Power factor correction (PFC) converters with a diode bridge are extensively used in different AC-DC applications. However, the diode bridge has to employ four diodes to complete the AC to DC at the expense of high conduction losses. Thus, many bridgeless PFC converters have been proposed with dual converter cells to minimize the number of conducted diodes for better efficiency. Unfortunately, these dual-converter cell-based bridgeless converters need almost double components. To solve this issue, this paper proposes a true bridgeless buck-type PFC converter, which annihilates the diode bridge completely with only fewer component counts. The proposed converter uses buck and buck-boost cells to obtain the novel bridgeless topology, which features a simple structure and control to achieve high PF and low total harmonics of input current (THDi). Simulations are given to validate the feasibility of the proposed topology and the control method. Comparisons with the conventional buck PFC converter are also given to confirm the better performances of the proposed topology.

Electric vehicles (EVs) can act as virtual energy routers (VERs) in the grid, giving them the flexibility to change the direction of energy flow. Therefore, a day-ahead scheduling for radial microgrids deploying EV-based VERs is proposed. In the day-ahead scheduling, the charging/discharging operation, state of charge (SOC), and available time of EV-based VERs are involved in the social utility maximization problem. With the laxity model of EV-based VERs and the forecasted reference demand, the supply and demand in the microgrid are optimized to minimize generation costs and maximize consumer utility in a whole day. Binary variables, which indicate the charging and discharging choices of the EV-based VERs, exist in the day-ahead scheduling. Therefore, mixed integer nonlinear programming (MINLP) is adopted to solve the optimization problem. The simulation cases are then provided to verify the effectiveness of the suggested day-ahead scheduling approach.

The application of wireless power transfer (WPT) in electric vehicles (EVs) has brought great convenience, safety, and flexibility to EV owners. Traditional EV charging converters can only support wired charging or wireless charging with low integration. In order to realize both wired and wireless charging functions in the same system, excessive power switches will be utilized, resulting in a redundant structure and low power density. To solve this problem, this paper proposes a novel multi-functional converter for EV charging. Using one set of power switches, the proposed converter can output DC voltage for wired charging or high-frequency AC voltage for wireless charging. Circuit topology and control method are discussed and analyzed. Finally, simulations in MATLAB/SIMULINK are conducted to verify the effectiveness of the proposed multi-functional converter.

In this paper, an optimal retail market pricing design for demand response in day-ahead scheduling of smart distribution networks is investigated. Through the well-designed retail market electricity price, the profit of each user is maximized; while the profit of the Distribution Network Operator (DNO) is guaranteed and the risk management model based on the Information Gap Decision Theory (IGDT) method is proposed to protect the DNO from financial risk arising out of the uncertainty of wholesale market prices. Because of the convexity of the problems of users and the DNO, the demand response program is developed based on the Predictor Corrector Proximal Multiplier, which is a distributed algorithm and guaranteed to converge to a global optimal solution, i.e. the retail market electricity price. The numerical simulation is given to show the effectiveness of the proposed pricing method.