “soil sensing” so that the dishes do not 

have to be dirtied before each cycle. Some newer smart appliances have options to set when the 

cycle begins (either with a delay function or via a mobile application). Otherwise, a researcher 

will manually begin the cycle at the desired time.

The appliances that operate continuously are paired with systems that load them in an 

appropriate manner. To drive the refrigerators, there is thermal mass in the fridge and freezer 
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compartments (liquid and frozen water, respectively) and incandescent light strings in both 

compartments to add heat on a schedule that mimics the addition of room temperature food. The 

water heater supplies hot water to appliances that need hot water and to a fixture with controls on 

the hot water line. A controllable solenoid valve is scheduled to impose a simulated hot water 

draw profile on the water heater, which we vary to simulate a range of homeowner profiles. The

HVAC system requires a more complex hardware-in-the-loop (HIL) system to drive the 

equipment in a realistic fashion. HIL is a technique that combines hardware and software in a 

continual feedback loop and is applied here to drive the air conditioner without needing all the 

components of a real house (Sparn et al. 2018). Figure 3 shows a diagram of the HVAC HIL 

system.

Figure 3. HVAC HIL system. Source: Illustration by Bethany Sparn, NREL

An EnergyPlus building model runs in real time at one-minute intervals using an hourly 

weather file for the location of interest. The EnergyPlus model uses the building characteristics, 

internal gains, outdoor temperature, solar insolation, and real-time data from the physical air 

conditioner in the SPL to calculate the indoor temperature as the air conditioner turns on and off. 

This configuration allows us to recreate the operation of an air conditioner or heat pump in 

homes with different building characteristics or in different climates.

The outdoor condensing unit is located inside an insulated chamber where the 

temperature is controlled to match the outdoor temperature from the weather file. The air 

handling unit portion of the air conditioner/heat pump is installed in a duct loop with heaters to 

ensure that the return air temperature matches the value found by the EnergyPlus simulation. 

Airflow and air temperature measurements at the outlet of the air handling unit are used to 

determine the amount of cooling delivered by the air conditioner and that measurement is used 
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by the EnergyPlus simulation, instead of data from a simulated air conditioner as is typically 

done. There are two HVAC HIL systems in the SPL: one system currently houses a SEER 21, 

two-speed, two-ton air conditioner; and the other system contains a 3-ton, SEER 18, variablespeed heat pump. 

 The air conditioner is controlled by a thermostat that sits in a small environmental 

chamber that is controlled to match the indoor air temperature as determined by the EnergyPlus 

simulation. Multiple brands of Internet-connected thermostats have been used for control, which 

allows the set point to be controlled via an application programming interface (API). The set 

point temperature of the thermostat can be set on a schedule, or dynamically changed via API, 

depending on the research need. 

Figure 4. Photos of one of the HVAC HIL systems; the environmental chamber used to house the 

thermostat is shown in the inset. Source: Main photo by Dennis Schroeder, NREL 38915; inset photo by 

Bethany Sparn, NREL.

Representative Projects

The intent of the SPL was to accommodate a wide range of projects, big and small, simple and 

complex. This section describes a variety of projects that have been conducted in the SPL during 

the three years that the lab has been fully operational. 

Least Complex: Sensor and Component Testing

The simplest experiments that have been conducted in the SPL involve single 

components or sensor evaluations. The residential infrastructure in the SPL provides a 

convenient and controllable environment for evaluating new sensors. This might involve a study 

of the installation process, usability, or accuracy of the sensor. Other simple projects involve the 

evaluation of a collection of devices tested independently. Examples of these types of projects 

are given next.
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Nonintrusive Power Meter Testing. Several projects in the last few years focused on evaluating 

different circuit breaker-level power meter solutions. Whisker Labs makes a novel power meter

that sticks to the front of the breakers (see Figure 5) and measures the electric and magnetic 

fields at the breaker as a means of calculating power flow (Sparn et al. 2017). The laboratory 

tests were intended to evaluate the installation process and the accuracy of the meters. The SPL 

is an ideal test bed for these projects because the breaker panels are consistent with a house, 

contain a variety of load types, and already have high accuracy power meters on every circuit.

