Understanding end-use and premise load characteristics is a critical component of system planning, rate design, and time-differentiated energy savings. With the rapid growth of solar photovoltaic and distributed energy resources, utility investments and conservation efforts are increasingly focused on managing peak loads on the transmission and distribution system. Understanding how loads and DSM load impacts align with peaking conditions is a key part of properly valuing resources and comparing options. We have also performed demand response potential studies which look at the achievable, economic, and program potential of various DR products and produce a supply curve of DR options system planners can integrate in with traditional generation resources.
- In 2014, Mr. Smith designed and led a Commercial Lighting Metering Study for the state of Pennsylvania. For the first five years of ratepayer funded programs in Pennsylvania, savings assumptions for commercial lighting measures, such as hours-of-use values and coincidence with the system peak were taken from secondary research based on studies in other jurisdictions with several daisy-chained (and sometimes circular) references. To rectify this the PUC tasked the Statewide Evaluation Team to conduct on one of North America’s largest Commercial Light Metering studies in order to update measure assumptions in the Technical Reference Manual used in the calculation of savings. Using tablet-based data collection and nearly 2,500 data loggers across 500 participating facilities, the Statewide Evaluation Team developed Pennsylvania-specific load shapes, operating hours, coincidence factors, and HVAC interactive factors for the 10 most prevalent building types in the state. These outputs became foundational inputs for estimates of market potential and savings goals across the state.
- During his tenure at Nexant, Mr. Smith led an assessment of non-residential demand response potential for the Pennsylvania Public Utility Commission. The seven Electric Distribution Companies in the state have a combined summer peak of load of nearly 30,000 MW and $244 million in annual DSM program budgets. Previous rate-payer funded demand response offerings in the state failed to pass the TRC test so the first task in the study scope was to consider program design characteristics and recommend a more effective model given the various technical and policy constraints in place. The study classified residential and small commercial accounts by building type, demand magnitude, and weather-sensitivity. Large commercial and industrial accounts were assigned to one of fourteen distinct business types. Jesse calculated price elasticity values for each business type using actual demand response program data in California, PJM, and previous offerings in Pennsylvania. These estimates of electricity price sensitivity provided data-driven intelligence on how large commercial and industrial accounts can be expected to respond to DR offerings. The study also considered the interplay between a potential state DR program and the PJM DR markets, which many large C&I customers already actively participate in. The study presents both full potential and potential net of existing DR commitments in wholesale markets.