Unlocking Electrification with Hourly Emissions Data

抽象的

International agencies are working to create a sense of urgency toward climate action. Specific actions such as replacing fossil-fuel-fired heating equipment with heat pumps, electrifying transportation, and energy storage are recommended. These broad actions will be evaluated and implemented at individual facilities. The carbon impact of buildings and industrial manufacturing must include the embodied carbon of the steel, wood, glass, and concrete used in construction. But you can’t manage what you measure incorrectly. Currently the dominant method for measuring carbon emissions is to multiply energy consumption for each fuel by an emissions factor, using the average contributors to electricity generation. Relying on this method for cost assessments will undercut GHG emission reductions and lead to slower investment in necessary technologies. Recent standards have recommended utilizing long-run marginal contributions to electrical generation (“consequential analysis”). This study addresses the question: How much difference would it make for facility managers to use long-run marginal emissions rather than annual emissions in their feasibility assessments for measures at industrial facilities? We performed a comparative analysis using a sample of approximately 30,000 industrial facilities. We calculated emissions data using two distinct inputs: the eGRID (2021 annual average factors) and the Cambium (8-year average, 2023-2030) hourly long-run marginal emissions factors (as suggested in new draft standards). This comparison tests the hypothesis that using average impacts undercuts global policy goals such as electrification.

介绍

The energy efficiency industry aims to contribute to stabilizing the electricity system, ensuring that future power planning aligns with public needs and policy objectives. As has been the case throughout the regulated utility industry’s history, key priorities include safety, affordability, reliability, and abundance. However, with increasing investment and policy direction towards decarbonization and electrification, adjustments are needed to incentivize future capacity that aligns with these key priorities and promotes technologies essential for combating climate change and reducing emissions. These adjustments, if done optimally, can greatly reduce the cost of grid modernization by encouraging efficiency and controllability of demand to replace simple increases in kW capacity.

There are some technologies that we know will lead broadly to decreased greenhouse gas (GHG) emissions, such as industrial heat pumps and battery and thermal storage (IEA 2023). However, if a facility is considering such measures, the engineers and facility managers need to calculate the costs, feasibility, and present the technology’s effect on the facility’s overall GHG emissions over time. Predicting future emissions requires that the assumptions that get used in these models make sense and properly account for what would happen in the future (Gagnon and Cole, 2022). There are three primary ways to predict greenhouse gas emissions to inform these calculations: average annual emissions, short-run marginal emission rates, and long-run marginal emission rates. This article focuses on the difference between average emissions and long-run marginal emissions. Each of these concepts has appropriate use-cases based on their development and intent.

Emissions Rates for Engineers and Facility Managers

Why is this difference important? Because these technologies require significant investment and will be implemented one-by-one after careful consideration by decision makers who rely on the analysis analyses from their engineers and facility managers at each corporation, campus, facility, plant, or building. Facilities will be required to comply with efficiency standards, performance standards, and corporate decarbonization goals, and the engineers and facility managers representing those entities will make the case for which equipment makes sense after they calculate and compare the feasibility, cost savings, and GHG savings of specific measures. As standards improve and data available increases, the costs and paybacks from installing heat

pumps to supply heat, industrial dryers, or thermal storage systems will be significantly impacted by operation calculations taking into account the impacts of operating during hours when grid electricity is cleaner and when the grid is dirtiest.

These estimates not only affect whether the manager in charge of the facilities of interest approves the improvement, but also others that may be involved in the go/no-go decision: utilities, state or federal government energy efficiency/decarbonization advisors, accountants who review emissions disclosures, etc. The early years of including carbon estimates in cost analyses will face additional scrutiny to ensure compliance with all applicable standards and requirements.

Recalling back to the concept of average emissions and long-run emissions, we have identified that using one or the other leads to significant differences in the cost and emission outcomes of a feasibility assessment for the aforementioned high-interest technologies such as industrial heat pumps, dryers, and storage. Some (or perhaps most) economically and technically feasible projects will appear to fail to reduce GHG emissions significantly, or even at all, if the analysis uses average emissions. This conclusion is not well documented in the literature because published papers usually focus on successes—such as why a particular project achieved its goals—rather than failures. And it is a failure when viable and necessary projects are not implemented because the preliminary analysis erroneously did show lackluster GHG emissions reductions. This research begins to correct this failing and provide support for upcoming data and standards on GHG emissions analysis for these technologies. Although it may be common within engineering circles and utility industry conference settings to discuss the comparison between nascent and legacy methods, research with the best possible available data is necessary to demonstrate how to implement the newer methods in cost analyses and feasibility assessments.

This article will discuss show the differences in GHG emissions from the legacy and nascent inputs and provide guidance on how to correct the errors that underlie current GHG calculations. It will evaluate the magnitude of the error, demonstrating that it makes a big difference in most grid regions in the U.S., and thus likely in most grids everywhere, and provide a path forward for decision makers, engineers, and technology developers to make recommendations and decisions that lead to a better way to reduce GHG emissions.

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This article written by Craig Sinnamon, David B. Goldstein， 和 Anna Kelly and originally published in the International Journal of Energy Management (IJEM) in June 2024.