Smart Sustainable Freight Transport for a City Multi-Floor Manufacturing Cluster: A Framework of the Energy Efficiency Monitoring of Electric Vehicle Fleet Charging
This study focuses on the problem of the efficient energy management of an independent fleet of freight electric vehicles (EVs) providing service to a city multi-floor manufacturing cluster (CMFMC) within a metropolis while considering the requirements of smart sustainable electromobility and the li...
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| Format: | Article |
| Language: | English |
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MDPI AG
2022-05-01
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| Series: | Energies |
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| Online Access: | https://www.mdpi.com/1996-1073/15/10/3780 |
| _version_ | 1827669208687706112 |
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| author | Liudmyla Davydenko Nina Davydenko Andrii Bosak Alla Bosak Agnieszka Deja Tygran Dzhuguryan |
| author_facet | Liudmyla Davydenko Nina Davydenko Andrii Bosak Alla Bosak Agnieszka Deja Tygran Dzhuguryan |
| author_sort | Liudmyla Davydenko |
| collection | DOAJ |
| description | This study focuses on the problem of the efficient energy management of an independent fleet of freight electric vehicles (EVs) providing service to a city multi-floor manufacturing cluster (CMFMC) within a metropolis while considering the requirements of smart sustainable electromobility and the limitations of the power system. The energy efficiency monitoring system is considered an information support tool for the management process. An object-oriented formalization of monitoring information technology is proposed which has a block structure and contains three categories of classes (information acquisition, calculation algorithms, and control procedures). An example of the implementation of the class “Operation with the electrical grid” of information technology is presented. The planning of the freight EVs charging under power limits of the charging station (CS) was carried out using a situational algorithm based on a Fuzzy expert system. The situational algorithm provides for monitoring the charging of a freight EV at a charging station, taking into account the charge weight index (CWI) assigned to it. The optimization of the CS electrical load is carried out from the standpoint of minimizing electricity costs and ensuring the demand for EV charging without going beyond its limits. A computer simulation of the EV charging mode and the CS load was performed. The results of modeling the electrical grid and CS load using the proposed algorithm were compared with the results of modeling using a controlled charging algorithm with electrical grid limitations and an uncontrolled charging algorithm. The proposed approach provides a reduction in power consumption during peak hours of the electrical grid and charging of connected EVs for an on-demand state of charge (SOC). |
| first_indexed | 2024-03-10T03:57:14Z |
| format | Article |
| id | doaj.art-9a27fe26654744388417629bdd16b8ad |
| institution | Directory Open Access Journal |
| issn | 1996-1073 |
| language | English |
| last_indexed | 2024-03-10T03:57:14Z |
| publishDate | 2022-05-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Energies |
| spelling | doaj.art-9a27fe26654744388417629bdd16b8ad2023-11-23T10:53:02ZengMDPI AGEnergies1996-10732022-05-011510378010.3390/en15103780Smart Sustainable Freight Transport for a City Multi-Floor Manufacturing Cluster: A Framework of the Energy Efficiency Monitoring of Electric Vehicle Fleet ChargingLiudmyla Davydenko0Nina Davydenko1Andrii Bosak2Alla Bosak3Agnieszka Deja4Tygran Dzhuguryan5Department of Electrical Engineering, Faculty of Architecture, Civil Engineering and Design, Lutsk National Technical University, 75 Lvivska Street, 43018 Lutsk, UkraineDepartment of Electrical Engineering, Faculty of Architecture, Civil Engineering and Design, Lutsk National Technical University, 75 Lvivska Street, 43018 Lutsk, UkraineDepartment of Automation of Electrical and Mechatronic Complexes, Educational and Research Institute of Energy Saving and Energy Management, National Technical University of Ukraine “Igor Sikorsky Kyiv Polytechnic Institute”, 115 Borshchahivska Street, 03056 