Multipurpose Charging Schedule Optimization Method for Electric Buses: Evaluation Using Real City Data
The use of electric vehicles (EVs) and photovoltaics (PV) is increasing worldwide. Transportation networks require the effective use of renewable energy (RE) for EVs, whereas power networks require local consumption of PV energy, mainly at the initiative of local governments. Although many previous...
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| Format: | Article |
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IEEE
2022-01-01
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| Series: | IEEE Access |
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| Online Access: | https://ieeexplore.ieee.org/document/9780415/ |
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| author | Yuki Tomizawa Yuto Ihara Yasuhiro Kodama Yutaka Iino Yasuhiro Hayashi Ohsei Ikeda Jun Yoshinaga |
| author_facet | Yuki Tomizawa Yuto Ihara Yasuhiro Kodama Yutaka Iino Yasuhiro Hayashi Ohsei Ikeda Jun Yoshinaga |
| author_sort | Yuki Tomizawa |
| collection | DOAJ |
| description | The use of electric vehicles (EVs) and photovoltaics (PV) is increasing worldwide. Transportation networks require the effective use of renewable energy (RE) for EVs, whereas power networks require local consumption of PV energy, mainly at the initiative of local governments. Although many previous studies have addressed these requirements using private EVs as mobile storages, their uncertainty and uncontrollability remain highly problematic. Therefore, our previous studies focused on electric buses because of their high controllability and certainty. These studies involved the development and evaluation of two independent minimization problems—kilowatts (KW) and kilowatt-hours (KWH) of surplus RE—as a charging schedule optimization method using mixed integer linear programming. However, the feasibility of simultaneously minimizing KW and KWH still presented technical problems. This study aims to extend and generalize the method to the simultaneous minimization of KW and KWH of the PV-derived reverse power flow (RPF). With this multiobjective optimization, the KW peak-cut of the RPF improves the hosting capacity and increases the availability of connectable RE resources, whereas the minimization of KWH promotes the local consumption of RE and decarbonization of public transportation. Two simulations using detailed data of actual bus operations and actual power flow data for a real city confirmed the feasibility of simultaneously optimizing KW and KWH and the relationship between these indicators and number of EV chargers. The optimized charging of the 17 electric buses achieved a maximum of 211.4 kW peak-cut and 1318.4 kWh RE-RPF absorption, reducing CO<sub>2</sub> emissions by 495.7 kg/day. |
| first_indexed | 2024-04-12T18:00:28Z |
| format | Article |
| id | doaj.art-5f282ac69aa04906ba696856697db838 |
| institution | Directory Open Access Journal |
| issn | 2169-3536 |
| language | English |
| last_indexed | 2024-04-12T18:00:28Z |
| publishDate | 2022-01-01 |
| publisher | IEEE |
| record_format | Article |
| series | IEEE Access |
| spelling | doaj.art-5f282ac69aa04906ba696856697db8382022-12-22T03:22:11ZengIEEEIEEE Access2169-35362022-01-0110560675608010.1109/ACCESS.2022.31776189780415Multipurpose Charging Schedule Optimization Method for Electric Buses: Evaluation Using Real City DataYuki Tomizawa0https://orcid.org/0000-0001-6089-1763Yuto Ihara1https://orcid.org/0000-0003-3670-6198Yasuhiro Kodama2https://orcid.org/0000-0002-2165-5722Yutaka Iino3https://orcid.org/0000-0001-5750-2894Yasuhiro Hayashi4https://orcid.org/0000-0002-4009-4430Ohsei Ikeda5Jun Yoshinaga6Department of Electrical Engineering and Bioscience, Waseda University, Tokyo, JapanAdvanced Collaborative Research Organization for Smart Society, Waseda University, Tokyo, JapanAdvanced Collaborative Research Organization for Smart Society, Waseda University, Tokyo, JapanAdvanced Collaborative Research Organization for Smart Society, Waseda University, Tokyo, JapanDepartment of Electrical Engineering and Bioscience, Waseda University, Tokyo, JapanTEPCO Power Grid Inc., Tokyo, JapanTEPCO Power Grid Inc., Tokyo, JapanThe use of electric vehicles (EVs) and photovoltaics (PV) is increasing worldwide. Transportation networks require the effective use of renewable energy (RE) for EVs, whereas power networks require local consumption of PV energy, mainly at the initiative of local governments. Although many previous studies have addressed these requirements using private EVs as mobile storages, their uncertainty and uncontrollability remain highly problematic. Therefore, our previous studies focused on electric buses because of their high controllability and certainty. These studies involved the development and evaluation of two independent minimization problems—kilowatts (KW) and kilowatt-hours (KWH) of surplus RE—as a charging schedule optimization method using mixed integer linear programming. However, the feasibility of simultaneously minimizing KW and KWH still presented technical problems. This study aims to extend and generalize the method to the simultaneous minimization of KW and KWH of the PV-derived reverse power flow (RPF). With this multiobjective optimization, the KW peak-cut of the RPF improves the hosting capacity and increases the availability of connectable RE resources, whereas the minimization of KWH promotes the local consumption of RE and decarbonization of public transportation. Two simulations using detailed data of actual bus operations and actual power flow data for a real city confirmed the feasibility of simultaneously optimizing KW and KWH and the relationship between these indicators and number of EV chargers. The optimized charging of the 17 electric buses achieved a maximum of 211.4 kW peak-cut and 1318.4 kWh RE-RPF absorption, reducing CO<sub>2</sub> emissions by 495.7 kg/day.https://ieeexplore.ieee.org/document/9780415/Charging controlelectric busmixed integer linear programmingmultiobjective optimizationphotovoltaicreverse power flow |
| spellingShingle | Yuki Tomizawa Yuto Ihara Yasuhiro Kodama Yutaka Iino Yasuhiro Hayashi Ohsei Ikeda Jun Yoshinaga Multipurpose Charging Schedule Optimization Method for Electric Buses: Evaluation Using Real City Data IEEE Access Charging control electric bus mixed integer linear programming multiobjective optimization photovoltaic reverse power flow |
| title | Multipurpose Charging Schedule Optimization Method for Electric Buses: Evaluation Using Real City Data |
| title_full | Multipurpose Charging Schedule Optimization Method for Electric Buses: Evaluation Using Real City Data |
| title_fullStr | Multipurpose Charging Schedule Optimization Method for Electric Buses: Evaluation Using Real City Data |
| title_full_unstemmed | Multipurpose Charging Schedule Optimization Method for Electric Buses: Evaluation Using Real City Data |
| title_short | Multipurpose Charging Schedule Optimization Method for Electric Buses: Evaluation Using Real City Data |
| title_sort | multipurpose charging schedule optimization method for electric buses evaluation using real city data |
| topic | Charging control electric bus mixed integer linear programming multiobjective optimization photovoltaic reverse power flow |
| url | https://ieeexplore.ieee.org/document/9780415/ |
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