Grid-interactive Efficient Buildings

Projects Summary

July 2020
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Grid-interactive Efficient Buildings: Projects Summary

SUMMARY OF ACTIVE BTO GEB PROJECTS

Buildings offer a unique opportunity for cost-effective demand-side management, because they are the nation’s 

primary users of electricity: 75% of all U.S. electricity is consumed within buildings, and perhaps more 

importantly, building energy use drives a comparable share of peak power demand. The electricity demand 

from buildings results from a variety of electrical loads that are operated to serve the needs of occupants. 

However, many of these loads are flexible to some degree; with proper communications and controls, loads 

can be managed to draw electricity at specific times and at different levels, while still meeting occupant 

productivity and comfort requirements. Through its grid-interactive efficient building (GEB) research, DOE’s 

Building Technologies Office seeks to build on existing energy efficiency efforts to optimize the interplay 

among energy efficiency, demand response, behind-the-meter generation and energy storage to increase the 

flexibility of demand-side management. BTO envisions a future where buildings dynamically operate as part 

of a low-cost, reliable electricity grid while meeting the needs and expectations of building occupants.

BTO’s mission supports the R&D, validation, and integration of affordable, energy efficiency technologies, 

techniques, tools, and services for U.S. buildings (existing and new, residential and commercial). In support of 

this mission, BTO is developing a GEB strategy that aims to optimize energy use across DERs to advance the 

role buildings can play in energy system operations and planning. This summary covers key projects 

contributing to the grid-interactive efficient buildings work and breaks projects into four areas of focus: 

• Value Proposition for GEB

• Building Technologies for Flexible Loads

• Optimization of Buildings for Flexible Loads

• Validation & Verification of Building Performance for Grid Services
Grid-interactive Efficient Buildings: Projects Summary

Table of Contents

1. Value Proposition for GEB..........................................................................................................................1

1.1 Valuation Inputs ............................................................................................................................. 1

1.1.1 End Use Load Shapes........................................................................................................... 1

1.1.2 Time Sensitive Valuation..................................................................................................... 1

1.1.3 Locational Value of Distributed Energy Resources............................................................. 1

1.2 GEB Potential Analysis.................................................................................................................. 1

1.2.1 GEB Technical Report Webinar Series................................................................................ 1

1.2.2 National GEB Roadmap....................................................................................................... 2

1.2.3 System-Level Assessment of EE&DR................................................................................. 2

1.2.4 Understanding the Impact of Demand Response on Building Energy Efficiency Metrics.. 2

1.2.5 Framework and Methodology to Define Flexible Loads in Building .................................. 2

1.2.6 Load Flexibility Study.......................................................................................................... 2

1.3 Stakeholder Value Streams and Analytical Needs ......................................................................... 2

1.3.1 Utility Working Group......................................................................................................... 2

1.3.2 Regulators and State Energy Office Working Group........................................................... 3

1.3.3 Better Buildings Commercial Buildings-to-Grid Working Group....................................... 3

2. Building Technologies for Flexible Loads ................................................................................................3

2.1.1 Characterization of Connected Lighting Systems Potential to Provide Grid Services......... 3

2.1.2 Connected Lighting Systems................................................................................................ 3

2.2 Building Envelope and Windows................................................................................................... 4

2.2.1 Solid State Tunable Thermal Energy Storage for Smart Building Envelopes ..................... 4

2.2.2 Thermal Switch Materials for Building Envelopes: A New Paradigm for Spatial and 

Temporal Optimization of Building Thermal Energy.......................................................... 4

2.2.3 Low-cost Composite Phase Change Material ...................................................................... 4

2.2.4 Anisotropic Thermal Management for Building Envelopes ................................................ 4

2.2.5 Thermal Behind the Meter Storage ...................................................................................... 4

2.2.6 Model Predictive Control for Dynamic Integrated Facades................................................. 5

2.2.7 Establishment of Energy Ratings for Automated Shading................................................... 5

2.3 HVAC, Water Heating, and Appliances......................................................................................... 5

2.3.1 Novel Solar Absorption Cooling System to Reduce Peak Loads......................................... 5

2.3.2 A Novel Framework for Performance Evaluation and Design Optimization of PCM 

Embedded Heat Exchangers for the Built Environment ...................................................... 5

2.3.3 Grid Connected Heat Pumps................................................................................................ 5

3. Optimization of Buildings for Flexible Loads ..........................................................................................6

3.1 Analytical Inputs............................................................................................................................. 6

3.1.1 Weather Forecasting Projects............................................................................................... 6

3.1.2 Advanced Monitoring and Analytics of Building Loads..................................................... 6

3.2 Controls R&D................................................................................................................................. 7

3.2.1 Optimization within Buildings............................................................................................. 7

3.2.2 Optimization across a Set of Buildings................................................................................ 8

3.3 Building Energy Modeling (BEM) that accounts for GEB ............................................................ 9
Grid-interactive Efficient Buildings: Projects Summary

3.3.1 Spawn of Energy Plus.......................................................................................................... 9

3.3.2 URBANopt: District Analytics Platform for the Optimization of Building Efficiency, 

Flexible Loads and Storage.................................................................................................. 9

3.3.3 Deep Reinforcement Learning for GEB............................................................................. 10

3.4 Cybersecurity................................................................................................................................ 10

3.4.1 Adaptive Cyber-Physical Resilience for Building Control Systems.................................. 10

3.4.2 Securing Grid-interactive Efficient Buildings (GEB) through Cyber Defense and Resilient 

System................................................................................................................................ 10

3.4.3 Building Intelligence with Layered Defense using Security-Constrained Optimization and 

Security Risk Detection (BUILD-SOS)............................................................................. 10

4. Validation & Verification of Building Performance for Grid Services............................................... 10

4.1 Component & Systems Validation & Verification....................................................................... 11

4.1.1 Grid Connected HPWHs.................................................................................................... 11

4.1.2 Validation of a Co-optimized, Smart Hybrid Heat Pump Control for Energy and Cost 

Savings, Peak Load Management, and Grid Resiliency .................................................... 11

