The electric vehicles (EVs) have played an important role in people's travelling due to the clean energy and environment-friendly. Considering the endurance issue of EVs, wireless charging is regarded as a convenient and effective solution. However, the charging power and the efficiency would be greatly affected when the transmitting coil (TC) and the receiving coils (RC) are non-aligned. This paper presents a flexible and high-accuracy positioning device based on electromagnetic balance, which could automatically achieve wireless charging and two-level positioning without communication between TC and EVs during location. Besides, a six-coils cross-coupled circuit model has been built to optimize key parameters that affect the positioning accuracy. Theoretical analysis and experimental results show that the proposed structures and location method have certain advantages in positioning accuracy, operation complexity and practicability. Within the range of first level positioning, the accuracy could achieve 1 cm. There is a high fitting performance between the simulation and experimental results, which verify the correctness of the theoretical analysis and the validity of the structures. Moreover, an additional comparative experiment has been designed to verify the correctness of the proposed method used in the wireless charging positioning system with ferrite cores and a magnetic shielding layer.

Given the current situation of large-scale energy storage system(ESS) access in distribution network, a practical distributed ESS location and capacity optimization model is proposed. Firstly, a weighted voltage sensitivity is proposed to select the grid-connected node set of ESS. On this basis, the distributed ESS location model is established，which aims at reducing voltage deviation and active power loss of the distribution network. Then, an ESS partition method based on the improved flame propagation model is proposed, and the partition results are obtained by constructing the flammability of nodes, the wind direction of flame propagation, speed of flame propagation and other indicators. Based on partition results, the capacity optimization model is established with the maximum annual net income of energy stored in the partition as the objective function. Finally, the improved IEEE-33 bus distribution network is used to demonstrate the effectiveness and feasibility of the proposed model.