Load flexibility is essential for balancing supply and demand during peak price periods, supporting grid stability and lowering energy costs. However, traditional utility-led direct load control programs have been criticized for occupant discomfort and declining participation. In contrast, the proposed transactive method accounts for household preferences while intelligently balancing comfort with cost and coordinating the operation of in-home appliances. This paper presents the methodology and test results for a transactive coordinated load control of space cooling and water heating to respond to time-of-use and real-time electricity pricing. The method employs data-driven models for both cooling and water heating to show that effective demand response can be achieved at short control intervals (10~min), with demand curves generated dynamically at each interval and aggregated to determine a clearing price that coordinates power allocation while maintaining occupant comfort. The algorithm was implemented and validated in a physical home using commercially available internet-connected thermostats and water heater controllers, demonstrating that for time-of-use pricing, the strategy achieved 41.7\% demand reduction; for real-time pricing, 32.5\% demand reduction while maintaining temperatures within the comfort range.

Efficiently managing energy usage to balance supply and demand on the electric grid is crucial, especially with the widespread deployment of distributed variable renewable electricity generation. This paper introduces two duty-cycle control methods for heating systems, adjusting thermostat setpoints to limit and shift electricity demand. The control approaches employ innovative techniques, such as adaptive duty cycling, to prioritize household thermal comfort while reducing peak demand. These control methods can respond to signals from the electric grid, including demand targets and time-of-use tariffs, and were tested physically on an electric furnace and heat pump in a test home during winter conditions in 2021 and 2022. The results are given as average demand reductions and energy use impacts with respect to the average indoor-outdoor temperature difference during the control period. For heat pumps, demand limiting control reduced power by 18.5% and 23.3% for indoor-outdoor temperature differences of 30 degrees F and 40 degrees F. Preheating-based demand shifting achieved reductions of 34.8% and 33.2% for the same temperature differences. Electric furnace tests showed demand reductions of 33.8% and 25.3% for demand limiting, and 56.1% and 45.7% for preheating-based demand shifting. These findings highlight the potential for innovative control methods to enhance grid efficiency and reduce energy consumption.

The management of end-use energy loads, including commercial buildings, has been increasingly investigated as a promising source of services for the electric power grid. Lighting consumes about 17% of the total electricity use of U.S. commercial buildings; however, it may contribute significantly to services that improve the reliability and resilience of the grid due to its rapid speed of response. Connected lighting systems (CLS), which build upon solid-state light-emitting diode (LED) technology, can change their power demand more quickly than most other building electricity end-uses. But the potential of CLS to provide grid services has not been fully investigated. In this paper, we describe initial research to evaluate the potential of CLS for providing frequency regulation grid service. Frequency regulation is a reliability service that corrects in a matter of seconds for short-term changes in the balance between supply and demand that might affect the stability of the power system in a specific balancing area. Frequency regulation signals for a medium office building are generated from the normalized test signals for the PJM Regional Transmission Organization Reg-A and Reg-D regulations services. CLS are controlled in simulations to follow the Reg-A or Reg-D signal and thereby provide frequency regulation service. The performance of CLS providing frequency regulation is evaluated using the PJM 40-Minute Performance Score Template. The performance scores obtained for five different CLS categories responding to both Reg-A and Reg-D signals far exceed the minimum qualification score, a very promising result for CLS aiming to provide frequency regulation service.

Automated fault detection and diagnostic tools are beginning to appear on the market embedded in heating, ventilating, air-conditioning equipment and lighting systems, as stand-alone tools, and as remote services provided to buildings. The sensor has physically changed, but its value can be corrected simply by subtracting 5 F from every value reported. This chapter describes a process that can be used to automatically correct faults using algorithms implemented in controls and provides examples of such capabilities that have been developed and demonstrated by a team at the US Department of Energy Pacific Northwest National Laboratory. Self-correction and fault tolerance require redundancy, which can be physical or analytical. Physical redundancy requires duplicate equipment and components so that when one fails or degrades sufficiently, another or a group of others can replace the one that failed. Fault corrections can be simple subtractive elements or more complex corrections that can depend on time or values of multiple variables.

