研究目的
To jointly design charging stations and photovoltaic (PV) power plants with time-dependent charging fee, to improve the management of the coupled transportation and power systems.
研究成果
The study demonstrates the effectiveness of the optimal design of charging stations, PV plants, and time-dependent charging fee strategy in managing coupled transportation and power networks. The proposed SBO algorithm performs well in solving the model, and numerical examples provide important insights into infrastructure design and price management.
研究不足
The research assumes that traffic flow reaches an equilibrium in each period, ignoring that drivers may make choices across more than one period. This simplification may not capture all behavioral features of EV drivers.
1:Experimental Design and Method Selection:
An extended label-setting algorithm is proposed to solve the EV joint routing and charging problem. A variational inequality problem is formulated to model the equilibrium of EV traffic on transportation networks, and an optimal power flow model is proposed to model the power network flow with PV power plants.
2:Sample Selection and Data Sources:
The study uses test networks (Nguyen-Dupius and Sioux-Falls) for numerical examples.
3:List of Experimental Equipment and Materials:
MATLAB R2018a, CONOPT
4:14, CPLEX 8, YALMIP toolbox. Experimental Procedures and Operational Workflow:
The methodology involves solving the joint routing and charging problem, modeling traffic equilibrium, and optimizing power flow with PV plants.
5:Data Analysis Methods:
The study employs surrogate-based optimization (SBO) algorithm to solve the model and analyzes the results through numerical examples.
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