Automated demand response (Auto-DR) is expected to close the loop between buildings and the grid by providing machine-to-machine communications to curtail loads without the need for human intervention. Hence, it can offer more reliable and repeatable demand response results to the grid than the manual approach and make demand response participation a hassle-free experience for customers. However, many building operators misunderstand Auto-DR and are afraid of losing control over their building operation. To ease the transition from manual to Auto-DR, we designed and implemented granular control of Auto-DR systems so that building operators could modify or opt out of individual load-shed strategies whenever they wanted. This paper reports the research findings from this effort demonstrated through a field study in large commercial buildings located in New York City. We focused on (1) understanding how providing granular control affects building operators’ perspective on Auto-DR, and (2) evaluating the usefulness of granular control by examining their interaction with the Auto-DR user interface during test events. Through trend log analysis, interviews, and surveys, we found that: (1) the opt-out capability during Auto-DR events can remove the feeling of being forced into load curtailments and increase their willingness to adopt Auto-DR; (2) being able to modify individual load-shed strategies allows flexible Auto-DR participation that meets the building’s changing operational requirements; (3) a clear display of automation strategies helps building operators easily identify how Auto-DR is functioning and can build trust in Auto-DR systems.

Demand response (DR) – allowing customers to respond to reliability requests and market prices by changing electricity use from their normal consumption pattern – continues to be seen as an attractive means of demand-side management and a fundamental smart-grid improvement that links supply and demand. From October 2011 to December 2013, the Demand Response Research Center at Lawrence Berkeley National Laboratory, the New York State Energy Research and Development Authority, and partners Honeywell and Akuacom, have conducted a demonstration project enabling Automated Demand Response (Auto-DR) in large commercial buildings located in New York City using Open Automated Demand Response (OpenADR) communication protocols. In particular, this project focuses on demonstrating how the OpenADR platform, enabled by Akuacom, can automate and simplify interactions between buildings and various stakeholders in New York State and enable the automation of customers’ price response to yield bill savings under dynamic pricing. In this paper, the cost control opportunities under day-ahead hourly pricing and Auto-DR control strategies are presented for four demonstration buildings; present the breakdown of Auto-DR enablement costs; summarize the field test results and their load impact; and show potential bill savings by enabling automated price response under Consolidated Edison’s Mandatory Hourly Pricing (MHP) tariff. For one of the sites, the potential bill savings at the site’s current retail rate are shown. Facility managers were given granular equipment-level opt-out capability to ensure full control of the sites during the Auto-DR implementation. The expected bill savings ranged from 1.1% to 8.0% of the total MHP bill. The automation and enablement costs ranged from $70 to $725 per kW shed. The results show that OpenADR can facilitate the automation of price response, deliver savings to the customers and opt-out capability of the implementation retains control of the sites by facility managers.

During the past decade, the technology to automate demand response (DR) in buildings and industrial facilities has advanced significantly. Automation allows rapid, repeatable, reliable operation. This study focuses on costs for DR automation in commercial buildings with some discussion on residential buildings and industrial facilities. DR automation technology relies on numerous components, including communication systems, hardware and software gateways, standards-based messaging protocols, controls and integration platforms, and measurement and telemetry systems. This report compares cost data from several DR automation programs and pilot projects, evaluates trends in the cost per unit of DR and kilowatts (kW) available from automated systems, and applies a standard naming convention and classification or taxonomy for system elements. Median costs for the 56 installed automated DR systems studied here are about $200/kW. The deviation around this median is large with costs in some cases being an order of magnitude great or less than the median. This wide range is a result of variations in system age, size of load reduction, sophistication, and type of equipment included in cost analysis. The costs to automate fast DR systems for ancillary services are not fully analyzed in this report because additional research is needed to determine the total cost to install, operate, and maintain these systems. However, recent research suggests that they could be developed at costs similar to those of existing hot-summer DR automation systems. This report considers installation and configuration costs and does include the costs of owning and operating DR automation systems. Future analysis of the latter costs should include the costs to the building or facility manager costs as well as utility or third party program manager cost.

Current state-of-the-art demand response systems are expensive due to extreme reliability constraints in telemetry, control, and metering. The typical cost of enabling a site for regulation services is between $50k and $80k. These costs are orders of magnitude too high for small loads to participate in high-value grid services. Traditional demand response (DR) schedules events in advance and provides basic on/off control. We developed fast DR measurement and communication technologies, which are scalable cost-effective demand response systems with sufficient reliability for real-time control and monitoring of loads over the internet, and we demonstrated an example system for under $100. We installed FastDR systems for lighting, motor, and thermostat control along with power metering at a total of 10 sites, including 6 commercial buildings and 4 residential buildings. This demonstration addressed the following important methodological questions: 1) Can we reliably control loads simultaneously and with low latency across multiple sites within a specified response time; 2) How reliable is using the internet or 4G cellular network as the mode of control and metering; and 3) Can existing Smart Meters provide data for real-time telemetry services. Testing shows fast DR is capable of control to response in 4 seconds and loads complete transition in seconds to less than one minute depending on load type. We demonstrated 4s regulation services and synchronized load control, and we successfully met specifications for ancillary services across the US. Telemetry via the 4G cellular network demonstrated 94.5% success rate, and residential Internet demonstrated a 98% success rate.

The electricity system in California, from generation through loads, must be prepared for high renewable penetration and increased electrification of end uses while providing increased resilience and lower operating cost. California has an aggressive renewable portfolio standard that is complemented by world-leading greenhouse gas goals. The goal of this project was to evaluate methods of enabling fast demand response (DR) signaling to small loads for low-cost site enablement. We used OpenADR 2.0 to meet telemetry requirements for providing ancillary services, and we used a variety of low-cost devices coupled with open-source software to enable an end-to-end fast DR. The devices, architecture, implementation, and testing of the system is discussed in this report. We demonstrate that the emerging Internet of Things (IoT) and Smart Home movements provide an opportunity for diverse small loads to provide fast, low-cost demand response. We used Internet-connected lights, thermostats, load interruption devices, and water heaters to demonstrate an ecosystem of controllable devices. The system demonstrated is capable of providing fast load shed for between $20 and $300 per kilowatt (kW) of available load. The wide range results from some loads may have very low cost but also very little shed capability (a 10 watt [W] LED light can only shed a maximum of 10 W) while some loads (e.g., water heaters or air conditioners) can shed several kilowatts but have a higher initial cost. These costs, however, compare well with other fast demand response costs, with typically are over $100/kilowatt of shed. We contend these loads are even more attractive than their price suggests because many of them will be installed for energy efficiency or non-energy benefits (e.g., improved lighting quality or controllability), and the ability to use them for fast DR is a secondary benefit. Therefore the cost of enabling them for DR may approach zero if a software-only solution can be deployed to enable fast DR after devices are installed for other reasons. We recommend that the DR research community continue to engage with the IoT community to encourage the use of documented and open development interfaces. A library of device drivers and machine-readable interface specifications would significantly reduce the burden on users or system integrators for deploying systems in large numbers of buildings in California.