scholarly journals Bringing Automated Fault Detection and Diagnostics Tools for HVAC&R Into the Mainstream

2020 ◽  
Vol 1 (3) ◽  
Author(s):  
Mohammed Albayati ◽  
Ravi Gorthala ◽  
Amy Thompson ◽  
Prathamesh Patil ◽  
Annika Hacker
Keyword(s):  
Energy Consumption ◽  
Fault Detection ◽  
Ground Truth ◽  
Hvac Systems ◽  
Commercial Buildings ◽  
Evaluation Methodology ◽  
Incentive Programs ◽  
Utility Companies ◽  
Testing And Evaluation

Abstract Heating, ventilation, and air-conditioning (HVAC) systems consume over 5 quads of energy annually, representing 30% of energy consumption in the U.S. commercial buildings. Additionally, commercial refrigeration (R) systems add about 1 quad to commercial buildings energy consumption. Most HVAC systems operate with one or more faults that result in increased energy consumption. Fault detection and diagnostics (FDD) tools have been developed to address this national issue, and many tools are commercially available. FDD tools have the potential to save considerable energy for an existing commercial rooftop unit (RTU) and refrigeration systems. These devices can be used for both retro commissioning and, when faults are addressed, continuous commissioning. However, there appears to be multiple market barriers for this technology. Although there are efforts to develop FDD tool standards, currently there are no standards and methods to define functions, capabilities, accuracy, and reliability of FDD tools in the field. Moreover, most of the commercial FDD tools have not been verified in the field independently. This paper presents a comprehensive approach for bringing HVAC FDD tools into the mainstream. The approach involves demonstrating ten commercially available FDD tools installed at ten different sites, independent testing and evaluation of the FDD tools, communication with various stakeholders, identifying and assessing market barriers, creating a process evaluation methodology, and assisting utility companies in developing incentive programs. The preliminary baseline results from the case study demonstrate how the use of an independent monitoring system (IMS) can be used for ground-truth in evaluating FDD tools in the field.

An Approach to Bringing Automated Fault Detection and Diagnosis (AFDD) Tools for HVAC&R Into the Mainstream

2019 ◽  
Author(s):  
Annika Hacker ◽  
Ravi Gorthala ◽  
Amy Thompson
Keyword(s):  
Energy Consumption ◽  
Fault Detection ◽  
Evaluation Method ◽  
Field Testing ◽  
Hvac Systems ◽  
Commercial Buildings ◽  
Fault Detection And Diagnosis ◽  
Utility Companies ◽  
Detection And Diagnosis ◽  
Testing And Evaluation

Abstract Heating, ventilation and air-conditioning (HVAC) systems can consume over 5 quads of energy annually, representing 30% of energy consumption in the U.S. in commercial buildings. Additionally, commercial refrigeration (R) systems add about 2 quads to commercial buildings energy consumption. Most HVAC systems have one or more faults (low/high refrigerant charge, valve leakage, condenser/evaporator fouling, filter/dryer restriction, economizer faults, controls faults) that result in increased energy consumption. Automated fault detection and diagnosis (AFDD) tools have been developed to address this national issue and many tools are commercially available. AFDD tools have the potential to save considerable energy for existing commercial RTUs, chillers and refrigeration systems. These devices can be used for both retro commissioning, and, when faults are addressed, continuous commissioning as well. However, there appears to be multiple market barriers for this technology. A key market barrier for this technology is the lack of awareness of AFDD products among potential customers. Most HVAC contractors are not familiar with the latest AFDD technologies and HVAC technicians lack skills regarding these technologies. Quantifying potential benefits to building owners is difficult since there are several FDD tools with varying capabilities. For instance, there are several FDD products ranging from handling just economizer faults to those that also handle full-blown refrigerant-side and air-side faults. Methods/algorithms used in FDD vary significantly. Even though there are efforts to develop standards, currently there are no standards/methods to define functions, capabilities, accuracy, and reliability of FDD tools. Moreover, most of the commercial AFDD tools have not been verified in the field independently. This paper presents a comprehensive approach to bringing HVAC AFDD tools into the mainstream. The approach involves demonstrating ten commercially available tools at ten different sites, independent testing and evaluation of the FDD tools, communication with various stakeholders, identifying market barriers, and assisting utility companies in developing incentive programs. This paper presents selection of AFDD tools, site identification, and field testing and evaluation method.

