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Conference Paper

NREL/CP-5500-77415

September 2020

The Future of Zero Energy Buildings: 

Produce, Respond, Regenerate

Preprint

Paul A. Torcellini, Sammy Houssainy, Shanti D. Pless,

William Livingood, and Ben Polly

National Renewable Energy Laboratory

Presented at the 2020 ACEEE Summer Study on Energy Efficiency in 

Buildings

August 17-21, 2020
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Office of Energy Efficiency & Renewable Energy

Operated by the Alliance for Sustainable Energy, LLC

This report is available at no cost from the National Renewable Energy

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Conference Paper

NREL/CP-5500-77415

September 2020

The Future of Zero Energy Buildings: 

Produce, Respond, Regenerate

Preprint

Paul A. Torcellini, Sammy Houssainy, Shanti D. Pless,

William Livingood, and Ben Polly

National Renewable Energy Laboratory

Suggested Citation 

Torcellini, Paul A., Sammy Houssainy, Shanti D. Pless, William Livingood, and Ben Polly. 

2020. The Future of Zero Energy Buildings: Produce, Respond, Regenerate: Preprint. 

Golden, CO: National Renewable Energy Laboratory. NREL/CP-5500-77415. 

https://www.nrel.gov/docs/fy20osti/77415.pdf. 
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The Future of Zero Energy Buildings: Produce, Respond, Regenerate

Paul A. Torcellini, NREL

Sammy Houssainy, NREL 

Shanti D. Pless, NREL

William Livingood, NREL

Ben Polly, NREL

ABSTRACT

The zero energy buildings concept is more than 20 years old, and the paradigm shift from 

buildings as energy consumers to buildings as energy producers is underway. Buildings also 

consume land and material resources, however, with additional environmental impacts. Another 

paradigm is emerging: a built environment that produces energy and is environmentally

responsive and regenerative. This paper investigates an updated framework for thinking about 

zero energy buildings that includes discussions of prioritizing renewables; determining on-site 

versus off-site generation; exploring how and when buildings should use energy; and balancing 

renewables, storage, and energy efficiency. 

Buildings are typically connected to the utility grid and the utility grid develops largely in 

response to the built environment. If more buildings’ real time electricity use aligned with 

renewable generation, more renewables would be added to the grid. Ultimately, a key goal for 

zero energy buildings will be to use 100% renewables, 100% of the time, matching loads with 

energy storage and renewable generation at each discrete timestep over a year. This target is 

beyond the current zero energy definitions, which focus on an annual balance of renewable 

supply and energy demand and use the grid to “store” excess production to make up for hours 

without sufficient on-site renewable generation. This paper looks at simple metrics to evaluate 

the alignment of renewable sources and storage with building loads. This process can provide 

insights on building design considerations, including the use of flexible loads and optimal 

resource management and will improve with better data and analysis techniques. 

Background

Today’s buildings are much more energy-efficient than those of 40 years ago, thanks to 

improvements in high performance heating, ventilating, and air-conditioning (HVAC) systems; 

lighting systems; and electrical equipment combined with tighter, better-insulated thermal 

envelopes with advanced glazing. Even though energy efficiency has improved, greater overall 

energy consumption reductions are needed as the number of buildings continues to increase. 

In other words, the rate of deployment of energy efficiency and on-site renewable energy 

is being closely matched with addition of new conventional buildings (EIA 2020). The utility

grid responds to the needs of the buildings adding and subtracting generation capacity and as 

buildings demand resources at different times of day—particularly in the late afternoon. This, 

largely driven by air-conditioning, has reduced the capacity factor of the grid over the last 50 

years from 70 percent to near 40 percent—in other words, buildings produce higher peaks for 

shorter periods of time (EIA 2019). 

