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The increasing utilization of distributed energy resources such as behind-the-meter solar has given rise to a grid-supplied load profile conditional on solar conditions that are difficult to forecast using conventional methods. As a result, the accuracy of the load forecasts is reduced, representing a possible operational challenge to system operators. This paper presents a method to resolve this challenge using New York City electricity zone data. The analysis presented in this paper demonstrates that the load forecasting challenges associated with behind-the-meter solar can be successfully addressed using econometric time-series methods and better forecast information. • Distributed energy resources have the potential to reduce the accuracy of the system operator's load forecasts. • Inaccurate load forecasts may adversely affect the power grid's resiliency. • A method is presented to predict near-real-time grid-supplied load accurately. [ABSTRACT FROM AUTHOR]