scholarly journals Determining the Modelling Input Parameters for Heating, Ventilation, and Air Conditioning Systems in New Zealand Commercial Buildings

2021 ◽  
Author(s):  
◽  
Anthony Gates
Keyword(s):  
Energy Consumption ◽  
New Zealand ◽  
Air Conditioning ◽  
Energy Performance ◽  
Hvac Systems ◽  
Commercial Buildings ◽  
Hvac System ◽  
Input Parameters ◽  
Parameter Values ◽  
The Ideal

<p>Template energy calculation models that have been produced by the Building Energy End-use Study (BEES) team are used to quickly and reliably model commercial buildings and calculate their energy performance. The template models contain standardised equipment, lighting, and occupancy loads; cooling and heating requirements are calculated using an ideal loads air system. Using seven buildings, Cory et al. 2011a have demonstrated that the template models have the potential to closely match the monthly energy performance of detailed (individually purpose built) models and the real buildings. Three of these models were within the ±5% acceptable tolerance to be considered calibrated. The four template models that were not within the acceptable tolerance have been identified to have complex Heating, Ventilation, and Air Conditioning (HVAC) systems that the ideal loads air systems could not replicate. Because HVAC systems consume one of the largest proportions of energy in commercial buildings, this has a significant impact on the reliability of the template models. To address this issue, a set of detailed HVAC systems were needed to replace the ideal loads air systems. Due to HVAC system parameters not being collected by the BEES team and the lack of published modelling input parameters available, it is unknown what values are reasonable to use in the models. This study used a Delphi survey to collect real building information of the commonly installed HVAC systems in New Zealand commercial buildings. The survey formed a consensus between HVAC engineers that determined what the most commonly installed systems are and their associated performance values. The outcome of the survey was a documented set of system types and modelling input parameters that are representative of New Zealand HVAC systems. The responses of the survey were used to produce a set of HVAC system templates that replace the ideal loads air systems. The HVAC template models updated the software default parameter values with values that are representative of commonly installed systems in New Zealand. The importance of the updated input values was illustrated through a comparison of the calculated monthly energy consumption. The resulting difference in energy consumption using the updated parameter values is typically <5% monthly; at worst it is 75% for Variable Air Volume (VAV) system in the Wellington climate during June.</p>

scholarly journals Application of DMAIC to improve energy consumption in a commercial building

2021 ◽  
Author(s):  
◽  
Kanyinda Kabuya
Keyword(s):  
Energy Consumption ◽  
Six Sigma ◽  
Energy Use ◽  
Electrical Energy ◽  
Commercial Buildings ◽  
Commercial Building ◽  
Total Consumption ◽  
Pareto Chart ◽  
Electrical Consumption

Improving energy use in a commercial building has become the subject of great importance in organizations worldwide. Improving energy usage refers to the efforts to reduce energy consumption. Reducing energy consumption in commercial buildings can be accomplished through continuous supervision using appropriate managerial techniques. Commercial companies are required to use energy more efficiently and participate in energy improvement. This study seeks to improve electrical energy consumption in commercial buildings by Analysing the electrical data consumption and identifying the factors that contribute to high consumption using Six Sigma DMAIC (Define-Measure- Analyse-Improve-Control) problem solving methodology. A case study was used to validate the DMAIC framework. Two years of electrical consumption data of a case study done from January 2018 to December 2019 was collected and analysed. The study revealed an average increment in energy consumption of 3.9 %. The outcomes using statistical Pareto chart showed that the boiler is the highest significant energy user in the building with 38.3% due; followed by the kitchen with 24.2 %, followed by DB A and lifts with 20,1 % and the rest with 17.37 %. After the campaign of DMAIC, there was a reduction of 6 % in boiler consumption which was 2.3 % reduction of total consumption of the month for the building. Therefore, the study successfully demonstrates how Six Sigma DMAIC methodology can be applied to improve electrical consumption in a commercial building and reduce its related costs.

