The Study of Artificial Intelligent Building Automation Control System in Hong Kong Commercial Building

Intelligent building is a safe, comfortable, efficient, energy-saving, convenient and flexible modern building designed and built by organically combining high-tech and architectural art. Building automation control system is an important part of intelligent building, which realizes its own development through the development platform of intelligent building. It can improve the quality of building entities and supporting equipment and the quality of building environment in intelligent building to varying degrees. The building automation system in the intelligent building takes the humanized interface as the emphasis, and takes the combination of mechanical and electrical system, fire control system, access control system and parking management system as the method to create a convenient and comfortable living and working environment for building users. This paper mainly studies the building automation control system of intelligent building, and then describes the content of the building automation control system in intelligent building, and at the same time, carries out in-depth research on related issues, hoping to provide reference for researchers in this field.

Against the backdrop of increasing technological innovation and rising demand for sustainability in the built environment, there is a clear need to explore the application of Building Management System BMS in the Nigerian real estate sector. Accordingly, this paper examined the concept of adopting Building Management System (BMS) in commercial buildings in Lagos State, Nigeria with a view to assessing performance on SDG 11 (Sustainable cities and communities) where issues around resilience in buildings is hosted. The study administered one hundred and eighteen questionnaires to facility managers of commercial buildings that have adopted BMS in five local government areas in Lagos State. The data were processed using the principal component (factor) analysis and regression correlation analysis tool. It was found that a range of social and cost factors influenced the adoption of BMS in the study area. Specifically, level of occupant comfort and ease of use of the system were the most significant factor while implementation cost and extent of energy savings also strongly influenced BMS adoption in the study area. The chapter offers suggestions on strategies to improve adoption of BMS and recommends awareness campaigns and the introduction of promotional incentives to the public on BMS.

Advanced control systems engineering for energy and comfort management in a building environment—A review

Despite the potential for significant energy savings by reducing duct leakage or other thermal losses from duct systems in large commercial buildings, California Title 24 has no provisions to credit energy-efficient duct systems in these buildings. A substantial reason is the lack of readily available simulation tools to demonstrate the energy-saving benefits associated with efficient duct systems in large commercial buildings. The overall goal of the Efficient Distribution Systems (EDS) project within the PIER High Performance Commercial Building Systems Program is to bridge the gaps in current duct thermal performance modeling capabilities, and to expand our understanding of duct thermal performance in California large commercial buildings. As steps toward this goal, our strategy in the EDS project involves two parts: (1) developing a whole-building energy simulation approach for analyzing duct thermal performance in large commercial buildings, and (2) using the tool to identify the energy impacts of duct leakage in California large commercial buildings, in support of future recommendations to address duct performance in the Title 24 Energy Efficiency Standards for Nonresidential Buildings. The specific technical objectives for the EDS project were to: (1) Identify a near-term whole-building energy simulation approach that can be used in the impacts analysis task of this project (see Objective 3), with little or no modification. A secondary objective is to recommend how to proceed with long-term development of an improved compliance tool for Title 24 that addresses duct thermal performance. (2) Develop an Alternative Calculation Method (ACM) change proposal to include a new metric for thermal distribution system efficiency in the reporting requirements for the 2005 Title 24 Standards. The metric will facilitate future comparisons of different system types using a common ''yardstick''. (3) Using the selected near-term simulation approach, assess the impacts of duct system improvements in California large commercial buildings, over a range of building vintages and climates. This assessment will provide a solid foundation for future efforts that address the energy efficiency of large commercial duct systems in Title 24. This report describes our work to address Objective 1, which includes a review of past modeling efforts related to duct thermal performance, and recommends near- and long-term modeling approaches for analyzing duct thermal performance in large commercial buildings.