4.1.3 Technology Analysis & Validation of Integrated Connected Lighting, Auto Shading and 

Intelligent Storage for GEB ............................................................................................... 11

4.1.4 Standardized Field Validation Protocols and Performance Data for EMIS Technologies. 11

4.1.5 Building-Level DC Distribution Systems.......................................................................... 11

4.1.6 Commercial Buildings Integration Lab.............................................................................. 12

4.1.7 Incentivizing Cold-climate Efficiency in Juneau ............................................................... 12

4.1.8 Hardware-in-the-loop Laboratory Performance Verification of Flexible Building 

Equipment in a Typical Commercial Building .................................................................. 12

4.1.9 A Framework to Characterize the Performance of Flexible Loads and Building Services 

Using a Hardware-in-the-Loop Approach.......................................................................... 12

4.1.10 A Scalable Hardware-and-Human-in-the-Loop Grid-interactive Efficient Building 

Equipment Performance Dataset........................................................................................ 12

4.2 Validation & Verification across a Set of Buildings.................................................................... 12

4.2.1 Smart Neighborhoods Research & Field Verification ....................................................... 12

4.2.2 Scaling of Building Transactive Control and Coordination to Support Grid Operations 

a.k.a The Campus Project................................................................................................... 13

4.2.3 GT-FLEX Atlanta .............................................................................................................. 13

This document focuses on active projects that build on the foundation of BTO’s EE work (it does not include 

core EE work) and the R&D needed to enable building technologies to provide flexible building loads. It is 

difficult to precisely delineate what is a “GEB project” and there are GEB-relevant projects that are not 

included in this summary (at BTO and other offices). 

Additional BTO GEB materials can be found here; including an Overview (44 pp.) and a Fact Sheet (1 p.).
Grid-interactive Efficient Buildings: Projects Summary

Current as of 6.1.2020 For more information, visit: energy.gov/eere/buildings/GEB 1

1. Value Proposition for GEB 

Includes analysis for national and sectoral GEB potential, research on inputs needed for determining the 

impact of flexibility on building load shapes and the electricity system, and work related to GEB stakeholder 

value propositions. 

1.1 Valuation Inputs 

In order to properly value flexibility temporal and locational considerations must be accurately captured.

1.1.1 End Use Load Shapes 

(FY19-21; NREL/LBNL): This project will result in: 1) end-use load profiles for U.S. building stock 

at both aggregate and individual building scales; 2) calibrated building stock end use models with 

ability to estimate EE/DR savings profiles for existing and emerging technologies. These datasets and 

associated methodology will be made publicly available.

1.1.2 Time Sensitive Valuation 

(FY20; LBNL): This project will advance the consideration of the value of energy efficiency during 

times of peak electricity demand and high electricity prices by summarizing analysis that quantifies 

the additional benefits of electric efficiency measures/programs during these periods. The project will 

cover two areas: 1) documenting existing studies that estimate the time-varying energy and demand 

impacts of efficiency measures/programs in multiple geographic regions and 2) summarizing end-use 

load research data available for this purpose and application of the data in electricity resource 

planning. 

1.1.3 Locational Value of Distributed Energy Resources 

(SPIA) (FY20; LBNL): This project, while not managed by BTO, is aligned with BTO’s GEB 

priorities. It focuses on how different types of distributed energy resources (DERs) provide different 

value based on DER location and how the value of DERs change depending on the type of feeder to 

which they are interconnected and its characteristics. The project will produce a technical report 

considering these aspects, as well as approaches state regulators and policymakers use to estimate the 

benefits and costs of DER investment with respect to their locational value. 

1.2 GEB Potential Analysis

Estimate the impact that energy efficiency and demand response measures (flexibility) will have on aggregate 

building load shapes and the electricity system. 

1.2.1 GEB Technical Report Webinar Series 

(FY20; BTO): BTO is holding a webinar series covering the recent publications on the grid-interactive 

efficient buildings technical reports. These reports provide researchers with an understanding of the 

flexibility opportunities of building loads for grid services. The webinar series will include six topics: 

• Heating, Ventilation, & Air Conditioning (HVAC); Water Heating; and Appliances

• Lighting & Electronics

• Building Envelope & Windows 

• Sensors & Controls and Modeling & Data Analytics 

• Building Equipment Integration 

• Distributed Energy Resources Integration 
Grid-interactive Efficient Buildings: Projects Summary

Current as of 6.1.2020 For more information, visit: energy.gov/eere/buildings/GEB 2

1.2.2 National GEB Roadmap 

(FY20-21; LBNL/Brattle): This project will estimate the value of the untapped GEB opportunity, 

identify and prioritize barriers to achieving the GEB potential, and define key solutions for 

overcoming the barriers, including actionable next steps for DOE and all key industry stakeholders. 

1.2.3 System-Level Assessment of EE&DR 

(FY19-21; LBNL): This project will develop a new integrated valuation methodology based on energy 

efficiency (EE) and demand response (DR) measure load shapes and regional electricity features to 

assess the load and economic relationships of EE and DR. Key deliverables include: 1) a technical 

report summarizing a conceptual framework of criteria driving interactive EE/DR effects with a 

detailed analysis of the ways in which specific EE and DR measures (and portfolios thereof) interact 

with one another; 2) a database of typical, regionally representative end-use load shapes with the 

highest potential for interactive EE/DR effects; and 3) a quantification of changes in system-level 

costs from the addition of different EE and DR measure portfolios.

1.2.4 Understanding the Impact of Demand Response on Building Energy Efficiency Metrics 

(FY19-21; SLAC): This project will analyze the impact DR capabilities have on the efficiency of 

buildings and the impact that EE strategies may have on demand response capacity. Results of this 

analysis will be presented in a technical report and incorporate data from three different locations in 

the analysis.