Ambient-Temperature Regression Analysis for Estimating Retrofit Savings in Commercial Buildings

1998 ◽  
Vol 120 (3) ◽  
pp. 168-176 ◽  
Author(s):  
J. K. Kissock ◽  
T. A. Reddy ◽  
D. E. Claridge
Keyword(s):  
Regression Analysis ◽  
Ambient Temperature ◽  
Change Point ◽  
Regression Models ◽  
Hvac Systems ◽  
Commercial Buildings ◽  
Heating And Cooling ◽  
Change Point Models ◽  
Selection Of

This paper describes a procedure for estimating weather-adjusted retrofit savings in commercial buildings using ambient-temperature regression models. The selection of ambient temperature as the sole independent regression variable is discussed. An approximate method for determining the uncertainty of savings and a method for identifying the data time scale which minimizes the uncertainty of savings are developed. The appropriate uses of both linear and change-point models for estimating savings based on expected heating and cooling relationships for common HVAC systems are described. A case study example illustrates the procedure.

scholarly journals An Autonomic Cycle of Data Analysis Tasks for the Supervision of HVAC Systems of Smart Building

Energies ◽  
2020 ◽  
Vol 13 (12) ◽  
pp. 3103
Author(s):  
Jose Aguilar ◽  
Douglas Ardila ◽  
Andrés Avendaño ◽  
Felipe Macias ◽  
Camila White ◽  
...  
Keyword(s):  
Data Analysis ◽  
Fault Detection ◽  
Hvac Systems ◽  
Economic Benefits ◽  
Fault Detection And Diagnosis ◽  
Hvac System ◽  
Smart Buildings ◽  
Detection And Diagnosis ◽  
Early Fault Detection

Early fault detection and diagnosis in heating, ventilation and air conditioning (HVAC) systems may reduce the damage of equipment, improving the reliability and safety of smart buildings, generating social and economic benefits. Data models for fault detection and diagnosis are increasingly used for extracting knowledge in the supervisory tasks. This article proposes an autonomic cycle of data analysis tasks (ACODAT) for the supervision of the building’s HVAC systems. Data analysis tasks incorporate data mining models for extracting knowledge from the system monitoring, analyzing abnormal situations and automatically identifying and taking corrective actions. This article shows a case study of a real building’s HVAC system, for the supervision with our ACODAT, where the HVAC subsystems have been installed over the years, providing a good example of a heterogeneous facility. The proposed supervisory functionality of the HVAC system is capable of detecting deviations, such as faults or gradual increment of energy consumption in similar working conditions. The case study shows this capability of the supervisory autonomic cycle, usually a key objective for smart buildings.

scholarly journals Energy and Environmental Effects of Human Habits in Residential Buildings Due to COVID-19 Outbreak Scenarios in a Dwelling near Rome

Energies ◽  
2021 ◽  
Vol 14 (21) ◽  
pp. 7408
Author(s):  
Domenico Palladino ◽  
Silvia Di Di Turi ◽  
Iole Nardi
Keyword(s):  
Energy Consumption ◽  
Environmental Effects ◽  
Calculation Method ◽  
Residential Buildings ◽  
Residential Building ◽  
Hvac Systems ◽  
Cooling Period ◽  
Energy Needs ◽  
Containment Measures

The COVID-19 pandemic and resulting containment measures have shown that energy consumption in buildings is linked to several factors, such as living habits, occupancy profiles, and heating ventilation and air conditioning (HVAC) systems. This paper addresses the influences of such factors on energy consumption in a residential building, analysing different scenarios (pre-COVID-19, lockdown, post-COVID-19), in terms of discomfort and energy needs, through the new hourly calculation method (UNI EN ISO 52016). Energy and environmental effects were studied in a real case study near Rome by varying occupancy profiles, lighting and appliance schedules, and HVAC systems. Results show that, during the heating period, the lockdown scenario led to the lowest hours of discomfort (−29% on average), but the highest in the cooling period (up to +154%, +28% on average). The same scenario led to reasonable reduction of energy needs for heating (−14%), but also highlighted a significant increase (+60%) for the cooling period. This study underlines how the pandemic has influenced the energy and environmental behaviours in buildings. Moreover, the new hourly calculation method points out the importance of analysing HVAC systems, in terms of hours of discomfort, which could provide results that are more reliable.

