摘要：SummaryFailing to incorporate accurate distributed energy resource penetration forecasts into long-term resource and transmission planning can lead to cost inefficiencies at best and system failures at worst. We have developed an open-source tool that employs an advanced Bass specification to calibrate and forecast technology adoption. The advanced specification includes geographic clustering, exogenously estimated market size, and dynamic time steps. Training on historical adoption of rooftop photovoltaics at the U.S. county-level and using detailed techno-economic estimates, our model achieves a two-year average mean-absolute-percentage-error of 19% in predicting system counts at the county-level, weighted by population. Model error was negatively correlated with market maturity—the error was 12% for counties in states with at least 28 W-per-capita of installed capacity. The advanced specification significantly reduces unweighted forecasting percent error compared to a conventional Bass specification: from 196% to 25% for capacity and from 226% to 22% for system count.Graphical abstractDisplay OmittedHighlights•Developed open-sourced tool to calibrate and validate forecasts of residential PV•The method introduces three improvements to the traditional Bass model•Demonstrate improvement to accuracy by > 170% compared to traditional specification•Model achieves mean absolute percentage error of <20% for system countsEnergy resources; Energy policy; Energy management; Energy Modeling; Energy Systems
