scholarly journals A multi-objective optimization model for fast electric vehicle charging stations with wind, PV power and energy storage

2021 ◽  
Vol 288 ◽  
pp. 125564
Author(s):  
Baojun Sun
Keyword(s):  
Energy Storage ◽  
Electric Vehicle ◽  
Optimization Model ◽  
Multi Objective Optimization ◽  
Multi Objective ◽  
Electric Vehicle Charging ◽  
Vehicle Charging ◽  
Power And Energy ◽  
Charging Stations

scholarly journals Portfolio Optimization of Photovoltaic/Battery Energy Storage/Electric Vehicle Charging Stations with Sustainability Perspective Based on Cumulative Prospect Theory and MOPSO

2020 ◽  
Vol 12 (3) ◽  
pp. 985 ◽  
Author(s):  
Jicheng Liu ◽  
Qiongjie Dai
Keyword(s):  
Energy Storage ◽  
Portfolio Optimization ◽  
Prospect Theory ◽  
Electric Vehicle ◽  
Optimization Model ◽  
Cumulative Prospect Theory ◽  
Battery Energy Storage ◽  
Electric Vehicle Charging ◽  
Battery Energy ◽  
Charging Stations

Recently, an increasing number of photovoltaic/battery energy storage/electric vehicle charging stations (PBES) have been established in many cities around the world. This paper proposes a PBES portfolio optimization model with a sustainability perspective. First, various decision-making criteria are identified from perspectives of economy, society, and environment. Secondly, the performance of alternatives with respect to each criterion is evaluated in the form of trapezoidal intuitionistic fuzzy numbers (TrIFN). Thirdly, the alternatives are ranked based on cumulative prospect theory. Then, a multi-objective optimization model is built and solved by multi-objective particle swarm optimization (MOPSO) algorithm to determine the optimal PBES portfolio. Finally, a case in South China is studied and a scenario analysis is conducted to verify the effectiveness of the proposed model.

scholarly journals A Hierarchical Optimization Model for a Network of Electric Vehicle Charging Stations

Energies ◽  
2017 ◽  
Vol 10 (5) ◽  
pp. 675 ◽  
Author(s):  
Cuiyu Kong ◽  
Raka Jovanovic ◽  
Islam Bayram ◽  
Michael Devetsikiotis
Keyword(s):  
Electric Vehicle ◽  
Optimization Model ◽  
Hierarchical Optimization ◽  
Electric Vehicle Charging ◽  
Vehicle Charging ◽  
Charging Stations

Energy Storage Sizing for Plug-in Electric Vehicle Charging Stations

2021 ◽  
pp. 119-141
Author(s):  
I. Safak Bayram ◽  
Ryan Sims ◽  
Edward Corr ◽  
Stuart Galloway ◽  
Graeme Burt
Keyword(s):  
Energy Storage ◽  
Electric Vehicle ◽  
Electric Vehicle Charging ◽  
Vehicle Charging ◽  
Charging Stations

scholarly journals Optimal Network Reconfiguration with Distributed Generation and Electric Vehicle Charging Stations

2021 ◽  
Vol 6 (4) ◽  
pp. 1174-1185
Author(s):  
Surender Reddy Salkuti
Keyword(s):  
Renewable Energy ◽  
Electric Vehicle ◽  
Distributed Generation ◽  
Network Reconfiguration ◽  
Multi Objective ◽  
Electric Vehicle Charging ◽  
Optimal Network ◽  
Vehicle Charging ◽  
Charging Stations ◽  
Single Objective

This paper proposes an optimal network reconfiguration (ONR) by integrating the renewable energy (RE) based distributed generation (DG) resources, i.e., wind and solar photovoltaic (PV) modules, and electric vehicle charging stations (EVCS). The uncertainties related to renewable energy sources (RESs) are handled by using probability analysis. In this work, wind uncertainty is handled by using Weibull probability density function (PDF), and solar PV uncertainty is modeled by using Beta PDF. This paper also models the load of EVCSs. The ONR is a tool to operate distribution systems (DSs) at optimum cost/loss. In the literature, most of the ONR problems are solved as single objective type. This neccessiate the development of multi-objective based ONR problem and solved using the multi-objective algorithms by considering multiple objectives. Therefore in this paper, total cost of operation and power losses are considered as two objectives functions. The single objective-based ONR is solved using crow search algorithm (CSA) and multi-objective-based ONR is solved using multi-objective-based CSA. As the DS is unbalanced, the power flow for the unbalanced system will include the three-phase transformer. The ONR problem has been solved by considering 17 bus unbalanced and balanced DSs.

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