Building Automation And Control Systems Research Articles

Understanding the opportunities and challenges of building automation and control systems to support facility management – an extensive literature review

PurposeThis paper aims to highlight the expanding link between facility management (FM) and building automation and control systems (BACS) through a review of literature. It examines the opportunities and challenges of BACS for facility managers and proposes solutions for mitigating the risks associated with BACS implementation.Design/methodology/approachThis paper reviews various research papers to explore the positive influences of BACS on FM, such as support with strategic decision-making, predictive maintenance, energy efficiency and comfort improvement. It also discusses the challenges of BACS, including obsolescence, interoperability, vendor lock-in, reliability and security risks and suggests potential solutions based on existing literature.FindingsBACS offers numerous opportunities for facility managers, such as improved decision-making, energy efficiency and comfort levels in office buildings. However, there are also risks associated with BACS implementation, including obsolescence, interoperability, vendor lock-in, reliability and security risks. These risks can be mitigated through measures such as hardware and software obsolescence management plans, functional requirement lists, wireless communication protocols, advanced feedback systems and increased awareness about BACS security.Originality/valueTo the best of the authors’ knowledge, no prior academic research has been conducted on the expanding link between FM and BACS. Although some papers have touched upon the opportunities and challenges of BACS for FM, this paper aims to provide a comprehensive overview of these findings by consolidating existing literature.

Automated PLC Code Generation for the Implementation of Mode-Based Control Algorithms in Buildings

Faulty programming of control functions in Building Automation and Control Systems (BACS) might result in inefficient building operations. To reduce programming errors, an automated implementation process of control functions might be a promising solution. Recently, Building Information Modeling (BIM) contributes to digitizing building construction projects but is rarely used in the planning and implementation of control functions in BACS. The control description in BIM also remains unclear. Regarding these problems, a control documentation method for BIM and an automated control implementation approach can simplify control implementation in BACS and hence improve the building operation. In the previous work, we developed the MODI method for a structured planning process of mode-based control algorithms for building energy systems. This method showed the potential to support digitized control planning and implementation in BACS. Based on this, in this paper, we introduce a documentation method to report mode-based control algorithms in the industrial foundation class (IFC), enabling data sharing among BIM, and a software-assisted approach to automatically generate PLC codes for implementing these algorithms. The case study demonstrates the documentation of a desired mode-based control strategy for an energy supply network in IFC and the implementation of this strategy in a PLC program. In the simulation phase, we test the implemented control strategy to verify the functionalities of the PLC program. The results prove that mode-based control strategies can be fully automatically implemented in a PLC program based on IFC data.

Feasibility analysis of the application of building automation and control system and their interaction with occupant behavior

Occupant behavior is among the main causes for the mismatch between simulated and in-use energy performance of buildings. One of the strategies considered capable of reducing user’s behavior induced energy consumption, while increasing indoor environmental quality is the application of Building Automation and Control Systems (BACS). In this study, three building user’s profiles have been considered depending on their energy consumption. The energy savings due to BACS class increase have been calculated, and a cost–benefit analysis (CBA) has been performed to evaluate the feasibility of different scenarios. Additional co-benefits perceived by the individuals have been accounted for in the form of willingness-to-pay (WTP). The methodology is applied to two case studies: a nearly zero-energy building (NZEB) rural single-family house and a recently renovated dwelling in an apartment block. The results show that the main reductions are achieved by the users’ behavior alone, and the adoption of BACS is economically feasible only when an incentive program is in place, and the WTP is repeated as a recurrent co-benefit over the years. In particular, relying only on energy reduction due to higher BACS class introduction is not economically desirable. The greatest savings are achieved by the behavioral change of the user when coupled with BACS, supporting their potential role in improving user’s energy literacy. Finally, incentive schemes are necessary to reduce the investment costs of such projects, being these the most influential variables in the feasibility of BACS applications.

