Combined Framework with Heuristic Programming and Rule-Based Strategies for Scheduling and Real Time Operation in Electric Vehicle Charging Stations
This paper proposes a flexible framework for scheduling and real time operation of electric vehicle charging stations (EVCS). The methodology applies a multi-objective evolutionary particle swarm optimization algorithm (EPSO) for electric vehicles (EVs) scheduling based on a day-ahead scenario. Then...
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| Format: | Article |
| Language: | English |
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MDPI AG
2021-03-01
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| Series: | Energies |
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| Online Access: | https://www.mdpi.com/1996-1073/14/5/1370 |
| _version_ | 1797415718601359360 |
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| author | Héricles Eduardo Oliveira Farias Camilo Alberto Sepulveda Rangel Leonardo Weber Stringini Luciane Neves Canha Daniel Pegoraro Bertineti Wagner da Silva Brignol Zeno Iensen Nadal |
| author_facet | Héricles Eduardo Oliveira Farias Camilo Alberto Sepulveda Rangel Leonardo Weber Stringini Luciane Neves Canha Daniel Pegoraro Bertineti Wagner da Silva Brignol Zeno Iensen Nadal |
| author_sort | Héricles Eduardo Oliveira Farias |
| collection | DOAJ |
| description | This paper proposes a flexible framework for scheduling and real time operation of electric vehicle charging stations (EVCS). The methodology applies a multi-objective evolutionary particle swarm optimization algorithm (EPSO) for electric vehicles (EVs) scheduling based on a day-ahead scenario. Then, real time operation is managed based on a rule-based (RB) approach. Two types of consumer were considered: EV owners with a day-ahead request for charging (scheduled consumers, SCh) and non-scheduling users (NSCh). EPSO has two main objectives: cost reduction and reduce overloading for high demand in grid. The EVCS has support by photovoltaic generation (PV), battery energy storage systems (BESS), and the distribution grid. The method allows the selection between three types of charging, distributing it according to EV demand. The model estimates SC remaining state of charge (SoC) for arriving to EVCS and then adjusts the actual difference by the RB. The results showed a profit for EVCS by the proposed technique. The proposed EPSO and RB have a fast solution to the problem that allows practical implementation. |
| first_indexed | 2024-03-09T05:52:34Z |
| format | Article |
| id | doaj.art-bc7d61b32e3d4fd4933108d831e5ee8f |
| institution | Directory Open Access Journal |
| issn | 1996-1073 |
| language | English |
| last_indexed | 2024-03-09T05:52:34Z |
| publishDate | 2021-03-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Energies |
| spelling | doaj.art-bc7d61b32e3d4fd4933108d831e5ee8f2023-12-03T12:16:03ZengMDPI AGEnergies1996-10732021-03-01145137010.3390/en14051370Combined Framework with Heuristic Programming and Rule-Based Strategies for Scheduling and Real Time Operation in Electric Vehicle Charging StationsHéricles Eduardo Oliveira Farias0Camilo Alberto Sepulveda Rangel1Leonardo Weber Stringini2Luciane Neves Canha3Daniel Pegoraro Bertineti4Wagner da Silva Brignol5Zeno Iensen Nadal6Department of Electrical Engineering , Federal University of Santa Maria—UFSM, Santa Maria 97105-900, BrazilDepartment of Electrical Engineering , Federal University of Santa Maria—UFSM, Santa Maria 97105-900, BrazilDepartment of Electrical Engineering , Federal University of Santa Maria—UFSM, Santa Maria 97105-900, BrazilDepartment of Electrical Engineering , Federal University of Santa Maria—UFSM, Santa Maria 97105-900, BrazilDepartment of Electrical Engineering , Federal University of Santa Maria—UFSM, Santa Maria 97105-900, BrazilDepartment of Electrical Engineering , Federal University of Santa Maria—UFSM, Santa Maria 97105-900, BrazilElectric Energy Paranaense Company—COPEL-DIS, Curitiba 81200-240, BrazilThis paper proposes a flexible framework for scheduling and real time operation of electric vehicle charging stations (EVCS). The methodology applies a multi-objective evolutionary particle swarm optimization algorithm (EPSO) for electric vehicles (EVs) scheduling based on a day-ahead scenario. Then, real time operation is managed based on a rule-based (RB) approach. Two types of consumer were considered: EV owners with a day-ahead request for charging (scheduled consumers, SCh) and non-scheduling users (NSCh). EPSO has two main objectives: cost reduction and reduce overloading for high demand in grid. The EVCS has support by photovoltaic generation (PV), battery energy storage systems (BESS), and the distribution grid. The method allows the selection between three types of charging, distributing it according to EV demand. The model estimates SC remaining state of charge (SoC) for arriving to EVCS and then adjusts the actual difference by the RB. The results showed a profit for EVCS by the proposed technique. The proposed EPSO and RB have a fast solution to the problem that allows practical implementation.https://www.mdpi.com/1996-1073/14/5/1370EVCSEPSOrule-basedEV scheduling |
| spellingShingle | Héricles Eduardo Oliveira Farias Camilo Alberto Sepulveda Rangel Leonardo Weber Stringini Luciane Neves Canha Daniel Pegoraro Bertineti Wagner da Silva Brignol Zeno Iensen Nadal Combined Framework with Heuristic Programming and Rule-Based Strategies for Scheduling and Real Time Operation in Electric Vehicle Charging Stations Energies EVCS EPSO rule-based EV scheduling |
| title | Combined Framework with Heuristic Programming and Rule-Based Strategies for Scheduling and Real Time Operation in Electric Vehicle Charging Stations |
| title_full | Combined Framework with Heuristic Programming and Rule-Based Strategies for Scheduling and Real Time Operation in Electric Vehicle Charging Stations |
| title_fullStr | Combined Framework with Heuristic Programming and Rule-Based Strategies for Scheduling and Real Time Operation in Electric Vehicle Charging Stations |
| title_full_unstemmed | Combined Framework with Heuristic Programming and Rule-Based Strategies for Scheduling and Real Time Operation in Electric Vehicle Charging Stations |
| title_short | Combined Framework with Heuristic Programming and Rule-Based Strategies for Scheduling and Real Time Operation in Electric Vehicle Charging Stations |
| title_sort | combined framework with heuristic programming and rule based strategies for scheduling and real time operation in electric vehicle charging stations |
| topic | EVCS EPSO rule-based EV scheduling |
| url | https://www.mdpi.com/1996-1073/14/5/1370 |
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