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Demand Side Management Trends to Watch in 2020
This blog was coauthored by Adam Knickelbein.
What’s in store for demand side management (DSM) programs in 2020 and beyond? At Navigant, a Guidehouse company, we see four important trends that utility DSM leaders should keep an eye on.
Grid Impacts of Energy Efficiency Need Improved Granularity in Time and Space
The value of clean energy impacts is higher during peak load and in areas with grid constraints. This isn’t earth-shattering news, but in a future grid typified by renewables, energy efficiency savings have zero or even negative value if delivered when renewable supply exceeds demand. And the inverse is also true—those savings are worth a great deal when delivered during times of extreme peak.
To properly value these impacts among their supply assets, utilities need to improve their measured load shapes to account for where the peaks happen. The avoided costs for energy and demand savings delivered on constrained feeders are dramatically higher than unconstrained feeders. This improves the cost-effectiveness for energy efficiency and non-wires alternatives programs. The cost savings support increased marketing, incentive, and data collection investments.
Beneficial Electrification Impacts Require Development of New Goals and Tools
What are the primary objectives of policymakers enabling and requiring utility clean energy programs? They want to help make people’s lives better by promoting clean, reliable, and economical energy for all customers. Historically, many jurisdictions have done this through the reduction of annual electricity (and natural gas) consumption. Yet renewable electricity will play an important part in meeting aggressive carbon reduction goals, and this may actually increase electricity consumption measured at the meter. For example, losses in distributed storage systems will increase consumption slightly relative to a no storage baseline to deliver electricity for the same services.
This is a bit of a chicken and egg problem. Our society needs both large amounts of renewable generation capacity and a set of electricity-fueled (or other low carbon-fueled) technologies to displace fossil-fueled end uses. The current systems of evaluating program cost-effectiveness generally look at the short-term, marginal costs and benefits of changes. The industry needs to collectively work out cost-effectiveness assumptions to align with policy objectives.
The Lines between Distributed Energy Resources Continue to Blur
What do you call a program promoting high efficiency utility-controlled EV charging infrastructure with variable peak pricing? Could it be energy efficiency or demand response? What about storage, load building, or rates?
It doesn’t matter how such a program is classified. The industry needs new language that recognizes distributed energy resources (DER) as a generalized set of tools with specific quantifiable impacts on the grid. And those impacts differ depending on DER type and program structure. Some may provide value in the form of annual energy impacts, peak demand reductions, or load shifting, while others do it through capacity avoidance or carbon savings. All DER must have their grid impacts considered in total to quantify the full benefits of the investment.
Better Ways of Quantifying the Marginal Carbon Impact of DER Are Needed
If policymakers change goals to reduce carbon, a clear way of estimating impacts is needed—it is not enough to multiply through by a single emissions factor. One way is by assessing whether DER is enabling additional renewable penetration. In the same way that we need a time dollar value and location dollar value of grid impacts, we need to understand carbon impacts as a function of time and place.