1.2.5 Framework and Methodology to Define Flexible Loads in Building 

(FY19-21; LBNL): This project advances methods quantifying buildings’ flexibility from a regional 

and building type perspective. The project will incorporate bottom-up techniques to create a consistent 

framework and methodology that defines buildings’ grid resource flexibility. The research will 

determine a building’s grid-resource flexibility based on factors including climate/weather, location, 

space types and operation history/status. Typical building end-uses such as: HVAC, lighting, 

miscellaneous electric loads (MELS), refrigeration and certain process loads, etc., will be considered 

as appropriate. The work will include validation testing in FLEXLAB and model results; project 

outputs will be shared in a technical report and will include publicly available metrics and calculation 

procedures.

1.2.6 Load Flexibility Study 

(FY19-20: NREL): This project involves a high-level stochastic analysis of the main value streams 

(including capacity, energy, and ancillary services) for building flexibility, by leveraging NREL’s 

Standard Scenarios and the prototype Cambium tool. The analysis will hinge on defining generic 

flexible resources to be analyzed. These flexible resources will represent potential GEBs that shift 

loads within a 24-hour window and will be chosen in collaboration with BTO and NREL’s building 

experts.

1.3 Stakeholder Value Streams and Analytical Needs

Identify key stakeholder needs in order to value flexibility under current frameworks and determine future 

analytical resources. 

1.3.1 Utility Working Group 

(FY19-20; ACEEE): A webinar series that will result in a summary of best practice approaches and 

challenges/gaps related to utility programs supporting the integration of EE/DR programs or GEB 

pilots. 
Grid-interactive Efficient Buildings: Projects Summary

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1.3.2 Regulators and State Energy Office Working Group 

(FY19-20; NASEO/NARUC): A webinar series to learn about the needs and questions of state leaders 

related to the value proposition of flexibility. This project will result in a set of documents that will 

support the development of state flexibility roadmaps and the initiation of state-led pilot projects. The 

GMLC technical assistance project described below will support states participating in this working 

group. 

1.3.3 Better Buildings Commercial Buildings-to-Grid Working Group 

(FY19-20; NREL): This project will work with Better Buildings Alliance and Challenge partners to 

understand key opportunities and challenges in the commercial sector, as well as document the size of 

the building resource to the grid across a set of diverse building portfolios or geographies. 

An important Grid Modernization Laboratory Consortium (GMLC) foundational project for FY20-21 that 

BTO is co-funding on behalf of EERE focuses on direct technical assistance (TA) over two years to state 

energy offices (SEOs) and public utility commissions (PUCs) to advance buildings that can provide grid 

services through demand flexibility—using distributed energy resources (DERs) to reduce, shed, shift, 

modulate and generate electricity. TA will support four key topics related to GEB and demand flexibility: 

programs and policies in public buildings, potential, pilots, and valuation. This work is in partnership with the 

NASEO-NARUC working group.

Another important collaborative effort BTO participates in is the SEE Action Network. This group has focused 

on developing a series of GEB related reports, two of which were published in FY20: 1) An Introduction for 

State and Local Governments and 2) Determining Utility System Value of Demand Flexibility. A third report 

that is forthcoming, Issues and Considerations for Advancing Performance Assessments of Demand Flexibility, 

will summarize current practices and opportunities to encourage robust and cost-effective assessments of 

demand flexibility performance and improve planning and implementation based on verified performance. 

2. Building Technologies for Flexible Loads

Includes identification of building technologies and R&D opportunities that can provide greater building 

flexibility. The projects below do not include core EE work that is an important foundation to GEB but instead 

focus on exploring how to make building technologies more flexible. 

2.1 Lighting

2.1.1 Characterization of Connected Lighting Systems Potential to Provide Grid Services 

(FY19-21; PNNL): Connected lighting systems (CLS) incorporating solid-state lighting (SSL) 

technology have the potential to provide a broad range of electric grid services, including those that 

rely on fast response. SSL power draw can be quickly modulated by dimming deeply and varying light 

spectrum and distribution, and thereby provide grid services at time frames of hours (e.g., for energy 

services) to seconds or less (e.g., for frequency regulation). However, the ability of CLS to deliver 

potential grid services while simultaneously delivering sufficient lighting service and occupant 

satisfaction has not yet been proven or quantified. This project will evaluate and advance the ability of 

CLS to provide grid services through modeling and simulation, laboratory testing, and field testing. 

Project results will be disseminated via targeted mechanisms to technology developers, lighting 

manufacturers, building owners and operators, system integrators, industry standards organizations, 

and other researchers. This project aims to advance the use of CLS towards achieving the 8 GW 

national peak reduction potential that has been estimated for grid-integrated lighting by 2035. 

2.1.2 Connected Lighting Systems 

(FY19-21; PNNL): The objective of PNNL’s connected lighting systems research is to increase the 

likelihood that emerging products and integrated systems will result in significant lighting (as well as 

non-lighting) energy savings, lighting service improvements, and value-added benefits for building 
Grid-interactive Efficient Buildings: Projects Summary

Current as of 6.1.2020 For more information, visit: energy.gov/eere/buildings/GEB 4

owners and occupants, as well as city managers and residents. This task area defines technical 

research in six areas that are key to enabling the energy savings potential of CLS: energy reporting 

accuracy, system-level energy performance, interoperability and system integration, key new features, 

cybersecurity vulnerability, and grid integration. The majority of the proposed work is carried out in 

the Connected Lighting Test Bed (CLTB) established by PNNL in Portland, OR, and focuses on 

examining and revealing common challenges and limitations as well as potential value-added 

opportunities emerging from CLS technologies. 

2.2 Building Envelope and Windows 

2.2.1 Solid State Tunable Thermal Energy Storage for Smart Building Envelopes 

(FY19-21; LBNL/NREL): This project will develop phase change materials (PCMs) that undergo 

solid-solid phase change and allows for dynamic tunability of the transition temperature. This research 

will enable a next generation of grid-interactive building thermal management schemes, capable of 

micro-zoned thermal energy control, spatial and temporal control of thermal energy storage, and 

dynamic control of heat flow throughout the building.

