Srinivas Katipamula

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

Pacific Northwest GridWise™ Testbed Demonstration Projects; Part I. Olympic Peninsula Project

This report describes the implementation and results of a field demonstration wherein residential electric water heaters and thermostats, commercial building space conditioning, municipal water pump loads, and several distributed generators were coordinated to manage constrained feeder electrical distribution through the two-way communication of load status and electric price signals. The field demonstration took place in Washington and Oregon and was paid for by the U.S. Department of Energy and several northwest utilities. Price is found to be an effective control signal for managing transmission or distribution congestion. Real-time signals at 5-minute intervals are shown to shift controlled load in time. The behaviors of customers and their responses under fixed, time-of-use, and real-time price contracts are compared. Peak loads are effectively reduced on the experimental feeder. A novel application of portfolio theory is applied to the selection of an optimal mix of customer contract types.

The Smart Grid: An Estimation of the Energy and CO2 Benefits

This report articulates nine mechanisms by which the smart grid can reduce energy use and carbon impacts associated with electricity generation and delivery. The quantitative estimates of potential reductions in electricity sector energy and associated CO2 emissions presented are based on a survey of published results and simple analyses. This report does not attempt to justify the cost effectiveness of the smart grid, which to date has been based primarily upon the twin pillars of cost-effective operation and improved reliability. Rather, it attempts to quantify the additional energy and CO2 emission benefits inherent in the smart grid’s potential contribution to the nation’s goal of mitigating climate change by reducing the carbon footprint of the electric power system.

GridLAB-D Technical Support Document: Residential End-Use Module Version 1.0

1.0 Introduction The residential module implements the following end uses and characteristics to simulate the power demand in a single family home: • Water heater • Lights • Dishwasher • Range • Microwave • Refrigerator • Internal gains (plug loads) • House (heating/cooling loads) The house model considers the following four major heat gains/losses that contribute to the building heating/cooling load: 1. Conduction through exterior walls, roof and fenestration (based on envelope UA) 2. Air infiltration (based on specified air change rate) 3. Solar radiation (based on CLTD model and using tmy data) 4. Internal gains from lighting, people, equipment and other end use objects. The Equivalent Thermal Parameter (ETP) approach is used to model the residential loads and energy consumption. The following sections describe the modeling assumptions for each of the above end uses and the details of power demand calculations in the residential module.

Small- and Medium-Sized Commercial Building Monitoring and Controls Needs: A Scoping Study

Buildings consume over 40% of the total energy consumption in the U.S. A significant portion of the energy consumed in buildings is wasted because of the lack of controls or the inability to use existing building automation systems (BASs) properly. Much of the waste occurs because of our inability to manage and controls buildings efficiently. Over 90% of the buildings are either small-size ( 100,000 sf). Lawrence Berkeley National Laboratory (LBNL), Oak Ridge National Laboratory (ORNL) and Pacific Northwest National Laboratory (PNNL) were asked by the U.S. Department of Energy’s (DOE’s) Building Technologies Program (BTP) to identify monitoring and control needs for small- and medium-sized commercial buildings and recommend possible solutions. This study documents the needs and solutions for small- and medium-sized buildings.

Modeling Power Systems as Complex Adaptive Systems

Physical analogs have shown considerable promise for understanding the behavior of complex adaptive systems, including macroeconomics, biological systems, social networks, and electric power markets. Many of todays most challenging technical and policy questions can be reduced to a distributed economic control problem. Indeed, economically based control of large-scale systems is founded on the conjecture that the price-based regulation (e.g., auctions, markets) results in an optimal allocation of resources and emergent optimal system control. This report explores the state-of-the-art physical analogs for understanding the behavior of some econophysical systems and deriving stable and robust control strategies for using them. We review and discuss applications of some analytic methods based on a thermodynamic metaphor, according to which the interplay between system entropy and conservation laws gives rise to intuitive and governing global properties of complex systems that cannot be otherwise understood. We apply these methods to the question of how power markets can be expected to behave under a variety of conditions.

Efficient Low-Lift Cooling with Radiant Distribution, Thermal Storage, and Variable-Speed Chiller Controls— Part I: Component and Subsystem Models

Component and subsystem models used to evaluate the performance of a low-lift cooling system are described. An air-cooled chiller, a hydronic radiant distribution system, variable-speed control, and peak-shifting controls are modeled. A variable-speed compressor that operates over 20:1 speed range and pressure ratios ranging from one to six is at the heart of the chiller. Condenser fan and chilled-water pump motors have independent speed controls. The load-side distribution is modeled from the refrigerant side of the evaporator to the conditioned zone as a single subsystem controlled by chilled-water flow rate for a specified instantaneous cooling load. Performance of the same chiller when operating with an all-air distribution system is also modeled. The compressor, condenser fan, and chilled-water pump motor speeds that achieve maximum coefficient of performance (COP) at a given condition are solved at each point on a grid of load and outdoor temperature. A variable-speed dehumidification subsystem is modeled and simulated as part of a dedicated outdoor air system to condition the ventilation air. A companion paper evaluates the annual cooling system energy use and potential energy savings to be gained by integrating radiant cooling, cool storage, and variable-speed compressor and transport motor controls.

Efficient Low-Lift Cooling with Radiant Distribution, Thermal Storage, and Variable-Speed Chiller Controls—Part II: Annual Use and Energy Savings

This paper evaluates the cooling efficiency improvements that can be achieved by integrating radiant cooling, cool storage, and variable-speed compressor and transport motor controls. Performance estimates of a baseline system and seven useful combinations of these three efficient low-lift inspired cooling technologies are reported. The technology configurations are simulated in a prototypical office building with three levels of envelope and balance-of-plant performance: standard-, mid- and high-performance, and in five climates. The standard performance level corresponds to ANSI/ASHRAE/IESNA Standard 90.1-2004 Energy Standard for Buildings Except Low-Rise Residential Buildings (ASHRAE 2004a). From the savings estimates for an office building prototype in five representative climates, estimates of national energy saving technical potential are developed. Component and subsystem models used in the energy simulations are developed in a companion paper.

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.

A review of fault detection and diagnostics methods for building systems

The current article provides a summary of automated fault detection and diagnostics studies published since 2004 that are relevant to the commercial buildings sector. The review updates a previous review conducted in 2004 and published in 2005, and it categorizes automated fault detection and diagnostics methods into three groups. The examples of automated fault detection and diagnostics in the primary category are selectively reviewed to identify various methods that are suitable for building systems and to understand the strengths and weaknesses of the methods. The distribution of studies based on each automated fault detection and diagnostics method and heating, ventilation, and air-conditioning system is also described. Researchers and industries can use the current article as a guideline for selecting an appropriate automated fault detection and diagnostics method.