|Title||Fast Automated Demand Response to Enable the Integration of Renewable Resources|
|Year of Publication||2012|
|Authors||Watson, David S., Nance Matson, Janie Page, Sila Kiliccote, Mary Ann Piette, Karin Corfee, Betty Seto, Ralph Masiello, John Masiello, Lorin Molander, Samuel Golding, Kevin Sullivan, Walt Johnson, and David Hawkins|
This study examines how fast automated demand response (AutoDR) can help mitigate grid balancing challenges introduced by upcoming increases in intermittent renewable generation resources such as solar and wind in an environmentally friendly and cost effective manner. This study gathers data from multiple sources to determine the total electric end-use loads in the commercial and industrial sectors of California. The shed capacity available from AutoDR in these sectors varies based on many factors including weather, time of year and time of day. This study estimates that the lowest shed capacity could occur on cold winter mornings and the highest on hot summer afternoons. Based on this analysis, a large-scale deployment of fast AutoDR could provide between 0.18 and 0.90 GW of DR-based ancillary services from the existing stock of commercial and industrial facilities throughout California. With modest investments to upgrade and expand use of automated control systems in commercial and industrial facilities the estimated shed potential could approximately double to between 0.42 and 2.07 GW. Deployed costs for fast AutoDR (installation, materials, labor and program management) are about 10% of the deployed costs of grid scale battery storage. However, AutoDR in California has less capacity than what is required to meet the grid balancing challenges introduced by the 2020 renewable portfolio standard goals. There are many different types of ancillary services necessary to keep the electric grid in balance. Though AutoDR may not be suitable for all forms of ancillary services, the lower installed cost of AutoDR indicates that it should be considered for use in the time domains and capacities for which it is applicable. By combining AutoDR with traditional gas fired thermal generation and battery storage technologies, an optimal mix of generation, AutoDR and storage should be considered to meet upcoming challenges introduced by the increased use of renewable generation.
|LBNL Report Number|| |
Fast Automated Demand Response to Enable the Integration of Renewable Resources