2.2.2 Thermal Switch Materials for Building Envelopes: A New Paradigm for Spatial and Temporal 

Optimization of Building Thermal Energy 

(FY19-21; LBNL/NREL/SLAC): This project seeks to develop dynamically-tunable thermal switches 

as a disruptive new paradigm for thermal management in buildings. Across three interrelated thrusts, 

the project will develop two new thermal switches, develop new tools for high-throughput 

measurements of low-conductivity porous materials, and conduct multiscale modeling to guide 

materials and prototype development. 

2.2.3 Low-cost Composite Phase Change Material 

(FY19-21; Multiple awardees): These eight projects will develop stable, low-cost salt hydrate and biobased phase change materials with a focus on reducing the cost and enhancing the performance and 

utilization of thermal energy storage in buildings. The projects will work to address the main barriers 

around low cost materials utilizing novel techniques for encapsulation, stabilization, packaging, and 

manufacturing. These projects aim to advance the state of the art by realizing a 10x reduction in the 

cost of deploying PCMs for building envelopes or equipment. 

2.2.4 Anisotropic Thermal Management for Building Envelopes 

(FY19-21; ORNL): Finite element simulations show that the application of thermally anisotropic 

composites (TACs) could reduce heat gains through walls by at least 75% compared to walls with 

cavity and exterior insulation. TACs coupled with a thermal loop is a novel technology that can redirect and reduce unwanted heat flows through the building envelope. This project aims to optimize 

the design of TAC systems for walls and roofs using lab tests, field evaluations, and calibrated 

models. As a conservative estimate, this project aims for 15% reductions in overall energy 

consumption attributed to walls and roofs. Additional capabilities of the proposed technology are 

shaving peak energy demand, modulating energy consumption, lowering energy use during power 

outages, especially during extreme heat events, and harvesting heat for water or space heating. 

2.2.5 Thermal Behind the Meter Storage 

(FY19-20; NREL): The objective of the project is to explore the use of thermal behind the meter 

storage to help facilitate grid-interactive efficient buildings. It will determine synergistic effects 

between thermal and battery energy storage, as well identify system tradeoffs between these energy 

storage systems in building applications. The project will develop the experimental protocols for 

characterizing thermal storage technologies at the material, component, and system level, including 

experiments integrating electrochemical and thermal energy storage. It will also determine the key 

material and component-level parameters that impact the performance of thermal storage systems and 

quantify the impact of these parameters. This includes material properties, component geometry, 
Grid-interactive Efficient Buildings: Projects Summary

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operating conditions, and how they impact cycling dynamics (charge/discharge rates), round-trip 

efficiency, overall load shifting capability, and ramp rates and dispatchability. 

2.2.6 Model Predictive Control for Dynamic Integrated Facades 

(FY17-FY20; LBNL): The objective of the project is to optimize control functions to fully utilize 

switchable glazings, motorized shading and daylighting systems, operable windows, and ventilation 

systems with predictive capability. Key driving parameters include peak electricity demand, energy 

savings, energy pricing, and comfort that require balancing of electric lighting and thermal loads while 

harvesting natural light. The work is being done in collaboration with the California Energy 

Commission. Over the last decade, the dynamic glazing industry has seen over 2B in private sector 

funding and now three suppliers have passed rigorous durability standards. The new control functions 

are applicable to a wide range of façade dynamic products including conventional automated shading 

and automated operable windows. 

2.2.7 Establishment of Energy Ratings for Automated Shading 

(FY18-22; LBNL/ORNL): LBNL is working to develop energy rating simulation software for a wide 

range of window attachments based on detailed laboratory testing that is then used by the Attachment 

Energy Rating Council (AERC) to establish product performance ratings for use in commercial and 

policy formulation. Complex geometry, shading materials, and operation schedules add to the 

variability and challenge. ORNL is modeling energy savings potential for automated shading for 

various commercial building sector applications and is collaborating with AERC to develop 

automated shading protocols that are essential to accurately access energy savings, grid response, and 

peak load reduction for individual products. 

2.3 HVAC, Water Heating, and Appliances 

2.3.1 Novel Solar Absorption Cooling System to Reduce Peak Loads 

(FY18-FY20; ORNL): The goal of this project is to examine novel and hybrid heat pumps that could 

work on solar as well as electricity or natural gas to provide space conditioning and water heating in 

residential homes. The use of solar energy is to be the prime driver and the use of electricity or natural 

gas is a secondary source of energy to fulfill the needs of a residential home. The purpose is to 

mitigate the use of prime energy and utilize as much renewable as possible to meet demand. Liquid 

desiccants (LD) have the capacity to store dehumidification capacity, indefinitely, without requiring 

any thermal insulation. In conventional air-conditioning, the burden of latent heat removal falls 

entirely on the air-conditioner. If an LD is used to pre-process the air to remove the latent loads, then 

the energy consumption for air-conditioning is mainly limited to processing sensible loads. It is 

possible for LDs to remove about 70% of air-conditioning loads and lower the size and energy 

requirements for air-conditioning. 

2.3.2 A Novel Framework for Performance Evaluation and Design Optimization of PCM Embedded 

Heat Exchangers for the Built Environment 

(FY19-21; University of Maryland, College Park): This project will work to develop a design and 

optimization framework for a solid-state energy storage composite phase change material embedded 

heat exchanger that can improve the performance of conventional heat exchangers. The project will 

focus on software tool development and validation using Heat Exchanger prototypes. Results of the 

project could lead to a widely applicable public domain design tool for PCM HVAC use that would be 

useful for embedded PCM-HXs and standalone PCM use in general. 

2.3.3 Grid Connected Heat Pumps 

(FY19-22; PNNL): PNNL will work with Portland General Electric and the Bonneville Power 

Administration to measure the load shed and shifting potential of using heat pumps enabled with 

CTA-2045. This communication protocol allows third party implementers and/or utilities to send load 

shifting signals to individual heat pumps within a utility territory. This project, which is the first of its 
Grid-interactive Efficient Buildings: Projects Summary

Current as of 6.1.2020 For more information, visit: energy.gov/eere/buildings/GEB 6

kind, aims to quantify the impact of these load shifting signals on homes in the Pacific Northwest. The 

goal will be to shift as much load as possible without affecting the comfort of the occupants in a 

discernable way. 

