Abstract
Lawrence Berkeley National Laboratory (LBNL) and the Demand Response Research Center (DRRC) performed a technology demonstration and evaluation for Bonneville Power Administration (BPA) in Seattle City Light's (SCL) service territory. This report summarizes the process and results of deploying open automated demand response (OpenADR) in Seattle area with winter morning peaking commercial buildings. The field tests were designed to evaluate the feasibility of deploying fully automated demand response (DR) in four to six sites in the winter and the savings from various building systems. The project started in November of 2008 and lasted 6 months. The methodology for the study included site recruitment, control strategy development, automation system deployment and enhancements, and evaluation of sites participation in DR test events. LBNL subcontracted McKinstry and Akuacom for this project. McKinstry assisted with recruitment, site survey collection, strategy development and overall participant and control vendor management. Akuacom established a new server and enhanced its operations to allow for scheduling winter morning day-of and day-ahead events. Each site signed a Memorandum of Agreement with SCL. SCL offered each site $3,000 for agreeing to participate in the study and an additional $1,000 for each event they participated. Each facility and their control vendor worked with LBNL and McKinstry to select and implement control strategies for DR and developed their automation based on the existing Internet connectivity and building control system. Once the DR strategies were programmed, McKinstry commissioned them before actual test events. McKinstry worked with LBNL to identify control points that can be archived at each facility. For each site LBNL collected meter data and trend logs from the energy management and control system. The communication system allowed the sites to receive day-ahead as well as day-of DR test event signals. Measurement of DR was conducted using three different baseline models for estimation peak load reductions. One was three-in-ten baseline, which is based on the site electricity consumption from 7 am to 10 am for the three days with the highest consumption of the previous ten business days. The second model, the LBNL outside air temperature (OAT) regression baseline model, is based on OAT data and site electricity consumption from the previous ten days, adjusted using weather regressions from the fifteen-minute electric load data during each DR test event for each site. A third baseline that simply averages the available load data was used for sites less with less than 10 days of historical meter data. The evaluation also included surveying sites regarding any problems or issues that arose during the DR test events. Question covered occupant comfort, control issues and other potential problems.
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