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Author(s): Wetter, M; Ehrlich, P; Gautier, A; Grahovac, M; Haves, P; Hu, J; Prakash, A; Robin, D; Zhang, K | Abstract: The current process for specifying, installing and commissioning building control sequences is largely manual and based on ambiguous natural language specifications. It lacks a formal end-to-end quality control and it has been shown not to deliver high performance sequences at scale. While high-performance HVAC control sequences enable significant reductions in energy consumption, errors in implementing the control logic are common even for less advanced sequences. To improve this situation, we present a digitized building control delivery workflow with formal end-to-end verification, a Control Description Language for the digital specification of building control sequences within this workflow, and software tools that enable digitization of this process. Using the process and tools introduced here, mechanical designers can customize, test and improve these sequences within annual energy simulation, store them in a library for use in other projects, and export them for bidding. Control providers can implement the sequences on existing control product lines through code generation. Commissioning providers can formally verify whether as-installed sequences conform to the digital design specification that was exported by the mechanical designer. Moreover, control product development teams can use the reference implementations of these libraries within their product testing to ensure that their products reproduce the behavior of the reference implementations. This paper presents this process, the language and the supporting software, together with examples of all of the above steps. The presented work has given rise to a new proposed standard, ASHRAE 231P, that will allow digitizing the building control delivery process through the standardization of a control-vendor independent format for exchanging control logic that we pioneered through the here presented work.

Author(s): Wetter, Michael; Ehrlich, Paul; Gautier, Antoine; Grahovac, Milica; Haves, Philip; Hu, Jianjun; Zhang, Kun | Abstract: Best practice control sequences are often not implemented correctly, or are not implemented at all, in large commercial buildings. This typically leads to 10-30 percent energy waste, along with reduced occupant productivity and unnecessary equipment wear. The current process of designing and implementing such control sequences is a manual process that starts with designers who often don’t have adequate training, then requires controls programmers to interpret and program a verbose written sequence. This process has been shown to fail to deliver high performance control sequences at scale. The Open Building Control project digitizes the current control delivery process. The project is developing tools for system designers to select control sequences, assess their energy performance and load flexibility potential using whole building simulation, specify the sequence for implementation using machine-to-machine translation by a control provider and formally testing the as-installed sequences by a commissioning agent. The project developed tools for each stage of this delivery process. The key innovation of the project is the development of the Control Description Language, a language that allows such a digitized control delivery process with end-to-end verification. Libraries of control sequences have been implemented using the Control Description Language, and their performance has been demonstrated using whole building energy simulation. An automated translation of such sequences to a commercial control product line has been conducted using a prototype translator. Tools for formal verification of as-installed control sequences relative to their specification have been developed and demonstrated. The American Society of Heating, Refrigerating and Air-Conditioning Engineers (ASHRAE) started the process of forming a committee to make this language an ASHRAE/ANSI Standard. This new standard will complement existing and emerging ASHRAE standards for building communication and semantic modeling by providing a standard for expressing the control logic - the actual brain of the building. We expect this language and the process it enables to be an important contribution to the deployment of high performance building control sequences at scale because it allows taming the complexity of the control delivery process, which is continually increasing due to the need for higher performance and increased load flexibility to meet goals for net zero energy and increased renewable integration.

Radiant slab systems have the potential to significantly reduce energy consumption in buildings. However, control of radiant slab systems is challenging. Classical feedback control is inadequate due to the large thermal inertia of the systems and heuristic feed-forward control often leads to unacceptable indoor comfort and may not achieve the full energy savings potential. Model predictive control (MPC) is now attracting increasing interest in the building industry and holds promise for radiant systems. However, an often-cited barrier to its implementation in the building industry is the high computational cost and complexity relative to the feedback controls used in conventional systems. The objectives of this study were to (i) verify the correct operation of an open source MPC toolchain developed for radiant slab systems, and (ii) demonstrate its efficacy in a test facility. A matched pair of cells in the FLEXLAB building test facility at the Lawrence Berkeley National Laboratory was used in the study. The proposed MPC toolchain was implemented in one cell and the performance compared to that of the other cell, which used a conventional heuristic control strategy. The results showed that the simplified MPC approach applied in the toolchain worked as expected and realized energy savings over the conventional control strategy. The MPC yielded 42% chilled water pump power reduction and 16% cooling thermal energy savings, while maintaining equal or better indoor comfort.

