A new paradigm for long-term forecasting of loads and distributed energy resources includes more geospatially and temporally granular, scenario-based methods to ensure grid reliability and effective planning.
The Energy Systems Integration Group (ESIG) has released a new report, Long-Term Load and DER Forecasting, addressing key challenges in long-term load and distributed energy resource (DER) forecasting in today’s transforming grid.
Long-term load and DER forecasting is critical to achieve clean energy goals and ensure a reliable, resilient, and affordable energy system. Traditionally, these forecasts focused on total annual energy and peak demand. However, the evolving energy landscape—marked by variable renewable generation, unprecedented load growth from electrification (buildings, transportation, data centers, manufacturing), and rising customer-sited solar, battery storage, electric vehicles—necessitates a paradigm shift. ESIG convened a Long-Term Load and DER Forecasting Task Force to address the key forecasting challenges.
“Load forecasting has been rapidly evolving, first with the adoption of distributed energy resources, and then increased electrification of heat and transport, and today with the rapid growth of large loads such as data centers,” said Debra Lew, executive director of ESIG. “This report outlines key principles and practices to navigate this complexity.”
Traditional methods, which allocate load and DER growth based on proportional scaling of energy consumption, peak demand, or customer count, often fail to capture emerging geospatial adoption patterns. To accurately predict future energy demand requires explicit modeling of various demand-side modifiers to arrive at a net load forecast—including energy efficiency, solar, battery storage, economic growth, new customer business loads, electric vehicle charging, and building electrification.
“The evolving energy landscape demands careful modeling in load and DER forecasting practices as well as the need to study multiple future scenarios,” said Julieta Giraldez, of Electric Power Engineers and chair of the task force. “Multiple entities often produce forecasts for overlapping regions, and improving forecast alignment is critical for planners to manage differences in forecast components, reconcile how local and system peaks relate, and properly allocate system level data to local grid areas. This ultimately improves integrated planning approaches and creates greater coordination across system operators, utilities, and other planning entities.”
The report outlines key elements of a more geospatially and temporally granular, scenario-based approach, including (1) high-resolution, time-based (hourly) forecasts to capture the correlated impacts of weather on demand, generation, and the nuances of DER behavior, and (2) methods that account for the underlying drivers of new sector demands and technology adoption, such as price signals and policy drivers.
Scenario-based forecasting approaches better equip planners across grid planning entities and within planning departments to assess a range of possible futures and provide opportunities for greater coordination across planning entities to improve system-wide preparedness.
While the challenges of long-term load and DER forecasting are complex and evolving, they present promising opportunities for innovation and improvement. As energy systems integrate new technologies, demand patterns, and policies, more advanced, geospatially and temporally granular forecasting methods are crucial for ensuring grid reliability and effective planning. By adopting a flexible, scenario-based approach and fostering better coordination across entities, energy planners can pave the way for a more resilient and efficient grid, prepared to meet the demands of tomorrow’s energy landscape.