Kyiv, UkraineDepartment of Automation of Electrical and Mechatronic Complexes, Educational and Research Institute of Energy Saving and Energy Management, National Technical University of Ukraine “Igor Sikorsky Kyiv Polytechnic Institute”, 115 Borshchahivska Street, 03056 Kyiv, UkraineFaculty of Economics and Transport Engineering, Maritime University of Szczecin, 1/2 Wały Chrobrego Street, 70-507 Szczecin, PolandFaculty of Economics and Transport Engineering, Maritime University of Szczecin, 1/2 Wały Chrobrego Street, 70-507 Szczecin, PolandThis study focuses on the problem of the efficient energy management of an independent fleet of freight electric vehicles (EVs) providing service to a city multi-floor manufacturing cluster (CMFMC) within a metropolis while considering the requirements of smart sustainable electromobility and the limitations of the power system. The energy efficiency monitoring system is considered an information support tool for the management process. An object-oriented formalization of monitoring information technology is proposed which has a block structure and contains three categories of classes (information acquisition, calculation algorithms, and control procedures). An example of the implementation of the class “Operation with the electrical grid” of information technology is presented. The planning of the freight EVs charging under power limits of the charging station (CS) was carried out using a situational algorithm based on a Fuzzy expert system. The situational algorithm provides for monitoring the charging of a freight EV at a charging station, taking into account the charge weight index (CWI) assigned to it. The optimization of the CS electrical load is carried out from the standpoint of minimizing electricity costs and ensuring the demand for EV charging without going beyond its limits. A computer simulation of the EV charging mode and the CS load was performed. The results of modeling the electrical grid and CS load using the proposed algorithm were compared with the results of modeling using a controlled charging algorithm with electrical grid limitations and an uncontrolled charging algorithm. The proposed approach provides a reduction in power consumption during peak hours of the electrical grid and charging of connected EVs for an on-demand state of charge (SOC).https://www.mdpi.com/1996-1073/15/10/3780city multi-floor manufacturing clustersmart sustainable cityelectric vehicle fleetsmart energy managementenergy efficiency monitoringstate of charge |
| spellingShingle | Liudmyla Davydenko Nina Davydenko Andrii Bosak Alla Bosak Agnieszka Deja Tygran Dzhuguryan Smart Sustainable Freight Transport for a City Multi-Floor Manufacturing Cluster: A Framework of the Energy Efficiency Monitoring of Electric Vehicle Fleet Charging Energies city multi-floor manufacturing cluster smart sustainable city electric vehicle fleet smart energy management energy efficiency monitoring state of charge |
| title | Smart Sustainable Freight Transport for a City Multi-Floor Manufacturing Cluster: A Framework of the Energy Efficiency Monitoring of Electric Vehicle Fleet Charging |
| title_full | Smart Sustainable Freight Transport for a City Multi-Floor Manufacturing Cluster: A Framework of the Energy Efficiency Monitoring of Electric Vehicle Fleet Charging |
| title_fullStr | Smart Sustainable Freight Transport for a City Multi-Floor Manufacturing Cluster: A Framework of the Energy Efficiency Monitoring of Electric Vehicle Fleet Charging |
| title_full_unstemmed | Smart Sustainable Freight Transport for a City Multi-Floor Manufacturing Cluster: A Framework of the Energy Efficiency Monitoring of Electric Vehicle Fleet Charging |
| title_short | Smart Sustainable Freight Transport for a City Multi-Floor Manufacturing Cluster: A Framework of the Energy Efficiency Monitoring of Electric Vehicle Fleet Charging |
| title_sort | smart sustainable freight transport for a city multi floor manufacturing cluster a framework of the energy efficiency monitoring of electric vehicle fleet charging |
| topic | city multi-floor manufacturing cluster smart sustainable city electric vehicle fleet smart energy management energy efficiency monitoring state of charge |
| url | https://www.mdpi.com/1996-1073/15/10/3780 |
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