The World Wide Web (the Web) is rapidly transforming many business practices. The purpose of this chapter is to show readers how facility management tools provided by application service providers (ASPs) via the Web may represent a simple, cost-effective solution to their facility and energy management problems. All participants in the management of a facility, from building operations staff to tenants, can get convenient access to information and tools to meet their needs more effectively by simply using a web browser and an Internet connection. Further, energy tools that are integrated into these facility management software environments become readily accessible and can be linked to other tools for managing work orders for getting energy-wasting problems fixed. The chapter also describes how the Federal Energy Management Program (FEMP) is working to make such energy tools readily available.

Synopsis This paper presents a case for application of automated monitoring, analysis and diagnostic tools for monitoring-based commissioning. Selected examples are presented in which such tools have been used successfully to support commissioning activities in southwestern Canada and the U.S. Pacific Northwest. The first example involves use of spreadsheet-based tools to automatically generate diagnostic plots that are visually examined for specific features that reveal operational problems in space conditioning systems of large commercial buildings. The findings then guide re-tuning actions to increase building energy efficiency. This is followed by application of a tool for continuous monitoring of whole-building energy use to automatically track energy savings resulting from a utility commissioning program. This tool also provides a means by which to detect degradation of savings and performance to guide monitoring-based commissioning actions. The potential use of automated diagnostic tools for chillers and packaged air conditioners is then described for continually commissioning these units. The paper concludes with a discussion of the impacts of this approach on commissioning, including potential time savings, associated cost savings, and improvements in the quality of commissioning.

This chapter provides an overview of fault detection and diagnostics (FDD), including descriptions of fundamental processes, important definitions, and examples that building operators and managers can implement using data collected from the building automation systems or dedicated logging devices. Poorly maintained, degraded, improperly controlled equipment wastes an estimated 10% to 30% of the energy used in commercial buildings. Much of this waste could be prevented with widespread adoption of FDD, an area of investigation concerned with automating the processes of detecting faults in physical systems and diagnosing their causes. Fault detection and diagnostics can be performed "manually" through visual inspection of charts, trends or can be fully automated. In addition to the data, the basic building blocks of automated FDD systems are the methods for detecting faults and diagnosing their causes. Approaches to FDD range from methods based on physical, analytical models based entirely on first principles, to those driven by performance data and using artificial intelligence or statistical techniques.

Variable-air-volume (VAV) systems are used in many office buildings. The minimum airflow rate setting of VAV terminal boxes has a significant impact on both energy consumption and indoor air quality. Conventional controls usually have the terminal's minimum airflow rate at a constant (e.g., 30% or more of the terminal design airflow rate), irrespective of the occupancy status, which may cause problems, such as excessive simultaneous heating and cooling, under ventilation, and thermal comfort issues. This paper examines the potential of energy savings from occupancy-based controls (OBCs). The sensed occupancy information, either occupant presence or people count, is used to determine the airflow rate of terminal boxes, the thermostat setpoints, and the lighting control. Using EnergyPlus, a whole-building energy modeling software, the energy savings of OBC strategies are evaluated for representative existing medium office buildings in the U.S. The simulation results show that the conventional OBC, based on occupant presence sensing, can save 8% of whole-building energy use in Miami (hot climate) for systems without air-side economizer and about 13% in both Baltimore (mixed climate) and Chicago (cold climate). Comparatively, the advanced OBC, based on people counting, can save 8% in Miami to 23% in Baltimore for systems with economizers. The outdoor-air fraction of the supply air from air-handling units significantly affects the potential energy savings from the advanced OBC strategy. In addition to energy savings, the advanced OBC satisfies the zone ventilation during all occupied hours over the whole year.

This chapter discusses the benefits of commissioning and describes a vision of the future where most of the objectives of commissioning will be accomplished automatically by capabilities built into the building systems themselves. It identifies some of the technologies that will be needed to realize this vision and ends with a call for all involved in the enterprise of building commissioning and automation to embrace and dedicate themselves to a future of automated commissioning. Together these technologies will enable realization of highly automated commissioning and operation. Even then, a market demand will need to develop to drive the creation of new equipment and control systems with automated commissioning capabilities. The recommend that the building commissioning community embrace the opportunities posed by new technology and employ them to deliver better services. The benefits in having a full-blown enterprise energy management system have been tremendous.

