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\n  \n 2023\n \n \n (2)\n \n \n
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\n \n\n \n \n \n \n \n \n Version [OpenIPSL 2.0.0] - [iTesla Power Systems Library (iPSL): A Modelica library for phasor time-domain simulations].\n \n \n \n \n\n\n \n de Castro, M.; Winkler, D.; Laera, G.; Vanfretti, L.; Dorado-Rojas, S., A.; Rabuzin, T.; Mukherjee, B.; and Manuel, N.\n\n\n \n\n\n\n SoftwareX, 21. 2023.\n \n\n\n\n
\n\n\n\n \n \n \"VersionWebsite\n  \n \n\n \n \n doi\n  \n \n\n \n link\n  \n \n\n bibtex\n \n\n \n  \n \n abstract \n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n \n \n \n \n \n \n \n \n \n \n\n\n\n
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@article{\n title = {Version [OpenIPSL 2.0.0] - [iTesla Power Systems Library (iPSL): A Modelica library for phasor time-domain simulations]},\n type = {article},\n year = {2023},\n keywords = {Modelica,Power system dynamics.,Power system modeling,Power systems,Simulation},\n volume = {21},\n websites = {https://doi.org/10.1016/j.softx.2022.101277},\n id = {6322aa11-a733-3756-948a-ce38782ca030},\n created = {2022-12-08T13:06:55.186Z},\n file_attached = {false},\n profile_id = {b148566c-bc4a-3e6b-bcd9-eb0286561c6f},\n last_modified = {2022-12-08T13:11:40.657Z},\n read = {false},\n starred = {false},\n authored = {true},\n confirmed = {true},\n hidden = {false},\n private_publication = {false},\n abstract = {© 2023 ELSEVIER. This paper describes Open-Instance Power System Library (OpenIPSL) version 2.0.0 and its most recent enhancements. This new version brings upgrades that include more robust models that are better documented, and example systems that illustrate certain functionalities to users. Repository and library documentations have been enhanced and expanded, and the library is now released under a new license. Changes are meant to foster user and developer communities, while providing more attractive frameworks for collaborative work to be carried out with the library.},\n bibtype = {article},\n author = {de Castro, Marcelo and Winkler, Dietmar and Laera, Giuseppe and Vanfretti, Luigi and Dorado-Rojas, Sergio A. and Rabuzin, Tin and Mukherjee, Biswarup and Manuel, Navarro.},\n doi = {https://doi.org/10.1016/j.softx.2022.101277},\n journal = {SoftwareX}\n}
\n
\n\n\n
\n © 2023 ELSEVIER. This paper describes Open-Instance Power System Library (OpenIPSL) version 2.0.0 and its most recent enhancements. This new version brings upgrades that include more robust models that are better documented, and example systems that illustrate certain functionalities to users. Repository and library documentations have been enhanced and expanded, and the library is now released under a new license. Changes are meant to foster user and developer communities, while providing more attractive frameworks for collaborative work to be carried out with the library.\n
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\n \n\n \n \n \n \n \n \n Optimized Planning of Chargers for Electric Vehicles in Distribution Grids Including PV Self-consumption and Cooperative Vehicle Owners.\n \n \n \n \n\n\n \n Mukherjee, B.; and Sossan, F.\n\n\n \n\n\n\n Energy Conversion and Economics,1-11. 2023.\n \n\n\n\n
\n\n\n\n \n \n \"OptimizedPaper\n  \n \n\n \n \n doi\n  \n \n\n \n link\n  \n \n\n bibtex\n \n\n \n  \n \n abstract \n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n \n \n \n \n \n \n \n \n\n\n\n
\n
@article{\n title = {Optimized Planning of Chargers for Electric Vehicles in Distribution Grids Including PV Self-consumption and Cooperative Vehicle Owners},\n type = {article},\n year = {2023},\n keywords = {Charging stations,Electric vehicles,PV self-consumption,Siting},\n pages = {1-11},\n id = {5419f96a-167b-38bc-a656-b9f81ea6347d},\n created = {2023-02-21T11:29:39.010Z},\n file_attached = {true},\n profile_id = {b148566c-bc4a-3e6b-bcd9-eb0286561c6f},\n last_modified = {2023-02-21T13:07:49.513Z},\n read = {false},\n starred = {false},\n authored = {true},\n confirmed = {true},\n hidden = {false},\n private_publication = {false},\n abstract = {© 2023 IET. This paper presents a mathematical model to site and size the charging infrastructure for electric vehicles (EVs) in a distribution grid to minimize the required capital investments and maximize self-consumption of local PV generation jointly. The formulation accounts for the operational constraints of the distribution grid (nodal voltages, line currents, and transformers' ratings) and the recharging times of the EVs. It explicitly models the EV owners' flexibility in plugging and unplugging their vehicles to and from a charger to enable optimal utilization of the charging infrastructure and improve self-consumption (cooperative EV owners). The problem is formulated as a mixed-integer linear program (MILP), where nonlinear grid constraints are approximated with linearized grid models.},\n bibtype = {article},\n author = {Mukherjee, Biswarup and Sossan, Fabrizio},\n doi = {10.1049/enc2.12080},\n journal = {Energy Conversion and Economics}\n}
\n
\n\n\n
\n © 2023 IET. This paper presents a mathematical model to site and size the charging infrastructure for electric vehicles (EVs) in a distribution grid to minimize the required capital investments and maximize self-consumption of local PV generation jointly. The formulation accounts for the operational constraints of the distribution grid (nodal voltages, line currents, and transformers' ratings) and the recharging times of the EVs. It explicitly models the EV owners' flexibility in plugging and unplugging their vehicles to and from a charger to enable optimal utilization of the charging infrastructure and improve self-consumption (cooperative EV owners). The problem is formulated as a mixed-integer linear program (MILP), where nonlinear grid constraints are approximated with linearized grid models.\n
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\n  \n 2022\n \n \n (1)\n \n \n
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\n \n\n \n \n \n \n \n \n Optimal Planning of Single-Port and Multi-Port Charging Stations for Electric Vehicles in Medium Voltage Distribution Networks.\n \n \n \n \n\n\n \n Mukherjee, B.; and Sossan, F.\n\n\n \n\n\n\n IEEE Transactions on Smart Grid. 2022.\n \n\n\n\n
\n\n\n\n \n \n \"OptimalWebsite\n  \n \n\n \n \n doi\n  \n \n\n \n link\n  \n \n\n bibtex\n \n\n \n  \n \n abstract \n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n\n\n\n
\n
@article{\n title = {Optimal Planning of Single-Port and Multi-Port Charging Stations for Electric Vehicles in Medium Voltage Distribution Networks},\n type = {article},\n year = {2022},\n keywords = {Charging stations,Distribution networks,EVs,Optimal power flow,multi-port chargers,single-port chargers.},\n websites = {https://ieeexplore.ieee.org/document/9877870},\n id = {4d7800cd-1d9a-3d22-bdf5-61075e7dd154},\n created = {2022-09-06T11:57:32.445Z},\n file_attached = {false},\n profile_id = {b148566c-bc4a-3e6b-bcd9-eb0286561c6f},\n last_modified = {2022-09-08T22:10:20.657Z},\n read = {false},\n starred = {false},\n authored = {true},\n confirmed = {true},\n hidden = {false},\n private_publication = {false},\n abstract = {© 2022 IEEE. This paper describes a method to cost-optimally locate and size chargers for electric vehicles (EVs) in power distribution grids as a function of the driving demand while respecting the grid’s constraints. The problem accounts for the notion of single-port chargers (SPCs), where a charger can interface one EV maximum, and multi-port chargers (MPCs), where the same charger can interface multiple EVs, leading to possible cost savings and improved arbitrage of the charging power. The formulation is capable of accounting for and modeling the flexibility of EV owners’ in plugging and unplugging their EVs from and to chargers at different hours of the day, a factor that can impact chargers’ utilization and thus charging infrastructure requirements. Simulation results from a synthetic case study show that implementing MPCs is cost-beneficial over both SPCs and owners’ flexibility for EVs with small batteries (16 kWh). However, this cost benefit vanishes when considering EVs with larger batteries (60 kWh).},\n bibtype = {article},\n author = {Mukherjee, Biswarup and Sossan, Fabrizio},\n doi = {10.1109/TSG.2022.3204150},\n journal = {IEEE Transactions on Smart Grid}\n}
