An overmodulation (OVM) technique is proposed based on Fourier analysis. The OVM trajectory is a mixture of 6 arc segments of the inscribed circle and 6 vertices of the voltage hexagon. By adjusting the holding angle at each vertex, the modulation index is determined. The fundamental component is expressed as a function of the holding angle, and the linearity with the modulation index is obtained by the inverse relation. This algorithm guarantees seamless transitions from the space vector PWM (SVPWM) to OVM and finally to the six-step. Apart from the VVVF control, the proposed algorithm works well with the interior permanent magnet synchronous motor (IPMSM) current controller. By computer simulation and experimental evidences, the effectiveness is demonstrated.

A direct deadbeat voltage control design method for inverter-based microgrid applications is proposed in this paper. When the inductor-capacitor (LC) filter output voltage is directly controlled using voltage source inverters (VSIs), the plant dynamics exhibit second-order resonant characteristics with a load current disturbance. To effectively damp the resonance caused by the output LC filter, an active damping strategy that does not cause additional energy loss is utilized. The proposed direct deadbeat voltage control law is devised from a detailed, actively damped LC plant model. The proposed deadbeat control method enhances voltage control performance owing to its better disturbance rejection capability than the conventional deadbeat or proportional-integral-based control methods. The most important advantage of the proposed deadbeat control method is that it makes the deadbeat control more robust by bringing discrete closed-loop poles closer to the origin. Simulation and experimental results are shown to verify the enhanced voltage control performance and stability of the proposed voltage control method.

Synchronous reluctance motors (SynRM) show nonlinear behavior in the high torque region due to core saturation, especially on the d-axis. In this study, the maximum torque per ampere (MTPA) solution is sought in the mathematical frame. Firstly, flux data are obtained from finite element method (FEM), and fitted as the plane functions of currents by the least square method. Thereafter, the inductances are derived as binomials in i_d and i_q. These analytic expressions of inductances are used in deriving a necessary condition for the MTPA, and constructing an on-line MTPA control method. The effectiveness is verified through simulation and experimental results.

Superconducting magnetic energy storage (SMES) system is getting increasing acceptance in variation applications of power system because of its higher efficiency and faster response. This paper proposes a high quality power conditioner system for the SMES system operation. The power conditioner consists of a voltage source converter using IGBT (Insulated Gate Bipolar Transistor). In order to compensate several problems such as voltage sag and harmonic current flowing in to utility, active filter systems could be a good solution method. SMES is a very good promising source due to the high response time of charge and discharge. This paper presents a simulation technique for a decision method of the specification of the active filter system combined with SMES system. Through the results of several analyses and simulations carried out by PSCAD/EMTDC, this paper demonstrates the significant effect of the control by SMES on the improvement of power system performance. Based on this simulation, authors developed a power conditioner connected to the utility system. It was shown that the developed power conditioner was well-designed and effective.

This paper describes the design results, loss analysis, and experiment testing of the real manufactured toroid-type superconducting magnetic energy storage (SMES). We analysed heat load through the conduction and radiation of the cryostat and magnetization loss caused by the charging and discharging of the toroid-type SMES system. We also measured the characteristics of toroid-type SMES under three different types of operating conditions (steady state, one-cycle charging and discharging, series charging and discharging). The fundamental design specifications and the data obtained from the experiment will be applied to a large-scale toroid-type SMES system design.

Low-power photovoltaic distributed generators are increasing rapidly in number by the grids of the modern era, but they also bring up the concern of grid stability. To maintain grid stability, it is essential for the network operators to update the grid codes at regular intervals due to the case of highly penetrated grid-connected photovoltaic systems (GCPVs). Integration of large-scale electrical grids with renewable energy sources, one being photovoltaic systems, faces the challenge of riding through low-voltage (LVRT) phases. As compared to the previous grid codes for power generation, recent advances require distributed generation resources to provide for such capabilities under grid faults. This work contributes to the ongoing investigation of this specified and destabilizing fault condition. Various simulations of a PV microgrid system are carried out with the ability to ride through low-voltage faults, with the help of a DC-chopper circuit to absorb DC-link over-voltage, and the current is also maintained within acceptable limits according to the required standards. The fundamental contribution of this research is a proposed neural network (NN) control framework. This framework effectively detects voltage sags, comprehends their characteristics, and provides support to the system by injecting reactive current in accordance with the demands imposed by designated grid codes. This NN control model has been systematically developed utilizing data gathered from a vast array of testing simulations conducted under different and dynamic conditions. The proposed strategy, on the other hand, is compared with the RMS fault detection method in combination with the conventional LVRT algorithm. The NN control approach showed better results as compared to the conventional methods in terms of accuracy and robustness, especially when confronted with difficult sag situations.