Recent industry trends show that installation of metering devices after the primary utility meter that measure actual resource consumption are bringing multiple benefits to commercial building owners. These submetering systems could allow GSA to monitor energy usage for individual tenants, departments, whole floors, pieces of equipment or other loads individually to account for their actual energy usage.The GSA developed a Submeter Framework that provides a standardized means to map submeter functionalities to a range of benefits. The framework also assists stakeholders with identifying data needed to determine the associated costs and monetary savings resulting from submetering projects.

The use of submeters has grown significantly in recent years at both the National and State level. As the value of submeters becomes more well known and practiced, the allowance and requirement of metering systems has increased tremendously to attain the wide array of benefits they offer. The presentation summarizes the current state of policies related to submetering at the National, State, and City level.

All dashboards are not created equal. The term “dashboard” today continues to be flaunted when marketing any screen-based display with flashy graphics and energy related charts. But what do you get when you decide to purchase a dashboard?  This workshop presents a rational method for categorizing building automation dashboards to indicate required features at each level so that owners, operators, designers, and contractors can discuss their needs in the same terms.

The presentation will provide the latest available technology in smart grid interface through building automation systems.  Practical scenarios and applicable "rule-of-thumb" checks in smart metering will be discussed.  The presentation will include an overview of governing code and various ASHRAE and IEEE guidelines and standards.

Both the ASHRAE Standard 90.1 and California Title 24 Building Energy Efficiency Standards require AHU supply duct pressure setpoints on variable-air-volume (VAV) systems with direct digital controls (DDC) be reset at the zone level. While many different implementation methods have been proposed, the Trim and Respond (TR) method is one of the more popular strategies. Although the TR methods are popular many are difficult to successfully implement due to issues maintaining stable control, complexity of tuning parameters, or sacrificed zone level comfort. A newer “Tiered Trim and Respond” (TTR) strategy has improved control stability, increased response time and eased implementation in the field compared to the traditional TR method, while achieving similar fan energy savings. The TTR method recognizes that the instability of the Trim and Respond (TR) methods is often caused by targeting the system’s maximum damper position at nearly 100% open. At these extreme positions the system is most sensitive to disturbances or load changes and therefore stable control is difficult. The TTR method compares the maximum VAV damper command or position value to three different tiers of high/low thresholds, and responds by varying the trim and respond rates to adjust the static pressure set points. The targeted average maximum VAV damper value is lowered from the traditionally recommended 95% or 98% open position to a lessor range of 80% to 90% open. The TTR method pushes the setpoints slightly off the “ideal static pressure curve”, but provides more stable system control while maintaining a quick response to load changes. The TTR method is being implemented in a year-long demonstration at five different building sites in various building types and usage on four different building automation systems. Preliminary demonstration results show that among seven AHUs fan energy savings vary from 6% ~ 47% with the TTR compared their normal or existing fixed static pressure control setup.  In four of the RTUs the fan energy savings are 33% to 36%. Additionally, two of the demonstration AHUs utilize two implementations of Trim and Respond strategies. The TTR method is more responsive to load changes and maintains better indoor air quality while using a similar amount of fan energy. This paper describes the TTR methodology, the five demonstration sites and their direct digital systems, the preliminary energy savings compared to fixed static pressure control, and control performance characteristics compared to two different TR methods.

