Yong Cheol Kang

To enhance the frequency nadir without causing the excessive deceleration of the rotor speed (${{{{\omega }}}_{{r}}}$), synthetic inertia control (SIC) schemes of a wind turbine generator (WTG) need to provide incremental power in response to event magnitude and ${{{{\omega }}}_{{r}}}$. Conventional stepwise SIC approaches face limitations during large events due to the increase of predefined incremental power, which does not match the actual event size. This paper presents an SIC strategy for WTGs that adjusts incremental power in relation to event size and ${{{{\omega }}}_{{r}}}$. During the frequency-support phase, the incremental power is modulated based on the frequency deviation, along with a control gain proportional to ${{{{\omega }}}_{{r}}}$, rather than the rate of change of frequency. While this approach accounts for the power imbalance, it remains vulnerable to noise and delays in practical applications. After the frequency-support phase, the proposed method decreases the active power reference in accordance with ${{{{\omega }}}_{{r}}}$, ensuring it stabilizes within a secure operating range. Following stabilization, the WTG transitions smoothly back to maximum power point tracking operation. Simulation results indicate that the proposed approach significantly enhances the frequency nadir during large events, even under low wind conditions, while avoiding excessive deceleration of the rotor speed.

Increasing penetration of replenished renewable energy sources (RES) to the power grid is inevitable and brings stability challenges to traditional electric power systems (EPS). One of them is the frequency fluctuation due to the high participation of RES in the EPS. To reduce the grid frequency deviation, in this paper, an autonomous frequency regulation (FR) controller is proposed using the power of battery energy storage systems (BESS) in electric vehicle charging stations (EVCS) while providing the charging service. A proportional-integral (PI) controller scheme with a contribution factor is used in the proposed FR controller. The contribution factor determines the maximum power from BESS used for the proposed FR. The required power for the FR is then used to generate the setpoint for the inner-loop current controller of the grid-connected inverter (GCI). An impedance-based stability analysis considering the PI current controller and PLL gains for the LCL-filtered GCI is conducted. For the performance evaluation, the proposed FR controller is demonstrated in the IEEE 14-bus power system in PSCAD simulation.

Following a frequency event in a power system, synthetic inertia control (SIC) of a wind turbine generator (WTG) can improve the frequency nadir by instantly releasing the stored kinetic energy in the rotating masses. However, SIC might lower the settling frequency below the maximum steady-state frequency deviation, thereby disabling automatic generation control (AGC). This delays frequency recovery to the nominal value. This paper proposes a closed-loop SIC scheme for a WTG in association with slightly over-speeded deloading operation (SODO) that can improve both the frequency nadir and settling frequency. To achieve this, prior to an event, the proposed SIC scheme performs SODO, which can store more releasable energy into the rotating masses of a WTG while minimizing the energy loss. The proposed scheme can improve the frequency nadir by releasing more energy, improve the settling frequency, which enables AGC, and avoid over-deceleration of the rotor speed of a WTG in the low wind speed region. Simulation results clearly demonstrate that the proposed SIC scheme can improve both the frequency nadir and settling frequency under various wind conditions, event sizes, and penetration levels, thereby supporting the frequency stability in a power system that has a high penetration of wind power.

Power electronic converters are more and more widely used, and abnormal temperature of converter components is the most important factor in converter failure. To improve the reliability of the converter design, it is necessary to monitor the temperature of key components in the converter during the prototype test stage. The temperature measurement method of infrared thermal images has rich temperature information, wide detection range, and does not affect the original circuit design. However, in the current automatic temperature measurement methods, it is necessary to manually establish a standard matching template for the infrared thermal image of the circuit to be tested, which indicates a large workload and poor versatility. This paper proposes a method for fully automatic temperature monitoring of converter components. This method is based on a deep learning object detection algorithm, which can automatically identify the type of converter components, obtain partial infrared thermal images of components through heterogeneous image registration, achieve accurate component temperature monitoring and facilitate the converter state monitoring and fault detection. The advantages of this method are: 1) there is no need to manually establish a standard template for each converter; 2) it can monitor the converter temperature without manual intervention; 3) combining the temperature information and circuit prior knowledge, the state monitoring and fault diagnosis can further be realized. The experimental results also verify the feasibility and accuracy of this method.