\n
\n\n\n
\n © 2022 IEEE. This paper describes a method to cost-optimally locate and size chargers for electric vehicles (EVs) in power distribution grids as a function of the driving demand while respecting the grid’s constraints. The problem accounts for the notion of single-port chargers (SPCs), where a charger can interface one EV maximum, and multi-port chargers (MPCs), where the same charger can interface multiple EVs, leading to possible cost savings and improved arbitrage of the charging power. The formulation is capable of accounting for and modeling the flexibility of EV owners’ in plugging and unplugging their EVs from and to chargers at different hours of the day, a factor that can impact chargers’ utilization and thus charging infrastructure requirements. Simulation results from a synthetic case study show that implementing MPCs is cost-beneficial over both SPCs and owners’ flexibility for EVs with small batteries (16 kWh). However, this cost benefit vanishes when considering EVs with larger batteries (60 kWh).\n
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\n  \n 2021\n \n \n (3)\n \n \n
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\n \n\n \n \n \n \n \n \n A PMU-Based Control Scheme for Islanded Operation and Re-synchronization of DER.\n \n \n \n \n\n\n \n Mukherjee, B.; De Castro Fernandes, M.; and Vanfretti, L.\n\n\n \n\n\n\n International Journal of Electrical Power & Energy Systems, 133: 107217. 2021.\n \n\n\n\n
\n\n\n\n \n \n \"APaper\n  \n \n \n \"AWebsite\n  \n \n\n \n \n doi\n  \n \n\n \n link\n  \n \n\n bibtex\n \n\n \n  \n \n abstract \n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n\n\n\n
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@article{\n title = {A PMU-Based Control Scheme for Islanded Operation and Re-synchronization of DER},\n type = {article},\n year = {2021},\n keywords = {Controlled islanding,Island operation,Modelica,OpenIPSL,Power grid DER,Power systems modeling PMU,Re-synchronization},\n pages = {107217},\n volume = {133},\n websites = {https://doi.org/10.1016/j.ijepes.2021.107217},\n id = {40d66d30-eb13-30bf-8208-d1271cb228dd},\n created = {2021-06-29T06:39:01.266Z},\n file_attached = {true},\n profile_id = {b148566c-bc4a-3e6b-bcd9-eb0286561c6f},\n last_modified = {2021-10-30T22:20:20.155Z},\n read = {false},\n starred = {false},\n authored = {true},\n confirmed = {true},\n hidden = {false},\n private_publication = {false},\n abstract = {© 2021 ELSEVIER. This article proposes a novel synchrophasor-based control scheme enabling controlled islanding, islanded operation and automatic re-synchronization of a distributed energy resource (DER) in a distribution network. The performance of the proposed control system is studied using a test power system model. The DER controller uses a centralized architecture, receiving phasor measurement unit (PMU) measurements from both the transmission and distribution grids. In simulation, the frequency control function inside the proposed controller uses frequency estimates calculated using a new formula that exploits the bus voltage in rectangular form (real and imaginary values). The performance of the proposed frequency computation method is studied and compared with the conventional washout filter (WF) approach used by most power system software tools. The study also discusses why unwrapped bus angles are necessary to perform the automatic re-synchronization process. The performance of the proposed controller is evaluated using both deterministic and stochastic load models, allowing the assessment of variability in distribution grids. The implementation of the proposed control scheme and the simulation of the test system is carried out leveraging rich features of Modelica language and the Open-Instance Power System Library (OpenIPSL).},\n bibtype = {article},\n author = {Mukherjee, Biswarup and De Castro Fernandes, Marcelo and Vanfretti, Luigi},\n doi = {10.1016/j.ijepes.2021.107217},\n journal = {International Journal of Electrical Power & Energy Systems}\n}