A rapidly growing amount of office buildings in the Netherlands is using an Aquifer Thermal Energy Storage (ATES) system. An ATES system uses a well pump to extract cold groundwater for cooling. The returned warm water is injected and stored in a second well. During winter this warm water is used for heating and the returned cold water is injected again in the first well. An optimal functioning ATES system can significantly reduce energy use and CO₂emissions of an office building. An essential condition for optimal ATES operation is the thermal balance of the system. Office buildings typically store much more heat than cold, causing the entire underground slowly to heat up and causing cooling capacity problems on the long term. This is compensated by using cold outdoor air to store additional cold during the winter, called regeneration. In this research a methods were evaluated to keep the thermal storage in balance Model Predictive Control (MPC) is used to control the amount of regenerated cold to maintain the ATES balance. The key element in the method is the reference model to calculate the expected stored amount and use as model for MPC. A reference model was constructed based on a case study building and it contains three main blocks: ATES, Heating/Ventilation/Air-conditioning (HVAC) and load simulation. For the ATES system a lightweight finite element simulation method is developed, based on an axisymmetric grid. An additional method was developed to reconstruct the injected water temperatures and volumes, because these were not measured in the case study installation. The HVAC and load simulation models are based on logged building management system (BMS) data. The use of BMS data has the large advantage that models are easily configured and can automatically adjust to changes in the building. Using MPC it was possible to keep the ATES in balance over a simulated 20 years period. By using a slight cold surplus as target, the effect of exceptionally warm winters is minimal and extraction temperatures are very constant. For the case study building it can be concluded that MPC, using the developed reference model, is capable of automatically maintaining the ATES balance. Because the case study building type and size is comparable to the majority of the new Dutch office buildings, it is expected that large parts of the method are universally applicable.

District cooling system (DCS) consists of chillers, cooling towers and pumps, and is widely used owing to high energy efficiency. However, due to higher energy costs and greenhouse gas emission issues, more energy-efficient total plant operation, not only the chiller system but also the cooling water system, is required to reduce the energy consumption and CO2 emission. In this report, we will present real-time online optimization control, to minimize the energy consumption, in district cooling plants.  As well as the theoretical background for real-time online optimization control methodology, the report contains examples of successful application including the reduction in primary energy consumption rates. Herein, the objective function of the optimization is to minimize the primary energy consumption rate whilst satisfying chilled water demand, and the optimization controls are constructed and realized by:  Optimum Chiller control, Optimum cooling tower control, Optimum cooling water pump control, Optimum primary pump control and Optimum secondary pump control. The effectiveness of the real-time online optimization control methodology and the actual reduction of the primary energy consumption by applying the optimization are shown based on the result of operation data.

Single zone (SZ) air handling units (AHU) are widely applied in a large conditioned spaces. A SZ AHU typically consists of a chilled water cooling coil, a hot water heating coil and a supply fan. For a constant volume (CV) SZ AHU or variable air volume (VAV) SZ AHU operating at a minimum airflow, the control valve of either the cooling coil or heating coil is modulated to vary the supply air temperature and consequently control space air temperature. Traditionally, a single control loop is applied to modulate the control valve directly based on the space air temperature. The traditional control is simplistic in nature however, suffers significant drawbacks. Due to the thermal capacity of both the water in the coils and the air in the conditioned space, the system often becomes unstable if the controller is not well tuned. On the other hand, cascade control makes the control system more adaptive and robust. A cascade control can be applied to SZ AHU in order to stabilize the system. The primary controller reads the room air temperature and determines the required supply air temperature for secondary controller which then controls the heating/cooling coil valve. The purpose of this paper is to demonstrate the stability of the cascade control method in SZ AHU system, theoretically and experimentally. First a theoretical model of the single zone AHU system with transfer functions is developed and root-locus analysis is performed with MATLAB. Then the experiment is conducted on a SZ AHU to evaluate the system performance using the traditional and cascade control respectively. The simulation and experiment results shows the cascade control stabilizes the system operation.

As an energy delivery public utility, Ameren is responsible for the grid components that carry power to your  business. We've been incorporating smart grid improvements into the distribution system for years - with a focus on improving reliability and reducing outages. As part of our infrastructure improvements, we will be implementing even more projects, including: advanced customer meters, automated switches and controls, and training for our employees to ensure that electric and gas service is there when needed. The presentation will highlight where Ameren stands in the deployment of smart grid technology and what that means for building owners, operators and designers.

Task tuning is an innovative approach to lighting control in commercial buildings that is growing in popularity. It has the potential to save energy without decreasing occupant satisfaction because many commercial spaces are over lit. More widespread adoption of dimmable ballasts and LED lighting would create more opportunities to apply this simple control strategy that may help satisfy a client’s efficiency goals. In addition, the combination of smart grids and increasingly sophisticated lighting controls opens up the possibilities of using this strategy for demand response and energy cost management. We will define proper task tuning techniques and other best practices.