NOTE: The first page of text has been automatically extracted and included below in lieu of an abstract Session 1526 Electronically-Controlled Artificial Sky Dome @ OSU … in Progress Khaled Mansy, Steven O’Hara / Thomas Gedra, Qamar Arsalan School of Architecture / School of Electrical and Computer Engineering Oklahoma State University, Stillwater, OK 74078 Abstract Indeed, design of daylighting systems is increasingly becoming an integral part of the design of energy-efficient buildings. In order to accurately design, test, and analyze daylighting systems, a controlled luminous environment is required to simulate different sky conditions, under which a physical model can be tested. An artificial sky dome is needed. This paper reports on the ongoing effort to build an Artificial Sky Dome for the School of Architecture at Oklahoma State University. The paper discusses the technical challenges faced by the team in charge of designing the Artificial Sky Dome. Challenges that relate to the structure of the dome, uniform distribution of light sources, avoiding the star effect, effect of internal reflections, models of different sky conditions, control of sky luminance, and the need for a post-construction calibration of the lighting control system. The construction of the Artificial Sky Dome is expected to be completed by the end of summer 2005. This laboratory is funded by the National Science Foundation, Division of Undergraduate Education, (CCLI) Course, Curriculum, and Laboratory Improvement-Adaptation and Implementation. This new laboratory will help integrate the engineering of daylighting systems into the school’s curriculum, with the anticipation that this will nurture the scientific background and design skills of undergraduate students. The secondary mission of the laboratory is to disseminate the same knowledge and/or skills between graduate students, faculty, and practicing professionals. The laboratory will also be an effective venue to integrate teaching and research. 1. Design of Daylighting Systems in Buildings Integration between daylighting and electric lighting systems in commercial buildings may result in a significant reduction in the annual energy consumption and operating cost. Indeed, daylight is a free source of energy. Moreover, it is rather a cool source of light that reduces space cooling load. Despite of this fact, the majority of building designers still does not use accurate design tools to design daylighting systems in buildings. Currently, design of daylighting systems relies on the use of rules of thumb, which are not accurate because they only offer general guidance that is not case-specific. The use of inaccurate design tools results in losing the opportunity of saving energy. Currently used daylighting design tools include, but not limited to, simple formulas, daylighting nomographs, and graphical methods. Each of these design-assisting tools “Proceedings of the 2005 American Society for Engineering Education Annual Conference & Exposition Copyright © 2005, American Society for Engineering Education”

According to the California Energy Commission (CEC 1998a), California commercial buildings account for 35% of statewide electricity consumption, and 16% of statewide gas consumption. Space conditioning accounts for roughly 16,000 GWh of electricity and 800 million therms of natural gas annually, and the vast majority of this space conditioning energy passes through thermal distribution systems in these buildings. In addition, 8600 GWh per year is consumed by fans and pumps in commercial buildings, most of which is used to move the thermal energy through these systems. Research work at Lawrence Berkeley National Laboratory (LBNL) has been ongoing over the past five years to investigate the energy efficiency of these thermal distribution systems, and to explore possibilities for improving that energy efficiency. Based upon that work, annual savings estimates of 1 kWh/ft{sup 2} for light commercial buildings, and 1-2 kWh/ft{sup 2} in large commercial buildings have been developed for the particular aspects of thermal distribution system performance being addressed by this project. Those savings estimates, combined with a distribution of the building stock based upon an extensive stock characterization study (Modera et al. 1999a), and technical penetration estimates, translate into statewide saving potentials of 2000 GWh/year and 75 million thermal/year, as well as an electricity peak reduction potential of 0.7 GW. The overall goal of this research program is to provide new technology and application knowledge that will allow the design, construction, and energy services industries to reduce the energy waste associated with thermal distribution systems in California commercial buildings. The specific goals of the LBNL efforts over the past year were: (1) to advance the state of knowledge about system performance and energy losses in commercial-building thermal distribution systems; (2) to evaluate the potential of reducing thermal losses through duct sealing, duct insulation, and improved equipment sizing; and (3) to develop and evaluate innovative techniques applicable to large buildings for sealing ducts and encapsulating internal duct insulation. In the UCB fan project, the goals were: (1) to develop a protocol for testing, analyzing and diagnosing problems in large commercial building built-up air handling systems, and (2) to develop low-cost measurement techniques to improve short term monitoring practices. To meet our stated goals and objectives, this project: (1) continued to investigate and characterize the performance of thermal distribution systems in commercial buildings; (2) performed energy analyses and evaluation for duct-performance improvements for both small and large commercial buildings; (3) developed aerosol injection technologies for both duct sealing and liner encapsulation in commercial buildings; and (4) designed energy-related diagnostic protocols based on short term measurement and used a benchmarking database to compare subject systems with other measured systems for certain performance metrics. This year's efforts consisted of the following distinct tasks: performing characterization measurements for five light commercial building systems and five large-commercial-building systems; analyzing the potential for including duct performance in California's Energy Efficiency Standards for Residential and Non-Residential Buildings (Title 24), including performing energy and equipment sizing analyses of air distribution systems using DOE 2.1E for non-residential buildings; conducting laboratory experiments, field experiments, and modeling of new aerosol injection technologies concepts for sealing and coating, including field testing aerosol-based sealing in two large commercial buildings; improving low-cost fan monitoring techniques measurements, and disseminating fan tools by working with energy practitioners directly where possible and publishing the results of this research and the tools developed on a web-site. The final report consists of five sections listed below. Each section includes its related background information, the research methods employed, new measurement techniques developed, the results, and discussion.