\n
\n\n\n
\n © 2021 ELSEVIER. This article proposes a novel synchrophasor-based control scheme enabling controlled islanding, islanded operation and automatic re-synchronization of a distributed energy resource (DER) in a distribution network. The performance of the proposed control system is studied using a test power system model. The DER controller uses a centralized architecture, receiving phasor measurement unit (PMU) measurements from both the transmission and distribution grids. In simulation, the frequency control function inside the proposed controller uses frequency estimates calculated using a new formula that exploits the bus voltage in rectangular form (real and imaginary values). The performance of the proposed frequency computation method is studied and compared with the conventional washout filter (WF) approach used by most power system software tools. The study also discusses why unwrapped bus angles are necessary to perform the automatic re-synchronization process. The performance of the proposed controller is evaluated using both deterministic and stochastic load models, allowing the assessment of variability in distribution grids. The implementation of the proposed control scheme and the simulation of the test system is carried out leveraging rich features of Modelica language and the Open-Instance Power System Library (OpenIPSL).\n
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\n \n\n \n \n \n \n \n \n Smart Charging, Vehicle-to-Grid, and Reactive Power Support from Electric Vehicles in Distribution Grids: A Performance Comparison.\n \n \n \n \n\n\n \n Mukherjee, B.; Kariniotakis, G.; and Sossan, F.\n\n\n \n\n\n\n In 2021 IEEE PES Innovative Smart Grid Technologies Europe (ISGT Europe), pages 1-6, 10 2021. IEEE\n \n\n\n\n
\n\n\n\n \n \n \"SmartWebsite\n  \n \n\n \n \n doi\n  \n \n\n \n link\n  \n \n\n bibtex\n \n\n \n  \n \n abstract \n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n\n\n\n
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@inproceedings{\n title = {Smart Charging, Vehicle-to-Grid, and Reactive Power Support from Electric Vehicles in Distribution Grids: A Performance Comparison},\n type = {inproceedings},\n year = {2021},\n pages = {1-6},\n websites = {https://ieeexplore.ieee.org/document/9639954/},\n month = {10},\n publisher = {IEEE},\n day = {18},\n city = {Espoo, Finland},\n id = {ae24c317-cc7d-3ccb-8d5b-e0deb299e453},\n created = {2022-01-19T17:51:15.936Z},\n accessed = {2022-01-19},\n file_attached = {false},\n profile_id = {b148566c-bc4a-3e6b-bcd9-eb0286561c6f},\n last_modified = {2022-02-11T11:22:37.413Z},\n read = {false},\n starred = {false},\n authored = {true},\n confirmed = {true},\n hidden = {false},\n private_publication = {false},\n abstract = {© 2021 IEEE. This paper compares different charging strategies for electric vehicles (EVs) and mechanisms to support local distribution grids. First, a general scheduling problem for EVs based on convex optimization and linearized power grid models is presented. Then, it is shown how it can be adapted to model different charging strategies. These include: i) uncoordinated charging, where EVs maximize a local utility function regardless of grid constraints; ii) smart charging, where a charge schedule of all EVs is determined by maximizing their utility function subject to grid constraints; iii) vehicle-to-grid, where bidirectional power from the EVs is allowed; and iv) reactive power support, where 2- and 4-quadrant EV chargers can provide reactive power. The performance of these strategies are investigated considering the CIGRE benchmark system for medium-voltage distribution grids. It shows that, in the proposed scenario, smart charging with reactive power support is conducive to the shortest global recharging time.},\n bibtype = {inproceedings},\n author = {Mukherjee, Biswarup and Kariniotakis, Georges and Sossan, Fabrizio},\n doi = {10.1109/ISGTEurope52324.2021.9639954},\n booktitle = {2021 IEEE PES Innovative Smart Grid Technologies Europe (ISGT Europe)}\n}
