Pub Date : 2018-07-01DOI: 10.1109/INDIN.2018.8472000
Daniel Schachinger, W. Kastner
In building operation, the continuous forward planning of energy-efficient schedules to maintain user comfort is a challenging task. Although the design of building energy management systems is an active field of research, existing solutions are often faced with limited reusability due to specialization on certain buildings, comfort parameters, or building automation technologies. Thus, this work introduces a set of context-aware strategies that are generally applicable for the optimization in building energy management systems. For this purpose, machinereadable semantics of the building and the building automation system is exploited in order to design a heuristic approach. The aim is to reduce the optimization effort while targeting both energy efficiency and cross-domain comfort satisfaction on a building-independent level. An embedding of the proposed approach into common metaheuristics is described to provide a basis for further reuse. Finally, case studies are used for evaluation of a proof-of-concept implementation.
{"title":"Context-aware optimization strategies for universal application in smart building energy management","authors":"Daniel Schachinger, W. Kastner","doi":"10.1109/INDIN.2018.8472000","DOIUrl":"https://doi.org/10.1109/INDIN.2018.8472000","url":null,"abstract":"In building operation, the continuous forward planning of energy-efficient schedules to maintain user comfort is a challenging task. Although the design of building energy management systems is an active field of research, existing solutions are often faced with limited reusability due to specialization on certain buildings, comfort parameters, or building automation technologies. Thus, this work introduces a set of context-aware strategies that are generally applicable for the optimization in building energy management systems. For this purpose, machinereadable semantics of the building and the building automation system is exploited in order to design a heuristic approach. The aim is to reduce the optimization effort while targeting both energy efficiency and cross-domain comfort satisfaction on a building-independent level. An embedding of the proposed approach into common metaheuristics is described to provide a basis for further reuse. Finally, case studies are used for evaluation of a proof-of-concept implementation.","PeriodicalId":6467,"journal":{"name":"2018 IEEE 16th International Conference on Industrial Informatics (INDIN)","volume":"10 1","pages":"478-483"},"PeriodicalIF":0.0,"publicationDate":"2018-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"84092087","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2018-07-01DOI: 10.1109/INDIN.2018.8472085
A. Armentia, Elisabet Estévez-Estévez, D. Orive, M. Marcos
Global competition has resulted in changes on product demand which have to be managed by current manufacturing systems. In this context, modularity seems to be a suitable solution to provide manufacturing systems with the flexibility required to adapt to demand fluctuations when they occur, maintaining thus competitiveness and productivity. In concrete, machine modularity allows modifying a machine structure but it should be accomplished easily and rapidly. The current work proposes a model-driven methodology that allows modular machine definition and the automatic generation of the corresponding automation project, including the machine hardware configuration and its control software. It is based on the use of eXtensible Markup Language (XML) format and technologies for both model definition and code generation. The methodology has been implemented as a tool suite whose proof of concept has been developed for the particular case of the Siemens Totally Integrated Automation Portal (TIA Portal) PLC programming tool.
{"title":"A Tool Suite for Automatic Generation of Modular Machine Automation Projects","authors":"A. Armentia, Elisabet Estévez-Estévez, D. Orive, M. Marcos","doi":"10.1109/INDIN.2018.8472085","DOIUrl":"https://doi.org/10.1109/INDIN.2018.8472085","url":null,"abstract":"Global competition has resulted in changes on product demand which have to be managed by current manufacturing systems. In this context, modularity seems to be a suitable solution to provide manufacturing systems with the flexibility required to adapt to demand fluctuations when they occur, maintaining thus competitiveness and productivity. In concrete, machine modularity allows modifying a machine structure but it should be accomplished easily and rapidly. The current work proposes a model-driven methodology that allows modular machine definition and the automatic generation of the corresponding automation project, including the machine hardware configuration and its control software. It is based on the use of eXtensible Markup Language (XML) format and technologies for both model definition and code generation. The methodology has been implemented as a tool suite whose proof of concept has been developed for the particular case of the Siemens Totally Integrated Automation Portal (TIA Portal) PLC programming tool.","PeriodicalId":6467,"journal":{"name":"2018 IEEE 16th International Conference on Industrial Informatics (INDIN)","volume":"4 1","pages":"553-558"},"PeriodicalIF":0.0,"publicationDate":"2018-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"87891819","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2018-07-01DOI: 10.1109/INDIN.2018.8472017
Ricardo Silva Peres, A. Rocha, J. Matos-Carvalho, J. Barata
In the last decades, several research initiatives suggested new solutions regarding the interoperability and interconnectivity among heterogeneous production components and all the actors that somehow interact within the shop-floor. However, most of the proposed data representations are focused on the description of the production capabilities. In this paper, it is proposed a common data model focused not only in the production capabilities of the different components as well as the description of all the events, variables and resources that could indicate quality issues. Hence, the proposed data model describes all the information required by the GO0DMAN solution to reduce as much as possible, the defects, the respective causes and the strategies to avoid the propagation along the line. In order to increase the adoption of the proposed data model, it was developed using AutomationML. The proposed data model was designed and tested within the scope of the Horizon 2020 GO0DMAN project.
