The challenges of modern power systems with a high level of renewable generation penetration will impose increased ancillary service on Photovoltaic (PV) systems, including frequency regulation. In this paper, a frequency regulation strategy for PV systems without energy storage is proposed. The proposed strategy is divided into two layers: the frequency regulation layer and the power reserve control layer. In the power reserve control layer, a novel power reserve control is proposed as the core element and novel feature. The existing power reserve control for PV systems must estimate the maximum available power, which is difficult because of the variation in environmental conditions and complex modeling of PV systems. Instead, a power tracking control method based on a curtailment power-current curve is proposed. It can automatically track a given reserve ratio under any environmental condition without an irradiance sensor. In the frequency regulation layer, the combination of droop control and virtual inertia control is used to adjust the given power reserve ratio. Simulation results show that the proposed strategy offers good accuracy and tracking speed and can significantly improve the frequency response of the power system.

This study proposes a novel frequency regulation strategy based on a power reserve control method. Unlike existing strategies, irradiance information and complex model estimation are not required, except for the maximum power curve. The suboptimal power point at any irradiance and reserve ratio can be automatically converged with the proposed tracking method. Furthermore, an adaptive step‐size tracking method is proposed to improve the output power fluctuation around the suboptimal power point. The simulation results with several scenarios are used to verify that the proposed strategy can quickly and robustly track a given power reserve ratio under the irradiance and reserve ratio variation conditions. The proposed strategy can significantly improve the frequency response of power systems with photovoltaic (PV) generation.

Coordinated droop control strategies can provide frequency support for AC area grids from wind farms integrated through multi-terminal high-voltage DC (MTDC) transmission. However, such a strategy inevitably causes DC voltage deviation for transmitting AC area frequency information, thereby deteriorating the stability and security of the MTDC system operation. This paper reports an improved adaptive virtual capacitor control strategy that can provide inertial support for the system. Instead of increasing the capacitance of the physical capacitor, a virtual capacitor is generated by utilizing the rest energy of the deloaded wind farm. Furthermore, an S-shape function is designed to adaptively adjust the capacitance of the virtual capacitor based on the operating points of the system, in order to provide a better inertial support than with the fixed virtual capacitor control strategy. The proposed strategy not only enhances the DC voltage nadir but also improves the frequency nadir of the AC area by releasing additional power from the deloaded wind farm., a MTDC system of a four-terminal voltage source converter with two wind farms is simulated using PSCAD/EMTDC. Case studies are conducted to compare and demonstrate the effectiveness of the proposed strategy under sudden load variations.

As microgrids are the main carriers of renewable energy sources (RESs), research on them has been receiving more attention. When considering the increase in the penetration of renewable energy sources/distributed generators (DGs) in microgrids, their low inertia and high stochastic power disturbance pose more challenges for frequency control. To address these challenges, this paper proposes a model predictive control (MPC) secondary control that incorporates an unknown input observer and where RESs/DGs use a deloading virtual synchronous generator (VSG) control to improve the system’s inertia. An unknown input observer is employed to estimate the system states and random power disturbance from the RESs/DGs and load to improve the effect of the predictive control. The distributed restorative power of each DG is obtained by solving the quadratic programming (QP) optimal problem with variable constraints. The RESs/DGs are given priority to participate in secondary frequency control due to the proper weighting factors being set. An islanded microgrid model consisting of multiple photovoltaic and wind power sources was built. The simulation results demonstrate that the proposed method improves the system frequency, restoration speed, and reduces frequency deviations compared with the traditional secondary control method.