Meeting User Needs through Building Automation and Control Systems: A Review of Impacts and Benefits in Office Environments

Smart building technologies and building automation and control systems (BACS) can offer a range of additional benefits beyond energy savings, in particular by improving building responsiveness to user needs. Although in recent years these technologies have gained popularity as a means of reducing energy consumption and improving building performance, a clear picture of the role of BACS in providing a wider range of benefits is still missing. This review identifies and collects BACS impacts in office buildings with a special emphasis on improving indoor environmental quality by adapting building operation to changing conditions and guaranteeing feedback and real-time interaction with occupants. The resulting benefits, such as increased employee productivity, fewer occurrences of sick leave, and lower rates of absenteeism are highlighted. Offices represent an interesting field of application, as small improvements in the built environment can have a significant impact on labour costs which are the predominant share of the total operating costs. Furthermore, quantitative relationships between physical factors of the indoor environment and benefits have been displayed where available. This literature review aims at establishing an approach that comprehensively evaluates BACS across their entire spectrum, leading to the promotion of novel business cases.

A Network Intrusion Detection System for Building Automation and Control Systems

Building Automation and Control Systems (BACS) are traditionally based on specialized communications protocols, such as KNX or BACnet, and dedicated sensing and actuating devices. Despite the increased awareness about the security risks associated with BACS, there is a lack of security tools for protecting this special breed of cyber-physical systems. This is further aggravated by the fact that general-purpose security tools are typically not able to cope with the specific requirements and technologies associated with BACS, making it necessary to devise domain-specific approaches – as shown, for instance, by the KNX Secure initiative led by the KNX Association. Nevertheless, despite the advances brought by KNX Secure and similar initiatives, there is still a considerable gap between the security needs of BACS and the solutions available. In this paper, we address this gap by proposing a Network Intrusion Detection System (NIDS) specifically designed for BACS. This NIDS is protocol-agnostic and can potentially support different BACS protocols and technologies, such as KNX, BACnet, Modbus or mixed ecosystems, without loss of generality. We also present a specific proof-of-concept implementation of this NIDS concept for KNX – one of the more widespread BACS protocols. To this purpose, a real-world KNX deployment was used to showcase and evaluate the proposed approach.

A Hybrid Approach in Design of Building Energy Management System with Smart Readiness Indicator and Building as a Service Concept

Improving energy efficiency and increasing the level of intelligence are two main factors determining the current development trends for new and modernized buildings. They are especially important in the perspective of development of prosumer installations and local microgrids. A key tool to achieve these goals is a well-designed and implemented Building Automation and Control System (BACS). This paper presents a new hybrid approach to the design and technical organization of BACS based on the provisions of the EN 15232 standard and the guidelines of the Smart Readiness Indicator (SRI) defined in the Energy Performance of Buildings Directive 2018 (EPBD 2018). The main assumptions of this hybrid approach along with examples of functional BACS designs for small prosumer installations organized according to them are provided. Potential impact on building energy performance is discussed as well. Finally, a SWOT analysis of the possibility of merging the EN 15232 standard guidelines and the SRI assessment methodology to develop uniform technical guidelines for the BACS functions design and evaluation of their impact on the buildings’ energy efficiency are discussed.

Assessment of Building Automation and Control Systems in Danish Healthcare Facilities in the COVID-19 Era

A well-designed and properly operated building automation and control system (BACS) is key to attaining energy-efficient operation and optimal indoor conditions. In this study, three healthcare facilities of a different type, age, and use are considered as case studies to investigate the functionalities of BACS in providing optimal air quality and thermal comfort. IBACSA, the first-of-its-kind instrument for BACS assessment and smartness evaluation, is used to evaluate the current systems and their control functionalities. The BACS assessment is reported and analyzed. Then, three packages of improvements were implemented in the three cases, focusing on (1) technical systems enhancement, (2) indoor air quality and comfort, and (3) energy efficiency. It was found that the ventilation system domain is the best performer in the three considered cases with an overall score of 52%, 89% and 91% in Case A, B, and C, respectively. On the other hand, domestic hot water domain scores are relatively low, indicating that this is an area where Danish healthcare facilities need to provide more concentration on. A key finding indicated by the assessment performed is that the three buildings score relatively very low when it comes to the impact criteria of energy flexibility and storage.

