This paper presents the design and development of a three-phase 10-kV/400-V 500-kVA electronic power transformer (EPT). The power circuit is designed in a modular fashion, i.e., the main circuit consists of many identical ac-dc-dc-ac modules (abbreviated as power modules). Each power module consists of a high-voltage power cell, a low-voltage power cell (LVPC), a medium-frequency isolation transformer, and a filter. The corresponding control and protection system is developed. A special three-stage startup strategy is designed to shorten the startup time and reduce the startup inrush current. The negative-sequence current compensation is introduced in the input stage to handle the unbalanced loads. To keep the dc-link voltages balanced, an individual dc voltage balancing controller based on regulating the output power of each parallel LVPC is proposed. The detailed control hardware design and software implementation are discussed. The functions of this 10-kV EPT prototype are verified through the laboratory and field tests. The results are shown in this paper. Currently, the prototype is operating in the industrial power grid.

Energy router is an intelligent power electronic device that can realize the active management of power flow and provide convenient access to distributed energy resource. This paper presents the structure of an AC-DC hybrid multi-port energy router, which acts as the interface between the power consumer and the distribution network. The corresponding coordinated control strategy is developed to guarantee the regular operation of the energy router and a mode switch strategy with advanced compensation is proposed to achieve seamless transition between grid-connected mode and islanded mode. A novel and practical fuzzy logic controller considering unit-time electricity charge is proposed for the energy router to prolong battery life, to improve economic benefits of power consumers, and to smooth fluctuations of renewable energy generation or load consumption. The simulation and experimental results have validated the coordinated control and energy management strategies and demonstrated that the energy router has satisfactory performance.

When plug-in electric vehicles (PEVs) participate in grid operation, the inter-temporal feature of PEVs charging transforms the traditional optimal power flow (OPF) problem into multiperiod OPF (MOPF) problem. In the case that the population of PEVs is huge, the large number of variables and constraints render the centralized solution technique unsuitable to solve the MOPF problem. Therefore, a distributed algorithm based on alternating direction method of multipliers (ADMM) is developed to decompose the MOPF into two update steps that are solved in an alternating and iterative style. To improve the solution efficiency, the second update step is transformed into a Euclidean projection problem by approximating the original objective with a surrogate function. Then a projection algorithm is utilized to solve the approximate problem. Numerical results show that this reformulated model obtains suboptimal solutions with small relative error, but gains considerable speedup. Furthermore, its scalability and effectiveness are tested in the 119-bus and 906-bus distribution networks.

The concept of a microgrid of prosumers is demanded for the efficient utilization of renewable energy and the flexible energy trading between prosumers. This paper proposes a novel approach to optimize the charging/discharging schedule of battery energy storage systems in the microgrids of prosumers based on the energy router-based energy sharing structure. The proposed model aims to improve each prosumer's revenue with the arbitrage scheme in the peer-to-peer energy trading market. A novel internal pricing mechanism is presented according to the sharing energy in the prosumer community. A multi-objective evolutionary algorithm is implemented to solve the optimal solutions, and the fuzzy-decision-making method is used to select the schedule from the Pareto frontiers. The simulation results show that each prosumer's profit has been increased under different scenarios compared with the optimal profit of independent operation in the utility grid, with the reduction of the energy interchanged with the grid and the increase of the energy storage system life time. The experimental platform validates the feasibility of the energy router-based energy sharing structure for microgrids of prosumers.

This article presents a hybrid ac/dc system constructed by multiport energy routers (MERs), which have potential application prospects in future energy Internet. Two typical types of MER in the system are studied, and the selected main circuits are easy to realize multiple forms of power supply with high reliability, plug-and-play access of distributed generations, and high expansibility of power ports. The corresponding control and protection systems are developed to ensure the regular operation of MERs, and a smart energy management scheme is presented for the power flow management of MERs to meet the expectations of power consumers. Two MER prototypes are implemented, of which the experimental results validate the correctness of parameter design and the effectiveness of the control and energy management strategies, showing the satisfactory performance of MERs.

The optimal control of state‐of‐charge (SOC) for superconducting magnetic energy storage (SMES), which is used to smooth power fluctuations from wind turbine, is essential to improve its technical and economical performance. Without an efficient control strategy, the SMES may go to the state of over‐charge or deep‐discharge, which will pose a significant effect on its service life and its technical performance. In this study, combined with wind forecasting technology and real‐time monitoring of SOC for the SMES, a double fuzzy logic control strategy is proposed that is applied to regulate SOC of SMES with the purpose of not only effectively smoothing the power fluctuations of wind turbine, but also preventing the SMES from occurring of the state of over‐charge/deep‐discharge and adjusting it to the appropriate SOC. The effectiveness of the proposed control strategy is verified by the simulation results.