Zobrazeno 1 - 10
of 11
pro vyhledávání: '"Shahab Shokrzadeh"'
Publikováno v:
IEEE Transactions on Transportation Electrification. 9:886-895
State-of-Charge Prediction of Degrading Li-ion Batteries Using an Adaptive Machine Learning Approach
Publikováno v:
2022 IEEE Power & Energy Society General Meeting (PESGM).
Publikováno v:
2021 IEEE Electrical Power and Energy Conference (EPEC).
Publikováno v:
Energy Policy. 115:572-583
This paper employs a multi-level perspective approach to examine the development of policy frameworks around energy storage technologies. The paper focuses on the emerging encounter between existing social, technological, regulatory, and institutiona
Publikováno v:
Energy. 223:120116
Due to the significantly complex and nonlinear behavior of li-ion batteries, forecasting the state of charge (SOC) of the batteries is still a great challenge. Therefore, accurate SOC estimation is essential for the proper operation of batteries whil
Publikováno v:
Energy. 133:1121-1131
The introduction of electric vehicles on the power grid translates to operational challenges and opportunities of using these vehicles as distributed energy resources. This paper presents an algorithm for utilities to identify optimal scenarios for c
Publikováno v:
2019 IEEE Transportation Electrification Conference and Expo (ITEC).
Fast charging systems are a key element for the wide market adoption of electric vehicles. The integration of fast charging stations, however, cannot be possible without satisfying the operational constraints of the power grid. In this paper, the imp
Autor:
Shahab Shokrzadeh, Eric Bibeau
Publikováno v:
Energy. 106:701-711
This study presents a framework for the integration of electrified light-duty vehicles and intermittent renewable energy towards a sustainable transportation system. Batteries of plug-in electric vehicles, obtained at their automotive end of life, ar
Publikováno v:
Energy. 89:793-802
We propose a statistical algorithm for sizing the energy storage system required for delivering baseload electricity to a selected confidence level for a wind farm. The proposed algorithm can be utilized by utilities to assess wind integration and to
Publikováno v:
IEEE Transactions on Sustainable Energy. 5:1262-1269
Wind turbine power curve modeling is an important tool in turbine performance monitoring and power forecasting. There are several statistical techniques to fit the empirical power curve of a wind turbine, which can be classified into parametric and n