Radiant heating and cooling systems have significant energy-saving potential and are gaining popularity in commercial buildings. The main aim of the experimental study reported here was to characterize the behavior of radiant cooling systems in a typical office environment, including the effect of ceiling fans on stratification, the variation in comfort conditions from perimeter to core, control on operative temperature vs. air temperature and the effect of carpet on cooling capacity. The goal was to limit both the first cost and the perceived risk associated with such systems. Two types of radiant systems, the radiant ceiling panel (RCP) system and the radiant slab (RS) system, were investigated. The experiments were carried out in one of the test cells that constitute the FLEXLAB test facility at the Lawrence Berkeley National Laboratory in March and April 2016. In total, ten test cases (five for RCP and five for RS) were performed, covering a range of operational conditions. In cooling mode, the air temperature stratification is relatively small in the RCP, with a maximum value of 1.6 K. The observed stratification effect was significantly greater in the RS, twice as much as that in the RCP. The maximum increase in dry bulb temperature in the perimeter zone due to solar radiation was 1.2 K for RCP and 0.9 K for RS – too small to have a significant impact on thermal comfort. The use of ceiling fans was able to reduce any excess stratification and provide better indoor comfort, if required. The use of thin carpet requires a 1 K lower supply chilled water temperature to compensate for the added thermal resistance, somewhat reducing the opportunities for water-side free cooling and increasing the risk of condensation. In both systems, the difference between the room operative temperature and the room air temperature is small when the cooling loads are met by the radiant systems. This makes it possible to use the air temperature to control the radiant systems in lieu of the operative temperature, reducing both first cost and maintenance costs.

Building energy models (BEMs) are typically used for design and code compliance for new buildings and in the renovation of existing buildings to predict energy use. The increasing adoption of BEM as standard practice in the building industry presents an opportunity to extend the use of BEMs into construction, commissioning and operation. In 2009, the authors developed a real-time simulation framework to execute an EnergyPlus model in real time to improve building operation. This paper reports an enhancement of that real-time energy simulation framework. The previous version only works with software tools that implement the custom co-simulation interface of the Building Controls Virtual Test Bed (BCVTB), such as EnergyPlus, Dymola and TRNSYS. The new version uses an open standard interface, the Functional Mockup Interface (FMI), to provide a generic interface to any application that supports the FMI protocol. In addition, the new version utilizes the Simple Measurement and Actuation Profile (sMAP) tool as the data acquisition system to acquire, store and present data. This paper introduces the updated architecture of the real-time simulation framework using FMI and presents proof-of-concept demonstration results which validate the new framework.

Author(s): Parker, A; Haves, P; Jegi, S; Garg, V; Ravache, B | Abstract: This paper describes a software system for automatically generating a reference (baseline) building energy model from the proposed (as-designed) building energy model. This system is built using the OpenStudio Software Development Kit (SDK) and is designed to operate on building energy models in the OpenStudio file format.

Faults in HVAC systems can have a significant negative impact on energy consumption, indoor thermal comfort, and air quality. Automatic fault detection and diagnosis tools can help commissioning providers, operators, and facility managers efficiently detect and diagnose faults. They also can help satisfy the increasing demand for commissioning. A model-based fault detection and diagnosis (FDD) method was developed to detect faults by comparing model prediction and measurement, and to diagnose faults using a rule-based fuzzy inferencing system. The method includes Monte Carlo analysis to improve the robustness of the fault detection and diagnosis and reduce false alarms. The Monte Carlo analysis is employed not only to predict uncertainties in reference model outputs, based on estimates of uncertainty in each of the measured inputs, but also to determine the confidence levels of fault diagnosis by combining the effects of input uncertainties at different operating points. A simulated variable-air-volume (V...

Building energy systems often consume approximately 16% more energy [Mills, E. 2011. “Building Commissioning: A Golden Opportunity for Reducing Energy Costs and Greenhouse Gas Emissions in the United States.” Energy Efficiency 4 (2): 145–173] than is necessary due to system deviation from the design intent. Identifying the root causes of energy waste in buildings can be challenging largely because energy flows are generally invisible. To help address this challenge, we present a model-based, real-time whole building energy diagnostics and performance monitoring system. The proposed system continuously acquires performance measurements of heating, ventilation and air-conditioning, lighting and plug equipment usage and compare these measurements in real-time to a reference EnergyPlus model that either represents the design intent for the building or has been calibrated to represent acceptable performance. A proof-of-concept demonstration in a real building is also presented.

