A clean energy transition on the electricity grid is underway with the addition of new renewable generation, improved capabilities for sensing and controls, and “distributed energy resources” (DER) that include efficiency, battery storage, flexible loads, and electrified heating and transportation.  The complex interactions between these advances require new analytic techniques to support decisions by utilities, regulators, and enterprises developing and deploying new DER.  In this paper we describe an approach for estimating the potential of flexible loads (often also referred to as “demand response” (DR)) to contribute to the planning and operation of the grid.  The analysis was developed in the California context in support of a California Public Utilities Commission rulemaking to reform DR.¹  This provided a unique opportunity to work directly with stakeholders and regulators in developing new frameworks for public interest scientific analysis.  We describe our modeling approach for load flexibility across four key dimensions: reshaping with rates (shape), shedding at critical time (shed), shifting timing of loads to capture renewables (shift), and fast response (shimmy) to balance the grid.  These concepts represent a new classification approach for responsive demand, driven by new needs on the grid and capabilities of controls and computing technology and designed to be both mathematically tractable and simple to understand by stakeholders and regulators.  The study identified significant potential for DR loads to support the grid and a need for integration of planning and deployment between DR and other DER.  Along with conventional peak load management, an emerging opportunity is for load shift—changing the timing of demand to better match renewable energy generation.  Shifting can avoid curtailment of renewable energy during times of surplus (an emerging and growing feature of the California grid) and directly support the transition to clean energy.  We identify how load shifting can improve the performance of the grid and reduce the cost of compliance with renewable energy targets.  Under a broad range of possible load shift frameworks, the overall outcomes show that shifting can reduce operational greenhouse gas emissions by approximately one-half for this shifted quantity of energy.