scholarly journals Getting Municipal Energy Management Systems ISO 50001 Certified: A Study with 28 European Municipalities

2021 ◽  
Vol 13 (7) ◽  
pp. 3638
Author(s):  
Jan Kaselofsky ◽  
Marika Rošā ◽  
Anda Jekabsone ◽  
Solenne Favre ◽  
Gabriel Loustalot ◽  
...  
Keyword(s):  
Climate Policy ◽  
Energy Management ◽  
Energy Use ◽  
Resource Constraints ◽  
Lessons Learned ◽  
Management Systems ◽  
Local Energy ◽  
Organizational Challenges ◽  
Energy Management Systems ◽  
Energy And Climate Policy

Managing energy use by municipalities should be an important part of local energy and climate policy. The ISO 50001 standard constitutes an internationally recognized catalogue of requirements for systematic energy management. Currently, this standard is mostly implemented by companies. Our study presents an approach where consultants supported 28 European municipalities in establishing energy management systems. A majority (71%) of these municipalities had achieved ISO 50001 certification by the end of our study. We also conducted two surveys to learn more about motivations and challenges when it comes to establishing municipal energy management systems. We found that organizational challenges and resource constraints were the most important topics in this regard. Based on the experiences in our study we present lessons learned regarding supporting municipalities in establishing energy management systems.

scholarly journals Ambient intelligence for optimal manufacturing and energy efficiency

2015 ◽  
Vol 35 (3) ◽  
pp. 234-248 ◽  
Author(s):  
David Charles Robinson ◽  
David Adrian Sanders ◽  
Ebrahim Mazharsolook
Keyword(s):  
Energy Efficiency ◽  
Energy Consumption ◽  
Energy Management ◽  
Ambient Intelligence ◽  
Energy Use ◽  
Management Systems ◽  
Content Type ◽  
Energy Management Systems ◽  
Knowledge Based ◽  
Comprehensive Information

Purpose – This paper aims to describe the creation of innovative and intelligent systems to optimise energy efficiency in manufacturing. The systems monitor energy consumption using ambient intelligence (AmI) and knowledge management (KM) technologies. Together they create a decision support system as an innovative add-on to currently used energy management systems. Design/methodology/approach – Energy consumption data (ECD) are processed within a service-oriented architecture-based platform. The platform provides condition-based energy consumption warning, online diagnostics of energy-related problems, support to manufacturing process lines installation and ramp-up phase and continuous improvement/optimisation of energy efficiency. The systems monitor energy consumption using AmI and KM technologies. Together they create a decision support system as an innovative add-on to currently used energy management systems. Findings – The systems produce an improvement in energy efficiency in manufacturing small- and medium-sized enterprises (SMEs). The systems provide more comprehensive information about energy use and some knowledge-based support. Research limitations/implications – Prototype systems were trialled in a manufacturing company that produces mooring chains for the offshore oil and gas industry, an energy intensive manufacturing operation. The paper describes a case study involving energy-intensive processes that addressed different manufacturing concepts and involved the manufacture of mooring chains for offshore platforms. The system was developed to support online detection of energy efficiency problems. Practical implications – Energy efficiency can be optimised in assembly and manufacturing processes. The systems produce an improvement in energy efficiency in manufacturing SMEs. The systems provide more comprehensive information about energy use and some knowledge-based support. Social implications – This research addresses two of the most critical problems in energy management in industrial production technologies: how to efficiently and promptly acquire and provide information online for optimising energy consumption and how to effectively use such knowledge to support decision making. Originality/value – This research was inspired by the need for industry to have effective tools for energy efficiency, and that opportunities for industry to take up energy efficiency measures are mostly not carried out. The research combined AmI and KM technologies and involved new uses of sensors, including wireless intelligent sensor networks, to measure environment parameters and conditions as well as to process performance and behaviour aspects, such as material flow using smart tags in highly flexible manufacturing or temperature distribution over machines. The information obtained could be correlated with standard ECD to monitor energy efficiency and identify problems. The new approach can provide effective ways to collect more information to give a new insight into energy consumption within a manufacturing system.

scholarly journals Design and development of IIoT-based system for behavior profiling of nonlinear dynamic production systems based on energy flow theory

2021 ◽  
pp. 228-228
Author(s):  
Milovan Medojevic ◽  
Branislav Tejic ◽  
Milana Medojevic ◽  
Miroslav Kljajic
Keyword(s):  
Energy Consumption ◽  
Energy Management ◽  
Nonlinear Dynamic ◽  
Energy Use ◽  
Production Systems ◽  
Fast Response ◽  
Management Systems ◽  
System Behavior ◽  
Energy Management Systems ◽  
Behavior Profiling

In this paper, a solution to effective energy consumption monitoring of fast-response energy systems in industrial environments was proposed, designed, and developed. Moreover, in this research, production systems are characterized as nonlinear dynamic systems, with the hypothesis that the identification and introduction of nonlinear members (variables) can have a significant impact on improving system performance by providing clear insight and realistic representation of system behavior due to a series of nonlinear activities that stimulate the system state changes, which can be spotted through the manner and intensity of energy use in the observed system. The research is oriented towards achieving favorable conditions to deploy dynamic energy management systems by means of the Internet of Things and Big Data, as highly prominent concepts of Industry 4.0 technologies into scientifically-driven industrial practice. The motivation behind this is driven by the transition that this highly digital modern age brought upon us, in which energy management systems could be treated as a continual, dynamic process instead of remaining characterized as static with periodical system audits. In addition, a segmented system architecture of the proposed solution was described in detail, while initial experimental results justified the given hypothesis. The generated results indicated that the process of energy consumption quantification, not only ensures reliable, accurate, and real-time information but opens the door towards system behavior profiling, predictive maintenance, event forensics, data-driven prognostics, etc. Lastly, the points of future investigations were indicated as well.

scholarly journals Scalable Local Energy Management Systems

2017 ◽  
Vol 142 ◽  
pp. 3069-3074 ◽  
Author(s):  
Amir Javed ◽  
Omer F. Rana ◽  
Liana M. Cipcigan ◽  
Charalampos Marmaras
Keyword(s):  
Energy Management ◽  
Management Systems ◽  
Local Energy ◽  
Energy Management Systems
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