Security of Building Automation and Control Systems: Survey and future research directions

Building Automation and Control Systems (BACS) designate the mechanisms that are used to automate buildings’ operations such as climate control, lightning and access control. As such, traditional BACS encompass extensively automated buildings managed in an integrated manner, with the support of Supervisory Control and Data Acquisition (SCADA) systems and specialized industry standards such as BACnet and KNX. More recently, the increasing adoption of IP-connected, IoT-like devices for automating single tasks led to a substantial increase in the number of automated building functions (especially for the smart home domain), although rarely with extensive or integrated automation levels. The interconnection with the building local area network (LAN) and even the Internet, comes with the cost of a wider exposition to attacks, that can either begin inside of the building or be initiated from anywhere outside of it.In contrast with other domains that recently received substantial attention (e.g. industrial control and automation systems), the security of BACS has been addressed in a somehow more superficial and less structured manner. Nevertheless, recent security incidents, combined with the fact that these systems are becoming more interconnected with the building networks and the Internet, are raising security concerns.This paper provides a systematic survey of recent research and industry developments related with the security and safety of building automation and control systems. It also presents an overview of the existing threats and known attacks against BACS, as well as open issues and future research directions.

Information modeling for the monitoring of existing buildings' indoor comfort

BEMS (Building Energy Management System) and BACS (Building Automation and Control System) make available a high quantity of data on consumptions, indoor and outdoor conditions and users' profiles of a buildind that can drive the choice of energy retrofit interventions. Moreover, the current developments in the digitalization of the building process, are leading the diffusion of BIM methods and tools which can provide a valid support to manage all data and information for the retrofit process. The paper is focused on the efficient integration of these systems.

Empirical BAC factors method application to two real case studies in South Italy

The application of Building Automation and Control (BAC) systems has many advantages. One of these is the reduction of the end-user electricity consumption and, if applied to lighting systems, the achievement of well-acknowledged benefits from daylight, such as productivity, health, visual comfort and well-being. Concerning the first aspect, the international Standard EN 15232 proposes the so-called BAC Factors (BF) method to assess the impact of BAC systems on the final energy consumption. The method provides a simplified estimation of the energy savings due to automation in buildings and questions arise on its applicability in some situations. For this reason, the authors have carried out an experimental study aiming at comparing the energy savings calculated using the simplified BAC factor method with those evaluated with a measurement campaign on a laboratory setup. In particular, the BF are evaluated for an office and a residential environment, using sets of data measured in two cases study in South Italy by testing two lighting control systems in different end-uses (residential and office). The comparison between the sets of data shows the limits of the simplified BAC factor method.

AUSTRET: An Automated Step Response Testing Tool for Building Automation and Control Systems

Building energy consumption is still one of the main contributions to global carbon emissions. With the overall digitalization in the building sector, building automation and control systems (BACS) are to play a more important and key role in improving the building sector performance. A well-designed BACS at the building design phase with a high level of control functionalities is not a guarantee for efficient building operation and successful control and management strategies in the operational phase. Thus, a systematic automated initial and retro-commissioning process is key to test the performance of the automation system and the response of the integrated HVAC systems. This is an arduous and time-consuming task susceptible to human errors. As an alternative, the current study proposes a methodological framework to automate step response testing of BACS and to optimize the different steps of this process in a cost-effective way. In addition to newly built buildings, the framework can be applied in existing or retrofitted medium to large-sized buildings that have a building management system capable of receiving actuator commands and responsible to provide updates of several state variables. Based on the proposed framework, a first-of-its kind tool “AUSTRET” for building automated step response testing of BACS is designed and developed. The tool provides the necessary input configuring parameters, building system selection, and output results for each performed test. The framework aims to act upon ventilation, room heating and cooling, and water heating and cooling modules in a building. The implementation and demonstration of the AUSTRET in a medium-sized building case study for two different building systems are presented and evaluated: (1) Ventilation/fan, (2) Room heating. The results show the different dynamic responses on these two systems and how misleading input parameter configuration can invalidate step response tests. The preliminary results highlight the capability of using AUSTRET as a key component in both building initial and retro-commissioning applications.

