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- W4200572227 abstract "This paper presents an expansion planning study on unbalanced distribution systems with high residential electric vehicle (EV) charging and solar photovoltaic (PV) power generation. A large increase in residential EV charging may overload current distribution systems if they are not adequately prepared. PV systems, on the other hand, can assists in supplying some of the demand in the network. However, most residential PV generation and EV charging are single-phase, which could lead to an increase in voltage and power imbalance. In this paper, a data-driven method is developed for expanding distribution systems while considering the uncertainty of the electricity demand, EV charging demand, and PV power generation. A mixed-integer linear programming (MILP) model is designed for improving the distribution system by constructing distribution lines and upgrading or building substations. An algorithm that combines the Alternating Direction Method of Multipliers (ADMM) algorithm and Column-and-Constraint Generation is developed in order to solve the optimization problem efficiently. Numerical results showed the effectiveness of the proposed method in expanding distribution systems in order to handle the new demand while limiting the imbalance in the system." @default.
- W4200572227 created "2021-12-31" @default.
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- W4200572227 date "2021-10-18" @default.
- W4200572227 modified "2023-09-27" @default.
- W4200572227 title "Data-Driven Distribution System Expansion Planning Considering High EV and PV Penetration" @default.
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- W4200572227 doi "https://doi.org/10.1109/isgteurope52324.2021.9639991" @default.
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