Decarbonizing the Built Environment | Maximizing Avoided Emissions

Decarbonizing the Built Environment

MAXIMIZING AVOIDED EMISSIONS

AN ELEMENTA ENGINEERING WHITE PAPER

Contents From Energy to Carbon

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Future Hourly Marginal Emissions

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It’s About Time

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Generation is not Enough

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Automated Dispatch Logic

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Shifting the Load Curve

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Summary and Findings

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Discussion and Outlook

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Front Cover and inside Back Cover Hourglass in red leather covered case, second of two views. Credit: Wellcome Collection.

Attribution 4.0 International (CC BY 4.0)

From Energy to Carbon It is time for a more robust and holistic measure of a building’s climate impact.

SHRESTH NAGPAL AND RUSHIL DESAI

The traditional metrics of reductions in site energy, source energy, and energy costs - that have served as benchmarks for high performance buildings for decades – no longer provide a comprehensive picture of a building’s true environmental impact.

Greenhouse gas emissions intensity (GHGI) associated with building energy use is, given what we know1, the pertinent metric to quantify building operational performance.

In fact, many local jurisdictions and institutions now identify the importance of reducing a building’s GHGI and are beginning to incorporate this into their programs and legislation. New York City’s Local Law 972 passed in 2019 aims to achieve a 40% reduction in GHG emissions from 2005 levels by 2030 and 80% by 2050, through absolute GHGI targets for buildings. Similarly, City of Berkeley’s Climate Action Plan3 aims to achieve a 33% reduction from 2000 levels by 2020 and 80% by 2050.

Shreshth Nagpal Principal at Elementa Engineering, New York, NY Shreshth’s professional focus over the past fifteen years has been to understand and model building performance that results from the interaction between envelope configuration, climatic context, functional requirements, conditioning systems, and occupant behavior.

The first step towards decarbonization is designing buildings that successfully respond to the constraints and opportunities of the local climate, passively maximize occupant comfort, eliminate energy waste through user engagement and controls, and incorporate high-efficiency energy systems to meet the demand remaining after passive design and load reduction strategies.

The second step is designing all-electric buildings. Since electricity is the only energy source that can realistically be completely carbon-free, electrification is the only credible path towards meaningful decarbonization of the built environment.

When full electrification is not feasible at present, it is imperative to plan a transition away from all on-site fossil fuel consumption in a building’s design.

The intent of this paper is to build upon these two widely recognized premises and focus on the third - relatively unexplored and poorly understood - strategy of demand management and load shifting of grid-purchased electricity. This paper will show that not only can load-shifting avoid significant grid emissions already, it can allow for a building’s GHGI to drop sharply even when it consumes a non-trivial amount of energy. This becomes especially relevant as the future grid gets cleaner.

It is time we moved past building energy metrics, it is time we focused on Avoided Emissions as a building performance metric and a more robust and holistic measure of a building’s climate impact.

Rushil Desai Building Performance Analyst at Elementa Engineering, New York, NY Rushil is a specialist in ‘Net Zero Energy’ buildings, electrification and decarbonization, building to grid interoperability, and urban scale energy modeling.

Future Hourly Marginal Emissions It is vital to recognize that the true GHGI of a building is affected not only by the magnitude of its energy use but also the periods during which it draws electricity from the grid.

The ability to reduce building electricity demand during such high emissions intensity hours, therefore, offers the largest GHGI avoidance.

Second, in addition to accounting for current variations in grid emissions on an hourly basis, it is important to consider how the rapidly changing grid is expected to evolve over the next few years.

This is because the grid’s energy generation mix varies throughout the day. While the traditionally employed annual average factors represent grid emissions from the corresponding generation mix over a year, actual emissions associated with generation respond to variation in demand for every hour. It is, therefore, imperative to consider marginal hourly profiles4 instead of an annual average factor when assessing the true GHG avoidance impact of design strategies.

For example, the dotted lines in Figure 1 compares 2030 grid GHG factor projections against 2020 factors. As the future grid gets cleaner and daytime factors approach zero due to high solar energy penetration, it will in fact be possible for a building to achieve zero-carbon operations if it can shift its load to only draw from the grid during these daytime hours; and carbon-positive operations if it can then feed surplus energy back into the grid during high intensity late afternoon hours.

Figure 1 illustrates this difference for a reference project, where the annual average emission factor for grid electricity is published at 0.13 MTCO2e/MWh, and the published marginal emissions factor can be 6 times higher at 0.78 MTCO2e/MWh for peak hours during a summer week.

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Figure 1: The difference between annual average and marginal hourly emission factors for 2020 and the marginal hourly emission factors for 2020 and 2030.

Decarbonizing the Built Environment

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It’s About Time in combination with hourly energy generated to calculate annual total GHG avoidance.