{"title":"GO0DMAN Data Model - Interoperability in Multistage Zero Defect Manufacturing","authors":"Ricardo Silva Peres, A. Rocha, J. Matos-Carvalho, J. Barata","doi":"10.1109/INDIN.2018.8472017","DOIUrl":"https://doi.org/10.1109/INDIN.2018.8472017","url":null,"abstract":"In the last decades, several research initiatives suggested new solutions regarding the interoperability and interconnectivity among heterogeneous production components and all the actors that somehow interact within the shop-floor. However, most of the proposed data representations are focused on the description of the production capabilities. In this paper, it is proposed a common data model focused not only in the production capabilities of the different components as well as the description of all the events, variables and resources that could indicate quality issues. Hence, the proposed data model describes all the information required by the GO0DMAN solution to reduce as much as possible, the defects, the respective causes and the strategies to avoid the propagation along the line. In order to increase the adoption of the proposed data model, it was developed using AutomationML. The proposed data model was designed and tested within the scope of the Horizon 2020 GO0DMAN project.","PeriodicalId":6467,"journal":{"name":"2018 IEEE 16th International Conference on Industrial Informatics (INDIN)","volume":"150 1","pages":"815-821"},"PeriodicalIF":0.0,"publicationDate":"2018-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"86660209","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2018-07-01DOI: 10.1109/INDIN.2018.8471966
Lucas Martinuzzo Batista, Diego Lucchil, F. M. Varejão, Alexandre Rodngues, F. Lima, Thiago Oliveira-Santos
Electric power distribution companies in Brazil assess the energy consumption of most of their costumers by reading the meters in loco. A human reader has an itinerary with clients that should be read on each working day. The number of meters per route tends to increase over time, as the number of customers is constantly growing. At a certain point, the route must be restructured so that it still runs in a single day. This paper proposes the use of clustering techniques integrated with community detection algorithms and a heuristic routing algorithm to solve the problem of globally restructuring the routes used by the readers of the energy distribution companies. Experimental results showed that the proposed method significantly reduced the number of routes required to perform the meters readings.
{"title":"Electricity Readers Routing Based on Clustering and Communities Detection","authors":"Lucas Martinuzzo Batista, Diego Lucchil, F. M. Varejão, Alexandre Rodngues, F. Lima, Thiago Oliveira-Santos","doi":"10.1109/INDIN.2018.8471966","DOIUrl":"https://doi.org/10.1109/INDIN.2018.8471966","url":null,"abstract":"Electric power distribution companies in Brazil assess the energy consumption of most of their costumers by reading the meters in loco. A human reader has an itinerary with clients that should be read on each working day. The number of meters per route tends to increase over time, as the number of customers is constantly growing. At a certain point, the route must be restructured so that it still runs in a single day. This paper proposes the use of clustering techniques integrated with community detection algorithms and a heuristic routing algorithm to solve the problem of globally restructuring the routes used by the readers of the energy distribution companies. Experimental results showed that the proposed method significantly reduced the number of routes required to perform the meters readings.","PeriodicalId":6467,"journal":{"name":"2018 IEEE 16th International Conference on Industrial Informatics (INDIN)","volume":"39 1","pages":"583-588"},"PeriodicalIF":0.0,"publicationDate":"2018-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"85911058","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2018-07-01DOI: 10.1109/INDIN.2018.8472061
Borja Ramis, Wael M. Mohammed, J. Lastra, Alberto Villalonga, Gerardo Beruvides, F. Castaño, R. Haber
Cyber-physical Systems (CPS) in industrial manufacturing facilities demand a continuous interaction with different and a large amount of distributed and networked computing nodes, devices and human operators. These systems are critical to ensure the quality of production and the safety of persons working at the shop floor level. Furthermore, this situation is similar in other domains, such as logistics that, in turn, are connected and affect the overall production efficiency. In this context, this article presents some key steps for integrating three pillars of CPS (production line, logistics and facilities) into the current smart manufacturing environments in order to adopt an industrial Cyber-Physical Systems of Systems (CPSoS) paradigm. The approach is focused on the integration in several digital functionalities in a cloud-based platform to allow a real time multiple devices interaction, data analytics/sharing and machine learning-based global reconfiguration to increase the management and optimization capabilities for increasing the quality of facility services, safety and energy efficiency and industrial productivity. Conceptually, isolated systems may enhance their capabilities by accessing to information of other systems. The approach introduces particular vision, main components, potential and challenges of the envisioned CPSoS. In addition, the description of one scenario for realizing the CPSoS vision is presented. The results herein presented will pave the way for the adoption of CPSoS that can be used as a pilot for further research on this emerging topic.
{"title":"Towards the Adoption of Cyber-Physical Systems of Systems Paradigm in Smart Manufacturing Environments","authors":"Borja Ramis, Wael M. Mohammed, J. Lastra, Alberto Villalonga, Gerardo Beruvides, F. Castaño, R. Haber","doi":"10.1109/INDIN.2018.8472061","DOIUrl":"https://doi.org/10.1109/INDIN.2018.8472061","url":null,"abstract":"Cyber-physical Systems (CPS) in industrial manufacturing facilities demand a continuous interaction with different and a large amount of distributed and networked computing nodes, devices and human operators. These systems are critical to ensure the quality of production and the safety of persons working at the shop floor level. Furthermore, this situation is similar in other domains, such as logistics that, in turn, are connected and affect the overall production efficiency. In this context, this article presents some key steps for integrating three pillars of CPS (production line, logistics and facilities) into the current smart manufacturing environments in order to adopt an industrial Cyber-Physical Systems of Systems (CPSoS) paradigm. The approach is focused on the integration in several digital functionalities in a cloud-based platform to allow a real time multiple devices interaction, data analytics/sharing and machine learning-based global reconfiguration to increase the management and optimization capabilities for increasing the quality of facility services, safety and energy efficiency and industrial productivity. Conceptually, isolated systems may enhance their capabilities by accessing to information of other systems. The approach introduces particular vision, main components, potential and challenges of the envisioned CPSoS. In addition, the description of one scenario for realizing the CPSoS vision is presented. The results herein presented will pave the way for the adoption of CPSoS that can be used as a pilot for further research on this emerging topic.","PeriodicalId":6467,"journal":{"name":"2018 IEEE 16th International Conference on Industrial Informatics (INDIN)","volume":"24 1","pages":"792-799"},"PeriodicalIF":0.0,"publicationDate":"2018-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"82119531","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2018-07-01DOI: 10.1109/INDIN.2018.8471942
S. Graziani, M. Xibilia
Deep Neural Network (DNN) based Soft Sensors (SSs) have been demonstrated as successful alternatives to other data-driven structures. Here, a dynamic DNN based SS is proposed for the estimation of the Research Octane Number (RON) for a Reformer Unit in a refinery. The SS is required to estimate the RON when the plant operates in two different working conditions. Nonlinear Finite Inputs Response (NFIR) models have been investigated. The regressors in the models have been selected according to a cross-correlation analysis between candidate inputs and the RON value. The performance of the proposed SSs has been compared with previously designed deep structures, based on different dynamic first level models, coupled with a fuzzy algorithm.
{"title":"Deep Structures for a Reformer Unit Soft Sensor","authors":"S. Graziani, M. Xibilia","doi":"10.1109/INDIN.2018.8471942","DOIUrl":"https://doi.org/10.1109/INDIN.2018.8471942","url":null,"abstract":"Deep Neural Network (DNN) based Soft Sensors (SSs) have been demonstrated as successful alternatives to other data-driven structures. Here, a dynamic DNN based SS is proposed for the estimation of the Research Octane Number (RON) for a Reformer Unit in a refinery. The SS is required to estimate the RON when the plant operates in two different working conditions. Nonlinear Finite Inputs Response (NFIR) models have been investigated. The regressors in the models have been selected according to a cross-correlation analysis between candidate inputs and the RON value. The performance of the proposed SSs has been compared with previously designed deep structures, based on different dynamic first level models, coupled with a fuzzy algorithm.","PeriodicalId":6467,"journal":{"name":"2018 IEEE 16th International Conference on Industrial Informatics (INDIN)","volume":"7 1","pages":"927-932"},"PeriodicalIF":0.0,"publicationDate":"2018-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"82133325","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2018-07-01DOI: 10.1109/INDIN.2018.8471961
E. Rokrok, M. Shafie‐khah, P. Siano, J. Catalão
Recent research works have demonstrated that providing ancillary services for future microgrids is a challenging task due to the lack of sufficient spinning reserves and high cost of storage devices. Therefore, an increasing attention has been given to demand response (DR) as an emerging source to provide the required reserve, especially in emergency operation of the system. This paper proposes a decentralized multi-agent based DR strategy to control the domestic demands during the emergency operation of the microgrid (MG). According to the proposed multi-agent based DR strategy, the domestic loads are grouped based on a predefined priority and are assigned to specific load agents. To implement the information sharing process among the load agents, the consensus strategy is used. Communications among the load agents as a challenging issue of multi-agent systems (MAS) is considered and the effect of communication time delay is investigated. Simulation studies have been carried out on the CIGRE benchmark microgrid with various microsources and domestic loads, showing the effectiveness of the proposed decentralized control scheme.
{"title":"Consensus-Based Demand-Side Participation in Smart Microgrid Emergency Operation","authors":"E. Rokrok, M. Shafie‐khah, P. Siano, J. Catalão","doi":"10.1109/INDIN.2018.8471961","DOIUrl":"https://doi.org/10.1109/INDIN.2018.8471961","url":null,"abstract":"Recent research works have demonstrated that providing ancillary services for future microgrids is a challenging task due to the lack of sufficient spinning reserves and high cost of storage devices. Therefore, an increasing attention has been given to demand response (DR) as an emerging source to provide the required reserve, especially in emergency operation of the system. This paper proposes a decentralized multi-agent based DR strategy to control the domestic demands during the emergency operation of the microgrid (MG). According to the proposed multi-agent based DR strategy, the domestic loads are grouped based on a predefined priority and are assigned to specific load agents. To implement the information sharing process among the load agents, the consensus strategy is used. Communications among the load agents as a challenging issue of multi-agent systems (MAS) is considered and the effect of communication time delay is investigated. Simulation studies have been carried out on the CIGRE benchmark microgrid with various microsources and domestic loads, showing the effectiveness of the proposed decentralized control scheme.","PeriodicalId":6467,"journal":{"name":"2018 IEEE 16th International Conference on Industrial Informatics (INDIN)","volume":"36 1","pages":"953-958"},"PeriodicalIF":0.0,"publicationDate":"2018-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"90078642","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2018-07-01DOI: 10.1109/INDIN.2018.8472076
H. Cherif, S. Tnani, J. Belhadj, A. R. Silva
In recent years, significant attention has been given to renewable energy integration within the context of water-energy nexus. Therefore, the present paper developed a methodology to design an autonomous micro- hydric/solar/eolic/battery system in Park of Covilhã, Portugal. Annual data of wind speed, solar irradiance and temperature are used. Afterwards, the components of the system and optimization objectives have been modelled. Based on a two- objective optimization, the present methodology combines loss of power supply probability and embodied energy. An optimal configuration has been put in place using a dynamic simulator and applying a controlled elitist genetic algorithm. Two study cases have been investigated in order to eco-size the system and evaluate the energetic potential in the park. The obtained results show that, in the first case, the PV/Wind/Battery system can provide more than 95% of the electric needs while in the second case, the micro hydric system can provide 100 % of the electric needs without the complementarity of solar and wind turbine sources (0% in the solar and wind energy output).
{"title":"Optimal sizing and technical evaluation of energy and water system based on micro-hydric solar and wind sources","authors":"H. Cherif, S. Tnani, J. Belhadj, A. R. Silva","doi":"10.1109/INDIN.2018.8472076","DOIUrl":"https://doi.org/10.1109/INDIN.2018.8472076","url":null,"abstract":"In recent years, significant attention has been given to renewable energy integration within the context of water-energy nexus. Therefore, the present paper developed a methodology to design an autonomous micro- hydric/solar/eolic/battery system in Park of Covilhã, Portugal. Annual data of wind speed, solar irradiance and temperature are used. Afterwards, the components of the system and optimization objectives have been modelled. Based on a two- objective optimization, the present methodology combines loss of power supply probability and embodied energy. An optimal configuration has been put in place using a dynamic simulator and applying a controlled elitist genetic algorithm. Two study cases have been investigated in order to eco-size the system and evaluate the energetic potential in the park. The obtained results show that, in the first case, the PV/Wind/Battery system can provide more than 95% of the electric needs while in the second case, the micro hydric system can provide 100 % of the electric needs without the complementarity of solar and wind turbine sources (0% in the solar and wind energy output).","PeriodicalId":6467,"journal":{"name":"2018 IEEE 16th International Conference on Industrial Informatics (INDIN)","volume":"9 1","pages":"1018-1023"},"PeriodicalIF":0.0,"publicationDate":"2018-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"82000905","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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