With the rapid development of renewable energy sources, the equivalent inertia of powersystems is decreasing, which leads to more drastic dynamic frequency response. This paper proposes an event-driven fast frequency...
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Digitally controlled PWM inverters are interfered by quantization errors caused by A/D converters (ADC) and Digital Pulse-Width Modulators (DPWMs), which may result in undesirable limit-cycle oscillations (LCO). In th...
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Different from power prediction for a single wind farm, the regional wind power prediction is to predict the total power of multiple wind farms located in the same region. Normally, abundant information on spatiotempo...
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ISBN:
(纸本)9781538645390
Different from power prediction for a single wind farm, the regional wind power prediction is to predict the total power of multiple wind farms located in the same region. Normally, abundant information on spatiotemporal correlations and nonlinearity is implicated in regional wind farms, and thus selecting the most representative explanatory variables becomes one of the most crucial issues to construct an effective regional wind power prediction model. This paper proposes a spatiotemporal quantile regression (SQR) algorithm to perform short-term nonparametric probabilistic prediction of regional wind power, incorporating the advantages of the hybrid neural network (HNN) and quantile regression (QR). In the approach, the high dimensional input data are reorganized into a feature graph that is ready for feature extraction by the HNN. And the advantages of HNN can therefore be utilized to extract the representative features and construct nonlinear regression models. Meanwhile, by following the QR rules, the model can obtain quantiles and perform probabilistic prediction. By properly addressing the explanatory variable selection issue, the approach provides a specific solution for regional wind generation probabilistic prediction with huge input information. Test results on a region with 10 wind farms demonstrate the effectiveness of the proposed approach.
With the increasing intermittent renewable sources integrated into active distribution networks (ADNs), distributed management should be adopted to improve the control and management level of ADNs effectively. Accurat...
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Higher penetration of wind power generation will introduce an unprecedented amount of uncertainty into power grid that might affect the risk assessment of cascading failures. To reflect the impact of wind power uncert...
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With the increasing penetration of renewable energy, the fluctuation of renewable energy source (RES) is one of the most important factors that affect the reliability and economy of powersystem. It is crucial to cons...
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Traditional shielding layer protector of single-core cable can only suppress lightning and fault overvoltage, and can not solve the induced overvoltage and harmonic overvoltage caused by harmonics. When a discharge da...
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The high penetration of renewable energy in powersystems leads to significant net load fluctuations. Coal-fired power generators conventionally designed for baseload operations are expected to be flexible with cyclin...
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As various industries experiencing post-pandemic economic recovery, powersystems face increased challenges. Short-term power load forecasting for regional power grids can assist in anticipating load fluctuations and ...
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The categories of black start resources (BSR) have been extended in the modern smart grid with the penetration of renewable energies. On one hand, the distributed renewable energy resources (RES) and storage facilitie...
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