This paper proposes a frequency regulation strategy applied to wind turbine generators (WTGs) in an isolated grid. In order to complement active power shortage caused by load or wind speed change, an improved deloading method is proposed to improve the regulation capabilities in different speed sections and to provide WTG power reserves. Considering torque compensation may cause power fluctuation, speed reference of conventional pitch control system should be reset. Moreover, to suppress disturbances caused by load and wind speed as well as overcome dependence on system parameters, a model predictive controller (MPC) is presented to generate torque compensation for each deloaded WTG, which allows each WTG to react to the disturbance differently, depending on its generator speed and the frequency deviation. Hardware-in-the-loop simulation and experimental results show that the proposed strategy can enhance frequency response ability during load changes and smoothen power fluctuations resulting from wind speed variations.

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The volatility of wind power generations could significantly challenge the economic and secure operation of combined electricity and heat networks. To tackle this challenge, this paper proposes a framework of optimal dispatch with distributed electric heating storage based on a correlation-based long short-term memory prediction model. The prediction model of distributed electric heating storage is developed to model its behavior characteristics which are obtained by the autocorrelation and correlation analysis with external factors including weather and time-of-use price. An optimal dispatch model of combined electricity and heat networks is then formulated and resolved by a constraint reduction technique with clustering and classification. Our method is verified through numerous simulations. The results show that, compared with the state-of-the-art techniques of support vector machine and recurrent neural networks, the mean absolute percentage error with the proposed correlation-based long short-term memory can be reduced by 1.009 and 0.481 respectively. Compared with conventional method, the peak wind power curtailment with dispatching distributed electric heating storage is reduced by nearly 30% and 50% in two cases respectively.

In most grid-connected power converter applications, the phase-locked loop (PLL) is probably the most widespread grid synchronization technique, owing to its simple implementation. However, its phase-tracking performance tends to worsen when the grid voltage is under unbalanced and distorted conditions. Many filtering techniques are utilized to solve this problem, however, at the cost of slowing down the transient response. It is a major challenge for PLL to achieve a satisfactory dynamic performance without degrading its filtering capability. To tackle this challenge, a hybrid filtering technique is proposed in this paper. Our idea is to eliminate the fundamental frequency negative sequence (FFNS) and other harmonic sequences at the prefiltering stage and inner loop of PLL, respectively. Second-order generalized integrators (SOGIs) are used to remove FFNS before the Park transformation. This makes moving average filters (MAFs) eliminate other harmonics with a narrowed window length, which means the time delay that is caused by MAFs is reduced. The entire hybrid filtering technique is included in a quasi-type-1 PLL structure (QT1-PLL), which can provide a rapid dynamic behavior. The small-signal model of the proposed PLL is established. Based on this model, the parameter design guidelines targeting the fast transient response are given. Comprehensive experiments are carried out to confirm the effectiveness of our method. The results show that the settling time of the proposed PLL is less than one grid cycle, which is shorter than most of the widespread PLLs. The harmonic rejection capability is also better than other methods, under both nominal and adverse grid conditions.

Frequency stability in an isolated grid can be easily impacted by sudden load or wind speed changes. Many frequency regulation techniques are utilized to solve this problem. However, there are only few studies designing torque compensation controllers based on power performances in different Speed Parts. It is a major challenge for a wind turbine generator (WTG) to achieve the satisfactory compensation performance in different Speed Parts. To tackle this challenge, this paper proposes a gain scheduled torque compensation strategy for permanent magnet synchronous generator (PMSG) based wind turbines. Our main idea is to improve the anti-disturbance ability for frequency regulation by compensating torque based on WTG speed Parts. To achieve higher power reserve in each Speed Part, an enhanced deloading method of WTG is proposed. We develop a new small-signal dynamic model through analyzing the steady-state performances of deloaded WTG in the whole range of wind speed. Subsequently, H ∞ theory is leveraged in designing the gain scheduled torque compensation controller to effectively suppress frequency fluctuation. Moreover, since torque compensation brings about untimely power adjustment in overrated wind speed condition, the conventional speed reference of pitch control system is improved. Our simulation and experimental results demonstrate that the proposed strategy can significantly improve frequency stability and smoothen power fluctuation resulting from wind speed variations. The minimum of frequency deviation with the proposed strategy is improved by up to 0.16 Hz at overrated wind speed. Our technique can also improve anti-disturbance ability in frequency domain and achieve power balance.