A bi-level optimization model for electric vehicle charging strategy based on regional grid load following

2021 ◽  
pp. 129313
Author(s):  
Xiaolong Yang ◽  
Dongxiao Niu ◽  
Lijie Sun ◽  
Zhengsen Ji ◽  
Jiancheng Zhou ◽  
...  
Keyword(s):  
Electric Vehicle ◽  
Optimization Model ◽  
Load Following ◽  
Electric Vehicle Charging ◽  
Vehicle Charging ◽  
Grid Load ◽  
Charging Strategy

scholarly journals Electric Vehicle Charging Strategy for Isolated Systems with High Penetration of Renewable Generation

Energies ◽  
2018 ◽  
Vol 11 (11) ◽  
pp. 3188 ◽  
Author(s):  
Jean-Michel Clairand ◽  
Javier Rodríguez-García ◽  
Carlos Álvarez-Bel
Keyword(s):  
Electric Vehicle ◽  
Co2 Emissions ◽  
Fossil Fuels ◽  
Renewable Energy Sources ◽  
Electric Vehicle Charging ◽  
High Penetration ◽  
Smart Charging ◽  
Vehicle Charging ◽  
Installed Capacity ◽  
Charging Strategy

Inhabited islands depend primarily on fossil fuels for electricity generation and they also present frequently a vehicle fleet, which result in a significant environmental problem. To address this, several governments are investing in the integration of Renewable Energy Sources (RESs) and Electric Vehicles (EVs), but the combined integration of them creates challenges to the operation of these isolated grid systems. Thus, the aim of this paper is to propose an Electric Vehicle charging strategy considering high penetration of RES. The methodology proposes taxing CO2 emissions based on high pricing when the electricity is mostly generated by fossil fuels, and low pricing when there is a RES power excess. The Smart charging methodology for EV optimizes the total costs. Nine scenarios with different installed capacity of solar and wind power generation are evaluated and compared to cases of uncoordinated charging. The methodology was simulated in the Galapagos Islands, which is an archipelago of Ecuador, and recognized by the United Nations Educational, Scientific and Cultural Organization (UNESCO) as both aWorld Heritage site and a biosphere reserve. Simulations results demonstrate that the EV aggregator could reduce costs: 7.9% for a case of 5 MW installed capacity (wind and PV each), and 7% for a case of 10 MW installed (wind and PV each). Moreover, the use of excess of RES power for EV charging will considerably reduce CO2 emissions

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

scholarly journals Electric Vehicle Charging Station Location Decision Analysis for a Two-Stage Optimization Model Based on Shapley Function

2021 ◽  
Vol 2021 ◽  
pp. 1-9
Author(s):  
Lifeng Yang ◽  
Zhongwei Cheng ◽  
Baojie Zhang ◽  
Fengyun Ma
Keyword(s):  
Electric Vehicle ◽  
Optimization Model ◽  
Evaluation Index System ◽  
User Preference ◽  
Two Stage ◽  
Alternative Scheme ◽  
Charging Station ◽  
Electric Vehicle Charging ◽  
Shapley Function ◽  
Vehicle Charging

The promotion of electric vehicles and their charging facilities to achieve carbon emission reduction is a research hotspot in the field of transportation. Aiming at the comprehensive decision of electric vehicle charging station (EVCS) location, this paper constructs an EVCS location evaluation index system that includes five indexes of grid load, traffic facilities, user preference, construction cost, and service radius. Firstly, we convert the exact number into interval judgment matrix, introduce Shapley fuzzy measure to calculate the weight of factors, and use the two-stage optimization model to further optimize the weight. Then, we combine the multiple criteria decision-making (MCDM) method in the Pythagorean fuzzy environment with partitioned normalized weighted Bonferroni mean (PFPNWBM) operator, and calculate the optimal ranking of alternatives according to the performance function and the accuracy function. Finally, a numerical example is used to analyze the difference between first-order linear optimization and two-stage optimization in alternative scheme evaluation, and the practical value of using model to evaluate EVCS location is verified.

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