Even in the present scenario, a west facing kW of PV with peak generation in the late afternoon hours avoids more GHG than an east facing kW, although its net generated energy is lower.

This gets especially pronounced in the 2030 scenario when the west kW avoids GHG emissions more than the roof kW, even when it only generates less than half of the energy.

These strategies can take the form of efficiency measures, generation, or load-shifting measures that displace the time of peak building energy demand.

For instance, a thermally massive building envelope can flatten the demand curve and shift as well as reduce the peak; on-site renewable generation systems can be optimized for peak generation during hours of high availability; and a loadshifting strategy such as thermal or electrical battery can draw more power from the grid during hours of low grid emissions intensity and dispatch to offset the project demand during hours of high emissions intensity.

As the future grid gets cleaner and the daytime marginal emissions approach zero in 2030, the significance of on-site renewable energy generation during the same daytime hours will drop considerably.

In this future scenario, it will become increasingly important to combine on-site renewable generation with load shifting strategies that charge during hours of low grid emissions, and then dispatch to offset grid draw during hours of the highest grid emissions. Without careful planning, even large magnitudes of on-site renewable generation could offer only minimal GHG emissions avoidance.

To illustrate the magnitude of GHG avoidance that can be achieved just by optimizing the hours of grid energy draw, Figure 2 presents the energy generation as well as GHG avoidance potential of three identical photovoltaic systems installed at different orientations.

As the grid gets cleaner, Net-Zero-Energy will be far from Net-Zero-Carbon.

The analysis considers hourly marginal GHG emission factors

Generated Energy MWh 18

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Figure 2: Energy generation and GHG avoidance potential of three identical photovoltaic system capacities facing different orientations for present and future scenarios. Energy offset in the late afternoon hours offers significantly higher GHG avoidance, especially pronounced in the future.

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West

Maximizing Avoided Emissions

Given that grid emissions have a temporal component to them, the focus needs to be on strategies that offer energy savings during specific hours of high grid emissions intensity.

Generation is not Enough As illustrated in Figure 3, the reference project where the daily demand peaks at about 4.5 MW during weekdays. The project incorporates a 2MWp rooftop PV array that offsets daytime project energy use and offers roughly a net 24% reduction in energy.

Using the grid intensity profiles from Figure 1, this level of generation translates to just about 12% reduction in project GHGI in 2020 and drops by another half to just about 6% in 2030. To reiterate, a 24% renewable energy offset will only avoid 6% of annual GHG emissions as the grid gets cleaner.

To ensure that energy offsets coincide with the hours of maximum GHG intensity, there is a need for a dispatch algorithm that can simultaneously look ahead at the building demand and marginal grid emissions factors, and enables a battery bank to charge and discharge optimally to minimize or eliminate drawing from the grid during high emissions intensity hours.

ELECTRICITY (kWh)

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Grid to Project PV to Project

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PV GHG Avoided GHG Emissions

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PV GHG Avoided GHG Emissions

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Figure 3: Electricity demand profile for the reference project during a typical summer week showing on-site PV generation that offsets 24% of the energy use [Top] but avoids only12% of GHG Emissions in 2020 [Middle] and only 6% in 2030 [Bottom].

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Automated Dispatch Logic The control logic then signals the battery bank to set its state to “charge” or “dispatch” for each hour to ensure that electricity is drawn from the grid during low emissions intensity hours and fed back into the grid during high intensity hours, as far as possible. Figure 4 graphically represents this dispatch sequence for the 2020 and 2030 scenarios.

An automated dispatch sequence configured this way is employed to parametrically study GHG avoidance from different PV and battery system capacity combinations, for different demand and emission profiles.

While the objective for this study was to minimize GHG emissions, the control sequence can as easily be adapted to minimize peak demand or time-of-use energy costs.

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Figure 4: Graphical representation of deployed dispatch sequence design to set the battery to ‘charge’ state during periods of low grid emissions intensity and to ‘dispatch’ state when the grid is dirtier. For 2020 [Top] and 2030 [Bottom] scenarios.

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Maximizing Avoided Emissions

To be able to quantify the magnitude of GHG emissions that can be potentially avoided by load shifting, we developed an automated dispatch logic that tracks and forecasts building electricity demand, renewable generation potential, and grid marginal emissions on an hourly basis for up to 7 days at a time.

Shifting the Load Curve Since grid marginal emissions are lowest during mid-day, a battery bank can shift the hours of grid draw by charging during these low emissions hours and dispatching to meet the project demand during high emissions hours.

Figure 5 shows the result of implementing the previously discussed dispatch sequence that tracks project demand against the grid emissions profile.

By shifting the renewable energy offset period to high GHG intensity hours, a 2 MW battery bank increases the GHG avoidance from 12% to 18% in the 2020 scenario.

The impact of the same 2 MW battery bank, using the same dispatch sequence, increases significantly as the relative difference between clean and polluting periods gets more prominent.

