Petr Stluka

Industrial Cloud-Based Cyber-Physical Systems: The IMC-AESOP Approach

This book presents cutting-edge emerging technologies and approaches in the areas of service-oriented architectures, intelligent devices and cloud-based cyber-physical systems. It provides a clear view on their applicability to the management and automation of manufacturing and process industries. It offers a holistic view of future industrial cyber-physical systems and their industrial usage and also depicts technologies and architectures as well as a migration approach and engineering tools based on these. By providing a careful balance between the theory and the practical aspects, this book has been authored by several experts from academia and industry, thereby offering a valuable understanding of the vision, the domain, the processes and the results of the research. It has several illustrations and tables to clearly exemplify the concepts and results examined in the text and these are supported by four real-life case-studies. We are witnessing rapid advances in the industrial automation, mainly driven by business needs towards agility and supported by new disruptive advances both on the software and hardware side, as well as the cross-fertilization of concepts and the amalgamation of information and communication technology-driven approaches in traditional industrial automation and control systems. This book is intended for technology managers, application designers, solution developers, engineers working in industry, as well as researchers, undergraduate and graduate students of industrial automation, industrial informatics and production engineering.

Energy management for buildings and microgrids

Intelligent consumer energy management systems will become important elements at the delivery points of the smart grid inside homes, buildings, and industrial plants. The end users will be able to better monitor and manage their energy consumption, while utilities will gain more flexible mechanisms for management of peak demands that will extend beyond demand response initiatives as they are implemented today. With a broader use of distributed generation many buildings and campuses will become microgrids interconnecting multiple generation, storage, and consumption devices of one or several end users. We discuss how energy management and control for such facilities can be viewed as a large-scale optimization problem. Specific supply-side and demand-side aspects include on-site renewable generation, storage technologies, electric cars, dynamic pricing, and load management. Technical challenges related to the optimization formulation are noted - in general, mixed-integer, nonlinear, constrained optimization is needed. We also describe an implementation of optimization-based energy management solution for a hospital in the Netherlands, providing economic details and an analysis of the savings achieved.

A SOA-based architecture for empowering future collaborative cloud-based industrial automation

The last years we are witnessing of rapid advances in the industrial automation domain, mainly driven by business needs towards agility and supported by new disruptive technologies. Future factories will rely on multi-system interactions and collaborative cross-layer management and automation approaches. Such a factory, configured and managed from architectural and behavioural viewpoints, under the service-oriented architecture (SOA) paradigm is virtualized by services exposed by its key components (both HW and SW). One of the main results of this virtualization is that the factory is transformed into a “cloud of services”, where dynamic resource allocation and interactions take place. This paper presents a view on such architecture, its specification, the main motivation and considerations, as well as the preliminary services it may need to support.

Technologies for SOA-based distributed large scale process monitoring and control systems

In a SOA-based system the applications are organized in a manner such that interoperable services can be used from different domains. In a process industry context, different domains can refer to, for example, process instrumentation and monitoring, execution of process control, data acquisition, etc. Large process industry systems are a complex and potentially very large sets of multi-disciplinary, heterogeneous, networked distributed systems. Current industrial process control systems are typically vendor specific; in addition the different domains are associated with different layers, different standards and different technologies. In the paper the authors report about the investigations and assessments performed to find answers for four major critical questions that arise as key when technologies have to be selected and used in a true Service Oriented Architecture (SOA) based distributed large scale Process Monitoring and Control system: (1) Real-time SOA (what are the limits of bringing SOA into high performance control loops?); (2) Management of large scale industrial distributed control systems (is it feasible to manage up to tens of thousands of service-oriented devices?); (3) Distributed event-based systems are asynchronous (what are the limits compared to traditional periodic scanning systems?) and (4) Service specification (which semantics are the most suitable for specifying process control and monitoring services?).

Automated Demand Response for Smart Buildings and Microgrids: The State of the Practice and Research Challenges

Keeping up with growing electricity demand and ensuring reliable grid operation, as renewable sources reach a large proportion of generation, require end-use facilities-commercial, residential, and industrial-to be sensitive and responsive to grid connections in new ways. Automated demand response (ADR) is widely acknowledged as a key approach. The technology has progressed substantially since early implementations, with worldwide projects and a new standard. Recent applications with grid-integrated buildings and microgrids are extending the functionality, with increasing sophistication of how demand-side load profiles are managed and with integration of distributed storage and generation. This paper reviews the motivation for demand response (DR) and outlines the architectural models, technology infrastructure, and communication and control protocols that are currently in use. Four projects for commercial buildings and microgrids, in the United States, United Kingdom, and China, are described. We also point out limitations of the state of the practice that represent opportunities for research and development. Several research topics are noted, focusing on needs for modeling, optimization, and control, and some preliminary related work is discussed.