\n
\n\n\n
\n © 2021 IEEE. This paper compares different charging strategies for electric vehicles (EVs) and mechanisms to support local distribution grids. First, a general scheduling problem for EVs based on convex optimization and linearized power grid models is presented. Then, it is shown how it can be adapted to model different charging strategies. These include: i) uncoordinated charging, where EVs maximize a local utility function regardless of grid constraints; ii) smart charging, where a charge schedule of all EVs is determined by maximizing their utility function subject to grid constraints; iii) vehicle-to-grid, where bidirectional power from the EVs is allowed; and iv) reactive power support, where 2- and 4-quadrant EV chargers can provide reactive power. The performance of these strategies are investigated considering the CIGRE benchmark system for medium-voltage distribution grids. It shows that, in the proposed scenario, smart charging with reactive power support is conducive to the shortest global recharging time.\n
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\n \n\n \n \n \n \n \n \n Scheduling the Charge of Electric Vehicles Including Reactive Power Support: Application to a Medium-Voltage Grid.\n \n \n \n \n\n\n \n Mukherjee, B.; Kariniotakis, G.; and Sossan, F.\n\n\n \n\n\n\n In CIRED 2021 - The 26th International Conference and Exhibition on Electricity Distribution, 2021. IET\n \n\n\n\n
\n\n\n\n \n \n \"SchedulingWebsite\n  \n \n\n \n \n doi\n  \n \n\n \n link\n  \n \n\n bibtex\n \n\n \n  \n \n abstract \n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n\n\n\n
\n
@inproceedings{\n title = {Scheduling the Charge of Electric Vehicles Including Reactive Power Support: Application to a Medium-Voltage Grid},\n type = {inproceedings},\n year = {2021},\n websites = {https://digital-library.theiet.org/content/conferences/10.1049/icp.2021.1680},\n publisher = {IET},\n id = {ca767233-0413-3f4a-b678-888823294446},\n created = {2022-02-11T11:50:15.152Z},\n file_attached = {false},\n profile_id = {b148566c-bc4a-3e6b-bcd9-eb0286561c6f},\n last_modified = {2022-02-11T11:51:19.160Z},\n read = {false},\n starred = {false},\n authored = {true},\n confirmed = {true},\n hidden = {false},\n private_publication = {false},\n abstract = {© 2021 IET. The simultaneous charging process of multiple electric vehicles (EVs) may cause violations of power distribution grids' operational constraints, such as voltage levels outside statutory limits, line currents above lines' ampacities, and congestion at the substation transformer. This paper investigates the impact on a medium voltage distribution grid of i) uncoordinated charging, ii) coordinated grid-aware charging, and iii) coordinated grid-aware charging of EVs with reactive power support for voltage regulation. In all these cases, the EVs' charging policy is determined with an optimal power flow (OPF) problem, where suitable sets of constraints are modeled to reproduce each specific case. Results are investigated for the 14-bus CIGRE MV benchmark network. The proposed methods are useful for grid operators to identify suitable control strategies for EV charging.},\n bibtype = {inproceedings},\n author = {Mukherjee, Biswarup and Kariniotakis, Georges and Sossan, Fabrizio},\n doi = {10.1049/icp.2021.1680},\n booktitle = {CIRED 2021 - The 26th International Conference and Exhibition on Electricity Distribution}\n}
\n
\n\n\n
\n © 2021 IET. The simultaneous charging process of multiple electric vehicles (EVs) may cause violations of power distribution grids' operational constraints, such as voltage levels outside statutory limits, line currents above lines' ampacities, and congestion at the substation transformer. This paper investigates the impact on a medium voltage distribution grid of i) uncoordinated charging, ii) coordinated grid-aware charging, and iii) coordinated grid-aware charging of EVs with reactive power support for voltage regulation. In all these cases, the EVs' charging policy is determined with an optimal power flow (OPF) problem, where suitable sets of constraints are modeled to reproduce each specific case. Results are investigated for the 14-bus CIGRE MV benchmark network. The proposed methods are useful for grid operators to identify suitable control strategies for EV charging.\n
