More and more policymakers are developing policies to influence the amount, time, or place of net electricity demand in order to reduce emissions. From Distributed Energy Resources (DERs), to energy storage, to load shifting policies (like real-time pricing or flexible appliance standards), to low carbon fuel standards, these policies all have effects on emissions. But how to know what effect, and design for success?
Typically, policymakers must rely on ‘proxy’ metrics such as locational marginal price, peak demand, static time periods, or battery efficiency to attempt to measure and track emissions reductions. And researchers have repeatedly found that aligning programs metrics to proxies for environmental impact has led to programs that are less successful than expected in reducing emissions--sometimes even backfiring and unintentionally increasing them.
So, WattTime supports policymakers working on such policies with tools to directly measure and optimize for their intended consequence: emissions reduction. For programs that relate specifically to changing net load in order to achieve environmental goals, replacing proxies and directly measuring marginal or total emissions effects can often dramatically increase efficacy, reduce costs on taxpayers and regulated entities alike, and avoid unintended consequences.
Case Study 1: SGIP
The California Self Generation Incentive Program provides incentives for qualifying energy storage systems. One of the goals of the program is to reduce GHG emissions, but a 2017 impact evaluation report found that SGIP commercial-storage projects had unintentionally been increasing GHG emissions. This was primarily because the metric used by the program—battery roundtrip efficiency—turned out not to be a close enough proxy to ensure emissions reduction, as other factors like timing also greatly influence emissions. To remedy this the California Public Utilities Commission issued a ruling requiring energy storage systems that receive an incentive to reduce emissions on an annual basis, to be measured directly by grid marginal emissions.
To aid energy storage developers in achieving the program requirements, a real-time marginal emissions signal with 5-minute granularity and 72-hour forecasts was developed for integration into control systems. This enables storage systems to co-optimize for both emissions and revenue and ensure they are in compliance with the program requirements. For more information about the SGIP signal visit the website.
What other energy storage incentive policies have you evaluated?
Along with our partners at Columbia and NYU, we evaluated the Massachusetts Clean Peak Standard, and the emissions metrics for the Maryland Energy Storage Pilot, 2020. Our analysis of the MA Clean Peak Standard was covered by several media sources including Forbes and Greentech Media.
What smart charging incentive programs have you evaluated?
We advocated for a real-time, marginal emissions signal to earn smart charging incremental credits at the California Air Resources Board Low Carbon Fuel Standards proceeding, and the Oregon Department of Environmental Quality Clean Fuels Program Electricity 2021.