In this paper, we propose a frequency and voltage control strategy for a standalone microgrid with high penetration of intermittent renewable generation systems, which might cause large frequency and voltage deviation in the system due to unpredictable output power fluctuations. To this end, a battery energy storage system (BESS) is suggested for generating the nominal system frequency instead of a synchronous generator, from a frequency control perspective. This makes the system frequency independent of the mechanical inertia of the synchronous generator. However, a BESS has a capacity limitation; a synchronous generator is used to maintain the state of charge (SOC) of the BESS at a certain value. For voltage control, we proposed that a reactive power/active power (Q/P) droop control be added to the conventional reactive power controller. By adding a Q/P droop control, renewable generation acquires a voltage-damping effect, which dramatically alleviates the voltage fluctuation induced by its own output power fluctuation. Simulation results prove the effectiveness of the proposed control strategy from both frequency and voltage control perspectives.

In this paper, a simple and cost-effective symmetric sensing coil set to be used for metal object detection (MOD) in a stationary wireless electric vehicle charger is newly proposed. Compared to the conventional non-overlapping sensing coil using the magnetic field change detection method, the proposed symmetric sensing coil set design offers the considerable advantage of eliminating all blind zones, i.e., regions where metal is undetectable in the conventional method. Moreover, by reducing the number of layers to one, the fabrication of the proposed sensing coil is easier and more cost-effective. The design of the proposed sensing coil is optimized for highly sensitive metal object detection based on a sensitivity equation and on finite element method simulations. An experiment conducted with a metal object $40 \times 40 \text{mm}^2$ in size and a 20A transmitting (Tx) coil current verifies the reliability and blind-zone elimination feature of the proposed sensing coil.

This paper presents a method to seek the PI controller parameters of a PMSG wind turbine to improve control performance. Since operating conditions vary with the wind speed, therefore the PI controller parameters should be determined as a function of the wind speed. Small-signal modeling of a PMSG WT is implemented to analyze the stability under various operating conditions and with eigenvalues obtained from the small-signal model of the PMSG WT, which are coordinated by adjusting the PI controller parameters. The parameters to be tuned are chosen by investigating participation factors of state variables, which simplifies the problem by reducing the number of parameters to be tuned. The process of adjusting these PI controller parameters is carried out using particle swarm optimization (PSO). To characterize the improvements in the control method due to the PSO method of tuning the PI controller parameters, the PMSG WT is modeled using the MATLAB/SimPowerSystems libraries with the obtained PI controller parameters.

In this article, a machine learning algorithm is applied for the first time in inductive power transfer (IPT) to find a ferrite core structure with high magnetic coupling between transmitting (Tx) and receiving (Rx) coils for an electric vehicle (EV) wireless charging system. Since formula-based theoretical design is not available due to the nonlinear magnetic field distortion stemming from the presence of the ferrite core in an IPT system, the proposed core structure design has been achieved through finite-element analysis simulation-based data learning. The proposed design methods are so general that they can be applied to any conventional IPT coil design. Furthermore, it can optimize the core structures for high coupling coefficient, mutual inductance, desired magnetic flux density in the specific area, etc. By training only 0.011% data out of the total possible cases, it is verified by simulation and experiment that the ferrite core structure obtained by the proposed method has a mutual inductance that is 0.6% higher than that of the conventional design level in the case of 15 cm distance between the Tx and Rx coils, even though the volume of the ferrite cores are reduced to 90%. Also, a prototype 3.0 kW stationary EV wireless charging system was implemented and showed fairly better performance than a conventional case.