Buildings have impacts beyond energy consumption. They use land and material 

resources for construction and ongoing maintenance and occupants use transportation, material, 

and food resources, all of which have a substantial impact. 
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The concept of a net-zero, zero-net, or zero energy (ZE) building that can fulfill its 

intended purpose without negative environmental impacts—and perhaps have a positive 

environmental impact—is compelling. Energy efficiency has its roots in the notion that using 

energy resources to power buildings has negative environmental impact. Energy has long been a 

surrogate for environmental impacts ranging from water and air quality, mercury and sulfur 

release, nuclear radiation and waste production, habitat destruction, and, more recently, carbon 

emissions (CO2e). The idea is that if less energy is consumed, the environmental impact because 

of building operations can be reduced. 

The thought experiment of imagining a building with no or minimal energy impact 

yielded the concept of a balance—extremely energy-efficient buildings could produce as much 

energy as they consume by adding on-site renewable energy sources, usually solar photovoltaics 

(PV). To validate this ZE concept at scale, Griffith et al. (2006, 2007, 2008) examined the entire 

commercial sector with a comprehensive energy model to determine which building types could 

achieve ZE and what levels of energy efficiency were needed to achieve that goal. The study 

found that the concept was technically feasible for significant portions of the commercial sector, 

including educational buildings. The study also determined that with moderate levels of 

efficiency, there are enough rooftops to power the built environment. 

A framework emerged around the effort to define these ZE buildings and included the 

development of calculation methods, led by the U.S. Department of Energy, with the goal of 

achieving consistent and widespread industry adoption (DOE 2015; Torcellini et. al. 2006; Pless 

and Torcellini 2010; Torcellini et al. 2016; Peterson et al. 2016). This common version 1.0 

definition states that a ZE building is “An energy-efficient building where, on a source energy 

basis, the actual annual delivered energy is less than or equal to the on-site renewable exported 

energy” (DOE 2015). This definition is not limited to buildings; it can also apply to campuses, 

communities, portfolios, or any other specified boundary as discussed further by Polly et al. 

(Polly 2016). In locations where on-site renewables installations are limited by utilities, policies, 

or economics, the building can be designed to be ZE Ready—that is, it is highly energy-efficient 

and ready to accept a solar system when circumstances allow. These definitions have been the 

foundation of the industry and are still very relevant as a vast majority of buildings are not 

zero—somewhere in the order of 2000 for commercial buildings and 22,000 for residential 

buildings (NBI 2019; TeamZero 2020). 

The interest in very low energy buildings and ZE buildings is growing. For example, 

California adopted ZE targets for 50% of the floor area of existing state-owned buildings by 

2025 and for all new or renovated state buildings beginning design after 2025 (SAM 2017). 

California has also set a target of making all new commercial buildings ZE by 2030 (CPUC 

2011). Several other states are thinking along the same lines and have established task forces that 

are working on the issue. Much has been written about what ZE buildings are, and the idea of a 

measurable, achievable ZE goal is taking hold in the marketplace (Liu et al. 2017; Torcellini et 

al. 2016). The zero energy building concept is simple and easy to understand and the version 1.0 

definition is valued across the high-performance buildings sector. 

Zero Energy Buildings Version 2.0 

An end goal is to create buildings that are environmentally benign, which may require 

giving back such that a building’s net operational impact is environmentally positive. This 

regenerative state represents buildings that can improve the environment rather than be neutral 

(sustainable) or cause resource depletion or environmental damage. This long-term goal has 
3 

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manifested itself in different goals and concepts over the last 40 years, including reducing the 

consumption of fossil fuels (for air and water pollution concerns as well as economic and energy 

security) to comfortable, healthy, high-performance buildings to climate change mitigation 

strategies, including carbon and refrigerants. More recently, DOE has expanded the 

understanding of Grid-interactive Efficient Buildings (GEB)1 as an energy-efficient building that 

uses smart technologies and on-site distributed energy resources to provide demand flexibility 

while co-optimizing for energy cost, grid services, and occupant needs and preferences in a 

continuous and integrated way.2 The GEB initiative focuses on buildings becoming smarter 

about the amount and timing of energy use, but ZEB 2.0 expands on these concepts and focuses 

on stakeholders that choose off-site and on-site renewable generation and shifting from ZEB 1.0 

accounting that nets out over the course of a year to a goal that aligns available renewables with 

building loads during a full year, which can be simplified to: 

100% renewable energy, 100% of the time 

provided that the renewable resources do not create additional issues related to the environmental 

goals. 