An air handling unit’s energy usage can vary from the original design as components fail or fault – dampers leak or fail to open/close, valves get stuck, and so on. Such problems do not necessarily result in occupant complaints and, consequently, are not even recognized to have occurred. In spite of recent progress in the research and development of diagnostic solutions for air handling units, there is still a lack of reliable, scalable, and affordable diagnostic solutions for such systems. Modeling limitations, measurement constraints, and the complexity of concurrent faults are the main challenges in air handling unit diagnostics. The focus of this paper is on developing diagnostic algorithms for air handling units that can address such constraints more effectively by systematically employing machine-learning techniques. The proposed algorithms are based on analyzing the observed behavior of the system and comparing it with a set of behavioral patterns generated based on various faulty conditions. We show how such a pattern-matching problem can be formulated as an estimation of the posterior distribution of a Bayesian probabilistic model. We demonstrate the effectiveness of the approach by detecting faults in commercial building air handling units.

Most commercial buildings do not perform as well in practice as intended by the design and their performances often deteriorate over time. Reasons include faulty construction, malfunctioning equipment, incorrectly configured control systems and inappropriate operating procedures. One approach to addressing this problems is to compare the predictions of an energy simulation model of the building to the measured performance and analyze significant differences to infer the presence and location of faults. This paper presents a framework that allows a comparison of building actual performance and expected performance in real time. The realization of the framework utilized the EnergyPlus, the Building Controls Virtual Test Bed (BCVTB) and the Energy Management and Control System (EMCS) was developed. An EnergyPlus model that represents expected performance of a building runs in real time and reports the predicted building performance at each time step. The BCVTB is used as the software platform to acquire relevant inputs from the EMCS through a BACnet interface and send them to the EnergyPlus and to a database for archiving. A proof-of-concept demonstration is also presented.

This paper describes the origin, structure and continuing development of a model of time varying energy consumption in the US commercial building stock. The model is based on a flexible structure that disaggregates the stock into various categories (e.g. by building type, climate, vintage and life-cycle stage) and assigns attributes to each of these (e.g. floor area and energy use intensity by fuel type and end use), based on historical data and user-defined scenarios for future projections. In addition to supporting the interactive exploration of building stock dynamics, the model has been used to study the likely outcomes of specific policy and innovation scenarios targeting very low future energy consumption in the building stock. Model use has highlighted the scale of the challenge of meeting targets stated by various government and professional bodies, and the importance of considering both new construction and existing buildings.

This paper presents an approach to comparing computer run time of building simulation programs. The computing run time of a simulation program depends on several key factors, including the calculation algorithm and modeling capabilities of the program, the run period, the simulation time step, the complexity of the energy models, the run control settings, and the software and hardware configurations of the computer that is used to make the simulation runs. To demonstrate the approach, simulation runs are performed for several representative DOE-2.1E and EnergyPlus energy models. The computer run time of these energy models are then compared and analyzed.

Author(s): Mills, Evan; Granderson, Jessica; Chan, Rengie; Diamond, Richard; Haves, Philip; Nordman, Bruce; Mathew, Paul; Piette, Mary Ann; Robinson, Gerald; Selkowitz, Stephen | Abstract: When it comes to innovation in energy and building performance, one can expect leading-edge activity from the technology sector. As front-line innovators in design, materials science, and information management, developing and operating high-performance buildings is a natural extension of their core business. The energy choices made by technology companies have broad importance given their influence on society at large as well as the extent of their own energy footprint. Microsoft, for example, has approximately 250 facilities around the world (30 million square feet of floor area), with significant aggregate energy use of approximately 4 million kilowatt-hours per day (Figure 1).

A comparison of the performance of two fault detection and diagnosis methods applied to a cooling coil subsystem in an air-handling unit installed in a real building is presented. Both methods employ a first principles based reference model of the target system. One scheme carries out diagnosis using expert rules and the other recursively re-estimates selected parameters of the system model that correspond to particular faults. The procedures and information required to configure the schemes for condition monitoring are discussed. The results of testing the methods on an HVAC cooling coil subsystem in a commercial office building in the UK over an entire cooling season are reported. Both methods were able to both detect faults and provide some diagnosis. The expert rule method, however, appears to be more robust. Issues associated with the con” guration and implementation of both methods are discussed in terms of performance and cost.