Advanced HVAC Control: Theory vs. Reality

Abstract Intelligent control of HVAC equipment is a key step towards improving the energy efficiency of commercial buildings. Although advanced control techniques have been developed and validated under real conditions, numerous buildings are still being poorly controlled due to wrong setpoints, incorrect PID settings, no coordination of individual PID loops, and other practical problems. This paper aims to summarize the major contributors to inefficient HVAC control and outline possible approaches towards better control strategies. Three areas are discussed: performance monitoring tools, rule-based control strategies and model-based predictive control (MPC). Performance monitoring tools help control engineers to quantify the performance of a particular control strategy, compare multiple control strategies among themselves, and define a baseline for such comparisons. Rule-based control strategies utilize various setpoint resets, rules and other heuristics to reduce HVAC energy consumption; however, such methods yield sub-optimal solutions only. Finally, MPC is a powerful and industrially-proven technology for optimal control of complex systems, but its use in building control seems to be so far limited. The paper analyzes challenges and constraints when implementing a control strategy in real projects, and covers topics such as missing sensors, legacy controllers and legislative changes needed to motivate building owners towards more efficient facility management.

Arrowhead compliant virtual market of energy

Industrial processes use energy to transform raw materials and intermediate goods into final products. Many efforts have been done on the minimization of energy costs in industrial plants. Apart from working on “how” an industrial process is implemented, it is possible to reduce the energy costs by focusing on “when” it is performed. Although, some manufacturing plants (e.g. refining or petrochemical plants) can be inflexible with respect to time due to interdependencies in processes that must be respected for performance and safety reasons, there are other industrial segments, such as alumina plants or discrete manufacturing, with more degrees of flexibility. These manufacturing plants can consider a more flexible scheduling of the most energy-intensive processes in response to dynamic prices and overall condition of the electricity market. In this scenario, requests for energy can be encoded by means of a formal structure called flex-offers, then aggregated (joining several flex-offers into a bigger one) and sent to the market, scheduled, disaggregated and transformed into consumption plans, and eventually, into production schedules for given industrial plant. In this paper, we describe the flex-offer concept and how it can be applied to industrial and home automation scenarios. The architecture proposed in this paper aims to be adaptable to multiples scenarios (industrial, home and building automation, etc.), thus providing the foundations for different concept implementations using multiple technologies or supporting various kinds of devices.

State of the Art in Industrial Automation

In the last decades, industrial automation has become a driving force in all production systems. Technologies and architectures have emerged alongside the growing organisational structures of production plants. Every innovation had to start from the latest state-of-the-art systems within the respective domain. While investigating the introduction of service-oriented architectures to automation, and even down to the shop floor, one has to consider latest standards, proofed technologies, industrial solutions and latest research works in the automation domain. This chapter tries, without any claim to completeness, to provide a short summary of today’s situation and trends in automation.

Fault Diagnosis of Air Handling Units

Abstract This paper presents an improved method for fault detection and diagnostics (FDD) of air handling units (AHUs). The fault detection module defines observable states of the AHU, where each state depends on current values of sensor data and control signals. The fault diagnostic module maps the observable states to the faults and then applies the cumulative sum chart (CUSUM) to define the size and development of each fault in time. The FDD method was tested on real datasets and its results were confirmed by the building technician. Finally, the method is compared with the standard APAR (AHU performance assessment rules) method developed by Schein et al.

Dynamic Alarm Management in Next Generation Process Control Systems

Current process control systems are composed of a large number of components and subsystems operating at different layers of the control system architecture model (i.e. measurement and control devices, Distributed Control Systems, Advanced Process Control systems, and Manufacturing Execution Systems). The IMC-AESOP project aims at designing the next generation architecture of process automation systems. In order to ensure system scalability and modularity, the new architectural design follows the SOA (Service-Oriented Architecture) design principles. Moreover, the design assumes adoption of various technologies with the aim to enable the control systems to meet all functional and performance requirements. The CEP (Complex Event Processing) technology has been selected for being able to provide efficient asynchronous communication (within and across architecture layers) and the capability of temporal reasoning over large amounts of system-generated events. This paper describes the intermediate results of the IMC-AESOP project, outlining the architectural concepts related to the use of the SOA and CEP technologies in the context of advanced alarm management applications - alarm load shedding and state-based alarming.