Although 100% renewable energy, 100% of the time is a difficult goal to achieve today, 

the process of achieving this goal provides the foundation for the next 20 years of ZE buildings, 

much like the current static balance definitions defined the last 20 years. Some organizations 

have expressed interest in this goal, including working through storage issues.3

ZEB 2.0 requires buildings to be designed and operated, and their equipment selected, so 

that a ZE building’s demand profile closely matches renewable supply profiles. In other words, 

buildings should focus on demand side management, but also address when energy is consumed 

and not just how much energy is consumed. Note that in this ZEB 2.0 future, the goal is not for 

every building to be “off-grid.” In this future, the grid would provide critical backup for 

individual buildings as well as a way for a building to back-feed renewables to offset the hours 

that the sun is not shining and the wind is not blowing, as well as providing additional grid 

services and utility cost reduction operations. 

Development of Effective Metrics, Boundaries, and Zero Energy Definitions

All building design decisions influence energy use and can have environmental impacts. 

Building design has a profound impact on how much energy a building requires to operate. The 

goals established and the metrics used to evaluate the progress toward a goal need to influence 

those that make decisions that impact the environmental outcomes. This is done with the span 

and control of all decision makers, which can be anyone who has interacted with a building 

project. This includes designers, occupants and building users, contractors, and building owners, 

at a minimum. Fundamentally, the creation of an energy definition (including a zero energy 

definition) has two parts—establishing a boundary and establishing energy metrics that are 

measured as they cross that boundary. Some rules include: 

1 https://www.energy.gov/eere/buildings/grid-interactive-efficient-buildings

2 https://www.nrel.gov/docs/fy20osti/75478.pdf

3 https://storage.googleapis.com/gweb-sustainability.appspot.com/pdf/24x7-carbon-free-energy-data-centers.pdf; 

https://www.pv-magazine.com/2019/01/04/off-grid-swedish-housing-block-to-be-supplied-100-by-pv-hydrogen/
4 

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• Energy flows of interest are measured as they cross the boundary. In general, these 

energy flows of interest are the commoditized energy sources such as electricity to

and from the utility grid and fossil and other fuels delivered (such as wood chips). 

Energy at the point of delivery is a common energy metric that can be measured 

effectively with conventional metering technologies. 

• Other metrics, such as CO2e, source energy, and primary energy are calculated using 

methodologies based on the site energy measurements. These metrics are based on 

models relating site energy to that metric.

• Boundaries are most easily established at the point of metering. This is typically the 

utility electric meter, the gas meter, or the delivery point of fuels such as propane and 

oil. For the last two, the storage tank can represent an issue for the balance depending 

on its size and the variation of the level of the fuel in the tank, in which case an 

alternative is to measure the fuel leaving the tank. 

ZEB 2.0 metrics should: 

• Influence design decisions such that the building has the potential to move towards 

the metric of interest, such as “save as much energy as possible” 

• Result in a well-designed building such that operators can more easily operate the 

building to its energy savings potential and understand how the ongoing operations 

align with the design metrics

• Move towards 100% renewables, 100% of the time. 

Boundaries need to be well established as a measurement point of the metric. Although this 

paper will generically refer to the building as the boundary location, it can be described a number 

of ways, including: 

• At the building site—typically at a point of metering

• A building portion that operates autonomously, e.g., a store within a retail strip mall

• A group of buildings that has logical interconnections and adjacency, in other words, 

a development district or a campus 

• A community of buildings including subdivisions and neighborhoods 

• Larger boundaries including towns, cities, and even states or utility balancing regions 

• A portfolio of buildings owned by a single entity such as a chain retail store.

The boundary chosen is often a function of the “span and control” of the building or 

collection of buildings. A building owner or tenant may be interested in just their space while a 

larger corporation or governmental authority may have a corporate commitment to purchase 

renewables for all their buildings. All levels are critical to achieve scale. Metrics that struggle at 

a building level will face similar struggles at multibuilding scales. Solutions that do not work at a 

building level can benefit from multibuilding scales and the metrics must recognize this. 