Consumers Energy’s Smart Energy Program will allow for an enhanced and exciting level of communication between our company and our customers. Installations for residential customers began in late 2012 and commercial and industrial customer smart meter upgrades began in early 2015 and continue through 2017. In the future, customers will also have the ability to sign up for money saving programs. This presentation highlights opportunities and next steps for the utility and its customers through smart grid implementation.

Building operators can save significant amounts of time by using Direct Digital Control (DDC) system programming logic and by creating concise Building Monitoring System (BMS) screens to troubleshoot heating, ventilating, and air conditioning (HVAC) systems.  They can also drive down energy costs.  A mature energy efficiency utility has proposed the use of fundamental psychrometric formulas and parameters into DDC systems’ control logic to check sensor accuracy, improve equipment performance, and to verify valve and damper operation.  Relative humidity sensors are used to control humidifiers and dehumidification coils, and have been indirectly used to calculate enthalpy in economizers. The application of fundamental HVAC formulas into the DDC control logic identifies inaccuracies in relative humidity sensors, which, if left uncorrected can result in poor economizer performance, or unnecessary humidification and/or dehumidification. These problems frequently increase the cost of operation of the HVAC equipment. The utility also has applied outdoor air dew point calculations to check sensor performance and to optimize chiller and humidification system performance.  This paper will define dew point under several conditions, describe how it differs from relative humidity, and describe their effects on latent and sensible cooling and heating loads.  It will also present psychrometric facts and how they can be used to check the performance of HVAC systems.  For example, if the chilled water temperature is higher than the entering  air dew point temperature of a cooling coil, the coil will not remove any moisture from the entering air; therefore, the dew point will remain the same.  Programing this logic into the DDC can be done with simple “if” statements, and can be used to identify faulty sensors.  The paper will present a sample programming statement that can be modified to the facility’s DDC system programming language. The paper will also describe how, once the logic statement is entered into the DDC, it is important that the BMS screens are easy to evaluate and thus make it easy for operators to troubleshoot any system performance issues. An example of a fault detection screen for air handling unit economizers and an outdoor air weather station will also be included.

Complexities, with the modern smart buildings are continuously increasing with time. Building automation systems encompass many sensors and controllers to achieve the desired level of comfort. However, in reality it is difficult to achieve the perceived comfort because of different faults, occupant misusages and their consequences. Though, sometimes occupants do not well aware with the origin of different causes and their unusual impact on comfort and cost. In order to fill the gap between expectation or what was planned before and reality, building energy management systems (BEMS) need to be designed in such a way that they will be able to react or advise different reactive actions to the occupants. Considering real time scenarios all major anomalies primarily arises from three main sources: Different failures in buildings including HVAC, Misusage i.e. human irrelevant behaviors and Various unplanned situations related to occupancy and appliances. Above abnormal situations could cause huge penalty over occupant’s comfort and operational cost. Potential faults and their causes need to be identified. Present work considers a hazard and operability analysis (HAZOP) for the whole building system. HAZOP is used to perform a detail analysis of all possible causes of discrepancies in building operation. HAZOP is a qualitative approach but it can be quantified by using “Risk assessment matrix” based on the frequency and severity of faults. According to HAZOP analysis, building facility is divided in different sub-systems and each sub-system is studied in detail. Each sub-system assigned with a variable and deviations from the normal range of these variables are considered as symptoms. Considering the detected symptoms, a global signature table can be computed. However due to presence of non-isolable causes this table is further reduced to observable signature table. To avoid the decision error a minimal set of diagnosis is performed on the basis of difference between computed and observable signatures. Further, all the possible risks are ranked according to their degree of severity and integrated with reactive energy management. Finally, paper will address the application of the developed methodology for an office without HVAC.