Hydronic heating and cooling systems are among the most common types of heating and cooling systems installed in older existing buildings, especially commercial buildings. According to the 2012 Commercial Building Energy Consumption Survey (CBECS) data set, hydronic heating systems in the United States include two main systems: (i) boilers inside the building represented with a boiler system and (ii) district steam and hot water systems represented with district heating, which are connected to seven different types of zone-level equipment. Similarly, there are two main hydronic cooling systems: central chillers inside (or adjacent to) the building and district chilled water piped in from outside the building. Chiller systems are investigated based on three different classes: (1) water-cooled, (2) air-cooled, and (3) absorption chillers. This study presents a deep analysis of the 2012 CBECS microdata to characterize hydronic heating and cooling systems by year of construction, census division, building area, building site hydronic system energy use index (EUI), and the types of mechanical systems. The results show that nearly 65% of commercial buildings built before 1990 utilize hydronic heating systems. Hydronic heating and cooling system design are a function of a building area. District heating systems are considered as the main heating systems in buildings with an area greater than 18,600 m2 (200,000 ft2). In addition, systems with central chillers inside the buildings are responsible for providing cooling for more than 50% of the commercial buildings with areas greater than 9,000 m2 (∼100,000 ft2). Among the types of chiller systems, the chiller systems connected to the central air handling units, fan coil units, and duct reheats are the most common systems for large buildings. The results of this building stock characterization provide useful insights into the characteristics of hydronic heating and cooling systems in US commercial buildings.

Construction, application and validation of selection evaluation model (SEM) for intelligent HVAC control system

Centrally controlled heating, ventilation, and air conditioning (HVAC) systems in commercial buildings are operated by building management systems (BMS) based on the predefined operational settings and a set of assumptions. Despite the high rate of energy consumption by HVAC systems in commercial buildings, observations showed that a significant portion of the occupants remain dissatisfied with thermal conditions. One of the main reasons is that HVAC systems do not take into account personalized comfort preferences in their operational rules. This study proposes a framework to integrate building occupants in the HVAC control loop, learn their comfort profiles, and control the HVAC system based on occupants’ personalized comfort profiles. The framework fuses occupants’ comfort perception indices (i.e., comfort votes provided by users and mapped to a numerical value), collected through participatory sensing, and ambient temperature data, collected through a sensor network, and computes occupants’ co...

In recent years, the use of artificial intelligence (AI) techniques such as Artificial Neural Networks (ANNs) and Support Vector Machines (SVMs), in combination with the Internet of Things (IoT), has gained significant attention for optimizing energy consumption in commercial buildings. With the increasing demand for energy and the rising costs of energy, there is a pressing need for efficient methods for energy management in commercial buildings. Smart energy consumption control systems that utilize machine learning algorithms and IoT devices can provide real-time data on energy usage and automate energy usage decisions in commercial buildings. In this paper, we investigate the potential of ANN and SVM-based smart energy consumption control systems in commercial buildings. We aim to analyze the impact of using these algorithms on energy consumption patterns in commercial buildings and evaluate the efficiency and effectiveness of these systems in reducing energy consumption and costs while maintaining the desired level of comfort for the occupants. Our study will focus on comparing the performance of ANN and SVM-based algorithms in terms of energy consumption reduction and cost savings. The results of this study can provide valuable insights into the application of ANN and SVM-based smart energy consumption control systems in commercial buildings and contribute to the development of more sustainable and energy-efficient buildings.

The Subcontract Statement of Work consists of two major tasks. This report is the Final Report in fulfillment of the contract deliverable for Task 1. The purpose of Task 1 was to evaluate existing and emerging protocols and standards for interfacing sensors and controllers for communicating with integrated lighting control systems in commercial buildings. The detailed task description follows: Task 1. Evaluate alternative sensor/field buses. The objective of this task is to evaluate existing and emerging standards for interfacing sensors and controllers for communicating with integrated lighting control systems in commercial buildings. The protocols to be evaluated will include at least: (1) 1-Wire Net, (2) DALI, (3) MODBUS (or appropriate substitute such as EIB) and (4) ZigBee. The evaluation will include a comparative matrix for comparing the technical performance features of the different alternative systems. The performance features to be considered include: (1) directionality and network speed, (2) error control, (3) latency times, (4) allowable cable voltage drop, (5) topology, and (6) polarization. Specifically, Subcontractor will: (1) Analyze the proposed network architecture and identify potential problems that may require further research and specification. (2) Help identify and specify additional software and hardware components that may be required for the communications network to operate properly. (3) Identify areas of the architecture that can benefit from existing standards and technology and enumerate those standards and technologies. (4) Identify existing companies that may have relevant technology that can be applied to this research. (5) Help determine if new standards or technologies need to be developed.