Independent of the boundary selected, the measurement techniques and metrics are the same.

Many of these secondary metrics require models that change independently of what is 

happening in the building (both in design and operation). Care must be exercised in metrics when 

externalities can influence the ability to meet a metric over time. For example, if the calculation

methodology changes or a boundary changes, then a building may fall in or out of “compliance” 
5 

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with no adverse action of the design team or the building operators. Examples might include 

changing the utility balancing regions for a carbon metric or changing from a fossil fuel 

equivalency to a captured energy equivalency for site to source calculations. 

The first generation of energy flow diagrams for ZE buildings did not account for electric 

vehicles or storage within the building. Figure 1 shows the current accounting for energy flows. 

Although transportation within the boundary was considered—elevators, forklifts, etc.—the 

notion of a large number of electric vehicles was not considered. Vehicles used exclusively 

within the boundary should be considered a building load, and vehicles that can leave the 

boundary are external to the boundary. Note that there is a provision for charging and 

discharging electric vehicles as well as an indication of on-site fixed storage, which is inside the 

boundary, much like on-site transportation. After electric vehicles, buildings can interact with the 

“grid” through the electric utility, delivery of fuels (including natural gas and oil), and delivered 

renewable fuels including biogas and wood products. Electricity exported to the utility grid 

should be from a renewable energy source. 

Figure 1. Energy flows across and within a boundary for an accounting system for a zero energy building.

Each energy flow can have an associated conversion ratio to alter the site energy to 

another metric. Historically these metrics have been source energy, CO2e, and energy costs 

(Pless 2009; DOE 2015). Expressing the energy balance in Figure 1: 

EEnnnnnn = ∑ �∑ �EE�ttjj�

dd dd,ii

rr�ttjj�

dd dd,ii

� − ∑ �EE�ttjj� eeeeeeee ,iirr�ttjj� eeeeeeee ,ii� TT/∆

jj=1

TT/∆

jj=1 � nn

ii Eq 1

Where

EEnnnnnn is the net delivery of energy or another metric through the conversion ratio 

r. 

EE�ttjj�

dd dd,ii

 is the delivery of energy type i at time step j
6 

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EE�ttjj� eeeeeeee ,ii is the export of renewable energy type i at time step j

rr�ttjj�

dd dd,ii

 is the delivered conversion ratio of energy type i at time step j

rr�ttjj� eeeeeeee ,ii is the exported conversion ratio of renewable energy type i at time step j 

n is the number of fuel sources that are measurable crossing the boundary. 

Table 1 compares the original concepts of ZE buildings as being strictly a balance of 

energy flows over a one-year period or longer. To align renewable resources with consumption, 

the renewable energy and storage must be valued as part of the consumption. Ironically, in a 

typical measurement of building energy, storage is often a drain on energy performance even 

though it will help align the renewable energy with the consumption. Version 1.0 represents the 

concepts of Pless (2010) where energy flows in and out of the boundary are not dependent on 

time or direction. Through application of this framework others have established time-fixed 

discount factors based whether is entering or leaving boundary and based on the proximity of the 

renewable resource to the building.4

 This accounts for direction through the utility meter and at 

a simplistic view can potentially represent the losses in the utility transformer and the 

distribution losses associated with moving the renewable energy to another consumer. To scale 

ZE for large markets and better align building energy consumption with renewable production, 

renewable energy must be valued at least at the building scale and, if data are available, at a grid 

scale. This provides the mechanism to measure whether a grid-connected building is 100% 

renewable, 100% of the time. 

Evaluation Metrics

ZEB 1.0 buildings represent the current state of the art. Although they are still a niche 

market, the values of r assume energy balance over a long period of time. There are three areas 

of focus in moving ZE to the mainstream: (1) ability to scale the concept; (2) ability to achieve 

100% renewables, 100% of the time; and (3) ability to maintain a simple concept of balance to 

maintain market acceptance. Note that these metrics are not an overall evaluation tool to assess a 

building, but a framework to examine the ability to balance and align consumption to renewable 

generation. The metrics are foundational to balancing building energy and not determined by 

market factors. Voss (2010) examined several metrics and the alignment of renewable resources 

to match the load. Two metrics, solar use index and load coverage factor, are used in this paper 

to help describe the relationship of generation to consumption. 