Monitoring data-driven Reinforcement Learning controller training: A comparative study of different training strategies for a real-world energy system

With increasing complexity of building energy systems and rising shares of renewable energies in the grids, the requirements for building automation and control systems (BACS) are increasing. The use of storage systems enables the decoupling of energy demand and supply and to consider dynamic constraints in the control of the systems. The resulting optimization problem is very challenging to solve with the state-of-the-art rule-based-control (RBC) approach. Model Predictive Control (MPC) on the other hand allows a nearly optimal operation but comes with expensive modeling efforts and high computational costs. These drawbacks are contrasted by promising results from the field of Reinforcement Learning (RL). RL can be model-free, is highly adaptive and learns a policy by interacting with the controlled system. However, the literature also addresses a number of questions, to be answered before RL for BACS can be realized. One is the slow convergence of the training process, which makes the application of a pre-training strategy necessary. Therefore, we design and compare different pre-training work-flows for a real-world energy system, in a demand response scenario. We apply a data-driven approach, covering all aspects from raw monitoring data to the trained algorithm. The considered energy system consists of two compression chillers and an ice storage. The objective of the control task is to charge and discharge the storage with respect to dynamic constraints. We use machine learning models of the energy system to train and evaluate a state-of-the-art RL algorithm (DQN) under five different pre-training strategies. We compare, online and offline training and initialization of the RL controller together with a guiding RBC. We demonstrate that offline training with a guiding RBC provides stable learning and a RL controller that always outperforms this guiding RBC. Unguided exploration on the other hand leads to higher accumulated cost savings. Based on our findings, we derive recommendations for practical application and future research questions.

Application of two promising Reinforcement Learning algorithms for load shifting in a cooling supply system

With the increasing use of volatile renewable energies, the requirements for building automation and control systems (BACS) are increasing. Load shifting within local energy systems stabilizes fluctuations in the grid and can be triggered by price signals. The energy purchase can thus be considered and solved as an optimal control problem. Classical approaches, often based on the optimization of mathematical models, are uneconomical in many cases, due to the high effort involved in the model creation. Algorithms from the field of Reinforcement Learning (RL), on the other hand, have a high potential for the automation of energy system optimization, due to their model-free and data-driven characteristics. However, there is still a lack of studies that examine algorithms for BACS-related applications in a structured way. Therefore, we present a study, investigating the potential of two different RL algorithms for load shifting in a cooling supply system. We combine the benefits of Modelica, a powerful modeling language, with RL algorithms and demonstrate how generalized relationships and control decisions can be learned. The case study is modeled according to a cooling supply system in Berlin, Germany. The two different algorithms (DQN and DDPG) are used to control the operation parameters of a central compression chiller, with respect to a price signal. While real monitoring data are used as exogenous influences, the thermal dynamics of the cooling network are simulated. With the learned policies, flexibility in the network is used which leads on average to weekly cost savings of 14 %, compared to direct load coverage. Our results suggest that, under certain conditions, RL is a suitable alternative to established methods. However, we also acknowledge that there are still research questions to address before RL can be applied in real BACS.

IBACSA: An interactive tool for building automation and control systems auditing and smartness evaluation

