Utilities struggle to distinguish energy consumed by customers from energy generated by their solar systems without expensive and complex sub-meter installations. This ambiguity leads to unclear and often inaccurate analytics, hampering effective decision-making and grid management.
Distributed solar production is a major cause of timing imbalances between supply and peak demand. While many solar customers could be converted to grid assets through battery storage or smart EV charging programs, a lack of data makes targeting the right customers challenging.
Solar installations challenge utilities who want to measure the impacts of energy efficiency (EE) and demand response (DR) using smart meter data, as changes in cloud cover or other variability can be mistaken for savings or increases.
Recurve’s SOLARmeter leverages AMI data, advanced machine learning, and insolation data to disaggregate solar production from energy consumption. This capability allows utilities to quantify the effective size and orientation of the solar resource and measure and forecast production.
The ability of SOLARmeter to separate solar generation from consumption also enables more reliable measurement of behind-the-meter VPPs, including energy efficiency and demand response, even when solar is present.
Disaggregation of Consumption - Using smart meter data, SOLARmeter cleanly separates solar production from energy consumption, giving utilities insight and clarity for enhancing grid management and planning accuracy.
Enhanced Measurement of EE and DR - SOLARmeter enables precise measurement of the impact of energy efficiency and demand response solutions, even when solar systems are present.
Data-Driven Forecasting - Offers tools to forecast solar potential, its orientation, and interplay with energy efficiency and demand response initiatives on the grid.
By measuring actual generation using AMI data, without the need for solar sub-meters or bespoke integrations, Recurve's SOLARmeter solves key critical challenges of distributed solar for utilities, allowing them to turn grid liabilities into assets and fully integrate solar customers into demand-side programs and comprehensive behind-the-meter virtual power plants.
Schedule a call with one of our specialists to learn how our solutions can transform your distributed energy resource strategy.
Schedule a MeetingGRIDmeter 2.0: Advancing Comparison Group State of the Art With Machine Learning Clustering