Solar Use Index (SUI): Percentage of on-site solar energy that is used at the time of generation 

for direct use in the building. 

SSSSSS = ∑ PPii,oooooo∆ TT/ΔΔ

ii=1

∑ LL(ii) TT/ΔΔ

ii=1

 Eq 2

or 

4 ASHRAE Standard 189.1 (https://www.ashrae.org/technical-resources/standards-and-guidelines/standardsaddenda/addenda-to-standard-189-1-2017), LEED Zero (https://www.usgbc.org/programs/leed-zero) and 

International Living Future Institute (https://living-future.org/zero-energy/) have all looked at ways of valuing 

renewable resources based on location.
7 

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SSSSSS = ∑ PPii,oooooo∆ TT/ΔΔ

ii=1

∑ �PPii,iiiiii ii∆ +PPii,oooo ∆ −PPii,eeee ∆ � TT/ΔΔ

ii=1

 Eq 3

Where 

Pi,osr= the power from the on-site renewables at time step i, 

Pi,import= the power imported from outside the energy boundary at time step i,

Pi,export= the power exported from inside the energy boundary to outside at time step i, 

L = Energy Load for timestep i or LL(ii) = PPii,iiii ∆tt + PPii, oo ∆tt − PPii, eeeeeeee ∆tt

∆t = the length of time of the time step i. 

T = the total time of the evaluation.

Equation 3 is useful as most electronic utility meters integrate the power to energy by 

tracking the flow of the power, either receiving electricity from the grid (“buy”) or sending 

electricity to the grid (“sell”). Equation 3 is easy to implement with monthly meter bills and the 

amount of renewable energy produced during the same period as the utility meter bills. A larger 

SUI indicates that on-site renewables are better used in the building versus exporting the excess. 

Low SUI, combined with net metering, indicates that the grid is being used as a virtual battery. A 

high SUI can also be achieved with small renewable systems indicating full use of the solar but 

will not meet the building’s energy needs in the context of a ZE building. Therefore, the load 

coverage factor (LCF) is an effective metric to complement the SUI.

Load Cover Factor (LCF): Percentage of the building load that is powered by renewable energy. 

LLLLLL = ∑ ��PPii,oooooo∆ �,LL(ii)� TT/ΔΔ

ii=1

∑ LL(ii) TT/ΔΔ

ii=1

 Eq 4

This equation can be expanded to account for off-site renewable energy on the utility grid to: 

LLLLLL = ∑ ��PPii,oooooo∆ +aaaa (LL(ii)−PPii,oooooo∆ )(%RREEGG GG(ii)

100 )�,LL(ii)� TT/ΔΔ

ii=1

∑ LL(ii) TT/ΔΔ

ii=1

 Eq 5

NREL/CP-5500-77013

Where: 

%REGrid = Percent of energy from grid-supplied renewable energy 

T = Total Time Under Consideration 

∆t = Time Step 
8 

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Table 1. Comparison of the development of zero energy definitions moving towards 100% 

renewables 100% of the time where r is a conversion ratio of the fuel source 

ZEB 1.0 

(limited market scale)

ZEB 2.0

(large market scale with the ability for full market 

adoption)

On-building

renewable 

energy

r=constant 

r=same for import and export

Classification A.5

A+ is no import, only export

r(import)>r(export)

Renewable energy valued if it can be used within the 

building at the time of generation. Building loads, 

including storage, can shift to use this resource. 

Note that values of r can account for inefficiencies of 

transformer/distribution losses of selling and buying 

back power or provide benefits of a system level 

optimization on efficiency, dispatch, or other metrics 

such as emissions. In this case is it possible for 

r(import)>r(export).