This paper proposes a frequency-smoothing scheme of a doubly-fed induction generator (DFIG) that can significantly eliminate the frequency fluctuations caused by continuously fluctuating wind speeds. To achieve this, a proportional-integral (PI) control loop depending on the frequency deviation instead of a proportional control loop used in conventional schemes is added to the maximum power point tracking loop. The P control loop in the proposed frequency-smoothing scheme eliminates the alternating component in the frequency deviation, whereas the I control loop eliminates the slowly-varying component. The gains for the P control loop and I control loop are suggested for effectively using the rotating masses of a DFIG while avoiding over-deceleration of the rotor speed. The simulation results evidently demonstrate that the proposed scheme nearly removes the frequency deviation under various wind conditions, by using the proposed PI control loop, especially in high penetration levels of wind.

This paper proposes a power-smoothing scheme for a variable-speed wind turbine generator (WTG) that can maintain the frequency within a narrow range under normal operations. The proposed scheme uses an additional control loop based on the frequency deviation that operates in conjunction with maximum power point tracking (MPPT). To improve the energy-absorbing capability in the overfrequency section (OFS) and energy-releasing capability in the underfrequency section (UFS), the scheme suggests separate control gains, which are determined based on the ratio of the output of the additional loop to that of the MPPT loop. The ratio in the OFS is set to decrease with respect to the rotor speed whereas the ratio in the UFS is set to increase with respect to the rotor speed. The simulation results demonstrate that the proposed scheme can significantly lessen the WTG output power fluctuations by adjusting the control gains of the UFS and the OFS even though the WTG output power is severely fluctuating, thereby mitigating the frequency fluctuations. The scheme effectively uses the heavy rotating masses of a WTG as an energy storage system for enhancing the power grid flexibility in terms of frequency, particularly in high penetration levels of variable renewable energy.

To ensure the frequency stability of a power grid, the settling frequency following a frequency event should be stabilized within the maximum steady-state frequency deviation (SSFD) band. If the frequency is stabilized at a value beyond the maximum SSFD band for high penetrations of variable renewable energy, the frequency cannot be restored to the nominal frequency because automatic generation cannot be activated. This paper proposes a primary frequency control support scheme of a doubly-fed induction generator (DFIG) to improve the settling frequency following an event. In the proposed scheme, if the frequency following an event is stabilized at a value beyond the maximum SSFD band, to reduce the output power of synchronous generators, the output power of a DFIG is instantly increased by a constant and maintained until the frequency increases to within the maximum SSFD band. At the same time, the mechanical input power of the synchronous generators is maintained so that the difference between the mechanical input power and electrical output power of the synchronous generators increases the frequency to a value within the maximum SSFD band. The simulation results demonstrate that the proposed scheme can improve the settling frequency while avoiding additional system defense plans when the settling frequency is stabilized at a value beyond the maximum SSFD band.

Correct and fast detection of a micro-grid (MG) islanding is essential to the MG since operation, control, and protection of the MG depend on its operating mode i.e., an interconnected mode or islanding mode. This study describes the design, evaluation and implementation of an islanding detection method for an MG, which includes a natural gas-fired generator, a doubly fed induction generator type wind generator, a photovoltaic generator, and some associated local loads. The proposed method is based on the instantaneous active and reactive powers at the point of common coupling (PCC) of the MG. During the islanding mode, the instantaneous active and reactive powers at the PCC are constants, which depend on the voltage of the PCC and the impedance of the dedicated line. The performance of the proposed method is verified under various scenarios including islanding conditions for the different outputs of the MG, and fault conditions by varying the position, type, inception angle and resistance of the fault, using the PSCAD/EMTDC simulator. This paper also concludes by implementing proposed method into a TMS320C6701 digital signal processor. The results indicate that the proposed method successfully detects islanding for the MG in islanding conditions, and remains stable in fault conditions.