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\n  \n 2020\n \n \n (1)\n \n \n
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\n \n\n \n \n \n \n \n \n Impact of the Charging Demand of Electric Vehicles on Distribution Grids: a Comparison Between Autonomous and Non-Autonomous Driving.\n \n \n \n \n\n\n \n Sossan, F.; Mukherjee, B.; and Hu, Z.\n\n\n \n\n\n\n In 2020 Fifteenth International Conference on Ecological Vehicles and Renewable Energies (EVER), pages 1-6, 9 2020. IEEE\n \n\n\n\n
\n\n\n\n \n \n \"ImpactPaper\n  \n \n \n \"ImpactWebsite\n  \n \n\n \n \n doi\n  \n \n\n \n link\n  \n \n\n bibtex\n \n\n \n  \n \n abstract \n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n\n\n\n
\n
@inproceedings{\n title = {Impact of the Charging Demand of Electric Vehicles on Distribution Grids: a Comparison Between Autonomous and Non-Autonomous Driving},\n type = {inproceedings},\n year = {2020},\n pages = {1-6},\n websites = {https://ieeexplore.ieee.org/document/9243122/},\n month = {9},\n publisher = {IEEE},\n day = {10},\n id = {1ad4d964-76c8-3b58-810f-f77d44348a4a},\n created = {2020-11-13T11:47:12.242Z},\n file_attached = {true},\n profile_id = {b148566c-bc4a-3e6b-bcd9-eb0286561c6f},\n last_modified = {2021-10-30T23:04:20.535Z},\n read = {false},\n starred = {false},\n authored = {true},\n confirmed = {true},\n hidden = {false},\n private_publication = {false},\n abstract = {© 2020 IEEE. Charging many electric vehicles (EVs) might cause violations of cable ampacities, statutory voltage limits, and substation transformer ratings in power distribution grids. Besides affecting mobility patterns, autonomous driving will open new perspectives in terms of interactions with the power grid. This paper explores the potential of autonomous EVs of reducing grid congestions thanks to the possibility of reaching the most suitable recharging locations autonomously. We first develop an algorithm for the coordinated charging of non-autonomous EVs accounting for grid constraints. We then augment its formulation by modeling the charging locations as decision variables of the problem, adopting an efficient linear mixed-integer program based on a linearized grid model and McCormick (exact) relaxations to handle some bi-linear terms appearing in the formulation. Considering the CIGRE' benchmark system for LV residential grids, we compare non-autonomous versus autonomous EVs and show that the additional degree of freedom coming from autonomous driving achieves reducing grid congestions.},\n bibtype = {inproceedings},\n author = {Sossan, Fabrizio and Mukherjee, Biswarup and Hu, Zechun},\n doi = {10.1109/EVER48776.2020.9243122},\n booktitle = {2020 Fifteenth International Conference on Ecological Vehicles and Renewable Energies (EVER)}\n}
\n
\n\n\n
\n © 2020 IEEE. Charging many electric vehicles (EVs) might cause violations of cable ampacities, statutory voltage limits, and substation transformer ratings in power distribution grids. Besides affecting mobility patterns, autonomous driving will open new perspectives in terms of interactions with the power grid. This paper explores the potential of autonomous EVs of reducing grid congestions thanks to the possibility of reaching the most suitable recharging locations autonomously. We first develop an algorithm for the coordinated charging of non-autonomous EVs accounting for grid constraints. We then augment its formulation by modeling the charging locations as decision variables of the problem, adopting an efficient linear mixed-integer program based on a linearized grid model and McCormick (exact) relaxations to handle some bi-linear terms appearing in the formulation. Considering the CIGRE' benchmark system for LV residential grids, we compare non-autonomous versus autonomous EVs and show that the additional degree of freedom coming from autonomous driving achieves reducing grid congestions.\n
