ORIGINAL REPORTING: The Questions To Answer To Get New Energy Right
Demand charges vs. TOU rates: The great Arizona rate design experiment; Rate design experts debate APS's plan to be the first utility with mandatory demand charges for residential customers
Herman K. Trabish, September 26, 2016 (Utility Dive)
Editor’s note: Since this story ran, there is a rising trend of pilots and trials of these kinds of rates.
There are big differences in how utilities are planning for the rise of distributed solar and a lot can be learned from a close look at how they plan to integrate it, according to a new study which analyzed 30 integrated resource plans from cooperatives, municipal- and investor-owned utilities and the divergent approaches to integrating distributed solar as penetrations rise in certain service territories. The report also assesses planning by five system operators, along with distribution system analysis in California, New York, Hawaii, and Massachusetts. While the primary planning has zeroed in on customer adoption, planners are already beginning to think about how distributed solar can serve system needs, lead author Andrew Mills said.
Developing a forecast for deployment is key, since it guides planning in other areas. When accurately assessed, it can predict how distributed solar can meet generation needs, variability impact, and value and cost to the transmission and distribution system, according to Mills. The study describes four categories of deployment forecasting. Most planning uses essentially static or linear models based on the assumption that customers will continue to add DPV either to meet mandates or at an assumed rate or an historical rate. Such planning relies on few or no quantifiable predictive factors, according to the paper. But other types of forecasting, specifically customer-adoption planning, recognizes end user decision making hinging on photovoltaic economics and resource potential, among other factors. By using factors independent of mandates or historical trends, planners can generate new, self-consistent DPV adoption forecasts but it does not completely eliminate uncertainty… click here for more
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