Michael R. Brambley

Methods for Fault Detection, Diagnostics, and Prognostics for Building Systems— A Review, Part II

Part II of this article will be published in Volume 11, Number 2, April 2005. Poorly maintained, degraded, and improperly controlled equipment wastes an estimated 15% to 30% of energy used in commercial buildings. Much of this waste could be prevented with widespread adoption of automated condition-based maintenance. Automated fault detection and diagnostics (FDD) along with prognostics provide a cornerstone for condition-based maintenance of engineered systems. Although FDD has been an active area of research in other fields for more than a decade, applications for heating, ventilating, air conditioning, and refrigeration (HVAC&R) and other building systems have lagged those in other industries. Nonetheless, over the last decade there has been considerable research and development targeted toward developing FDD methods for HVAC&R equipment. Despite this research, there are still only a handful of FDD tools that are deployed in the field. This paper is the first of a two-part review of methods for automated FDD and prognostics whose intent is to increase awareness of the HVAC&R research and development community to the body of FDD and prognostics developments in other fields as well as advancements in the field of HVAC&R. This first part of the review focuses on generic FDD and prognostics, providing a framework for categorizing methods, describing them, and identifying their primary strengths and weaknesses. The second paper in this review, to be published in the April 2005 International Journal of HVAC&R Research, will address research and applications specific to the fields of HVAC&R

Energy Management and Control System: Desired Capabilities and Functionality

This document discusses functions and capabilities of a typical building/facility energy management and control systems (EMCS). The overall intent is to provide a building operator, manager or engineer with basic background information and recommended functions, capabilities, and good/best practices that will enable the control systems to be fully utilized/optimized, resulting in improved building occupant quality of life and more reliable, energy efficient facilities.

Uncertainty analysis for a virtual flow meter using an air-handling unit chilled water valve

A virtual water flow meter is developed that uses the chilled water control valve on an air-handling unit as a measurement device. The flow rate of water through the valve is calculated using the differential pressure (DP) across the valve and its associated coil, the valve command, and an empirically determined valve characteristic curve. Thus, the uncertainty in the measurements could be significantly greater than for conventional hardware flow meters. In this article, mathematical models are developed and used to conduct uncertainty analyses for the virtual flow meter, and the results from the virtual meter are compared to measurements made with an ultrasonic flow meter. Theoretical uncertainty analysis shows that the total uncertainty in flow rates from the virtual flow meter is 1.46% with 95% confidence; comparison of virtual flow meter results with measurements from an ultrasonic flow meter yielded an uncertainty of 1.46% with 99% confidence. The comparable results from the theoretical uncertainty analysis and empirical comparison with the ultrasonic flow meter corroborate each other and tend to validate the approach to computationally estimating uncertainty for virtual sensors introduced in this study. Furthermore, the results show that the total uncertainty in flow rates from this virtual flow meter is adequately low for use in place of common physical flow meters for monitoring thermal energy use in air handlers and detecting operational and equipment faults that affect energy consumption.

Advanced CHP Control Algorithms: Scope Specification

The primary objective of this multiyear project is to develop algorithms for combined heat and power systems to ensure optimal performance, increase reliability, and lead to the goal of clean, efficient, reliable and affordable next generation energy systems.

Final Project Report: Self-Correcting Controls for VAV System Faults Filter/Fan/Coil and VAV Box Sections

This report addresses original research by the Pacific Northwest National Laboratory for the California Institute for Energy and Environment on self-correcting controls for variable-air-volume (VAV) heating, ventilating and air-conditioning systems and focuses specifically on air handling and VAV box components of the air side of the system. A complete set of faults for these components was compiled and a fault mode analysis performed to understand the detectable symptoms of the faults and the chain of causation. A set of 26 algorithms was developed to facilitate the automatic correction of these faults in typical commercial VAV systems. These algorithms include training tests that are used during commissioning to develop models of normal system operation, passive diagnostics used to detect the symptoms of faults, proactive diagnostics used to diagnose the cause of a fault, and finally fault correction algorithms. Ten of the twenty six algorithms were implemented in a prototype software package that interfaces with a test bed facility at PNNLs Richland, WA, laboratory. Measurement bias faults were instigated in the supply-air temperature sensor and the supply-air flow meter to test the algorithms developed. The algorithms as implemented in the laboratory software correctly detected, diagnosed and corrected these faults. Finally, an economic and impact assessment was performed for the State of California for deployment of self-correcting controls. Assuming 15% HVAC energy savings and a modeled deployment profile, 3.1-5.8 TBu of energy savings are possible by year 15.

Self-Correcting HVAC Controls Project Final Report

This document represents the final project report for the Self-Correcting Heating, Ventilating and Air-Conditioning (HVAC) Controls Project jointly funded by Bonneville Power Administration (BPA) and the U.S. Department of Energy (DOE) Building Technologies Program (BTP). The project, initiated in October 2008, focused on exploratory initial development of self-correcting controls for selected HVAC components in air handlers. This report, along with the companion report documenting the algorithms developed, Self-Correcting HVAC Controls: Algorithms for Sensors and Dampers in Air-Handling Units (Fernandez et al. 2009), document the work performed and results of this project.

Beyond Commissioning: The Role of Automation

This article takes a brief look at 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. Commissioning will become an activity thats performed continuously rather than periodically, and only repairs requiring replacement or overhaul of equipment will require manual intervention. The article then 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.

Economic Investigation of Community-Scale Versus Building Scale Net-Zero Energy

The study presented in this report examines issues concerning whether achieving net-zero energy performance at the community scale provides economic and potentially overall efficiency advantages over strategies focused on individual buildings.

Specification of Selected Performance Monitoring and Commissioning Verification Algorithms for CHP Systems

Pacific Northwest National Laboratory (PNNL) is assisting the U.S. Department of Energy (DOE) Distributed Energy (DE) Program by developing advanced control algorithms that would lead to development of tools to enhance performance and reliability, and reduce emissions of distributed energy technologies, including combined heat and power technologies. This report documents phase 2 of the program, providing a detailed functional specification for algorithms for performance monitoring and commissioning verification, scheduled for development in FY 2006. The report identifies the systems for which algorithms will be developed, the specific functions of each algorithm, metrics which the algorithms will output, and inputs required by each algorithm.

Automated Diagnostics Software Requirements Specification, Version 1.1

This document specifies requirements for a computerized automated diagnostic tool for the detection of faults in certain heating, ventilation, and air-conditioning (HVAC) system components. The automated diagnostic tool is being developed for Architectural Energy Corporation (AEC) by Battelle as part of a program sponsored by the California Energy Commission (CEC). Supplemental cost-share funds are provided by U.S. Department of Energy through the Pacific Northwest National Laboratory (PNNL). This Requirements Specification (RS) specifies the essential capabilities required of the automated diagnostic tool. The purpose of this document is to clarify for AEC, the California Energy Commission (CEC), the Office of Buildings Programs, Office of Energy Efficiency and Renewable Energy (EERN) of the U.S. Department of Energy, and the project team the results that must be achieved by the automated diagnostic tool. The automated diagnostic tool detects and identifies faults in chillers and cooling tower subsystems of HVAC units using sensed data acquired from the unit, unit specifications, unit installation and configuration data, and unit operation data (such as schedules). The tool is a software product that will be utilized primarily by building operators and facilities managers and only secondarily by HVAC service technicians, energy service providers, and operation supervisors.