Faults in heating, ventilation and air conditioning (HVAC) systems results in excessive energy waste and space comfort issues. In this study, the goal is to identify fan belt slippage and pressure setpoint override faults. These faults can be easily detected based on the correlation of head, flow and power for fans and pumps. However, due to the lack of flow meters in HVAC systems, currently, these faults have to be detected by either model-based or rule-based fault detection and diagnosis (FDD) approaches. Model based approaches generally require high computational time, which makes them unsuitable for real time applications.  The rule based approaches use other operating data rather than flow rate and cannot accurately detect these faults. On the other hand, a virtual flow meter technology, which determines flow based on the measured head and power of fans and pumps, makes the flow measurement accurately and economically without the need of physical flow meters. The purpose of this paper is to evaluate a FDD method for faults in air and water distribution systsms using the measured head and power along with a virtual flow meter. First, the correlation between power and head and the correlation between the head and flow are derived without and with faults based on fan and pump performance and system curves. Then experiment is conducted to validate develop FDD method by comparing the actual corrections with the fault free correlations. The results show the proposed FDD method can effectively detect these faults.

The paper will be a case study of the New Orleans BioInnovation Center (NOBIC) design, commissioning, controls optimization, and analytic smart building system. NOBIC was awarded the AIA Committee On The Environment (COTE) Top Ten Award at this year's AIA conference for its sustainability features and opeations. In highly sustainable buildings, three main aspects are required. First, the building's design has to support low energy operation. Second, the building must be technically commissioned. Technical commissioning requires testing of all components and sequences with personal verification. Lastly, a highly sustainable building, as with all buildings, will start to drift from optimum operations, and it will start to consume more energy over time. Analytic programs can help maintain operation at optimal levels. Sustainability goals provided the design team with an opportunity to optimize the design without creating major cost additions to the design which would result in cost overruns. Many of the ways the design team lowered energy use was by optimizing systems rather than high inital capital outlays. Technical commissioning verified that the installed systems met the intent of the design team as well as providing a baseline performance of the building that was truly in an optimal condition. Technical commissioning also utilizes the facilities staff in the commissioning process so that they can fully understand the building and design, as well as know how to bring the building back to an optimal state. An analytics/ongoing commissioing program was added to the control system in order to maintain optimal performance. The analytics platform looks at a number of different rules from simple comparisons to complex analysis in order to provide the operators with actionable data to maintain their building. Smart Building Systems go beyond next level software analytics, controls packages, or day one installations. Smart Building Systems require an integrated approach in order to design, commission, and operate highly sustainable buildings long-term.

Significant research effort is developing urban building energy modeling (UBEM) tools, which allow evaluating city-wide energy demand and supply strategies. In order to characterize simulation data inputs for buildings, these are typically grouped into representative “archetypes” which simplify models and impact accuracy. The work presented addresses the current state of the UBEM field and presents the application for the City of Boston of an automated simulation workflow based on available GIS datasets. Then, a probabilistic calibration model for archetypes is proposed and validated for yearly and monthly energy use in districts in Kuwait and Cambridge.

The use of transient computer simulations for quantifying energy use of individual buildings is now standard in both research and industry. However, their use has been computationally prohibitive at the larger scales of districts and cities. We present a new simulation platform that offers a spatially differentiated, hourly analysis of energy consumed by the built environment. The City of Westminster, within central London, was chosen for the first pilot application due to diversity of building types and high-energy demand. This seminar highlights the challenges associated with its development, as well how it supports the assessment of energy systems in cities.

Speaker will provide an overview of the smart grid and demand response related regulatory process as it proceeds from laws promulgated at the federal level by Congress and associated regulations issued by the Federal Energy Regulatory Commission (FERC) including recent Supreme Court decision #745, to the Regional Transmission Authority (or Independent System Operator) and impacting state legislatures and regulatory commissions.

This speaker provides an overview of the state level regulatory process and how various utility tariffs are established by the rate case or "contested case" process.

This speaker provides an overview of the process of how 3rd party aggregators work with utilities and building owners to save energy and not only help manage energy cost for consumers but also produce savings in demand response programs.

