Daniel Olsen

Grid Integration of Aggregated Demand Response, Part 1: Load Availability Profiles and Constraints for the Western Interconnection

Grid Integration of Aggregated Demand Response, Part 1: Load Availability Profiles and Constraints for the Western Interconnection Daniel]. Olsen, Nance Matson, Michael D. Sohn, Cody Rose, Junqiao Dudley, Sasank Goli, and Sila Kiliccote Lawrence Berkeley National Laboratory Marissa Hurnmon, David Palchak, Paul Denholm, and Jennie Iorgenson National Renewable Energy Laboratory September 2013

Grid Integration of Aggregated Demand Response, Part 2: Modeling Demand Response in a Production Cost Model

NOTICE This report was prepared as an account of work sponsored by an agency of the United States government. Neither the United States government nor any agency thereof, nor any of their employees, makes any warranty, express or implied, or assumes any legal liability or responsibility for the accuracy, completeness, or usefulness of any information, apparatus, product, or process disclosed, or represents that its use would not infringe privately owned rights. Reference herein to any specific commercial product, process, or service by trade name, trademark, manufacturer, or otherwise does not necessarily constitute or imply its endorsement, recommendation, or favoring by the United States government or any agency thereof. The views and opinions of authors expressed herein do not necessarily state or reflect those of the United States government or any agency thereof. Foreword This report is one of a series stemming from the U.S. Department of Energy (DOE) Demand Response and Energy Storage Integration Study. This study is a multinational laboratory effort to assess the potential value of demand response (DR) and energy storage to electricity systems with different penetration levels of variable renewable resources and to improve our understanding of associated markets and institutions. This study was originated, sponsored, and managed jointly by the Office of Energy Efficiency and Renewable Energy and the Office of Electricity Delivery and Energy Reliability. Grid modernization and technological advances are enabling resources, such as DR and energy storage, to support a wider array of electric power system operations. Historically, thermal generators and hydropower in combination with transmission and distribution assets have been adequate to serve customer loads reliably and with sufficient power quality, even as variable renewable generation like wind and solar power become a larger part of the national energy supply. While DR and energy storage can serve as alternatives or complements to traditional power system assets in some applications, their values are not entirely clear. This study seeks to address the extent to which DR and energy storage can provide cost-effective benefits to the grid and to highlight institutions and market rules that facilitate their use. The project was initiated and informed by the results of two DOE workshops; one on energy storage and the other on DR. The workshops were attended by members of the electric power industry, researchers, and policymakers, and the study design and goals reflect their contributions to the collective thinking of the project team. Additional information …

Assessing the Control Systems Capacity for Demand Response in California Industries

Assessing the Control Systems Capacity for Demand Response in California Industries Girish Ghatikar, Aimee McKane, Sasank Goli, Peter Therkelsen, Daniel Olsen Lawrence Berkeley National Laboratory January 2012

Demand Response Availability Profiles for California in the Year 2020

Author(s): Olsen, Daniel; Sohn, Michael; Piette, Mary Ann; Kiliccote, Sila | Abstract: Demand response (DR) is being considered as a valuable resource for keeping the electrical grid stable and efficient, and deferring upgrades to generation, transmission, and distribution systems. However, simulations to determine how much infrastructure upgrades can be deferred are necessary in order to plan optimally. Production cost modeling is a technique, which simulates the dispatch of generators to meet demand and reserves in each hour of the year, at minimal cost. By integrating demand response resources into a production cost model (PCM), their value to the grid can be estimated and used to inform operations and infrastructure planning. DR availability profiles and constraints for 13 end-uses in California for the year 2020 were developed by Lawrence Berkeley National Laboratory (LBNL), and integrated into a production cost model by Lawrence Livermore National Laboratory (LLNL), for the California Energy Commission’s Value of Energy Storage and Demand Response for Renewable Integration in California Study. This report summarizes the process for developing the DR availability profiles for California, and their aggregate capabilities. While LBNL provided potential DR hourly profiles for regulation product in the ancillary services market and five-minute load following product in the energy market for LLNL’s study, additional results in contingency reserves and an assumed flexible product are also defined. These additional products are included in the analysis for managing high ramps associated with renewable generation and capacity products and they are also presented in this report.