3. Optimization of Buildings for Flexible Loads

BTO’s sensors & controls and modeling portfolios focus on enabling building energy performance 

optimization while also considering occupant comfort. The projects related to GEB enable the ubiquitous 

participation of building assets in grid operations and develop technology and standards to ensure 

compatibility between building-facing control systems and grid-level control systems. 

3.1 Analytical Inputs

In order to optimize building loads temporal and locational inputs must be included in modeling and control 

algorithms.

3.1.1 Weather Forecasting Projects 

Site-specific weather information is crucial for operating grid-interactive efficient buildings, but it is 

generally unavailable or expensive to obtain.

3.1.1.1 Spatial Temporal Data Drive Weather and Energy Forecasting

(FY19-21, ANL): This project will develop new weather and energy forecasting algorithms 

with uncertainty analysis through incorporating spatial-temporal data in and around the 

building. The project will develop a software platform/package that includes new 

methodologies for site-specific weather and energy forecasting based on crowd sourcing 

and building operation data, and then demonstrate this platform in a real building for

improved energy savings from advanced building controls. 

3.1.1.2 Machine Learning Site-Specific Weather Inference for Building Energy Forecast 

(FY19-21, NREL): This project will develop a foundational platform to provide sitespecific weather forecasts by using low-cost, total-sky imagers in conjunction with readily 

available weather station data. This project will identify energy savings potential in GEBs 

by integrating: 1) Site-specific weather forecasts provided by advanced machine learning 

methods to capture the spatiotemporal correlations between the local weather conditions and 

nearby weather station data; 2) building energy forecasts from model predictive control 

(MPC); and 3) data analytics for evaluating the accuracy of weather and building energy 

forecasts, and for understanding how the site-specific weather forecasts, building types, and 

climates affect the energy savings in buildings. 

3.1.2 Advanced Monitoring and Analytics of Building Loads

3.1.2.1 Multi-functional Wireless Sensor Networks 

Projects awarded through the BENEFIT FY16 FOA ($4.8 million) with both universities 

and national laboratory performers are focused on extending the operational lifetime and 

automated configuration and calibration processes for wireless sensors networks in building 

applications with the goal of driving down the cost to enable scale-up and ubiquitous 

adoption. 

3.1.2.2 Automated Fault Detection and Diagnostics 

Leveraging prior investment and development in automated fault detection and diagnostics 

(AFDD), BTO is supporting several national laboratories (PNNL, LBNL, NREL, and 

ORNL) in the development of novel whole-building approaches for detecting and 

diagnosing equipment-related and control logic faults that compromise building 

performance and available flexibility. In addition, the team is developing a series of test 
Grid-interactive Efficient Buildings: Projects Summary

Current as of 6.1.2020 For more information, visit: energy.gov/eere/buildings/GEB 7

procedures to establish baselines and curating datasets from which both developers and 

customers (i.e., building owners) can evaluate performance of new algorithms to meet 

specific use cases and needs. The prevalence of fault types is also being established to focus 

future development on opportunities that will best minimize faults that compromise building 

operations and provision of grid services.

3.2 Controls R&D

 Projects in this area seek to develop next generation adaptive and model-predictive control systems that enable 

integrated, affordable, and secure control logic that interoperates across buildings, districts of buildings, and 

utilities while responding to occupant behavior, maximizing the quality of building energy services, and 

minimizing device and energy cost. 

3.2.1 Optimization within Buildings

3.2.1.1 Risk Based Framework for Dynamic Assessment and Prioritization of Flexible Building 

Loads

(FY19-21; LBNL): This project will develop an open-source decision tool for commercial 

building operators that dynamically ranks flexible load control options based on associated 

risks, benefits, and operator preferences. The decision making tool yielded by this project 

will facilitate broader and more effective demand-response participation in commercial 

buildings by removing the burden of manual flexible load prioritization from building 

operators while retaining their response preferences. 

3.2.1.2 Hierarchal Model-free Transactive Control of Building Loads to Support Grid Services 

(FY19-21; ORNL): This project will develop a robust, scalable hierarchical transactional 

control mechanism incorporating elements of model-free control and game theory to 

harness buildings to provide grid services. This approach addresses the implementation of 

transactional control schemes by separating the control mechanism into two layers above 

and below the aggregator. The project will test the designed solution at partner sites on at 

least 50 buildings. During testing ORNL will measure the magnitude of grid services 

provided and economic incentive provided to participants. 

3.2.1.3 Comprehensive Pliant Permissive Priority Optimization

(FY19-21; PNNL): This project seeks to build a dynamic, real-time adaptive building load 

prioritization framework from a selected set of influential parameters, including building 

function and characteristics, occupancy, operational constraints from users, time of 

day/year, weather, and equipment-specific safety standards and operational constraints. The 

framework will consist of four functional elements: 1) building load utilization and utility 

modeling, including a list of permissive loads to be dynamically ranked based on their 

utilization and their occupant-specified permissive parameters; 2) parametrized building 

load representation characterizing the load pliability to consumption limits; 3) integration of 

dynamic signals from various data sources; and 4) real-time forecast-based optimization. 

Together these four elements will produce a generic tool that provides real-time (with 15-

minute updates) prioritization of building loads adaptive to changing user-defined 

operational constraints, weather, and/or dynamic grid signals. 

3.2.1.4 Scalable Load Management Using Reinforcement Learning 

(FY19-21; ORNL): This project will develop a cost-effective load management system

(algorithm) which is easy to deploy on existing homes, can enable interoperability, and 

optimizes the loads to meet the homeowners’ comforts and economic constraints. The 

scalability, performance, and accuracy of the algorithm will first be evaluated using the 

simulation environment that has been developed at ORNL for modeling the integrated 

control strategies that appear in smart grid applications. The load management system will 
Grid-interactive Efficient Buildings: Projects Summary

Current as of 6.1.2020 For more information, visit: energy.gov/eere/buildings/GEB 8

be deployed at ORNL’s Yarnell Station research house to demonstrate its performance and 

energy saving capabilities. 