Energy simulation (ES) and computational fluid dynamics (CFD) can play an important role in building design by providing complementary information of the building performance. However, separate applications of ES and CFD usually cannot give an accurate prediction of building thermal and flow behavior due to the assumptions used in the applications. An integration of ES and CFD can eliminate many of these assumptions, since the information provided by ES and CFD is complementary. This paper describes some efficient approaches to integrate ES and CFD, such as static and dynamic coupling strategies, in order to bridge the discontinuities of time-scale, spatial resolution and computing speed between ES and CFD programs. This investigation further demonstrates some of the strategies through two examples by using the EnergyPlus and MIT-CFD programs.

This paper discusses a demonstration of a technology to address the problem that buildings do not perform as well as anticipated during design. We partnered with an innovative building operator to evaluate a prototype information monitoring and diagnostic system (IMDS). The IMDS consists of a set of high-quality sensors, data acquisition software and hardware, and data visualization software including a web-based remote access system, that can be used to identify control problems and equipment faults. The information system allowed the operators to make more effective use of the building control system and freeing up time to take care of other tenant needs. They report observing significant improvements in building comfort, potentially improving tenant health and productivity. The reduction in the labor costs to operate the building is about US$ 20,000 per year, which alone could pay for the information system in about 5 years. A control system retrofit based on findings from the information system is expected to reduce energy use by 20% over the next year, worth over US$ 30,000 per year in energy cost savings. The operators are recommending that similar technology be adopted in other buildings.

This paper presents the major findings of the PhD work of Rees, who wrote the paper and is the lead author.

A nodal model has been developed to represent room heat transfer in displacement ventilation and chilled ceiling systems. The model uses precalculated air flow rates to predict the air-temperature distribution and the division of the cooling load between the ventilation air and the chilled ceiling. The air movements in the plumes and the rest of the room are represented separately using a network of 10 air nodes. The values of the capacity rate parameters are calculated by solving the heat and mass balance equations for each node using measured temperatures as inputs. Correlations between parameter values for a range of cooling loads and supply air flow rates are presented.

The efficiencies of methods employed in solution of building simulation models are considered and compared by means of benchmark testing. Direct comparisons between the Simulation Problem Analysis and Research Kernel (SPARK) and the HVACSIM+ programs are presented, as are results for SPARK versus conventional and sparse matrix methods. An indirect comparison between SPARK and the IDA program is carried out by solving one of the benchmark test suite problems using the sparse methods employed in that program. The test suite consisted of two problems chosen to span the range of expected performance advantage. SPARK execution times versus problem size are compared to those obtained with conventional and sparse matrix implementations of these problems. Then, to see if the results of these limiting cases extend to actual problems in building simulation, a detailed control system for a heating, ventilating and air conditioning (HVAC) system is simulated with and without the use of SPARK cut set reduction. Execution times for the reduced and non-reduced SPARK models are compared with those for an HVACSIM+ model of the same system. Results show that the graph-theoretic techniques employed in SPARK offer significant speed advantages over the other methods for significantly reducible problems and that by using sparse methods in combination with graph-theoretic methods even problem portions with little reduction potential can be solved efficiently.

Displacement ventilation and chilled ceiling panel systems are potentially more energy efficient than conventional air conditioning systems and are characterized by the presence of vertical temperature gradients and significant radiant asymmetry. The characteristics of this type of system have been studied by making temperature and air flow measurements in a test chamber over a range of operating parameters typical of office applications. Results from the displacement ventilation study are consistent with other studies and show that normalized temperature profiles are independent of internal heat gain. Linear temperature gradients in the lower part of the room were found, in all cases, to be driven by convection from the adjacent walls. Significant mixing, indicated by reduced temperature gradients, was evident in the upper part of the room in the chilled ceiling results at higher levels of heat gain. Visualization experiments, velocity measurements and related numerical studies indicated that with greater heat gains the plumes have sufficient momentum to drive flow across the ceiling surface and down the walls. The significance of forced, as opposed to natural convection, is also suggested by relatively low Richardson Number (Ri) values found near the ceiling. Furthermore, in cases with moderately high internal gains, comparison of the temperature gradients indicated that the effect of ceiling surface temperature on the degree of mixing and the magnitude of the temperature gradient were of secondary importance. These findings are in contrast to the view that it is natural convection at the ceiling that causes enhanced mixing.