In future smart communities, buildings must possess energy efficient systems, provide absolute comfort, empower occupants with information, adapt operations to energy grid situations and facilitate strategic maintenance. A key condition to realize these deliverables, is a proper designed and well-equipped building automation and control system (BACS). Thus, long-term solutions call for multi-criteria approaches capable of assessing and evaluating the building automation systems' performance based on multiple impacts. This paper introduces an innovative holistic tool ‘IBACSA’, for BACS assessment and smartness evaluation using a qualitative-based multi-criteria approach. A specific set of relevant systems and their associated services form the basis of the proposed auditing and evaluation methodology. The targeted building domains comprise 60 different services in total based on guidelines and functionalities listed in the EN15232 standard. The proposed tool is able to quantify the specific impacts of the selected control functionalities based on five criteria using the points grading principle. IBACSA demonstration in a case study university building is reported and evaluated. The building overall scored 79% on energy efficiency, 64% on maintenance & fault prediction, 24% on energy flexibility & storage, 70% on comfort and 84% on information to occupants. The implementation of IBACSA in the case study shows the potential of the tool in auditing various BACS features and reporting the impact of upgrades and retrofits. The proposed tool serves as a comprehensive and user-friendly instrument in a systematic building initial and retro commissioning platform, ensuring a good start-up for newly built and retrofitted energy efficient buildings.

Auditing and design evaluation of building automation and control systems based on eu.bac system audit – Danish case study

Abstract Improving the energy performance of buildings will prove vital for countries worldwide to reduce their energy consumption and emissions. A key player in reaching this goal is building automation and control, as having well-designed and operated building automation and control systems (BACS) provide large capabilities in optimizing the energy performance of different systems. In this regard, building owners and planners must be able to assess and evaluate the current status of their BACS and identify potential improvements. While there has been a large block of work done in Denmark along with regulations aiming to audit the overall building performance and individual systems characteristics, very little has been done in the field of auditing the building automation and control system and evaluating its structure and operation patterns. This lack of systematic BACS auditing and evaluation in Danish buildings is addressed in this work with the first implementation and evaluation of the eu.bac System methodology in a university office building. The building was found to comply with the lowest automation and control class E. Two BACS retrofit packages were proposed and evaluated, and energy savings up to 28.5% are reported. The preliminary assessment results reported demonstrate the potential of building automation and control retrofit measures in a combined holistic improvement package alongside building envelope upgrade. In addition, the impact of the eu.bac System improvements and labeling on the building's classification based on the recent Danish building regulation BR18 is evaluated. The study discusses the feasibility of eu.bac System tool implementation in Danish buildings and suggests improvements. It also correlates and compares the eu.bac System audit to the upcoming European SRI instrument. In light of the huge efforts to digitalize the Danish energy sector, ensuring proper design and operation of BACS is of great importance. Thus, a systematic and methodical BACS auditing and evaluation methodology will be a crucial part of buildings’ initial and retro-commissioning platforms.

Machine Learning for Benchmarking Models of Heating Energy Demand of Houses in Northern Canada

In most cases, the benchmarking models of energy use in houses are developed based on current and past data, and they continue to be used without any update. This paper proposes the method of retraining of benchmarking models by applying machine learning techniques when new measurements are made available. The method uses as a case study the measurements of heating energy demand from two semi-detached houses of Northern Canada. The results of the prediction of heating energy demand using static or augmented window techniques are compared with measurements. The daily energy signature is used as a benchmarking model due to its simplicity and performance. However, the proposed retraining method can be applied to any form of benchmarking model. The method should be applied in all possible situations, and be an integral part of intelligent building automation and control systems (BACS) for the ongoing commissioning for building energy-related applications.

Killer Whale – Backpropagation (KW-BP) Algorithm for Accuracy Improvement of Neural Network Forecasting Models on Energy-Efficient Data

<p>Green technology building is not newly introduced to the world nor Malaysia, but it is rarely practiced globally and now it has promoted noteworthy due to destructions caused by human hands towards the nature. Now people started to realize that the world is polluted by many hazardous substances. Therefore, Help University came up with the effort of preserving the nature through a new Green Technology campus, which has been fully operated since year 2017. In this research, neural network forecasting models on energy-efficient data of Help University, Subang 2 green technology campus at Subang Bistari, Selangor has been done with respect to value-for-money(VFM) attribute. Previously there were no similar research done on energy-efficient data of Help University, Subang 2 campus. The significant factors with respect to energy or electricity saved(MW/hr) in the year 2017 variable were studied as recorded by Building Automation and Control System(BAS) of Help University Subang 2 campus. Using multiple linear regression (stepwise method), the significant predictor towards energy saved(MW/hr) was Building Energy Index(BEI)(kWh/m2/year) based p-value<α=0.05. A mathematical model was developed. Moreover, the proposed neural network forecasting model using Killer Whale - Backpropagation Algorithm(KWBP) were found to better than existing conventional techniques to forecast BEI data. This research is expected to specifically assist maintenance department of Help University, Subang 2 campus towards load forecasting for power saving planning in years to come.</p>

