| Title |
Optimal operation and simultaneous analysis of the electric transport systems and distributed energy resources in the smart city |
| ID_Doc |
36284 |
| Authors |
Duan, PF; Askari, M; Hemat, K; Ali, ZM |
| Title |
Optimal operation and simultaneous analysis of the electric transport systems and distributed energy resources in the smart city |
| Year |
2021 |
| Published |
|
| DOI |
10.1016/j.scs.2021.103306 |
| Abstract |
Today due to population growth as well as air pollution and lack of energy many countries are motivated to use technology to provide services and solve city problems. The idea of a smart city allows to interact directly with urban infrastructure and monitoring whatever that happens and is in progress. A smart city is a city, based on information and communication technology. In this paper, optimal operation of electrical transportation system and energy distribution resources has been studied. The major energy consumption systems in a smart city are electrical transportation systems such as Electric Vehicles in power systems and Electric Railway systems. Analyses the interaction of an interconnected systems using a linear model for co-optimization planning and operation of subway system. For optimal operation of the smart city, an optimization problem that minimizes the total cost of all the energy systems and maximizes the Regenerative Braking energy to recover subway is solved. In this paper, considering the electric vehicles such as vehicle to Grid and Subway technology located in the special depot, the traffic and length of the routes are modeled. Based on degradation model has been presented to rise battery life of Electric vehicles. Also, a machine learning technique based on the long short-term memory (LSTM) is used to forecast the hourly solar radiation and wind speed. To depict the uncertain behavior of electric vehicles, electric transportation system and loads in smart city, Point Estimate Method, as a stochastic framework is suggested. All in all, using uncertainty and deterministic method the proposed model is analyzed. |
| Author Keywords |
Smart city; Machine learning; Electrical transportation systems; V2G; V2M |
| Index Keywords |
Index Keywords |
| Document Type |
Other |
| Open Access |
Open Access |
| Source |
Science Citation Index Expanded (SCI-EXPANDED) |
| EID |
WOS:000711888200001 |
| WoS Category |
Construction & Building Technology; Green & Sustainable Science & Technology; Energy & Fuels |
| Research Area |
Construction & Building Technology; Science & Technology - Other Topics; Energy & Fuels |
| PDF |
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