The emerging technology of wireless sensing shows promise for changing the way sensors are used in buildings. Lower cost, easier to install, sensing devices that require no connections by wires will potentially usher in an age in which ubiquitous sensors will provide the data required to cost-effectively operate, manage, and maintain commercial buildings at peak performance. This chapter provides an introduction to wireless sensing technology, its potential applications in buildings, three practical examples of tests in real buildings, estimates of impacts on energy consumption, discussions of costs and practical issues in implementation, and some ideas on applications likely in the near future.

Variable-air-volume (VAV) systems are used in many office buildings. The terminal's minimum air flowrate set point is an important parameter that has significant impact on energy consumption and indoor air quality. Conventional controls usually have the terminal's minimum air flowrate at a constant, irrespective of the occupancy status. Such practice may cause energy waste, ventilation and thermal comfort problems. This paper examines the potential of energy savings by occupancybased controls (OBCs). The sensed occupancy information, either presence or the people count, is used to determine the air flowrate of terminal boxes, the thermostat set points, and the lighting as well. Using EnergyPlus, energy savings of OBC strategies are evaluated for representative existing medium office buildings in the U.S. Simulation results show that for the location of Baltimore, MD, the use of air-side economizer or not does indeed have significant impact on the comparison between the two OBC strategies. The OBC based on the occupant presence has about 13% wholebuilding energy savings no matter whether the air-side economizer is used in the AHU operation. However, for the OBC based on the people count, the percentage of energy savings increases from 13% for the case of not using air-side economizer to 23% for the case of using airside economizer.

We describe initial research to evaluate the potential of connected lighting systems (CLS) to provide grid services. We develop a model for CLS, using a set of parameters to represent operation behaviors and constraints: maximum power, minimum power, nominal power, ramp rate, and time delay. Parameter values are generated for representative CLS. Lighting-power demand curves are constructed, indirectly capturing building-occupant preferences for lighting as functions of electricity price. The CLS model and the demand curves are incorporated into a transactive control platform to simulate CLS providing grid services. Previous research has shown transactive control (TC) to be a powerful tool to enable end uses to provide grid services through a hybrid economic-control approach. Initial quantitative results are provided for CLS in a medium commercial office building to show the amount of demand reduction and the associated energy savings.

Advanced controls play an essential role toward the improvement of building operational efficiency and the integration of responsive loads in buildings for grid services. Ideally, control algorithms must be sufficiently tested and validated before they are applied on real systems. This paper presents the development and current state of such an evolving test bed to support and enable experiments on advanced controls for buildings. The test bed presented in this paper consists of nine operating buildings—which possess various types of equipment and systems having different control systems and communication mechanisms (e.g., media and protocols) used in building automation systems—on the Pacific Northwest National Laboratory campus. The test bed architecture is developed in such a way that (1) it supports interactions among the buildings and heterogeneous building components and systems, including both virtual and physical devices, e.g., heating, ventilating, and air-conditioning and lighting systems; (2) it can be easily reconfigured for different control topologies and methodologies, e.g., centralized and distributed; (3) it allows selection of communication protocols, communication media, and computation resources; and (4) it is part of a larger cyber-physical test bed that includes both physical and virtual assets on distributed renewable generation, energy storage, and power system assets. Practical application: The test bed presented in this paper can be used by industry to develop and evaluate the performance of advanced control algorithms on real systems for buildings and buildings-to-grid applications. This provides practitioners an opportunity to test the applications and modify them accordingly based on their use cases and selection criteria, e.g., a controller modulating the temperature in a hospital will have different criterion as compared to an office building.

Although smart thermostats have increasingly provided homeowners with abundant operational data related to advanced HVAC control and energy usage management in homes, there is a lack of systematic frameworks that can utilize such data to generate actionable information for advanced home comfort system diagnosis and control. Recognizing that a home thermal model, which is capable of connecting weather and HVAC operational data, is crucial to this framework, this paper introduces a home thermal model that is built upon the standard RC (Resistor–Capacitor) approach and the one virtual envelope assumption to describe the thermal dynamics of a home. A parameter estimation scheme is also developed that enables automatic, sequential, and optimal estimation of the model parameters, i.e., the thermal properties, of a home. Finally, the home thermal model and its parameter estimation scheme are tested using data collected over 63 consecutive days from a test home. In the test, the length of data that can provide enough robustness for parameter estimation is investigated. It is found that 10 days of data are enough, although 20 or more days of data can provide more robust results. In addition, when the model is used to make 12-hour-ahead predictions of indoor temperature, the resulting mean, maximum, and 95%-confidence-interval absolute are 0.31°C, 1.72°C, and 0.90°C, respectively, if the model is trained using 10 consecutive days of data, and 0.27°C, 1.19°C, and 0.72°C, respectively, if 20 consecutive days are used. Therefore, the proposed home thermal model requires only a modest amount of training data to yield fairly accurate prediction and is able to perform better with more data.

