With the large-scale integration of wind power, the frequency stability of the power system is facing a significant challenge due to the wind power generation system typically operating in maximum power point tracking (MPPT) mode. Traditional frequency support control methods for wind turbines (WTs) do not consider the state of WTs and the frequency changes simultaneously. This paper proposes a fuzzy adaptive frequency support control strategy for WTs with improved rotor speed recovery. Based on fuzzy logic control, the proportional gain is adaptively adjusted using the rotor speed and frequency deviation to support the grid frequency. It can fully utilize the frequency support capability of WTs with more available rotor kinetic energy while averting the over-deceleration of WTs with low rotor speed. Moreover, as the frequency deviation increases, the output power of WTs is increased by a larger proportional gain to alleviate the excessive frequency degradation. In response to the shortcomings of traditional rotor speed recovery methods, an improved rotor speed recovery method is presented by integral control, which can restore the rotor speed in stages without affecting the frequency support performance of WTs and can avoid secondary frequency drop (SFD). Simulation results verify the effectiveness of the proposed scheme.

This paper mainly focuses on how to provide frequency supports by the doubly fed induction generator (DFIG) during system disturbances. Two coordinated controls that enable system frequency supports by DFIG-based wind turbines (WTs) are proposed in this paper. The first control scheme seeks to render system support via simultaneously utilizing the energy from the installed super-capacitor between the back-to-back converter of DFIG, and WT rotational kinetic energy (KE). The second one stabilizes system frequency by firstly exerting the installed super-capacitor energy and then WT rotational KE via a unique cascading control. Both proposed coordinated control schemes jointly utilize two virtual inertia sources, namely super-capacitor in the DFIG and rotor rotational mass in the WT to fast provide system frequency support. However, the second proposed one stands itself out by reducing its impaired impacts on the overall wind energy production. Two proposed controls on rapidly providing frequency support are effectively verified and compared in detail by different system disturbances in the DIgSILENT/Powerfactory software.

The electricity spot market is now being implemented in China. Demand response, as a kind of flexible resource, is also being studied and explored for the constructed power market. Among the many demand response applications, the virtual power plant (VPP) as an aggregator of distributed energy resources (DERs), receives ever-increasing attention. However, the participation manner and related impacts of the VPP to the electricity spot market are still unknown within the current power market rules. Under this background, obeying the present trading rules of China’s electricity spot market, a two-stage dispatching model with optimized bidding and operating strategy in the day-ahead (DA) and real-time (RT) market for the VPP is proposed. In the designed model, the conditional risk value (CVaR) is adopted to address the risk encountered by the uncertainty of the electricity spot market price. The impact of the user-side over-deviated revenue mechanism (UORM) of the China spot market on the income of the VPP in the DA and RT market is also analyzed. For a full evaluation, different coefficients for the influence of DA and RT risk, UORM, and energy storage system (ESS) are tested to investigate their respective impacts on the revenue of the VPP. The simulation cases prove that the proposed method is helpful for the VPP to optimize DERs’ output in the electricity spot market according to its own risk preference.

The integration of a large number of renewable energy sources (RES) into the micro-energy grid (MEG) brings certain challenges to its optimal dispatching, especially the impact of RES and load prediction error on optimal dispatching. Therefore, this article proposes a multi-timescale coordinated optimization framework for economic dispatch of MEG considering prediction error, including three stages: day-ahead economic dispatch, intra-day rolling optimization and real-time adjustment. In the day-ahead and intra-day stages, the device's output is solved with the objective of optimal system economy. The MEG is divided into three subsystems in the real-time adjustment stage using distributed model predictive control (DMPC). The subsystems cooperate to correct the intra-day device output, which reduces the complexity of solving system optimization problems. Meanwhile, considering that the prediction horizon in DMPC usually remains constant during the optimization, which affects the control performance of DMPC. This article analyzes the impact of the prediction horizon and control horizon on the control performance of DMPC. Then a DMPC method with adaptive adjustment of the prediction horizon according to the prediction errors of RES and loads power is proposed, which can balance the stability and prediction accuracy of the system. Finally, the case studies verify the feasibility of the proposed strategy.

The capability of black start (BS) is vital for microgrid, which can reduce the interruption time and the economic loss brought by outage. This paper presents a black start strategy for the microgrid with PV and hybrid energy storage systems, based on a serial restoration strategy. The primary reference source with black start capability runs V/f control mode to establish pre-specified voltage and frequency. After that, check the requirements to connect the loads and the photovoltaic (PV) system. If the requirements are met, adjust the active power and reactive power of the PQ adjustable microsources, and then the loads and the PV are connected to the bus. If the loads and microsources are all connected, the BS procedure is finished. The experimental results of microgrid black start validate the effectiveness and feasibility of the strategy.

The diode rectifier unit (DRU) based low-frequency AC transmission system is an attractive option for integrating offshore wind power due to its low construction cost and high economic efficiency. However, since DRU cannot transmit active power to offshore wind farms, an additional black start power source is required to provide the initial energy required for the wind turbines. In this paper, an auxiliary converter-based black start strategy is proposed for the above transmission system. The position and topology of the auxiliary converter are introduced, and the method for selecting its capacity is analyzed. The black start strategy of the transmission system is then designed, including the black start for the auxiliary converter and the gridforming wind turbines based on self-synchronizing control. Finally, a simulation model is developed using PSCAD/EMTDC, and the simulation results demonstrate the feasibility and effectiveness of the proposed black start strategy.