Most commercial buildings do not perform as well in practice as intended by the design and their performances often deteriorate over time. Reasons include faulty construction, malfunctioning equipment, incorrectly configured control systems and inappropriate operating procedures (Haves et al., 2001, Lee et al., 2007). To address this problem, the paper presents a simulation-based whole building performance monitoring tool that allows a comparison of building actual performance and expected performance in real time. The tool continuously acquires relevant building model input variables from existing Energy Management and Control System (EMCS). It then reports expected energy consumption as simulated of EnergyPlus. The Building Control Virtual Test Bed (BCVTB) is used as the software platform to provide data linkage between the EMCS, an EnergyPlus model, and a database. This paper describes the integrated realtime simulation environment. A proof-of-concept demonstration is also presented in the paper.

LBNL-XXXXX Automated Continuous Commissioning of Commercial Buildings ESTCP Project SI-0929 Trevor Bailey, Zheng O’Neill, Madhusudana Shashanka, Philip Haves, Xiufeng Pang, Prajesh Bhattacharya September 2011

Energy simulation is used in building design and has the potential to be used to support building operation. It is also used in product development and in scenario analysis to inform policy development. The wide variety of phenomena in buildings that need to be modeled in order to simulate building performance are discussed briefly, along with the variety of numerical methods that are used. There is a need to improve the computational speed of building simulation, particularly for use in optimization and parametric studies. Examples of the use of simulation in support of both building design and building operation are presented. The needs for further development of both tools and practices in order to improve the accuracy, robustness and effectiveness of simulation modeling are summarized.

EnergyPlus is a new generation building performance simulation program offering many new modeling capabilities and more accurate performance calculations integrating building components in sub-hourly time steps. However, EnergyPlus runs much slower than the current generation simulation programs. This has become a major barrier to its widespread adoption by the industry. This paper analyzed EnergyPlus run time from comprehensive perspectives to identify key issues and challenges of speeding up EnergyPlus: studying the historical trends of EnergyPlus run time based on the advancement of computers and code improvements to EnergyPlus, comparing EnergyPlus with DOE-2 to understand and quantify the run time differences, identifying key simulation settings and model features that have significant impacts on run time, and performing code profiling to identify which EnergyPlus subroutines consume the most amount of run time. This paper provides recommendations to improve EnergyPlus run time from the modeler?s perspective and adequate computing platforms. Suggestions of software code and architecture changes to improve EnergyPlus run time based on the code profiling results are also discussed.

