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Automation of Capacity Bidding with an Aggregator Using Open Automated Demand Response

Description: This report summarizes San Diego Gas& Electric Company?s collaboration with the Demand Response Research Center to develop and test automation capability for the Capacity Bidding Program in 2007. The report describes the Open Automated Demand Response architecture, summarizes the history of technology development and pilot studies. It also outlines the Capacity Bidding Program and technology being used by an aggregator that participated in this demand response program. Due to delays, the program was not fully operational for summer 2007. However, a test event on October 3, 2007, showed that the project successfully achieved the objective to develop and demonstrate how an open, Web?based interoperable automated notification system for capacity bidding can be used by aggregators for demand response. The system was effective in initiating a fully automated demand response shed at the aggregated sites. This project also demonstrated how aggregators can integrate their demand response automation systems with San Diego Gas& Electric Company?s Demand Response Automation Server and capacity bidding program.
Date: October 1, 2008
Creator: Kiliccote, Sila & Piette, Mary Ann
Partner: UNT Libraries Government Documents Department

Solutions for Summer Electric Power Shortages: Demand Response andits Applications in Air Conditioning and Refrigerating Systems

Description: Demand response (DR) is an effective tool which resolves inconsistencies between electric power supply and demand. It further provides a reliable and credible resource that ensures stable and economical operation of the power grid. This paper introduces systematic definitions for DR and demand side management, along with operational differences between these two methods. A classification is provided for DR programs, and various DR strategies are provided for application in air conditioning and refrigerating systems. The reliability of DR is demonstrated through discussion of successful overseas examples. Finally, suggestions as to the implementation of demand response in China are provided.
Date: November 30, 2007
Creator: Han, Junqiao & Piette, Mary Ann
Partner: UNT Libraries Government Documents Department

Automated Critical PeakPricing Field Tests: 2006 Pilot ProgramDescription and Results

Description: During 2006 Lawrence Berkeley National Laboratory (LBNL) and the Demand Response Research Center (DRRC) performed a technology evaluation for the Pacific Gas and Electric Company (PG&E) Emerging Technologies Programs. This report summarizes the design, deployment, and results from the 2006 Automated Critical Peak Pricing Program (Auto-CPP). The program was designed to evaluate the feasibility of deploying automation systems that allow customers to participate in critical peak pricing (CPP) with a fully-automated response. The 2006 program was in operation during the entire six-month CPP period from May through October. The methodology for this field study included site recruitment, control strategy development, automation system deployment, and evaluation of sites' participation in actual CPP events through the summer of 2006. LBNL recruited sites in PG&E's territory in northern California through contacts from PG&E account managers, conferences, and industry meetings. Each site contact signed a memorandum of understanding with LBNL that outlined the activities needed to participate in the Auto-CPP program. Each facility worked with LBNL to select and implement control strategies for demand response and developed automation system designs based on existing Internet connectivity and building control systems. Once the automation systems were installed, LBNL conducted communications tests to ensure that the Demand Response Automation Server (DRAS) correctly provided and logged the continuous communications of the CPP signals with the energy management and control system (EMCS) for each site. LBNL also observed and evaluated Demand Response (DR) shed strategies to ensure proper commissioning of controls. The communication system allowed sites to receive day-ahead as well as day-of signals for pre-cooling, a DR strategy used at a few sites. Measurement of demand response was conducted using two different baseline models for estimating peak load savings. One was the CPP baseline model, which is based on the site electricity consumption from noon to 6 p.m. ...
Date: June 19, 2007
Creator: Piette, Mary Ann; Watson, David; Motegi, Naoya & Kiliccote, Sila
Partner: UNT Libraries Government Documents Department

Field Test Results of Automated Demand Response in a Large Office Building

Description: Demand response (DR) is an emerging research field and an effective tool that improves grid reliability and prevents the price of electricity from rising, especially in deregulated markets. This paper introduces the definition of DR and Automated Demand Response (Auto-DR). It describes the Auto-DR technology utilized at a commercial building in the summer of 2006 and the methodologies to evaluate associated demand savings. On the basis of field tests in a large office building, Auto-DR is proven to be a reliable and credible resource that ensures a stable and economical operation of the power grid.
Date: October 20, 2008
Creator: Han, Junqiao; Piette, Mary Ann & Kiliccote, Sila
Partner: UNT Libraries Government Documents Department

