Load Modeling and Forecasting
NREL's work in load modeling is focused on the development and improvement of distributed energy resource models from a distribution system and the bulk system perspective.
With increasing amounts of distributed energy resources (such as rooftop photovoltaic systems) and changing customer energy use profiles, new load models are needed to support power system planning and operation. This work is increasingly complicated, and important, as distributed energy resources add voltage regulation capability (such as volt/VAR control) and bulk system reliability and dynamics are impacted by the pervasiveness of generation in the distribution system.
In addition, NREL researchers are developing load models for individual appliances and demonstration homes that include the impacts of energy management technologies such as advanced distribution management systems and home energy management systems.
Laboratory testing of individual pieces or suites of equipment
Model creation via high temporal-resolution field measurements
Validation of aggregate load models via advanced modeling and simulation on distribution and transmission system levels
This project is focused on the development of accurate load models on distribution transformer, distribution feeder, and substation levels. It is driven by the availability of high temporal-resolution measured load data across the United States. In addition, new models and improvements to existing models for the aggregate response of distributed energy resources are being developed using a mix of measured generation data and discrete laboratory evaluations of distributed energy resource-interfacing electronics.
Impacts of High Levels of Distributed PV and Load Dynamics on Bulk Power Transient Stability: Preprint, CIGRE International Colloquium on the Evolution of Power System Planning To Support Connection of Generation, Distributed Resources and Alternative Technologies (2016)
Field Testing and Modeling of Supermarket Refrigeration Systems as a Demand Response Resource, 2016 ACEEE Summer Study on Energy Efficiency in Buildings: From Components to Systems, From Buildings to Communities (2016)
Short-Term Distribution System State Forecast Based on Optimal Synchrophasor Sensor Placement and Extreme Learning Machine, Power and Energy Society General Meeting (2016)