California has been using DOE-2 as the main building energy analysis tool in the development of building energy efficiency standards (Title 24) and the code compliance calculations. However, DOE-2.1E is a mature program that is no longer supported by LBNL on contract to the USDOE, or by any other public or private entity. With no more significant updates in the modeling capabilities of DOE-2.1E during recent years, DOE-2.1E lacks the ability to model, with the necessary accuracy, a number of building technologies that have the potential to reduce significantly the energy consumption of buildings in California. DOE-2's legacy software code makes it difficult and time consuming to add new or enhance existing modeling features in DOE-2. Therefore the USDOE proposed to develop a new tool, EnergyPlus, which is intended to replace DOE-2 as the next generation building simulation tool. EnergyPlus inherited most of the useful features from DOE-2 and BLAST, and more significantly added new modeling capabilities far beyond DOE-2, BLAST, and other simulations tools currently available. With California's net zero energy goals for new residential buildings in 2020 and for new commercial buildings in 2030, California needs to evaluate and promote currently available best practice and emerging technologies to significantly reduce energy use of buildings for space cooling and heating, ventilating, refrigerating, lighting, and water heating. The California Energy Commission (CEC) needs to adopt a new building energy simulation program for developing and maintaining future versions of Title 24. Therefore, EnergyPlus became a good candidate to CEC for its use in developing and complying with future Title 24 upgrades. In 2004, the Pacific Gas and Electric Company contracted with Architectural Energy Corporation (AEC), Taylor Engineering, and GARD Analytics to evaluate EnergyPlus in its ability to model those energy efficiency measures specified in both the residential and nonresidential Alternative Calculation Method (ACM) of the Title-24 Standards. The AEC team identified gaps between EnergyPlus modeling capabilities and the requirements of Title 24 and ACMs. AEC's evaluation was based on the 2005 version of Title 24 and ACMs and the version 1.2.1 of EnergyPlus released on October 1, 2004. AEC's evaluation is useful for understanding the functionality and technical merits of EnergyPlus for implementing the performance-based compliance methods described in the ACMs. However, it did not study the performance of EnergyPlus in actually making building energy simulations for both the standard and proposed building designs, as is required for any software program to be certified by the CEC for use in doing Title-24 compliance calculations. In 2005, CEC funded LBNL to evaluate the use of EnergyPlus for compliance calculations by comparing the ACM accuracy test runs between DOE-2.1E and EnergyPlus. LBNL team identified key technical issues that must be addressed before EnergyPlus can be considered by the CEC for use in developing future Nonresidential Title-24 Standards or as an ACM tool. With Title 24 being updated to the 2008 version (which adds new requirements to the standards and ACMs), and EnergyPlus having been through several update cycles from version 1.2.1 to 2.1, it becomes crucial to review and update the previously identified gaps of EnergyPlus for use in Title 24, and more importantly to close the gaps which would help pave the way for EnergyPlus to be adopted as a Title 24 compliance ACM. With this as the key driving force, CEC funded LBNL in 2008 through this PIER (Public Interest Energy Research) project with the overall technical goal to expand development of EnergyPlus to provide for its use in Title-24 standard compliance and by CEC staff.

LBNL-58815 Demand Shifting With Thermal Mass in Large Commercial Buildings: Field Tests, Simulations and Audits Peng Xu, Philip Haves, MaryAnn Piette Lawrence Berkeley National Laboratory Leah Zagreus University of California at Berkeley Ernest Orlando Lawrence Berkeley National Laboratory 1 Cyclotron Road, MS90R3111 Berkeley, CA 94720 September 2005 This work described in this report was coordinated by the Demand Response Research Center and funded by the California Energy Commission, Public Interest Energy Research Program, under Work for Others Contract No. 500- 03-026 and by the U.S. Department of Energy under Contract No. DE-AC02-05CH11231.

On June 11, 2003, representatives from universities, federal and state government agencies, Department of Energy national laboratories, and the private sector attended a one-day workshop in Washington, DC. The objective of the workshop was to review and provide input into DOE's assessment of the market for advanced sensors and controls technology and potential RD best use of finite resources; greatest likelihood for market penetration; and ability to replicate results. The participants identified several promising R&D opportunities.

Significant energy savings can be achieved in commercial building operation, along with increased comfort and control for occupants, through the implementation of advanced technologies. This document provides a market assessment of existing building sensors and controls and presents a range of technology pathways (R&D options) for pursuing advanced sensors and building control strategies. This paper is actually a synthesis of five other white papers: the first describes the market assessment including estimates of market potential and energy savings for sensors and control strategies currently on the market as well as a discussion of market barriers to these technologies. The other four cover technology pathways: (1) current applications and strategies for new applications, (2) sensors and controls, (3) networking, security, and protocols and standards, and (4) automated diagnostics, performance monitoring, commissioning, optimal control and tools. Each technology pathway chapter gives an overview of the technology or application. This is followed by a discussion of needs and the current status of the technology. Finally, a series of research topics is proposed.

Typical buildings consume 20% more energy than required due to inefficient operation procedures, non-optimal control schedules, and system faults. A few of the systems are detected by well trained engineers through field measurement, specialized engineering calculation and analysis due to lack of skilled engineers and tedious commissioning process. Consequently, excessive amounts of energy are wasted daily in existing buildings. The development of HVAC automation systems and simulation software makes it possible to diagnose the mechanical and electrical problems by on-line simulation. This paper introduces simplified simulation software (AirModel) and investigates the feasibility of implanting the simplified simulation programs into the energy management and control system (EMCS) using a demonstration project, and presents the results of fault detection, problem diagnosis, and operation schedule optimization for large commercial buildings with built-up HVAC systems.