Linking Continuous Energy Management and Open Automated Demand Response

Description: Advances in communications and control technology, the strengthening of the Internet, and the growing appreciation of the urgency to reduce demand side energy use are motivating the development of improvements in both energy efficiency and demand response (DR) systems. This paper provides a framework linking continuous energy management and continuous communications for automated demand response (Auto-DR) in various times scales. We provide a set of concepts for monitoring and controls linked to standards and procedures such as Open Automation Demand Response Communication Standards (Open Auto-DR or OpenADR). Basic building energy science and control issues in this approach begin with key building components, systems, end-uses and whole building energy performance metrics. The paper presents a framework about when energy is used, levels of services by energy using systems, granularity of control, and speed of telemetry. DR, when defined as a discrete event, requires a different set of building service levels than daily operations. We provide examples of lessons from DR case studies and links to energy efficiency.
Date: October 3, 2008
Creator: Piette, Mary Ann; Kiliccote, Sila & Ghatikar, Girish
Partner: UNT Libraries Government Documents Department

Scenarios for Consuming Standardized Automated Demand Response Signals

Description: Automated Demand Response (DR) programs require that Utility/ISO's deliver DR signals to participants via a machine to machine communications channel. Typically these DR signals constitute business logic information (e.g. prices and reliability/shed levels) as opposed to commands to control specific loads in the facility. At some point in the chain from the Utility/ISO to the loads in a facility, the business level information sent by the Utility/ISO must be processed and used to execute a DR strategy for the facility. This paper explores the various scenarios and types of participants that may utilize DR signals from the Utility/ISO. Specifically it explores scenarios ranging from single end user facility, to third party facility managers and DR Aggregators. In each of these scenarios it is pointed out where the DR signal sent from the Utility/ISO is processed and turned into the specific load control commands that are part of a DR strategy for a facility. The information in these signals is discussed. In some cases the DR strategy will be completely embedded in the facility while in others it may be centralized at a third party (e.g. Aggregator) and part of an aggregated set of facilities. This paper also discusses the pros and cons of the various scenarios and discusses how the Utility/ISO can use an open standardized method (e.g. Open Automated Demand Response Communication Standards) for delivering DR signals that will promote interoperability and insure that the widest range of end user facilities can participate in DR programs regardless of which scenario they belong to.
Date: October 3, 2008
Creator: Koch, Ed & Piette, Mary Ann
Partner: UNT Libraries Government Documents Department

Northwest Open Automated Demand Response Technology Demonstration Project

Description: The Lawrence Berkeley National Laboratory (LBNL) Demand Response Research Center (DRRC) demonstrated and evaluated open automated demand response (OpenADR) communication infrastructure to reduce winter morning and summer afternoon peak electricity demand in commercial buildings the Seattle area. LBNL performed this demonstration for the Bonneville Power Administration (BPA) in the Seattle City Light (SCL) service territory at five sites: Seattle Municipal Tower, Seattle University, McKinstry, and two Target stores. This report describes the process and results of the demonstration. OpenADR is an information exchange model that uses a client-server architecture to automate demand-response (DR) programs. These field tests evaluated the feasibility of deploying fully automated DR during both winter and summer peak periods. DR savings were evaluated for several building systems and control strategies. This project studied DR during hot summer afternoons and cold winter mornings, both periods when electricity demand is typically high. This is the DRRC project team's first experience using automation for year-round DR resources and evaluating the flexibility of commercial buildings end-use loads to participate in DR in dual-peaking climates. The lessons learned contribute to understanding end-use loads that are suitable for dispatch at different times of the year. The project was funded by BPA and SCL. BPA is a U.S. Department of Energy agency headquartered in Portland, Oregon and serving the Pacific Northwest. BPA operates an electricity transmission system and markets wholesale electrical power at cost from federal dams, one non-federal nuclear plant, and other non-federal hydroelectric and wind energy generation facilities. Created by the citizens of Seattle in 1902, SCL is the second-largest municipal utility in America. SCL purchases approximately 40% of its electricity and the majority of its transmission from BPA through a preference contract. SCL also provides ancillary services within its own balancing authority. The relationship between BPA and SCL creates a unique ...
Date: March 17, 2010
Creator: Kiliccote, Sila; Piette, Mary Ann & Dudley, Junqiao
Partner: UNT Libraries Government Documents Department