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\n  \n 2019\n \n \n (1)\n \n \n
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\n \n\n \n \n \n \n \n \n Automatic re-synchronization controller analysis within a multi-domain gas turbine and power system model.\n \n \n \n \n\n\n \n Vanfretti, L.; Mukherjee, B.; Moudgalya, K.; and Gomez, F.\n\n\n \n\n\n\n In 7th Workshop on Modeling and Simulation of Cyber-Physical Energy Systems, MSCPES 2019 - Held as part of CPS Week, Proceedings, 2019. IEEE\n \n\n\n\n
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@inproceedings{\n title = {Automatic re-synchronization controller analysis within a multi-domain gas turbine and power system model},\n type = {inproceedings},\n year = {2019},\n keywords = {Automatic re-synchronization controller,Distribution network,Gas turbines,Modelica,Multi-domain modeling and simulation,OpenIPSL,Power grid,Power systems,Synchrophasors,ThermoPower},\n websites = {https://ieeexplore.ieee.org/document/8738797},\n publisher = {IEEE},\n id = {97398b0b-806a-3613-a295-e57affd34bc7},\n created = {2020-09-24T09:21:26.837Z},\n file_attached = {true},\n profile_id = {b148566c-bc4a-3e6b-bcd9-eb0286561c6f},\n last_modified = {2021-10-31T11:22:57.723Z},\n read = {false},\n starred = {false},\n authored = {true},\n confirmed = {true},\n hidden = {false},\n private_publication = {false},\n abstract = {© 2019 IEEE. This paper presents the design of a centralized controller architecture for automatic re-synchronization of islanded networks that uses remote synchrophasor measurements from Phasor Measurement Units (PMUs). The controller behaviour is tested in a multi-domain power system model, where a thermo-mechanical model of a gas turbine is used within the controlled generator to model a Distributed Energy Resource (DER), in substitution of a traditional turbine-governor representation. The controller architecture uses PMU data from substations at transmission and distribution level. Considering different power dispatch levels of the distribution generator model in the power system, the performance of frequency control module inside the overall re-synchronization controller has been analyzed and compared for both electrical-domain and multi-domain models. This paper shows that multi-domain models provide more detailed representation of the turbine behaviour and a better adjustment of the control signal behavior during the re-synchronization process.},\n bibtype = {inproceedings},\n author = {Vanfretti, L. and Mukherjee, B. and Moudgalya, K.M. and Gomez, F.J.},\n doi = {10.1109/MSCPES.2019.8738797},\n booktitle = {7th Workshop on Modeling and Simulation of Cyber-Physical Energy Systems, MSCPES 2019 - Held as part of CPS Week, Proceedings}\n}
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\n © 2019 IEEE. This paper presents the design of a centralized controller architecture for automatic re-synchronization of islanded networks that uses remote synchrophasor measurements from Phasor Measurement Units (PMUs). The controller behaviour is tested in a multi-domain power system model, where a thermo-mechanical model of a gas turbine is used within the controlled generator to model a Distributed Energy Resource (DER), in substitution of a traditional turbine-governor representation. The controller architecture uses PMU data from substations at transmission and distribution level. Considering different power dispatch levels of the distribution generator model in the power system, the performance of frequency control module inside the overall re-synchronization controller has been analyzed and compared for both electrical-domain and multi-domain models. This paper shows that multi-domain models provide more detailed representation of the turbine behaviour and a better adjustment of the control signal behavior during the re-synchronization process.\n
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