Renewable 

Resources not 

directly on a 

building or 

multiple 

buildings

Full credit to site (Classification B)

r=constant

r(import)>r(export)

Renewable energy valued if it can be used within the 

building at the time of generation. Building loads, 

including storage, can shift to use this resource. 

Note that values of r can account for inefficiencies of 

transformer/distribution losses of selling and buying 

back power or provide benefits of a system level 

optimization on efficiency, dispatch, or other metrics 

such as emissions. In this case is it possible for 

r(import)>r(export)

Grid level 

renewable 

energy

Full credit to site (Classification D)

=constant

Remainder of building load can shift to use available 

renewable energy resource. r is time dependent based 

on grid renewable availability—numbers based on 

long term renewable energy profile for planning or 

real-time data for actual performance.

Electric 

vehicles

r=constant Can provide additional load shifting capabilities based 

on the balance between the building needs and 

renewable availability.

The LCF equations indicate the percentage of the load that is met by renewable energy, 

either on-site or off-site. High values of LCF indicate large contributions of renewable energy to 

meet the load and that the building load matches the renewable resources available. Note that 

while the optional %REGrid term brings in externalities not in the designer’s control, it can 

enable better use of renewable grid resources encouraging designs to increase energy 

consumption when renewable energy is available shifting that load from times when renewable 

energy is not available. Energy efficiency is a key part of making a high load coverage factor 

possible. The concept of 100% renewables, 100% of the time equates to an LCF of 100%. For 

buildings that are exactly “zero” or for grid independent buildings, the two factors are identical. 

Although the SUI can use information readily available on utility bills and renewable 

consumption, the LCF requires that data in small time intervals in order to account for the 

branching of how renewables are used during that time period. In addition, both electricity 

imports and exports can apply to % RE from the Grid if a project is seeking to balance the 

impacts from both imports and exports. 

A key component of the LCF metric and ZEB 2.0 is the consideration of hourly 

renewable energy contribution from the grid. To enable building designers to consider this 

5 Classifications are adapted from (Torcellini 2006 and Pless 2009)
9 

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contribution over the lifetime of the building, regional grid planning hourly multipliers are 

needed. One future source of projected renewable energy data is expected to be available through 

the NREL Cambium project. The Cambium project is aiming to produce grid price and 

emissions data sets through 2050 based on the NREL Standard Scenarios across each region of 

the U.S. power grid (Hale 2019). An alternative is to have a mechanism to guarantee the 

purchase of off-site renewable energy based on both quantity and time. As ZEB 2.0 projects are 

designed and built, measuring success towards the 100% renewables, 100% of the time goal will 

require alignment and measurement of the renewable energy on the utility grid or the ability to 

only export energy from the building, either to the grid or other resources such as electric 

vehicles. This last concept is consistent with the highest classification of ZE in earlier

frameworks (Pless 2010). Emerging operational metric and evaluation systems such as 

GridOptimal6 can provide approaches to consistently measure a building’s progress toward ZEB 

2.0. 

Figure 2. Example data for the load coverage factor (top) and the solar use index (bottom). (Figures created by 

Amanda Farthing, NREL)

Examples of Metrics Applied to Zero Energy 

6 https://newbuildings.org/gridoptimal-metrics-offer-guidance-on-optimizing-building-grid-interaction/
10 

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Figure 2 shows a one-day example of the LCF and the SUI. The LCF focuses on the 

percentage of the load that is provided by solar while the SUI focuses on the percentage of solar 

energy that is used. In this one-day data set, 63.7% of the PV renewable energy is used in the 

building at the time of generation, the rest is exported to the grid, presumably to be purchased 

later through a net meter. During this day, only half the energy is produced by the renewable 

resource, indicating a poor alignment of the building load with the renewable resource. 