Opportunities for Open Automated Demand Response in Wastewater Treatment Facilities in California - Phase II Report. San Luis Rey Wastewater Treatment Plant Case Study

Description: This case study enhances the understanding of open automated demand response opportunities in municipal wastewater treatment facilities. The report summarizes the findings of a 100 day submetering project at the San Luis Rey Wastewater Treatment Plant, a municipal wastewater treatment facility in Oceanside, California. The report reveals that key energy-intensive equipment such as pumps and centrifuges can be targeted for large load reductions. Demand response tests on the effluent pumps resulted a 300 kW load reduction and tests on centrifuges resulted in a 40 kW load reduction. Although tests on the facility?s blowers resulted in peak period load reductions of 78 kW sharp, short-lived increases in the turbidity of the wastewater effluent were experienced within 24 hours of the test. The results of these tests, which were conducted on blowers without variable speed drive capability, would not be acceptable and warrant further study. This study finds that wastewater treatment facilities have significant open automated demand response potential. However, limiting factors to implementing demand response are the reaction of effluent turbidity to reduced aeration load, along with the cogeneration capabilities of municipal facilities, including existing power purchase agreements and utility receptiveness to purchasing electricity from cogeneration facilities.
Date: August 20, 2010
Creator: Thompson, Lisa; Lekov, Alex; McKane, Aimee & Piette, Mary Ann
Partner: UNT Libraries Government Documents Department

Comparison of Demand Response Performance with an EnergyPlus Model in a Low Energy Campus Building

Description: We have studied a low energy building on a campus of the University of California. It has efficient heating, ventilation, and air conditioning (HVAC) systems, consisting of a dual-fan/dual-duct variable air volume (VAV) system. As a major building on the campus, it was included in two demand response (DR) events in the summers of 2008 and 2009. With chilled water supplied by thermal energy storage in the central plant, cooling fans played a critical role during DR events. In this paper, an EnergyPlus model of the building was developed and calibrated. We compared both whole-building and HVAC fan energy consumption with model predictions to understand why demand savings in 2009 were much lower than in 2008. We also used model simulations of the study building to assess pre-cooling, a strategy that has been shown to improve demand saving and thermal comfort in many types of building. This study indicates a properly calibrated EnergyPlus model can reasonably predict demand savings from DR events and can be useful for designing or optimizing DR strategies.
Date: May 14, 2010
Creator: Dudley, Junqiao Han; Black, Doug; Apte, Mike; Piette, Mary Ann & Berkeley, Pam
Partner: UNT Libraries Government Documents Department

Open Automated Demand Response Dynamic Pricing Technologies and Demonstration

Description: This study examines the use of OpenADR communications specification, related data models, technologies, and strategies to send dynamic prices (e.g., real time prices and peak prices) and Time of Use (TOU) rates to commercial and industrial electricity customers. OpenADR v1.0 is a Web services-based flexible, open information model that has been used in California utilities' commercial automated demand response programs since 2007. We find that data models can be used to send real time prices. These same data models can also be used to support peak pricing and TOU rates. We present a data model that can accommodate all three types of rates. For demonstration purposes, the data models were generated from California Independent System Operator's real-time wholesale market prices, and a California utility's dynamic prices and TOU rates. Customers can respond to dynamic prices by either using the actual prices, or prices can be mapped into"operation modes," which can act as inputs to control systems. We present several different methods for mapping actual prices. Some of these methods were implemented in demonstration projects. The study results demonstrate show that OpenADR allows interoperability with existing/future systems/technologies and can be used within related dynamic pricing activities within Smart Grid.
Date: August 2, 2010
Creator: Ghatikar, Girish; Mathieu, Johanna L.; Piette, Mary Ann; Koch, Ed & Hennage, Dan
Partner: UNT Libraries Government Documents Department

Open Automated Demand Response Technologies for Dynamic Pricing and Smart Grid

Description: We present an Open Automated Demand Response Communications Specifications (OpenADR) data model capable of communicating real-time prices to electricity customers. We also show how the same data model could be used to for other types of dynamic pricing tariffs (including peak pricing tariffs, which are common throughout the United States). Customers participating in automated demand response programs with building control systems can respond to dynamic prices by using the actual prices as inputs to their control systems. Alternatively, prices can be mapped into"building operation modes," which can act as inputs to control systems. We present several different strategies customers could use to map prices to operation modes. Our results show that OpenADR can be used to communicate dynamic pricing within the Smart Grid and that OpenADR allows for interoperability with existing and future systems, technologies, and electricity markets.
Date: June 2, 2010
Creator: Ghatikar, Girish; Mathieu, Johanna L.; Piette, Mary Ann & Kiliccote, Sila
Partner: UNT Libraries Government Documents Department

