Lili Gong
Current Organizations / Institutes
The organizations/institutes from the scholar's latest article
Lili Gong has a total of 4 co-authors. Here are the top co-authors by number of shared publications:
- Jianfeng Zhao
School of Electrical Engineering, Southeast University, Nanjing 210096, China
1 shared publication - Kangli Liu
School of Electrical Engineering, Southeast University, Nanjing, China
1 shared publication - Wu Cao
School of Electrical Engineering, Southeast University, Nanjing 210096, China
1 shared publication - Xiang Li
LiuZhou Power Supply Bureau, GuangXi Power Grid Co., Ltd., Liuzhou 545006, China
1 shared publication
Latest Publications
- Open Access
Spatial and Temporal Optimization Strategy for Plug-In Electric Vehicle Charging to Mitigate Impacts on Distribution Network
The large deployment of plug-in electric vehicles (PEVs) challenges the operation of the distribution network. Uncoordinated charging of PEVs will cause a heavy load burden at rush hour and lead to increased power loss and voltage fluctuation. To overcome these problems, a novel coordinated charging strategy which considers the moving characteristics of PEVs is proposed in this paper. Firstly, the concept of trip chain is introduced to analyze the spatial and temporal distribution of PEVs. Then, a stochastic optimization model for PEV charging is established to minimize the distribution network power loss (DNPL) and maximal voltage deviation (MVD). After that, the particle swarm optimization (PSO) algorithm with an embedded power flow program is adopted to solve the model, due to its simplicity and practicality. Last, the feasibility and efficiency of the proposed strategy is tested on the IEEE 33 distribution system. Simulation results show that the proposed charging strategy not only reduces power loss and the peak valley difference, but also improves voltage profile greatly.
Open AccessSpatial and Temporal Optimization Strategy for Plug-In Electric Vehicle Charging to Mitigate Impacts on Distribution Network
The large deployment of plug-in electric vehicles (PEVs) challenges the operation of the distribution network. Uncoordinated charging of PEVs will cause a heavy load burden at rush hour and lead to increased power loss and voltage fluctuation. To overcome these problems, a novel coordinated charging strategy which considers the moving characteristics of PEVs is proposed in this paper. Firstly, the concept of trip chain is introduced to analyze the spatial and temporal distribution of PEVs. Then, a stochastic optimization model for PEV charging is established to minimize the distribution network power loss (DNPL) and maximal voltage deviation (MVD). After that, the particle swarm optimization (PSO) algorithm with an embedded power flow program is adopted to solve the model, due to its simplicity and practicality. Last, the feasibility and efficiency of the proposed strategy is tested on the IEEE 33 distribution system. Simulation results show that the proposed charging strategy not only reduces power loss and the peak valley difference, but also improves voltage profile greatly.