Private sector commercial office buildings are challenging environments for energy efficiency projects. This challenge is related to the complexity of business environments that involve ownership, operation, and tenant relationships. Whether it is poor quality design, inefficient operations, degradation of equipment over time, or merely the increasing use of energy by tenants and inattention from landlords, commercial office building energy use continues to increase. This research project was developed to examine the environment for building operations and identify causes of inefficient use of energy related to technical and organizational issues. This report discusses a second-generation Information Monitoring and Diagnostic System (IMDS) installed at a leased office building in Sacramento, California. The report begins with a brief summary of the IMDS research at the previous building, followed by a discussion of the building selection process, the IMDS design and installation, recent use of the IMDS, costs and benefits, and fault detection and diagnostic research using the IMDS. A web site describes the IMDS in detail (see imds.lbl.gov). The underlying principle of this research project is that high quality building performance data can help show where energy is being used and how buildings systems actually perform is an important first step toward improvingmore » building energy efficiency. The project utilizes a high-quality monitoring system that has been developed during the past decade by a partnership between LBNL and private industry. This research project has been successful in demonstrating that the IMDS is tremendously valuable to the building operators at the Sacramento site. The building operators not only accept the technology, but it has become the core of their day-to-day building control concepts. The innovative property management company, Jones Lang LaSalle, is interested in installing more sites to determine if the system could provide an economic platform for regional operations. One objective of this project was to install the IMDS and evaluate the costs and benefits of its use. The costs have been evaluated. The system cost about $0.70 per square foot, which includes the design, hardware, software, and installation, which is about 30% lower than the previous system in San Francisco. A number of operational problems have been identified with the IMDS as described in the report. Potential energy savings from addressing problems identified by the application of the IMDS have not yet been quantified, although the IMDS has been an important tool to the operations staff to help better assess planned future retrofits.« less

Traditional passive cooling systems are of limited effectiveness in the more humid climates. However, recently developed techniques can produce comfort with a lower power consumption than conventional air-conditioning. Indirect evaporative cooling systems and “roof dissipator” radiant and evaporative cooling systems are described and their sizing discussed. The need for dehumidification is discussed and alternative dehumidification systems are briefly described. The sizing of a simple solar regenerated desiccant dehumidification system is discussed. A unified approach to the selection of alternative cooling and dehumidification systems is presented.

A qualitative comparison is presented between three current North American and U.K. design cooling load calculation methods. The methods compared are the ASHRAE Heat Balance Method, the Radiant Time Series Method and the Admittance Method, used in the U.K. The methods are compared and contrasted in terms of their overall structure. In order to generate the values of the 24 hourly cooling loads, comparison was also made in terms of the processing of the input data and the solution of the equations required. Specific comparisons are made between the approximations used by the three calculation methods to model some of the principal heat transfer mechanisms. Conclusions are drawn regarding the ability of the simplified methods to correctly predict peak-cooling loads compared to the Heat Balance Method predictions. Comment is also made on the potential for developing similar approaches to cooling load calculation in the U.K. and North America in the future.

This paper gives an overview of recent developments in the Building Controls Virtual Test Bed (BCVTB), a framework for co-simulation and hardware-in-the- loop. First, a general overview of the BCVTB is presented. Second, we describe the BACnet interface, a link which has been implemented to couple BACnet devices to the BCVTB. We present a case study where the interface was used to couple a whole building simulation program to a building control system to assess in real-time the performance of a real building. Third, we present the ADInterfaceMCC, an analog/digital interface that allows a USB-based analog/digital converter to be linked to the BCVTB. In a case study, we show how the link was used to couple the analog/digital converter to a building simulation model for local loop control.

This brief presents a model-based predictive control (MPC) approach to building cooling systems with thermal energy storage. We focus on buildings equipped with a water tank used for actively storing cold water produced by a series of chillers. First, simplified models of chillers, cooling towers, thermal storage tanks, and buildings are developed and validated for the purpose of model-based control design. Then an MPC for the chilling system operation is proposed to optimally store the thermal energy in the tank by using predictive knowledge of building loads and weather conditions. This brief addresses real-time implementation and feasibility issues of the MPC scheme by using a simplified hybrid model of the system, a periodic robust invariant set as terminal constraints, and a moving window blocking strategy. The controller is experimentally validated at the University of California, Merced. The experiments show a reduction in the central plant electricity cost and an improvement of its efficiency.