3.2.1.5 VOLTTRON 

(FY19-20; PNNL): VOLTTRON is a communication and execution platform for connected 

systems, providing secure messaging and authenticated, “sandboxed” execution of specially 

defined software agents. VOLTTRON supports monitoring and control applications for 

buildings, DERs, and the grid. VOLTTRON stakeholder engagement, distribution, and 

requirements gathering are now managed by Eclipse Foundation. PNNL continues to 

support VOLTTRON with software updates, bug fixes, installation and configuration 

guides, and community technical assistance. 

3.2.1.6 Adaptive Controls 

(FY19-21; PNNL/ORNL): This project will develop and test advanced adaptive building 

controls that continuously ensure optical systems behavior in response to changing building 

operation conditions (e.g., outdoor air temperature and equipment performance 

degradation), otherwise known as adaptive supervisory control. This could eliminate the 

need for seasonal manual tuning of building operations and will ensure continuous 

automated maximization of system performance while simultaneously addressing both the 

variability of system loads and the uncertainty on equipment health state. 

3.2.1.7 Hot, Cold, or Just Right 

(FY19-21; LBNL): LBNL will work to provide a solution to the challenge of building 

overcooling: a wide-view (many-occupant) biometric comfort sensor integrated with closedloop HVAC control. Specifically, the intent is to supplement conventional wall-mounted 

room air temperature sensors with a ceiling-mounted, wide-angle sensor that views the 

occupants. The goals are to improve occupant comfort and save cooling energy by 

implementing a closed-loop HVAC sensor/controller that radiatively detects occupants, 

occupant comfort, and room surface temperature distribution, then uses this information to 

reduce overcooling (cooling-energy overuse that discomforts occupants) by regulating 

HVAC output. 

3.2.1.8 Open Building Control 

(FY20-22; LBNL): The Open Building Control (OBC) workflow is projected to reduce 

building HVAC energy consumption by 20-30%. The project will develop a platform for 

design and specification of HVAC control sequences that interoperates with both wholebuilding energy simulation and automated control implementation workflows. OBC 

leverages Spawn, which aims to unify control design, evaluation, and optimization via 

whole-building energy simulation with control implementation, eliminating the manual 

translation steps currently associated with HVAC control implementation, reducing both 

error as well as effort and cost. OBC complements Spawn with a Modelica-based library of 

high-performance control sequences, testing and commissioning tools, and technical 

assistance to vendors to implement translators from Modelica to their own proprietary 

control platforms and products. The OBC approach will reduce the effort, cost, and error of 

designing, testing and deploying HVAC control sequences, while providing the industry 

with a formal process to test and evaluate those control sequences. 

3.2.2 Optimization across a Set of Buildings

3.2.2.1 Transactive-Control-Based Connected Home Solution for Existing Residential Units and 

Communities 

(FY19-21; PNNL): This project aims to overcome two barriers to large-scale market 

adoption of flexible building load control: 1) difficulty in integrating a new connected 

platform with existing home systems; and 2) lack of quantification of benefits to home 
Grid-interactive Efficient Buildings: Projects Summary

Current as of 6.1.2020 For more information, visit: energy.gov/eere/buildings/GEB 9

inhabitants, like improved comfort, and benefits to the local utility, like grid services, 

resulting from connected home solutions. The project team will develop an end-to-end 

solution that addresses integration and cyber security. PNNL will validate the solution by 

quantifying the benefits such as the energy cost savings and demand reduction potentials 

through limited field tests. The project will provide data to show that existing homes can be 

cost effectively upgraded to provide grid services in the near future. 

3.2.2.2 AI Driven Smart Community Control for Accelerating PV Adoption and Enhancing Grid 

Resilience

(FY19-21; NREL/SETO lead with BTO Support): This project aims to advance the building 

sciences on net zero energy community modeling, sensing, and control aggregating with the 

goal of reducing PV curtailment in the ZNE community to 0% by PV self-consumption 

using flexible building loads and minimal battery storage. The project outputs include: 1) 

advanced control method for improving load flexibility and source energy savings; 2) costeffectiveness analysis of sensing and control devices under various utility rate structures; 

and 3) a report summarizing the regional differences in grid impact and savings potential of 

residential communities with high-penetration PV in various climate zones. During the third 

year, the project will conduct field testing in 20 homes to evaluate the performance of the 

smart community control.

3.2.2.3 Behind-the-Meter Storage (BTMS) 

(FY19-21: NREL/VTO lead with BTO support): The objective of this project is to 

determine the design, sizing, type, and control algorithms for thermal and battery storage to 

maximize energy efficiency, while reducing the cost and grid impact of a grid-interactive 

efficient building. This project will determine the characteristics needed for new thermal 

energy storage materials and systems to maximize energy efficiency and solve issues arising 

from changing electric load and generation profiles. The analysis of the BTMS assets will 

focus on scenarios with standard loads, standard level 2-charging for customer vehicles, fast 

charging for fleet vehicles, and PV. 

3.3 Building Energy Modeling (BEM) that accounts for GEB

The focus of these projects are to expand current building energy modeling capabilities to accurately represent 

energy demand in buildings at increasingly small timescales. 

3.3.1 Spawn of Energy Plus 

(FY20;LBNL): Next-generation BEM engine that reuses the EnergyPlus modules for lighting, 

building envelope, and loads but re-implements the HVAC and controls modules in the equationbased modeling language Modelica and is capable of supporting both traditional modeling 

applications as well as control design, testing, and implementation workflows. Spawn advances past 

EnergyPlus in several ways that are relevant to GEB: 1) it models realistic rather than idealized 

control sequences, correctly accounting for dynamics such as oscillation and overshoot, the control 

sequences themselves can be translated for direct execution; 2) it efficiently supports simulation of 

relevant phenomena at sub-minute time scales; ii) it supports co-simulation in a deep and intrinsic way 

and allows BEM to be dynamically combined with related simulations such as ones of district 

systems, electrical systems, and DERs; iv) its support for both co-simulation and optimization enables 

a range of model-predictive control implementations. Spawn is currently in the “alpha” stage, a “beta” 

tool is expected in late 2020 or early 2021. 