Aikido: Structuring data point identifiers of technical building equipment by machine learning

Building automation and control systems (BACS) generate large amounts of data. Manual interpretation of the data, e.g. for identifying energy efficiency measures, is in many cases either too costly or too complex. In order to reduce the manual effort of building data analysis, it is necessary that the labeling of data points is human- and machine-readable. As there is currently no widely accepted standard for labeling, these labeling texts differ greatly. We developed an algorithm based on Natural Language Processing (NLP) that automates the translation of BACS metadata. In previous works, we developed a schema based on 40 other schemas for the designation of data points (BUDO Schema) that we use for the translation. The user labels data points suggested by our algorithm Aikido and checks the prediction in a browser-based GUI (key interface). In our case study, we use a dataset that comprises five different projects, each using its own schema for structuring the metadata of data points in BACS. After ten training labels, our algorithm achieved an accuracy of 0.87 across all data sets. This increased to 0.95 with 50 training labels. We show that the chosen approach is able to normalize the metadata of different schemas to transfer to a previously defined schema. Thus, the manual effort is decreased significantly.

Cloud, wireless technology, internet of things: the next generation of building automation systems?

Building automation and control systems (BAS) have become a common part of non-residential buildings in the past decades. However, many automation systems rely on severely outdated technology that render it challenging, if not impossible, to implement recently developed, advanced building control approaches. By contrast, recent developments in cloud computing and wireless technology could support solutions to these challenges. However, many stakeholders require a suitable methodology to determine the potentials and the requirements of future, possibly next generation BAS. In this paper, we thus present and apply a method to answer the open questions and define minimum requirements. For that end, we investigate available communication technologies, protocols, and interfaces. Moreover, we present a simple test bench layout that could serve as a blueprint for future, more comprehensive test benches. It is a model a ventilation circuit consisting of a CO2 sensor for the supply air and an electronic damper. We turned these conventional components with analogue interfaces into IoT devices using a previously developed WiFi gateway. An exemplary test is the control of the CO2 concentration using a feedback controller implemented on an external machine. We aim to extend our initial prototype to a real-life building demonstration for dynamically scalable automation systems using wireless communication and develop our set-up into a platform enabling arbitrarily complex automation strategies and artificial intelligence applications.

Intelligent building systems: security and facility professionals’ understanding of system threats, vulnerabilities and mitigation practice

Intelligent Buildings or Building Automation and Control Systems (BACS) are becoming common in buildings, driven by the commercial need for functionality, sharing of information, reduced costs and sustainable buildings. The facility manager often has BACS responsibility; however, their focus is generally not on BACS security. Nevertheless, if a BACS-manifested threat is realised, the impact to a building can be significant, through denial, loss or manipulation of the building and its services, resulting in loss of information or occupancy. Therefore, this study garnered a descriptive understanding of security and facility professionals’ knowledge of BACS, including vulnerabilities and mitigation practices. Results indicate that the majority of security and facility professionals hold a general awareness of BACS security issues, although they lacked a robust understanding to meet necessary protection. For instance, understanding of 23 BACS vulnerabilities were found to be equally critical with limited variance. Mitigation strategies were no better, with respondents indicating poor threat diagnosis. In contrast, cybersecurity and technical security professionals such as integrators or security engineering design professionals displayed a robust understanding of BACS vulnerabilities and resulting mitigation strategies. Findings support the need for greater awareness for both security management and facility professionals of BACS vulnerabilities and mitigation strategies.