The high penetration of renewables to a power system causes power imbalance and reduced system inertia, resulting in various frequency instability problems. Therefore, the system operator is forced to curtail a certain amount of power from several wind power plants (WPPs) and prepare for effective frequency support in case of contingency. When a large disturbance occurs, some WPPs in the curtailed control mode are able to provide the power reserve for maintaining the power balance. The other WPPs in the maximum power point tracking control mode can give the inertial response to support the frequency stability. Therefore, there is a need for a method to assist the system operator in determining the proper control mode for multiple WPPs. This paper proposes an effective power curtailment method based on the new hybrid binary and continuous grey wolf optimization method for properly operating all WPPs in two control modes. This curtailment method provides key information to the system operator on operating the WPPs to provide the required amount of power curtailment and maximum frequency stability support. The effectiveness of proposed method is verified with several case studies on the practical Korea electric power system with 20 WPPs, which have a hosting capacity of 10.6 GW.

The high penetration of converter-based distributed generations (DGs) to power system can give rise to the lack of rotational inertia while replacing the conventional synchronous generators (SGs), which provide the primary frequency reserve (PFR) in power systems. As the result, the decrease in PFR aggravates the frequency stability. To overcome this problem, the droop coefficients of governors in the remaining conventional SGs must be re-determined newly and properly. This paper proposes a new solution based on the grey wolf optimization (GWO) method to optimally select the droop coefficients of SG governors in the low-inertia large-scale power system due to the high penetration of renewables. The proposed solution is very effective for reducing the computational effort significantly, and it is able to recover not only the steady-state but also the transient frequency stability. To verify the effectiveness of proposed optimization solution based on the GWO method, several case studies are carried out on the practical Korea electric power system with the penetration of wind power plants of 4 GW.

When renewable energy-based generations are increasing, they are subject to cause frequency stability problems in a power system. To solve this problem, various virtual inertial control methods (VICMs) have been recently developed. However, they all have dealt not with the steady-state frequency stability, but only with dynamic frequency stability issues. In particular, the wind power plants (WPPs) operated by these VICMs can only provide a similar inertial response (IR) to that by conventional synchronous generators without providing the primary frequency response (PFR). This results in lowering the settling frequency (SF) below the maximum steady-state frequency deviation (MSSD) band.This paper proposes the new hierarchical control strategy for the WPPs, which are operated by three virtual frequency response control methods (VFRCMs) to provide both IR and PFR. Firstly, the VFRCM-1 provides virtual IR. Next, the VFRCM-2 increases the output power from the WPPs to prevent the frequency drop, which can occur after the frequency nadir is arrested. Finally, the VFRCM-3 makes the WPPs possible to raise the SF above the MSSD band by providing the virtual PFR. The effectiveness of proposed hierarchical control strategy is verified by several case studies on the IEEE 39-bus test system with the high penetration of renewables.

As renewable energy penetrates the power system, system operators are required to curtail output power from generation units to balance the power supply and demand. However, large curtailment from wind power plants (WPPs) may instantly cause excessive output power decrement, causing system frequency to drop significantly before reaching its nominal value. In order to solve this problem, this paper proposes a cooperative control framework to determine the operation of WPPs in two control methods, which are the stepwise inertial control (SIC) method and the curtailed control method. The proposed framework first determines the WPPs to operate in the curtailed control method to provide the required power curtailment. Next, it determines the WPPs to operate in the SIC method considering their releasable kinetic energy to provide an effective inertial response and compensate for the sudden excessive output power decrement caused by other WPPs operated in the curtailed control method. Therefore, each WPP is operated in one of two control methods to provide required power curtailment while reducing the sudden excessive output power decrement. To verify the effectiveness of the proposed cooperative control framework, several case studies are carried out on the practical South Korea electric power system.

The high penetration of wind power decreases the system inertia and primary frequency reserve while replacing the conventional synchronous generators (SGs). Therefore, if the system operator does not take appropriate action on the remaining generation units (GUs) operation, high penetration of wind power will aggravate the frequency stability. To solve this problem, wind power plants (WPPs) may provide the inertial response and primary frequency response (PFR) to support the frequency stability. However, due to the variability of renewable energy, WPPs may not provide adequate frequency response whenever it is required. This paper proposes an algorithm to determine the operation of GUs to provide appropriate PFR for a power system with high penetration of wind power. Through the proposed algorithm, it calculates the required PFR to restore the decreased frequency stability caused by the high penetration of wind power. Then, while considering the available PFR from WPPs, it redetermines the droop coefficient of SGs governor to provide the sufficient PFR to recover the frequency stability. Finally, the effectiveness of the proposed algorithm is verified on the practical Korean electric power system.