The Whisker Labs sensors could be installed in minutes, without requiring access to the interior 

of the breaker panel. The laboratory testing in the SPL found that the single-circuit accuracy was 

±10%, with a typical interference rejection ratio of 10:1 for power on nearby circuits. Whisker 

Labs has continued to improve their technology and are now only measuring power at the main 

breakers in an electrical panel using the same stick-on meter technology, which should eliminate 

the interference that we measured in the SPL.

Figure 5. The Whisker Labs meters installed on the front of breakers in an 

electrical panel in the SPL. Source: Dennis Schroeder, NREL 41583

Development and Demonstration of Communicating Appliances. Another example of a 

simple experiment conducted in the SPL was a collaboration between NREL and the Electric 

Power Research Institute (EPRI) to develop and demonstrate the functionality of several 

connected appliances using open communication standards (Hudgins et al. 2018). A collection of 

residential appliances that were compatible with the CTA-2045 and SunSpec standards were 

installed in the SPL and underwent multiple rounds of testing to understand and improve their 

response to a standard set of grid service commands, such as load shed, load add, or grid 

emergency (CTA 2018; SunSpec Alliance 2015). Two water heaters (a standard electric 

resistance and a heat pump water heater), a thermostat controlling an air conditioner, a pool 

pump, EVSE used to charge an electric vehicle, and a PV inverter were installed in two of the 

SPL homes and subjected to simulated occupancy to measure normal operation and the change in 

operation when various commands were issued.

 The appliances were evaluated individually to understand how each manufacturer 

implemented the standard commands. The initial round of testing was used to evaluate which 

commands were implemented, which commands were missing or had problems, and if there 

were any usability issues. Based on the feedback from the initial tests, the manufacturers made 
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improvements to hardware or software (or both), and a second round of testing was conducted. 

The SPL provided the required infrastructure to install the appliances, apply simulated 

occupancy in a repeatable fashion, and collect data needed to quantify the impact of the controls. 

Figure 6. Residential appliances installed in the SPL as part of the NREL/EPRI project. Clockwise from 

upper left: thermostat, heat pump water heater, PV inverter, EVSE, and pool pump. Source: Photos 

provided by EPRI

More Complex: Whole-Home Control 

The next step in complexity is the coordinated control of multiple connected devices in a 

single home. One such project included a full complement of controllable appliances (PV 

inverter, home battery, refrigerator, dishwasher, clothes washer, dryer, electric resistance water 

heater, and thermostat connected to a heat pump) and an NREL-developed HEMS called foresee

(Jin et al. 2017). 

The connected devices communicate with foresee, running on a small computer, as 

shown in Figure 7, over a combination of wired and wireless protocols. Interoperability 

challenges are an area where laboratory testing can aid in the development of smart home 

technologies. Even when a controller has demonstrated compatibilities with a range of individual 

devices or communication protocols, integrating multiple systems can present new problems. 

In addition to using the infrastructure to configure foresee and the connected appliances 

in a realistic environment, this project took full advantage of the simulated occupancy tools 

developed for the SPL. A series of use cases determined the impact of the advanced controls that 

are built into foresee, which uses multi-criterion decision-making and model-predictive control

to improve whole-home efficiency and provide reliable grid services. We tested scenarios that 

are relevant in different climate regions, with the simulated occupancy tailored to reflect that 

location. This project was cosponsored by Bonneville Power Administration, so two of the 

simulation locations were Portland, Oregon, and Spokane, Washington. The final location 

chosen for the laboratory evaluation was Honolulu, Hawaii, because of the city’s unique 

challenges with excess rooftop solar. For each location, we used an EnergyPlus house model that 

reflected typical construction in that location for the HVAC HIL system.
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Figure 7. foresee user interface shown with PV inverter and home battery within the SPL. Source: Dennis 

Schroeder, NREL 45575

These scenario tests compared the home’s daily energy usage profile under normal 

operation (no foresee control), under optimized control aimed at energy efficiency, and during a 

day with some type of demand response (load add or load shed). In all cases, a time-of-use 

(TOU) price structure was applied and used to determine the daily cost of energy, another metric 

used to assess the results.

Figure 8. Power data collected in the SPL showing the load pattern under two conditions: baseline mode 

(no control) and energy-efficiency mode. The gray shading represents the TOU rate structure, with the 

darkest band representing the most expensive rate.