Building Energy Information Systems: User Case Studies

Description: Measured energy performance data are essential to national efforts to improve building efficiency, as evidenced in recent benchmarking mandates, and in a growing body of work that indicates the value of permanent monitoring and energy information feedback. This paper presents case studies of energy information systems (EIS) at four enterprises and university campuses, focusing on the attained energy savings, and successes and challenges in technology use and integration. EIS are broadly defined as performance monitoring software, data acquisition hardware, and communication systems to store, analyze and display building energy information. Case investigations showed that the most common energy savings and instances of waste concerned scheduling errors, measurement and verification, and inefficient operations. Data quality is critical to effective EIS use, and is most challenging at the subsystem or component level, and with non-electric energy sources. Sophisticated prediction algorithms may not be well understood but can be applied quite effectively, and sites with custom benchmark models or metrics are more likely to perform analyses external to the EIS. Finally, resources and staffing were identified as a universal challenge, indicating a need to identify additional models of EIS use that extend beyond exclusive in-house use, to analysis services.
Date: March 22, 2010
Creator: Granderson, Jessica; Piette, Mary Ann & Ghatikar, Girish
Partner: UNT Libraries Government Documents Department

Study on Auto-DR and Pre-Cooling of Commercial Buildings with Thermal Mass in California

Description: This paper discusses how to optimize pre-cooling strategies for buildings in a hot California climate zone with the Demand Response Quick Assessment Tool (DRQAT), a building energy simulation tool. This paper outlines the procedure used to develop and calibrate DRQAT simulation models, and applies this procedure to eleven field test buildings. The results of a comparison between the measured demand savings during the peak period and the savings predicted by the simulation model indicate that the predicted demand shed match well with measured data for the corresponding auto-demand response (Auto-DR) days. The study shows that the accuracy of the simulation models is greatly improved after calibrating the initial models with measured data. These improved models can be used to predict load reductions for automated demand response events. The simulation results were compared with field test data to confirm the actual effect of demand response strategies. Results indicate that the optimal demand response strategies worked well for most of the buildings tested in this hot climate zone.
Date: January 9, 2010
Creator: Yin, Rongxin; Xu, Peng; Piette, Mary Ann & Kiliccote, Sila
Partner: UNT Libraries Government Documents Department

Findings from Seven Years of Field Performance Data for Automated Demand Response in Commercial Buildings

Description: California is a leader in automating demand response (DR) to promote low-cost, consistent, and predictable electric grid management tools. Over 250 commercial and industrial facilities in California participate in fully-automated programs providing over 60 MW of peak DR savings. This paper presents a summary of Open Automated DR (OpenADR) implementation by each of the investor-owned utilities in California. It provides a summary of participation, DR strategies and incentives. Commercial buildings can reduce peak demand from 5 to 15percent with an average of 13percent. Industrial facilities shed much higher loads. For buildings with multi-year savings we evaluate their load variability and shed variability. We provide a summary of control strategies deployed, along with costs to install automation. We report on how the electric DR control strategies perform over many years of events. We benchmark the peak demand of this sample of buildings against their past baselines to understand the differences in building performance over the years. This is done with peak demand intensities and load factors. The paper also describes the importance of these data in helping to understand possible techniques to reach net zero energy using peak day dynamic control capabilities in commercial buildings. We present an example in which the electric load shape changed as a result of a lighting retrofit.
Date: May 14, 2010
Creator: Kiliccote, Sila; Piette, Mary Ann; Mathieu, Johanna & Parrish, Kristen
Partner: UNT Libraries Government Documents Department

Scenario Analysis of Peak Demand Savings for Commercial Buildings with Thermal Mass in California