The study presented focuses on control of central electric resistance heating (often referred to as electric furnaces) in a manner to meet a specified target reduction in average electric power demand over 5-minute utility verification periods. The paper describes a supervisory control method that uses a small number of sensed points to meet these target power demand reductions while ensuring that indoor temperature is maintained within a comfortable range. Testing of the control method is performed in two identical test homes with the control methodology augmented to account for practical complexities in the operation of the heating system equipment (e.g., minimum-off [lock-out] time, response activation delay, and data latency). The test homes, equipment in them, data collection apparatus, and control platform are described as well as results of the testing. The analysis of results shows the potential for control of electric heating systems to provide demand response as well as some limitations when used alone without coordinated control with other end-use equipment and appliances. Discussion of results includes a brief introduction to a method for coordinated control of multiple appliances in homes and identification of potential future research to realize the underlying vision of homes providing services to the power grid.

In general, a hardware-in-the-loop (HIL) building simulation has lower cost and fewer practical limitations (e.g., scheduling issues) than field tests in occupied buildings, while also overcoming limitations of simulations alone by capturing the full behavior of some physical systems, equipment, and components. However, the implementation of an HIL can be difficult due to the scarcity of appropriate tools. This paper presents an agent-based framework for HIL simulation. It can be used for investigation of controller performance via controller-in-the-loop simulations and also HIL for system synthesis. In the latter case, both controllers and major equipment participate in tests to ensure that dynamics of equipment operation are correctly captured in addition to controller performance. The HIL simulation framework presented allows such actual physical parts to be included in the framework while representing others for which behaviors are better known and modeled in simulation models. The mechanism implemented in the framework to synchronize simulations in software with real-time operation of physical equipment is described. As an example, use of the HIL simulation framework is illustrated through a brief study of speed control of the supply fan in the air handling unit of a variable-air-volume building heating, ventilating and air-conditioning system. (C) 2018 Elsevier B.V. All rights reserved.

This paper presents a review of recent research and development on methodologies relevant to automating mapping of points in building control systems and between building control systems and external or replacement software and hardware. Manual point mapping is labor intensive and costly, presenting a major impediment to innovations in building control (e.g., automated fault detection and diagnostics, self-healing, and automated commissioning for existing building control systems). The methods reviewed focus on classifying building control system points, especially sensor classifications by sensor type. Fewer publications address other important aspects of the point mapping problem, such as discovering spatial and functional relationships among points, relationships between control system points, physical systems, and equipment, and between various equipment and the systems of which they are part, and discovering metadata, normalizing it to a common namespace, and assigning the metadata to control system points. To motivate further development of new automated point mapping approaches, we identify many research questions organized into four key technical needs: 1) a complete solution and underlying problem formulation, 2) alignment of methods with the actual point mapping problem, 3) test cases, data sets for testing, explicit test procedures, and consistent performance metrics for reporting testing and evaluation results, and 4) understanding of the applicable data space to ensure future adaptability of automated BAS point mapping.

This paper presents the design, deployment, and initial testing of an agent-based test bed to support a wide range of experiments and demonstrations of advanced control of building systems for energy efficiency, occupant comfort, and reliable interaction with the electric power grid. The test bed possesses the following major characteristics: 1) it supports interactions among heterogeneous components and systems; 2) it can be easily reconfigured to test, validate, and demonstrate different control methodologies ranging from fully centralized to completely distributed control architectures; 3) it provides an option to choose the communication protocols/mediums and the location of agents for managing the distribution of computation resources; and 4) it is an integrated part of a larger test bed that includes distributed renewable generation, energy storage, power systems, and peer buildings. Some of these features are demonstrated using two experiments on a real building HVAC (heating, ventilation, and air-conditioning) system, which is a part of the test bed. Both experiments focus on control for buildings-grid integration applications. In the first experiment, several distributed control agents coordinate with one another to limit the fan power consumption of an air-handling unit (AHU). In the second experiment, a centralized controller tracks the total AHU fan power to a predefined profile.