This presentation investigates the use of utility billing data for residential buildings, combined with highly granular weather data to disaggregate energy data into end uses, determine the type of HVAC system in use, and predict future months’ disaggregated energy use. This is accomplished through the use of an inverse thermodynamic-based model that uses binned temperature values.  This methodology was verified using a dataset of several hundred homes. The resulting information can provide insights to residential building customers to motivate energy savings behaviors.

A simple gray box model has been developed for residential buildings to predict the future  HVAC energy use given the weather forecast.  The model is based on thermostat data (temperature, setpoint, and HVAC on/off information) and the outside weather conditions (outdoor temperature, solar irradiation and wind speed). The accuracy of the future HVAC energy use for over 1000 houses across the United States predicted by the models was compared with the actual data. Predicted energy use from the model is within +/- 10% of the actual HVAC used. The temperature prediction error was within +/- 0.3C.

The Cornell Temperature Datalogger Project placed temperature dataloggers into 200 people’s homes for two weeks at a low-cost of $5. With 3-minute time scale, we observe temperature setbacks and the rate of thermal decay to reach those setbacks. Using this data, we are able to create a histogram of thermal decay and thermal setpoints for benchmarking the community. Compared to utility-meter-based approaches, temperature analysis more directly isolates shell performance. This helps identify community energy “hot spots” (80/20 rule) where shell retrofits would make the most impact. Correlations with building age, size, and heating fuel type will also be presented.

Advances in drives and controls have made HVAC pumping smarter than ever.  Pumps with on-board intelligence are capable of controlling themselves without remotely-mounted sensors, and delivering energy savings that can easily exceed today’s standards.  This session also explores how commissioning can be simplified while the pump monitoring data can be used by facility managers to quickly respond to pump and system issues that could lead to higher operating costs, comfort issues, shorter equipment life or unexpected failures.

We can’t blame those who thought all was said and done in flow balancing and control, but this session will definitely prove them wrong. Smart Valves come with a repertoire of control modes, data points and flexibility that were unthinkable just a few years ago. This session explores the new possibilities and shows the energy savings, extended operation and stability now achievable.

Compressors floating on magnetic bearings can do much more than levitation tricks. This session shows how new levels of energy efficiency, operational flexibility, and robustness are now possible with high speed and precise embedded controls.

While smart equipment can bury the integrator in a deluge of data, smart integrators know how to KISS. This presentation shows how to use the smart equipment data to effortlessly optimize entire systems. It also provides guidelines to consolidate the data into insightful info for the operators and engineers.

This study demonstrates a newly proposed methodology that handles building energy modeling at urban scale using a reduced-order energy calculation engine with geographical information system (GIS). GIS provides general building information that either directly serves as model parameters, or links to the specific prototype building models for more detailed building and system specifications. Actual urban environment was considered by quantifying the micro environment boundary conditions in terms of mutual shading and urban heat island (UHI) effect through urban morphology. A case study of Manhattan, New York was presented to demonstrate the process. The calculation result and future extensions were discussed.

In anticipation of both climate change and global urbanization, we conduct research of microclimate impacts on energy systems. We analyze and quantify the relationships among modeled and measured climatic conditions, urban morphology, land cover and energy use; and use these relationships to inform energy-efficient urban development and planning. We apply: neighborhood resolution modeling and simulation of urban micrometeorological processes; projections informed by microclimate for future energy use under different urbanization and climate change scenarios; to produce analysis and visualization tools to help planners optimally use these projections to identify best strategies for energy-efficient urban morphological development.

City governments, NGOs, portfolio managers, and owners are looking better ways to reduce energy use in their existing building stock. Traditional methods rely on costly and time consuming audits, or on benchmarking tools with limited ability to identify retrofit measures. A more effective approach utilizes urban scale 3D models to perform virtual energy assessments. This workflow relies on building a 3D model from multiple types of GIS data, annual hourly energy simulations, geospatial analysis techniques, and statistical benchmarking. The following presentation outlines this workflow, and provides a case study for reducing the time and money needed to identify retrofit strategies.