Description: This paper reports on the potential impact of demand response (DR) strategies in commercial buildings in California based on the Demand Response Quick Assessment Tool (DRQAT), which uses EnergyPlus simulation prototypes for office and retail buildings. The study describes the potential impact of building size, thermal mass, climate, and DR strategies on demand savings in commercial buildings. Sensitivity analyses are performed to evaluate how these factors influence the demand shift and shed during the peak period. The whole-building peak demand of a commercial building with high thermal mass in a hot climate zone can be reduced by 30percent using an optimized demand response strategy. Results are summarized for various simulation scenarios designed to help owners and managers understand the potential savings for demand response deployment. Simulated demand savings under various scenarios were compared to field-measured data in numerous climate zones, allowing calibration of the prototype models. The simulation results are compared to the peak demand data from the Commercial End-Use Survey for commercial buildings in California. On the economic side, a set of electricity rates are used to evaluate the impact of the DR strategies on economic savings for different thermal mass and climate conditions. Our comparison of recent simulation to field test results provides an understanding of the DR potential in commercial buildings.
Date: May 14, 2010
Creator: Yin, Rongxin; Kiliccote, Sila; Piette, Mary Ann & Parrish, Kristen
Partner: UNT Libraries Government Documents Department

Commercial and Industrial Base Intermittent Resource Management Pilot

Description: This scoping study summarizes the challenges with integrating wind and solar generation into the California's electricity grid. These challenges include: Smoothing intra-hour variability; - Absorbing excess renewable energy during over-generation periods; - Addressing morning and evening ramping periods. In addition, there are technical challenges to integrating retail demand response (DR) triggered by the wholesale conditions into the CAISO markets. The study describes the DR programs available to the consumers through the utilities in California and CAISO's ancillary services market because an integration of the wholesale and retail DR requires an understanding of these different offerings and the costs associated with acquiring them. Demand-side active and passive storage systems are proposed as technologies that may be used to mitigate the effects of intermittence due to renewable generation. Commercial building technologies as well as industrial facilities with storage capability are identified as targets for the field tests. Two systems used for ancillary services communications are identified as providing the triggers for DR enablement. Through the field tests, issues related to communication, automation and flexibility of demand-side resources will be explored and the performance of technologies that participate in the field tests will be evaluated. The major outcome of this research is identifying and defining flexibility of DR resources and optimized use of these resources to respond to grid conditions.
Date: November 30, 2010
Creator: Kiliccote, Sila; Sporborg, Pamela; Sheik, Imran; Huffaker, Erich & Piette, Mary Ann
Partner: UNT Libraries Government Documents Department

Quantifying Changes in Building Electricity Use, with Application to Demand Response

Description: We present methods for analyzing commercial and industrial facility 15-minute-interval electric load data. These methods allow building managers to better understand their facility's electricity consumption over time and to compare it to other buildings, helping them to ask the right questions to discover opportunities for demand response, energy efficiency, electricity waste elimination, and peak load management. We primarily focus on demand response. Methods discussed include graphical representations of electric load data, a regression-based electricity load model that uses a time-of-week indicator variable and a piecewise linear and continuous outdoor air temperature dependence, and the definition of various parameters that characterize facility electricity loads and demand response behavior. In the future, these methods could be translated into easy-to-use tools for building managers.
Date: November 17, 2010
Creator: Mathieu, Johanna L.; Price, Phillip N.; Kiliccote, Sila & Piette, Mary Ann
Partner: UNT Libraries Government Documents Department

Using Whole-Building Electric Load Data in Continuous or Retro-Commissioning

Description: Whole-building electric load data can often reveal problems with building equipment or operations. In this paper, we present methods for analyzing 15-minute-interval electric load data. These methods allow building operators, energy managers, and commissioning agents to better understand a building's electricity consumption over time and to compare it to other buildings, helping them to 'ask the right questions' to discover opportunities for electricity waste elimination, energy efficiency, peak load management, and demand response. For example: Does the building use too much energy at night, or on hot days, or in the early evening? Knowing the answer to questions like these can help with retro-commissioning or continuous commissioning. The methods discussed here can also be used to assess how building energy performance varies with time. Comparing electric load before and after fixing equipment or changing operations can help verify that the fixes have the intended effect on energy consumption. Analysis methods discussed in this paper include: ways to graphically represent electric load data; the definition of various parameters that characterize facility electricity loads; and a regression-based electricity load model that accounts for both time of week and outdoor air temperature. The methods are illustrated by applying them to data from commercial buildings. We demonstrate the ability to recognize changes in building operation, and to quantify changes in energy performance. Some key findings are: 1) Plotting time series electric load data is useful for understanding electricity consumption patterns and changes to those patterns, but results may be misleading if data from different time intervals are not weather-normalized. 2) Parameter plots can highlight key features of electric load data and may be easier to interpret than plots of time series data themselves. 3) A time-of-week indicator variable (as compared to time-of-day and day-of-week indicator variables) improves the accuracy of regression models of electric ...
Date: July 1, 2011
Creator: Price, Phillip N.; Mathieu, Johanna L.; Kiliccote, Sila & Piette, Mary Ann
Partner: UNT Libraries Government Documents Department