scholarly journals Determining the Modelling Input Parameters for Heating, Ventilation, and Air Conditioning Systems in New Zealand Commercial Buildings

2021 ◽  
Author(s):  
◽  
Anthony Gates
Keyword(s):  
Energy Consumption ◽  
New Zealand ◽  
Air Conditioning ◽  
Energy Performance ◽  
Hvac Systems ◽  
Commercial Buildings ◽  
Hvac System ◽  
Input Parameters ◽  
Parameter Values ◽  
The Ideal

<p>Template energy calculation models that have been produced by the Building Energy End-use Study (BEES) team are used to quickly and reliably model commercial buildings and calculate their energy performance. The template models contain standardised equipment, lighting, and occupancy loads; cooling and heating requirements are calculated using an ideal loads air system. Using seven buildings, Cory et al. 2011a have demonstrated that the template models have the potential to closely match the monthly energy performance of detailed (individually purpose built) models and the real buildings. Three of these models were within the ±5% acceptable tolerance to be considered calibrated. The four template models that were not within the acceptable tolerance have been identified to have complex Heating, Ventilation, and Air Conditioning (HVAC) systems that the ideal loads air systems could not replicate. Because HVAC systems consume one of the largest proportions of energy in commercial buildings, this has a significant impact on the reliability of the template models. To address this issue, a set of detailed HVAC systems were needed to replace the ideal loads air systems. Due to HVAC system parameters not being collected by the BEES team and the lack of published modelling input parameters available, it is unknown what values are reasonable to use in the models. This study used a Delphi survey to collect real building information of the commonly installed HVAC systems in New Zealand commercial buildings. The survey formed a consensus between HVAC engineers that determined what the most commonly installed systems are and their associated performance values. The outcome of the survey was a documented set of system types and modelling input parameters that are representative of New Zealand HVAC systems. The responses of the survey were used to produce a set of HVAC system templates that replace the ideal loads air systems. The HVAC template models updated the software default parameter values with values that are representative of commonly installed systems in New Zealand. The importance of the updated input values was illustrated through a comparison of the calculated monthly energy consumption. The resulting difference in energy consumption using the updated parameter values is typically <5% monthly; at worst it is 75% for Variable Air Volume (VAV) system in the Wellington climate during June.</p>

scholarly journals Analysis of Energy Consumption and Possibilities of Thermal-Modernization in Residential Buildings in Poland Case Study: The Town of Zielona Góra

2017 ◽  
Vol 22 (4) ◽  
pp. 1083-1095
Author(s):  
A. Alsabry ◽  
P. Truszkiewicz ◽  
K. Szymański ◽  
K. Łaskawiec ◽  
Ł. Rojek
Keyword(s):  
Energy Consumption ◽  
Residential Buildings ◽  
Commercial Buildings ◽  
Public Utilities ◽  
The Town

Abstract The article presents an analysis of buildings belonging the Department of Public Utilities and Housing in Zielona Góra. The research was based on a set of questions for building operators. The questionnaires consisted of 30 questions concerning general and detailed information about the buildings. In order to clearly present the results, this article includes data only about residential and residential-commercial buildings. Forty building built in different periods were selected for analysis.

SMART METER CONFIGURATION FOR BETTER ENERGY CONSUMPTION WITH FAULT DETECTION

2019 ◽  
Vol 7 (1) ◽  
pp. 12
Author(s):  
PARAMANIK SAYAN ◽  
KUSHARY INDRANIL ◽  
SARKER KRISHNA ◽  
◽  
◽  
...  
Keyword(s):  
Energy Consumption ◽  
Fault Detection ◽  
Smart Meter
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