3.3.2 URBANopt: District Analytics Platform for the Optimization of Building Efficiency, Flexible Loads 

and Storage 

(FY19-21; NREL): The URBANopt project develops capabilities for design and optimization at the 

district level, combining both buildings and shared systems including DERs, micro-grids, and shared 

thermal systems. URBANopt leverages Spawn/OpenStudio and adds Modelica-based district system 
Grid-interactive Efficient Buildings: Projects Summary

Current as of 6.1.2020 For more information, visit: energy.gov/eere/buildings/GEB 10

modeling capabilities as well as Application Programming Interfaces (APIs) for integration with other 

simulations including DERs (FEMP’s REopt), distribution systems (EPRI’s OpenDSS), storage, and 

micro-grids. The project includes a private sector partnership to integrate the new capabilities into a 

user-facing tool and to use URBANopt in several active district redevelopment projects. This project 

will determine how buildings can be designed and optimized within a district in conjunction with 

DERs and the electric utility distribution system and explore the associated value propositions. 

3.3.3 Deep Reinforcement Learning for GEB 

(FY19; NREL): The project will overcome the shortcomings of the state-of-the-art by leveraging the 

emerging deep machine reinforcement learning (RL) paradigm. It will extend previous work on deep 

RL as well as previous efforts in the literature on RL control systems for buildings and will develop 

scalable multi-objective RL algorithms that will simultaneously address both building-centric and 

grid- serving objectives. All this will be achieved without the need for detailed and accurate building 

models by virtue of the RL methodology and will be replicable to heterogeneous buildings. The 

algorithms will be tested in simulation and compared to the model predictive control (MPC) 

algorithms that are based on detailed and accurate models.

3.4 Cybersecurity

Leveraging investments in adaptive controls and their advantages over rule-based approaches, new efforts are 

underway to optimize control strategies against attacks and to develop cyber-resilient controls that adaptive 

and capable of maintaining continuity of operations when compromised. Furthermore, investments in AFDD 

are being leveraged for detecting and diagnosing faulty equipment operation or control logic resulting from 

cyber-related attacks and vulnerabilities. 

3.4.1 Adaptive Cyber-Physical Resilience for Building Control Systems 

(FY19-22; General Electric Company [GE]): This project will advance adaptive cyber-physical 

resilience for building control systems by employing a reinforcement learning-based adaptive model 

predictive control architecture to ensure safe and near-optimal closed-loop operation under all 

identified cyber-fault scenarios.

3.4.2 Securing Grid-interactive Efficient Buildings (GEB) through Cyber Defense and Resilient System 

(FY19-22; Texas A&M): This project will help secure GEBs with a novel cyber defense and resilient 

system (a real-time building platform with cyber-attack-immune capabilities) by pursuing multi-layer 

prevention, detection, and adaptation. 

3.4.3 Building Intelligence with Layered Defense using Security-Constrained Optimization and Security 

Risk Detection (BUILD-SOS) 

(FY19-22; University of Central Florida): This project will develop an integrated cyber-physical threat 

awareness, layered defense, and fault and attack-tolerant control solution for building energy 

management systems using Security-Constrained Optimization and Security Risk Detection (BUILDSOS). 

4. Validation & Verification of Building Performance for 

Grid Services

The focus of this work is lab and field verification & validation of building technology performance and 

controls optimization for a grid-interactive efficient building.
Grid-interactive Efficient Buildings: Projects Summary

Current as of 6.1.2020 For more information, visit: energy.gov/eere/buildings/GEB 11

4.1 Component & Systems Validation & Verification

4.1.1 Grid Connected HPWHs 

(FY18-22; PNNL): PNNL will work with stakeholders in the Northwestern and Southeastern parts of 

the U.S. to measure the amount of load that can be shed and shifted by HPWHs using field validation 

in real homes. Building off of previous work, PNNL will help DOE answer questions like, "Can more 

energy be shifted using smart algorithms (compared to running conservative events for the whole 

population of water heaters) to predict human behavior at any given time without sacrificing the 

comfort of the occupants?" and "How different is the load shed and shifting potential of HPWHs in 

the SE vs. the NW of the U.S.?"

4.1.2 Validation of a Co-optimized, Smart Hybrid Heat Pump Control for Energy and Cost Savings, 

Peak Load Management, and Grid Resiliency 

(FY20-22; Newport Partners): This project will develop, validate, and optimize advanced controls for 

hybrid heat pumps (HHP), an electric heat pump and gas furnace, in cold climate existing homes. The 

project will examine one prototype home under varying scenarios and will improve the viability of 

dual fuel heat pumps based on control optimization for cost, energy savings, peak demand and carbon 

emissions. It will also evaluate mixed-fuel utility regions (efficiency, demand control, and renewable 

energy integration) as well as apply the results to other regions and building types through modeling. 

4.1.3 Technology Analysis & Validation of Integrated Connected Lighting, Auto Shading and Intelligent 

Storage for GEB 

(FY19; Slipstream): The project will validate high density sensor (lighting, shading) integration with 

Building Automation System (BAS) to reduce overall peak lighting and integrate hybrid roof top units 

(RTU) with thermal storage (Phase Change Materials [PCM] with wax and graphite) for a shift in two 

field sites (office or higher education buildings). Slipstream will partner with a local utility partner 

that will assist with field sites recruitment. The project will incorporate an integrated system control 

for GEB (shed, shift) with and without thermal storage. The Calibrated Building Energy Models will 

include rate structures for field sites varied by climate zone and control strategies across prototype 

buildings. 

4.1.4 Standardized Field Validation Protocols and Performance Data for EMIS Technologies 

(FY19-21; LBNL): This project aims to develop standardized field validation protocols and datasets 

for energy management information system (EMIS) software analytics technologies. This work has 

significance with regards to the development of utility programs, investments by building owners, and 

future R&D. The protocols will cover all aspects of performance assessment including new hardware 

needs, data integration efforts, energy and demand savings, maintenance savings, and reporting 

savings. After the project team develops the standardized protocols, they will conduct EMIS 

validation projects and release the results to the public via DOE’s Building Performance Database 

(BPD). 