Using data from a ZE house with a 9 kW PV array, Figure 3 shows the cumulative house 

consumption is shown as the blue line and the cumulative energy produced by the PV system is 

indicated by the orange line. The difference is either the net energy flow to the utility with the 

utility acting as a “virtual” battery for the net meter or, if the house was “off-grid,” it would 

represent the home’s storage requirement. In the past, this type of analysis has been used to size 

PV and battery systems for “off-grid” houses. For this all-electric house, the maximum delta seen 

by the utility is 2250 kWh. The amount of storage needed peaks on October 15, when the 

balance shifts from overproduction of the PV panels to the need to provide heat for the house 

coupled with less solar availability. As the lines do not cross, the storage is needed for the entire 

year due to the exact match of production and consumption. For this house, the SUI is 17% 

meaning that only 17% of the energy produced is used in the house at the moment it is generated. 

In other words, 83% of the power is exported to the grid and then purchased back at a later time. 

If the grid cannot accept the power or it has limited value, then additional storage may be 

warranted. The storage is 22.5% of the total energy consumption of the building for this 

example.

Figure 3. Energy used and energy generated for a zero energy house over a 1-year period cumulatively 

summed. 

The LCF metric provides a different viewpoint of achieved success in ZEB 2.0 buildings. 

An example analysis outlined in Figure 4 illustrates the potential of using thermal energy storage 

(TES) to meet various end-use loads for various example building models. The building models 

have enough on-site solar PV generation to meet ZE requirements on an annual basis, and TES is 

used to move towards meeting loads 100% of the time. The TES model is based on a daily 

predictive method, where the anticipated evening/nighttime end-use energy is predicted, in 

addition to peak solar generation times during each day. The algorithm stores peak surplus solar 

power during the day and meets the corresponding end-use loads during insufficient or no solar 

production periods. The modeled TES ultimately maximizes the LCF metric.

0

500

1000

1500

2000

2500

2/14/17 5/15/17 8/13/17 11/11/17 2/9/18 5/10/18

Net Cumulative Energy 

Storatge (kWh)

Date (Time)
11 

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One immediate observation from this example analysis is the relatively high potential for 

TES in aligning water heating loads with generation in the multifamily and single-family 

building types. In addition, the cumulative TES potential for increasing the LCF across the 

different building types varies and has the least impact on building types with inherently 

coincident temporal operations with solar generation, such as offices (~ 6% increase in on-site 

LCF) and malls (~6% increase in on-site LCF). In contrast, building types with higher 

occupancies during low or no solar generation periods typically exhibit a stronger potential, such 

as lodging (~20% increase in on-site LCF), food sales (~15% increase in on-site LCF), and 

multifamily (~12% increase in on-site LCF) buildings. A similar analysis can be performed to 

understand the technical potential and requirements for batteries to maximize the LCF metric. 

Figure 5 illustrates load duration curves of an example office building model with a battery and 

associated control scheme that stores any surplus on-site power and discharges the battery to 

meet the load. The battery model dedicates a portion of the total battery capacity towards load 

shifting (75%), and the remaining portion (25%) towards peak demand management. 

Transitioning from the baseline model to ZE V1.0 drastically reduces the peak import power 

(positive power values in Figure 5 indicate a power import) and introduces a high number of 

export power durations and amplitudes. Transitioning towards ZEB 2.0 by increasing battery size 

results in more hours of the year being balanced with on-site assets. Figure 5 demonstrates the 

nonlinear relationship between LCF and battery size, and the reduction in peak demand 

associated with ZE, TES, and increased battery size. 

The influence of energy storage and load to renewable generation mismatch shows the 

issue that buildings, especially ZEB 1.0 buildings, have low SUI and LCF. ZEB 1.0 benefited

from using the utility grid as an infinite storage mechanism to create a balance. The result is 

limitations on the ability to scale ZE buildings and increase renewable penetration. Tools exist 

today to move towards an alignment of loads. The typical utility meter has the ability to 

segregate total values for energy delivered and energy exported over a billing cycle. Although it 

is called a net meter, meters log imports and exports separately and a subtraction is done at the 

billing cycle. This provides a level of complexity in aggregating values that is transparent to the 

user of the metrics. It also provides an easy way to create incentives to better use on-site 

generation by changing the buy and sell rates (the value of r in and out) to provide market drivers 

for design strategies that better align renewables with storage. 

