Impact of Electric Vehicle Charging Infrastructure Expansion on Microgrid Economics: A Case Study

被引:0
|
作者
Sprengeler, Matti [1 ]
Freudenmacher, Till [1 ]
Popova, Raisa [2 ]
Nguyen, Hai Quang [2 ]
la Rotta, Mauricio Rojas [3 ]
Stryi-Hipp, Gerhard [1 ]
机构
[1] Fraunhofer ISE, Grp Smart Cities, Freiburg, Germany
[2] DB Energie GmbH, Deutsch Bahn AG, Berlin, Germany
[3] Schneider Elect GmbH, Digital Energy Div, Berlin, Germany
关键词
microgrid; electric vehicles; charging infrastructure; optimization; business models; infrastructure planning; data-driven decision support;
D O I
10.1109/sest48500.2020.9203561
中图分类号
TP301 [理论、方法];
学科分类号
081202 ;
摘要
The operation of public and semi-public charging infrastructure is often not profitable yet. However, the integration of charging infrastructure in microgrids enables the introduction of innovative business models, e.g. by local renewable energy generation and storage units. Another driver to improve profitability is to adapt the charging infrastructure expansion according to its usage characteristics. This study presents a method to optimize the charging infrastructure expansion. Therefore, a mixed integer linear program with the aim to minimize costs is formulated and applied on real-world data. Via the optimization, different scenarios are developed and the microgrid integration is simulated in an operation optimization algorithm. Different business models such as PV and battery storage integration are computed and the economics of the business models in the different scenarios are evaluated. It can be concluded that microgrid integration can he a significant driver of charging infrastructure operation profitability. Integrating PV generation shortens the payback period in all scenarios. Also, PV generation and battery storage combined improve profitability, but not to the same extent than without storage unit. Furthermore, the optimization of the charging infrastructure expansion leads to a significant improvement of profitability. Combining both the microgrid integration, as well as the expansion optimization, the payback period can be decreased by up until 67 %.
引用
收藏
页数:6
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