Statistical Analysis of Baseline Load Models for Non-Residential Buildings

Description: Policymakers are encouraging the development of standardized and consistent methods to quantify the electric load impacts of demand response programs. For load impacts, an essential part of the analysis is the estimation of the baseline load profile. In this paper, we present a statistical evaluation of the performance of several different models used to calculate baselines for commercial buildings participating in a demand response program in California. In our approach, we use the model to estimate baseline loads for a large set of proxy event days for which the actual load data are also available. Measures of the accuracy and bias of different models, the importance of weather effects, and the effect of applying morning adjustment factors (which use data from the day of the event to adjust the estimated baseline) are presented. Our results suggest that (1) the accuracy of baseline load models can be improved substantially by applying a morning adjustment, (2) the characterization of building loads by variability and weather sensitivity is a useful indicator of which types of baseline models will perform well, and (3) models that incorporate temperature either improve the accuracy of the model fit or do not change it.
Date: November 10, 2008
Creator: Coughlin, Katie; Piette, Mary Ann; Goldman, Charles & Kiliccote, Sila
Partner: UNT Libraries Government Documents Department

Design and Implementation of an Open, Interoperable AutomatedDemand Response Infrastructure

Description: This paper describes the concept for and lessons from the development and field-testing of an open, interoperable communications infrastructure to support automating demand response (DR). Automating DR allows greater levels of participation and improved reliability and repeatability of the demand response and customer facilities. Automated DR systems have been deployed for critical peak pricing and demand bidding and are being designed for real time pricing. The system is designed to generate, manage, and track DR signals between utilities and Independent System Operators (ISOs) to aggregators and end-use customers and their control systems.
Date: October 1, 2007
Creator: Piette, Mary Ann; Kiliccote, Sila & Ghatikar, Girish
Partner: UNT Libraries Government Documents Department

Estimating Demand Response Load Impacts: Evaluation of BaselineLoad Models for Non-Residential Buildings in California

Description: Both Federal and California state policymakers areincreasingly interested in developing more standardized and consistentapproaches to estimate and verify the load impacts of demand responseprograms and dynamic pricing tariffs. This study describes a statisticalanalysis of the performance of different models used to calculate thebaseline electric load for commercial buildings participating in ademand-response (DR) program, with emphasis onthe importance of weathereffects. During a DR event, a variety of adjustments may be made tobuilding operation, with the goal of reducing the building peak electricload. In order to determine the actual peak load reduction, an estimateof what the load would have been on the day of the event without any DRactions is needed. This baseline load profile (BLP) is key to accuratelyassessing the load impacts from event-based DR programs and may alsoimpact payment settlements for certain types of DR programs. We testedseven baseline models on a sample of 33 buildings located in California.These models can be loosely categorized into two groups: (1) averagingmethods, which use some linear combination of hourly load values fromprevious days to predict the load on the event, and (2) explicit weathermodels, which use a formula based on local hourly temperature to predictthe load. The models were tested both with and without morningadjustments, which use data from the day of the event to adjust theestimated BLP up or down.Key findings from this study are: - The accuracyof the BLP model currently used by California utilities to estimate loadreductions in several DR programs (i.e., hourly usage in highest 3 out of10 previous days) could be improved substantially if a morning adjustmentfactor were applied for weather-sensitive commercial and institutionalbuildings. - Applying a morning adjustment factor significantly reducesthe bias and improves the accuracy of all BLP models examined in oursample of buildings. - For buildings with low load variability, all BLPmodels perform reasonably well ...
Date: January 1, 2008
Creator: Coughlin, Katie; Piette, Mary Ann; Goldman, Charles & Kiliccote,Sila
Partner: UNT Libraries Government Documents Department