In addition, delivery of fuels also provides an energy value. A complexity arises with 

propane and oil as that energy is often stored in a tank, which acts as a storage element within the 

boundary. Either the assumption is made that the storage levels in the fuel tanks and battery 

storage are the same at the beginning and end of the period, or these need to be factored into the 

equation. Typically, battery storage has not been significant compared to the total throughput of 

energy and tanks are limited to buildings with significant oil tanks. Propane tanks typically are 

not as large and are insignificant to the total energy flows. 

For electricity, the impact of storage is at the time that the storage is charged both on an 

energy and an emissions level. From this perspective, values of r are dependent on the time a 

load occurs, including the storage elements. Charging storage when on-site renewable energy is 

available (reducing the export), the energy value and the emissions value is high. This high value 

energy can be used at a time when on-site energy is not available. The time of discharge is not 

needed in the accounting system. Today, renewables from buildings can be exported to the grid, 

although in some locations excess instantaneous renewable energy is not allowed, and this 

energy must be curtailed (lost) or stored. The idea of the next generation building is to reduce the 
12 

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

dependence on the “net” at some boundary scale, which is probably larger than the building to 

maximize flexibility and diversity of the load. The LCF allows this to be measured. Ultimately, 

this is what building designers can control today as buildings are designed for the future. 

Figure 4: Example analysis of the calculated load cover factor metric as thermal storage is added to store 

excess solar power to meet cooling, heating, and water heating end uses (note LCF is displayed from 40 to 

70 do visualize detailed differences) 

Figure 5. Net load duration curves (positive power indicates a power import) of an example office building 

model for the following cases: 1) Baseline model without on-site generation or storage 2) ZE office model 

without storage, 2) ZE office model with TES for heating, cooling, and water heating end uses, and 3) ZE

model with both TES and battery storage of various sizes

Conclusion 

With the advent of inexpensive renewables and the ability to create very low energy 

buildings, ZE buildings are gaining market traction largely based on definitions that have been 

used for 10 to 20 years. These equations conceptually looked at balancing the renewable energy 

supply with the demand. Many of the current generation of ZE buildings have a large mismatch 

between the renewable generation and the building consumption, which limits the effectiveness 

of the balance. A key ZEB 2.0 goal is to create buildings that use 100% renewables, 100% of the 
13 

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

time, which is a step beyond the current ZE metrics of site energy, source energy, or carbon. For

market acceptance to persist and grow, ZE must be easy to measure. Successfully meeting the 

ZE goal must be dependent on the design and operational characteristics of the building. 

Although complexities can be introduced that attempt to evaluate the building with respect to the 

utility grid, simple metrics can address the need to evaluate the alignment of the renewable 

resource with the building. Two such metrics, renewable use index and load coverage factor, 

help address the need. As consistent hourly marginal and average grid site to source multipliers 

and off-site renewable energy accounting are developed for both operational use and long-term 

building design planning, ZEB 2.0 buildings can be designed and operated at scale and balance 

loads with both on-site and grid-scale renewables.

With technology advancement, cost reductions and innovative business model 

development, on-site and off-site advantages will continue to evolve. Stakeholders will pursue all 

renewable generation locations that fit their needs. This paper is focused on circumstances where 

stakeholders mainly have a preference for on-site scenarios, because of various reasons, such as 

improving resilience. It also provides methods for recognizing off-site renewable contributions. 

At minimum, it is important to consider on-site scenarios for establishing aggressive, but 

achievable building performance goals based on local renewable potentials. 

Ultimately long-term market signals that are stable and trustworthy will make 

investments in ZE buildings a reality. Using this framework, we can use the built environment to 

regenerate and transition buildings from consumers to producers that can respond to available 

renewable resources. 

Acknowledgment

This work was authored in part by Alliance for Sustainable Energy, LLC, the manager 

and operator of the National Renewable Energy Laboratory for the U.S. Department of Energy 

(DOE) under Contract No. DE-AC36-08GO28308. Funding provided by U.S. Department of 

Energy Office of Energy Efficiency and Building Technology Office. The views expressed in 

this paper 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. The authors also wish to recognize Amanda Farthing who participated in creating 

early analysis and graphics for this effort.

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