In the 2030 scenario, presented in the bottom chart in Figure 5, with everything else held constant, GHG avoidance increases over five-fold from 6% to 32%.

ELECTRICITY (kWh)

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Grid to Project Battery to Project PV to Project Grid to Battery PV to Battery

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PV GHG Avoided

2020 GHG (kgCO2E )

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Battery GHG Avoided GHG Emissions

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Figure 5: Hourly energy balance with 2 MW PV and 2 MW battery bank that offset 24% of project energy use [Top], increase the GHG avoidance from 12% to 18% in 2020 [Middle], and a five-fold increase from 6% to 32% in 2030 [Bottom].

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Summary and Findings This trend, illustrated in Figure 6, is amplified even further with a 4 MW bank with 22% avoidance in 2020 increasing to a massive 48% in 2030.

The 12% GHG avoidance for the generation only scenario drops to about 6% in 2030 as the grid itself gets cleaner and the contribution of on-site renewable generation to GHG avoidance diminishes because it provides a benefit during the same hours as when the grid is cleaner; the 18% GHG avoidance with the 2 MW battery bank increases to 32% in 2030.

Although increased battery bank sizes only have limited impact on GHG avoidance in the present-day scenario - with avoidance increasing from 18% with 2MW to just over 22% with a 4 MW battery bank - GHG avoidance increases sharply for the 2030 scenario, from 32% with 2 MW to 48% with a 4 MW battery bank.

As the future grid gets cleaner with increased renewable penetration during daytime hours, strategies that allow for optimal load shifting from polluting early mornings and late afternoons to cleaner mid-day periods will become exceedingly important. In this case, a 24% renewable energy offset results in a potential 48% GHG emissions avoidance.

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2020 Scenario 2030 Scenario

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Figure 6: GHG emissions avoidance potential of an optimally designed generation plus load shifting strategy with different battery storage capacities for present and future scenarios.

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Maximizing Avoided Emissions

The reference case study demonstrates the significance of load-shifting - especially highlighted when the results are compared for present and future scenarios.

Discussion and Outlook The reference project demonstrates a significant GHG avoidance potential with load shifting. When dispatch sequences are well-configured and designed to respond to changing grid conditions, even a battery bank with a small capacity can avoid substantial GHG emissions. When not designed well, however, the GHG avoidance from on-site renewable resources can diminish in the future as the grid gets cleaner.

Accordingly, any design and system sizing decisions based on present grid emission profiles can seriously limit the future emissions avoidance potential.

The reference project is based in California within the context of an electric grid with high solar contribution already, and a projection that solar photovoltaic penetration will increase significantly over the next few years. While the exact results of a similar study will differ for other projects based on their demand profiles and grid-regions, the findings are applicable for any region with a reasonable Renewable Portfolio Standard. With renewable penetration increasing in grids across the board, periods of curtailment for intermittent renewable energy sources may differ but the magnitude of difference in GHG emission factors between mid-day and lateafternoon hours will be similar.

Finally, it is important to note that this paper focuses on only one of several mechanisms for load shifting - electrical storage and dispatch with the help of batteries. Similar arguments apply to load shifting through thermal storage and building demand management controls. Such microgrids - thermal or electric - that offer an optimal combination of building controls, distributed energy resources, and storage will play an increasingly important role towards decarbonization of the built environment, especially with the increasing penetration of intermittent renewables in the grid as time-of-use considerations becomes paramount to avoid future grid emissions.

Shreshth Nagpal Principal - Design Analytics | snagpal@elementaengineering.com Rushil Desai Building Performance Analyst | rdesai@elementaengineering.com

Endnotes

1 Desai R, Shah S, Nagpal S, Investigating the impact of cost-based and carbon-based renewable energy generation and storage sizing strategies on carbon emissions for all-electric buildings; 2018 BPACS 2 https://www.integralgroup.com/news/climate-mobilization-act/ 3 https://www.cityofberkeley.info/climate/ 4 Siler-Evans K, Azevedo IL, Morgan MG. Marginal emissions factors for the US electricity system.

Environmental science & technology. 2012 May 1;46(9):4742-8.

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Maximizing Avoided Emissions

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In 2014, Elementa Engineering DPC joined Integral Group LLC as part of an interactive global network of mechanical, electrical, plumbing and energy engineers, and firms collaborating under a single deep green engineering umbrella. We specialize in the design of simple, elegant, costeffective systems for a wide variety of project types.

Elementa Engineering DPC is a New York based professional services consulting engineering firm focused on positively impacting the built environment. Through a relationship with Integral Group LLC, we are creating a new realm of possibilities by combining our diversified leadership and common visionary approach to green buildings.

Collectively championing the use of the most innovative and sustainable systems, we give life to high performance buildings and communities that both respect and enrich the Earth, and provides our clients with global expertise in step with a local presence.

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