In this paper we review the current landscape of data-driven decision making in the context of operating residential and commercial building systems with energy management objectives. First, we present results from a literature review focused on identifying new sources of data that have become available (e.g., smart-phone sensors, utility smart meters) and their potential to impact the decision making processes involved in operating these facilities. Existing obstacles to realizing the full potential of these novel data sources are discussed and later explored more in depth through case studies. These include limited interoperability and standardization practices, high labor and/or maintenance costs for installing and maintaining the instrumentation and computationally expensive inference procedures for extracting useful information out of the measurements. Finally, two specific research projects that address some of these challenges are presented in detail: one on disaggregating the total electricity consumption of a building into its constituent loads for informing predictive maintenance practices; and another on standardizing meta-data about sensors and actuators in existing Building Automation Systems (BAS) so that software applications targeting building systems can be deployed in different buildings without the need for manual configuration. Our case studies reveal that the rapid proliferation of sensing/control devices, alone, will not improve the building systems being monitored or significantly alter the way these systems are managed or controlled. When data about the physical world is a commodity, it is the ability to extract actionable information from this resource what generates value and, more often than not, this process requires significant domain expertise.

Buildings and their occupants are responsible for a large portion of global energy consumption, roughly half of which is associated with the HVAC systems. HVAC systems in large buildings are connected and controlled by a Building Management System (BMS) which are prone to errors, faults and mismanagement and HVAC systems can suffer wastage of up to 30% of total energy consumption through poor controls (Zhang 2021, Granderson 2017). This discrepancy between design and reality is often referred to as the ‘performance gap’. Consequently, there is scope to save a significant amount of energy by addressing these issues. And with the global need to urgently reduce energy demands and carbon emissions it has been a popular topic of research.It follows that a method is needed to identify faults, miscalibration and energy wastage in buildings. Such methods are commonly referred to as fault detection and diagnosis (FDD) methods. Building Management Systems in commercial buildings often connect thousands of sensors and actuators together. The constant communication of these devices produces large amounts of data which has historically been discarded or used in a limited capacity for troubleshooting or commissioning. The infrastructure for this data already exists in most buildings, presenting opportunity for deeper analysis and optimisation. Using this data the FDD methods can be automated, taking engineering knowledge and supplying a data set with rule-based algorithms to find any root causes of control inefficiencies within the building. A secondary approach is to use artificial intelligence models over these data sets to find ways to operate the building more efficiently.This paper shows the effectiveness of an automated FDD approach via 6 case studies in commercial office buildings, highlighting the methods by which faults were identified and resolved, as well as the impacts of the corrective action. It then compares these examples with the findings of research into the effectiveness of the AI-based approach and discusses whether the AI-based approach is more effective than the automated FDD approach or whether the AI-based approach is using significantly more computer power and time to, in fact, find rules to correct control patterns that are already widely known within general engineering practise. The results of this research should indicate whether AI or automated FDD are currently more suitable to close the performance gap in commercial buildings.

At present, buildings account for a great share of energy consumption. It is well known that building automation control systems allow for increasing opportunities of improvement in the performance of buildings, with respect to e.g. energy performance and indoor comfort. As system within a building become more and more complex, buildings can be regarded not merely as a load but as a smart micro grid, with the possibility of actively interacting with a smart grid. In the depicted context, metering is essential for assessing the performance of management and detecting improvement opportunities. The scope of the present work is to propose a best practice for the implementation of smart metering systems in buildings and a practical methodology to classify the systems. In the present work, a novel classification protocol is devised; an existing metering system is then evaluated and an improved metering system is proposed. The proposed protocol rates the system performance via a set of weighted indicators -according to positioning of meters, measured data, system architecture, data visualization and monitored loads -, then calculates an overall grade. The protocol is tested on an existing metering system in an educational building. The metering system returns a poor rating and a number of flaws are detected thanks to the benchmark protocol. An improved metering system is then proposed which fixes existing flaws and returns a much better grade. In conclusion, the designed classification protocol allowed diagnosing an existing metering system and pinpointing improvement opportunities and it can be a useful practice in diagnostics or design of smart metering systems.

BIM assisted Building Automation System information exchange using BACnet and IFC