Figure 8 shows preliminary results for half of a Portland day where two cases were run: 

baseline without control and energy-efficiency mode. The black line represents the case without 

foresee control, and the blue shading shows when foresee was used to improve energy efficiency 
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and reduce costs. The gray shaded areas represent the TOU schedule, with the darkest section 

corresponding to the highest rate period; the light gray shows the medium rate periods; and the 

white section shows the lowest rate. The case with foresee running shifted some of the highpower loads and used the battery to offset some of the power consumption during the highest 

price periods. On this day, nearly 2 kWh of energy were saved, resulting in about 20% cost 

savings. 

Most Complex: Control of One Home in Coordination with Large-Scale Simulation

To date, the most complex project that has been executed in the SPL involved an 

application of the HIL concept. In this case, the “hardware” was one of the homes, complete with 

multiple controllable appliances and a HEMS, which was connected to a simulation of an 

electrical distribution feeder running on the HPC in the ESIF, as shown in Figure 9 (Sparn et al. 

2018). The feeder simulation included 20 homes, with one home replaced by the hardware home 

in the SPL. Each simulated home had its own dedicated HEMS that was optimizing control to 

achieve minimum cost under a TOU utility tariff while maintaining comfort. The collective grid

impact of the individual control decisions among the 20 homes was determined in the feeder

simulation, and any changes to feeder voltage were reflected in the SPL through a grid simulator 

used to power the home. Simulated occupancy and weather was applied to the devices in the 

home—PV inverter, EVSE, air conditioner, and water heater—and the power use profile of the 

SPL home was sent in real time to the feeder simulation to represent one of the homes on the 

feeder.

Figure 9. Diagram of the Smart Home Hardware-in-the-Loop experiment. Source: Illustration by Anthony 

Castellano, NREL

This project, known as the Smart Home Hardware-in-the-Loop, made use of the HPC in 

the ESIF and several tools that were developed to enable this experiment. The feeder simulation 

runs on the HPC, and the individual HEMS for each home are also optimized using the HPC. 

Weather and utility tariff information feed into both the HEMS optimizations and the feeder 

simulation. A cosimulation platform was developed in an earlier project that enables all the 

different simulation components to exchange data and control signals at the right time. Other 

standard ESIF equipment was needed to make the connection between the simulation and the 

SPL home, including a grid simulator to power the home with power consistent with the feeder 

simulation, a PV simulator to supply DC power to the PV inverter, and a real-time simulator to 
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manage the control to the grid simulator and PV simulator. Preliminary results in Figure 10 show 

that the HEMS control shifts energy usage away from the high-priced time periods, leading to 

both energy and cost savings at the house level; however, results from the feeder simulation 

show that the time-based controls lead to slightly more variation in grid voltage. 

Figure 10. Comparison of temperature and power data from the air conditioner hardware during two days under 

baseline control and HEMS control. The dashed blue lines indicate the bounds on the set point temperature. The 

pink shaded areas represent the TOU rate, with the darkest sections representing the highest cost periods.

Conclusions

Visitors to the SPL see a laboratory that looks and feels familiar because it contains smart 

home appliances and other residential equipment, but the lab was deliberately built to facilitate a 

new kind of research at NREL. The SPL enables researchers from across NREL and around the 

world to test everything from sensors and control components to sophisticated control algorithms 

in a controlled and controllable environment. The laboratory infrastructure includes major and 

minor appliances for three homes, along with sensors and controllers to apply simulated 

occupancy to all the different loads. DERs such as PV inverters and home batteries can be 

brought into the homes to explore new options for powering homes and providing stability to the 

grid. The homes can be integrated with other assets in the ESIF, which allows us to evaluate the 

grid-level impacts of the controls being explored for residential buildings. SPL has been used to 

evaluate novel sensor technologies, investigate whole-home energy and cost savings from HEMS 

systems, and understand the impact those controls will have on the electric grid when 

implemented more broadly. SPL provides the environment and the necessary tools to investigate 

a wide range of research questions related to buildings-to-grid integration, with enough 

flexibility to adapt as research needs change.

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This report is available at no cost from the National Renewable Energy Laboratory (NREL) at www.nrel.gov/publications. 

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