Preliminary Findings from an Analysis of Building Energy Information System Technologies

Description: Energy information systems comprise software, data acquisition hardware, and communication systems that are intended to provide energy information to building energy and facilities managers, financial managers, and utilities. This technology has been commercially available for over a decade, however recent advances in Internet and other information technology, and analytical features have expanded the number of product options that are available. For example, features such as green house gas tracking, configurable energy analyses and enhanced interoperability are becoming increasingly common. Energy information systems are used in a variety of commercial buildings operations and environments, and can be characterized in a number of ways. Basic elements of these systems include web-based energy monitoring, web-based energy management linked to controls, demand response, and enterprise energy management applications. However the sheer number and variety of available systems complicate the selection of products to match the needs of a given user. In response, a framework was developed to define the capabilities of different types of energy information systems, and was applied to characterize approximately 30 technologies. Measurement is a critical component in managing energy consumption and energy information must be shared at all organizational levels to maintain persistent, efficient operations. Energy information systems are important to understand because they offer the analytical support to process measured data into information, and they provide the informational link between the primary actors who impact building energy efficiency - operators, facilities and energy managers, owners and corporate decision makers. In this paper, preliminary findings are presented, with a focus on overall trends and the general state of the technology. Key conclusions include the need to further pursue standardization and usability, x-y plotting as an under-supported feature, and a general convergence of visualization and display capabilities.
Date: June 1, 2009
Creator: Granderson, Jessica; Piette, Mary Ann; Ghatikar, Girish & Price, Philip
Partner: UNT Libraries Government Documents Department

Open Automated Demand Response for Small Commerical Buildings

Description: This report characterizes small commercial buildings by market segments, systems and end-uses; develops a framework for identifying demand response (DR) enabling technologies and communication means; and reports on the design and development of a low-cost OpenADR enabling technology that delivers demand reductions as a percentage of the total predicted building peak electric demand. The results show that small offices, restaurants and retail buildings are the major contributors making up over one third of the small commercial peak demand. The majority of the small commercial buildings in California are located in southern inland areas and the central valley. Single-zone packaged units with manual and programmable thermostat controls make up the majority of heating ventilation and air conditioning (HVAC) systems for small commercial buildings with less than 200 kW peak electric demand. Fluorescent tubes with magnetic ballast and manual controls dominate this customer group's lighting systems. There are various ways, each with its pros and cons for a particular application, to communicate with these systems and three methods to enable automated DR in small commercial buildings using the Open Automated Demand Response (or OpenADR) communications infrastructure. Development of DR strategies must consider building characteristics, such as weather sensitivity and load variability, as well as system design (i.e. under-sizing, under-lighting, over-sizing, etc). Finally, field tests show that requesting demand reductions as a percentage of the total building predicted peak electric demand is feasible using the OpenADR infrastructure.
Date: May 1, 2009
Creator: Dudley, June Han; Piette, Mary Ann; Koch, Ed & Hennage, Dan
Partner: UNT Libraries Government Documents Department

Opportunities for Energy Efficiency and Automated Demand Response in Industrial Refrigerated Warehouses in California

Description: This report summarizes the Lawrence Berkeley National Laboratory's research to date in characterizing energy efficiency and open automated demand response opportunities for industrial refrigerated warehouses in California. The report describes refrigerated warehouses characteristics, energy use and demand, and control systems. It also discusses energy efficiency and open automated demand response opportunities and provides analysis results from three demand response studies. In addition, several energy efficiency, load management, and demand response case studies are provided for refrigerated warehouses. This study shows that refrigerated warehouses can be excellent candidates for open automated demand response and that facilities which have implemented energy efficiency measures and have centralized control systems are well-suited to shift or shed electrical loads in response to financial incentives, utility bill savings, and/or opportunities to enhance reliability of service. Control technologies installed for energy efficiency and load management purposes can often be adapted for open automated demand response (OpenADR) at little additional cost. These improved controls may prepare facilities to be more receptive to OpenADR due to both increased confidence in the opportunities for controlling energy cost/use and access to the real-time data.
Date: May 11, 2009
Creator: Lekov, Alex; Thompson, Lisa; McKane, Aimee; Rockoff, Alexandra & Piette, Mary Ann
Partner: UNT Libraries Government Documents Department