4.1.5 Building-Level DC Distribution Systems 

(FY19-21; NREL/LBNL): Since power is delivered through an alternating-current (AC) system and 

most electrical-powered equipment runs on direct-current (DC), each device in a building requires an 

AC-to-DC converter. Besides these converters in devices, buildings with on-site photovoltaic systems 

and battery storage may require several additional conversions between DC and AC. These 

conversions and other system inefficiencies account for energy losses between 2% and 18%. Using 

DC distribution systems in buildings represents an opportunity to reduce losses and realize significant 

energy and cost savings. This project will test DC distribution systems in real buildings in order to 

establish DC-system evaluation methods and metrics, document real-world performance, and assess 

technical barriers inhibiting robust adoption of these systems. The project team will also report on 

opportunities for improved performance through better integration and development of new 

technologies 
Grid-interactive Efficient Buildings: Projects Summary

Current as of 6.1.2020 For more information, visit: energy.gov/eere/buildings/GEB 12

4.1.6 Commercial Buildings Integration Lab 

(FY20; NREL): The ESIF commercial building lab will provide a research platform taking advantage 

of hardware-in-the-loop functionality for grid-interactive efficient buildings specifically in three key 

focus areas: flexibility for demand side management, intelligent efficiency, and interoperability 

(connectivity, controls, communication). This flexible laboratory space will include the electrical 

infrastructure to emulate three commercial buildings and will connect to ESIF infrastructure including 

megawatt scale photovoltaic array and grid emulators used to simulate different grid or renewable 

energy sources. The lab will include hardware-in-the-loop capabilities to drive HVAC systems and 

simulate any building components that are not physically represented in the lab to reduce the risk of 

new technology integration for utilities and building owners.

4.1.7 Incentivizing Cold-climate Efficiency in Juneau 

(FY20-22; Cold Climate Housing Research Center [CCHRC]): CCHRC will validate energy savings 

and fuel displacement using energy efficiency (EE) retrofit package in Juneau, Alaska. The study will 

include 50 households receiving EE retrofits, 50 households receiving heat pumps only, and 50 

households receiving EE retrofit packages and heat pumps. The EE package will likely include: LED 

lights, air sealing, insulation, window attachments, and hot water reduction. CCHRC will provide 

package specific training for installers and investigate bulk purchasing with finance options to 

incentivize future retrofitting. The project will evaluate increased electric heating without impact on 

the electricity grid load and compile a guide for replication. 

4.1.8 Hardware-in-the-loop Laboratory Performance Verification of Flexible Building Equipment in a 

Typical Commercial Building 

(FY19-22; Drexel University): This project will produce publicly-available, high-fidelity datasets that 

measure the holistic load flexibility performance of a suite of commonly-used commercial building 

HVAC and thermal storage equipment. 

4.1.9 A Framework to Characterize the Performance of Flexible Loads and Building Services Using a 

Hardware-in-the-Loop Approach 

(FY19-22; LBNL): This project will measure building equipment performance and impacts on 

building services using advanced testing capabilities with cutting-edge modeling tools.

4.1.10 A Scalable Hardware-and-Human-in-the-Loop Grid-interactive Efficient Building Equipment 

Performance Dataset 

(FY19-22; Northeastern University); This project will create a GEB equipment performance dataset 

using new occupant-centric control algorithms that produce grid services from heat pumps. 

4.2 Validation & Verification across a Set of Buildings 

4.2.1 Smart Neighborhoods Research & Field Verification 

(FY19-21; ORNL): This project will develop, demonstrate, and validate a scalable control framework 

to co-optimize energy cost, occupant comfort, grid reliability and resilience in next generation 

neighborhoods that integrate renewable energy sources and energy storage solutions. This includes 

home level and aggregated neighborhood level load optimization and forecasting. The framework will 

facilitate communication of aggregated load status and forecast with a micro-grid controller and 

engage in a transactive market with the micro-grid to optimize loads versus micro-grid assets. The 

aggregator will in turn communicate load response needs to the individual house and adjust major 

home loads (HVAC and water heating) accordingly. These projects are performed in partnership with 

Alabama Power and Georgia Power.
Grid-interactive Efficient Buildings: Projects Summary

Current as of 6.1.2020 For more information, visit: energy.gov/eere/buildings/GEB 13

4.2.2 Scaling of Building Transactive Control and Coordination to Support Grid Operations a.k.a The 

Campus Project 

(FY19-21; PNNL): This project will develop and demonstrate an open source, scalable, transactive 

control system (hardware and software) that enables both existing and new buildings to provide grid 

services without decreasing utility. It addresses a key gap which must be overcome to enable buildings 

to cost effectively provide grid services at the necessary scale to be impactful. This project will result 

in an automated agent-based control method for prioritizing controllable end-use loads for peak load 

management, dynamic load shaping and transactive control. Demonstration will be achieved by 

forming a multi-campus network using a layered transactive control and coordination approach that is 

tailored for low-cost embedded computers. The project will result in a published template for 

replication of transactive control and coordination of flexible building loads at scale.

4.2.3 GT-FLEX Atlanta 

(FY20-21; NREL): This project will validate the performance of optimized controls across 12-18 

existing education buildings on the Georgia Tech campus for the existing HVAC system, battery and 

thermal energy storage. The project evaluation will include peak load reduction, the ability to shift 

energy, and return on investment. 

BTO collaborated with the General Services Administration (GSA) to release a Request for Information (RFI) 

in FY20 focused on validating building technologies and energy services that can cost effectively provide 

building load flexibility as part of a GEB strategy. Several GSA and Better Building partner sites will be 

utilized to validate performance pf selected GEB solutions over multiple years.

DOE Contacts

Monica Neukomm monica.neukomm@ee.doe.gov 

David Nemtzow david.nemtzow@ee.doe.gov
DOE/EE-2136 ▪ July 2020

technologies-office

energy.gov/eere/buildings/buildingFor more information, visit: