Pub Date : 2022-06-16DOI: 10.1109/ICAT54566.2022.9811202
Edina Omerovic, Edin Golubovic, T. Uzunović
The broader use of devices powered by rechargeable batteries, especially constrained embedded devices, makes the efficient Battery Management System (BMS) increasingly more important. The estimation accuracy of the amount of remaining charge in the battery is critical as it affects the device’s operation and reliability. For that reason, the estimation of state-of-charge (SoC) is considered one of the main functionalities of a BMS. However, SoC estimation remains a complex task that depends on a range of internal and external factors. Most traditional SoC estimation methods are either computationally complex, require special laboratory equipment or additional configuration efforts. In addition, most methods require continuous measurement of battery parameters, which, in turn, renders these methods not applicable to the class of constrained embedded devices. This paper aims to extend the Coulomb counting method to the class of duty-cycled energy-constrained devices by designing an algorithm that combines voltage-based evaluation and pre-recorded task power profiles to estimate the SoC. In addition, a setup for identifying the battery parameters and algorithm validation setup were also developed and described in the paper.
{"title":"State of Charge Estimation on Constrained Embedded Devices","authors":"Edina Omerovic, Edin Golubovic, T. Uzunović","doi":"10.1109/ICAT54566.2022.9811202","DOIUrl":"https://doi.org/10.1109/ICAT54566.2022.9811202","url":null,"abstract":"The broader use of devices powered by rechargeable batteries, especially constrained embedded devices, makes the efficient Battery Management System (BMS) increasingly more important. The estimation accuracy of the amount of remaining charge in the battery is critical as it affects the device’s operation and reliability. For that reason, the estimation of state-of-charge (SoC) is considered one of the main functionalities of a BMS. However, SoC estimation remains a complex task that depends on a range of internal and external factors. Most traditional SoC estimation methods are either computationally complex, require special laboratory equipment or additional configuration efforts. In addition, most methods require continuous measurement of battery parameters, which, in turn, renders these methods not applicable to the class of constrained embedded devices. This paper aims to extend the Coulomb counting method to the class of duty-cycled energy-constrained devices by designing an algorithm that combines voltage-based evaluation and pre-recorded task power profiles to estimate the SoC. In addition, a setup for identifying the battery parameters and algorithm validation setup were also developed and described in the paper.","PeriodicalId":414786,"journal":{"name":"2022 XXVIII International Conference on Information, Communication and Automation Technologies (ICAT)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-06-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123856934","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 : 2022-06-16DOI: 10.1109/ICAT54566.2022.9811138
J. Tousi, M. A. Khatib, N. Bajçinca
Utilizing demand response (DR) in industries reduces the need for expensive utilities like storage or backup plants and renders the electricity market more flexible for industrial sites. This paper proposes an MPC-based approach for such sites to respond online to ancillary service requests and participate in DR by controlling optimally the machine speeds of a production line. The optimization program we define can cope with a large number of machines within a line and run therefore efficiently online at a network level without requiring high-power computational resources. We demonstrate the significance of our approach on a beverage production line consisting of a filling machine, two labelers, one shrink packer, and several conveying belts connecting the production machines.
{"title":"Model predictive control of demand response for large scale production lines and networks","authors":"J. Tousi, M. A. Khatib, N. Bajçinca","doi":"10.1109/ICAT54566.2022.9811138","DOIUrl":"https://doi.org/10.1109/ICAT54566.2022.9811138","url":null,"abstract":"Utilizing demand response (DR) in industries reduces the need for expensive utilities like storage or backup plants and renders the electricity market more flexible for industrial sites. This paper proposes an MPC-based approach for such sites to respond online to ancillary service requests and participate in DR by controlling optimally the machine speeds of a production line. The optimization program we define can cope with a large number of machines within a line and run therefore efficiently online at a network level without requiring high-power computational resources. We demonstrate the significance of our approach on a beverage production line consisting of a filling machine, two labelers, one shrink packer, and several conveying belts connecting the production machines.","PeriodicalId":414786,"journal":{"name":"2022 XXVIII International Conference on Information, Communication and Automation Technologies (ICAT)","volume":"24 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-06-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123413160","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 : 2022-06-16DOI: 10.1109/ICAT54566.2022.9811133
Behzad Heydaryan, N. Bajçinca
Large industrial factories can actively participate in the energy market. This does not only provide flexibility for the electrical grids, but also may introduce auxiliary options to their primary business models. However, Demand Response stays usually in contradiction with the production goals. Supplementary revenue contracts with the energy suppliers may help here to balance resulting production losses, thereby revealing a necessity for a trade-off. In this sense, we suggest a concept of demand response utilizing model predictive control for optimal adjustment of the production rate. In particular, in our study we consider the production lines of beverage factories as a use-case.
{"title":"Economic Model Predictive Control of Industrial Demand Response","authors":"Behzad Heydaryan, N. Bajçinca","doi":"10.1109/ICAT54566.2022.9811133","DOIUrl":"https://doi.org/10.1109/ICAT54566.2022.9811133","url":null,"abstract":"Large industrial factories can actively participate in the energy market. This does not only provide flexibility for the electrical grids, but also may introduce auxiliary options to their primary business models. However, Demand Response stays usually in contradiction with the production goals. Supplementary revenue contracts with the energy suppliers may help here to balance resulting production losses, thereby revealing a necessity for a trade-off. In this sense, we suggest a concept of demand response utilizing model predictive control for optimal adjustment of the production rate. In particular, in our study we consider the production lines of beverage factories as a use-case.","PeriodicalId":414786,"journal":{"name":"2022 XXVIII International Conference on Information, Communication and Automation Technologies (ICAT)","volume":"01 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-06-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134041445","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 : 2022-06-16DOI: 10.1109/ICAT54566.2022.9811195
Tobias Schürmann, Nils Kutter, S. Schwab, S. Hohmann
In the recent decades, the complexity of the auto-motive power network (APN) has been steadily increasing. This growing complexity is due to the electrification of former mechanical components and the increasing integration of telecommunication and entertainment devices. Additionally, autonomous driving functionalities lead to safety requirements that have to be met by the power supply infrastructure. Another challenge is the deviation in update cycles of the vehicle platform and the entertainment and telecommunication components. Thus, a modular and flexible power network management which allows for plug-and-play integration of new components is needed. In a previous contribution, we presented an auction-based approach for a modular load management in modern vehicles with multiple voltage levels. In this paper, we extend this basic approach by predictive measures in order to exploit flexible load capabilities by load shifting or load shaping. This leads to mitigated power peaks in the APN. As a result, the strain on the battery storage can be reduced and the forced deactivation of comfort components can be prevented. We demonstrate the working principle in a simulative study and show the effectiveness of the combination between the basic auction-based load management and the predictive extension introduced in this paper.
{"title":"Mitigating Power Peaks in Automotive Power Networks by Exploitation of Flexible Loads","authors":"Tobias Schürmann, Nils Kutter, S. Schwab, S. Hohmann","doi":"10.1109/ICAT54566.2022.9811195","DOIUrl":"https://doi.org/10.1109/ICAT54566.2022.9811195","url":null,"abstract":"In the recent decades, the complexity of the auto-motive power network (APN) has been steadily increasing. This growing complexity is due to the electrification of former mechanical components and the increasing integration of telecommunication and entertainment devices. Additionally, autonomous driving functionalities lead to safety requirements that have to be met by the power supply infrastructure. Another challenge is the deviation in update cycles of the vehicle platform and the entertainment and telecommunication components. Thus, a modular and flexible power network management which allows for plug-and-play integration of new components is needed. In a previous contribution, we presented an auction-based approach for a modular load management in modern vehicles with multiple voltage levels. In this paper, we extend this basic approach by predictive measures in order to exploit flexible load capabilities by load shifting or load shaping. This leads to mitigated power peaks in the APN. As a result, the strain on the battery storage can be reduced and the forced deactivation of comfort components can be prevented. We demonstrate the working principle in a simulative study and show the effectiveness of the combination between the basic auction-based load management and the predictive extension introduced in this paper.","PeriodicalId":414786,"journal":{"name":"2022 XXVIII International Conference on Information, Communication and Automation Technologies (ICAT)","volume":"358 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-06-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115874896","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 : 2022-06-16DOI: 10.1109/ICAT54566.2022.9811184
Nermin Colo, S. Huseinbegović, I. Džafić
The Advanced Distribution Management System (ADMS) has grown to be a highly complicated system that comprises distribution generation, batteries, power electronics, and, in case of an urban area, an electric transportation system. One of the most essential features of ADMS is maintaining node voltages and branch thermal ratings within defined limits while maintaining minimal system losses and maximizing the use of renewable energy. Voltage VAr control (VVC) is extensively used to address these challenges and is becoming increasingly significant in ADMS. A side from the necessity to manage the system status, VVC must be adaptable to accommodate future Smart City (SC) requirements such as electric-vehicle charging and energy recuperation management. The majority of existing systems control the DC electric transportation system separately from the entire AC system. This paper attempts to tackle the problem using a hybrid single model that incorporates both: AC and DC network components.
{"title":"Volt-Var Control for Smart Cities with Integrated Public Transportation System","authors":"Nermin Colo, S. Huseinbegović, I. Džafić","doi":"10.1109/ICAT54566.2022.9811184","DOIUrl":"https://doi.org/10.1109/ICAT54566.2022.9811184","url":null,"abstract":"The Advanced Distribution Management System (ADMS) has grown to be a highly complicated system that comprises distribution generation, batteries, power electronics, and, in case of an urban area, an electric transportation system. One of the most essential features of ADMS is maintaining node voltages and branch thermal ratings within defined limits while maintaining minimal system losses and maximizing the use of renewable energy. Voltage VAr control (VVC) is extensively used to address these challenges and is becoming increasingly significant in ADMS. A side from the necessity to manage the system status, VVC must be adaptable to accommodate future Smart City (SC) requirements such as electric-vehicle charging and energy recuperation management. The majority of existing systems control the DC electric transportation system separately from the entire AC system. This paper attempts to tackle the problem using a hybrid single model that incorporates both: AC and DC network components.","PeriodicalId":414786,"journal":{"name":"2022 XXVIII International Conference on Information, Communication and Automation Technologies (ICAT)","volume":"275 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-06-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115887760","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 : 2022-05-13DOI: 10.1109/icat54566.2022.9811119
{"title":"ICAT 2022 Cover Page","authors":"","doi":"10.1109/icat54566.2022.9811119","DOIUrl":"https://doi.org/10.1109/icat54566.2022.9811119","url":null,"abstract":"","PeriodicalId":414786,"journal":{"name":"2022 XXVIII International Conference on Information, Communication and Automation Technologies (ICAT)","volume":"15 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-05-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124324797","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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