Many post-disaster surveys have reported on the natural function and effectiveness of fringing reef in preventing the shoreline from the inundation caused by severe weather events. Prior studies mainly focus on the wave propagating, transforming, and breaking on the fringing reefs by assuming that ocean waves propagate in an ideal environment where the wind is absent. However, in the real severe ocean environment, huge surges and waves always occur simultaneously with the strong winds. The wave profile can be easily reshaped by the strong winds, which can also significantly affect the way that ocean waves propagate on the fringing reefs. Therefore, it is necessary to study the hydrodynamics of fringing reefs under the combined action of wind and waves. To study the influences of the onshore wind on the hydrodynamics of solitary wave on the fringing reef, the finite volume method is applied to solve the governing equations of two-phase incompressible flow and a high-resolution numerical wind-wave tank is established in this study. Effects of several main factors are analyzed in detail. The research results show that the onshore wind can significantly increase the maximum wave runup height (maximum by 38.49%) and decrease the wave reflection coefficient of solitary wave (maximum by 8.66%). It is hoped that the research results of this study can enhance the understandings on the hydrodynamics of ocean waves on the fringing reefs during severe weather events.

In order to defraud state subsidies, some unscrupulous users use improper means to steal photovoltaic (PV) power. This behavior brings potential safety hazards to photovoltaic grid-connected operations. In this paper, a photovoltaic power-stealing identification method based on similar-day clustering and interval prediction of the quantile regression model for long short-term memory neural network (QRLSTM) is proposed. First, photovoltaic data are clustered into three similar days by the similar-day clustering according to weather conditions. Second, compared with the quantile regression neural network (QRNN) prediction method, the good prediction performance of the QRLSTM method is illustrated. Third, using the prediction intervals with different confidence levels on three similar days, according to the time scale (short-term, medium-term and long-term) combined with different electricity-stealing judgment indicators, a three-layer photovoltaic power-stealing screening framework is constructed, and the degree of user power stealing is qualitatively analyzed. Last, the power generation data of eight photovoltaic users in a certain region of northwest China and the data of four groups of artificially constructed power-stealing users are used as an example for simulation. The simulation results prove the feasibility of the proposed method in this paper.

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Extreme waves, called rogue waves or freak waves, usually occur unexpectedly and with very large wave heights. In recent years, extreme waves were reported not only in deep ocean waters but also in shallow waters, which threaten the safety and intactness of the coastal regions. To prevent the coastal infrastructures and communities from the devastating power of extreme surges and waves, many coastal defense structures were built along the coastline, i.e., submerged permeable breakwaters. However, the number of studies on the hydrodynamic characteristics of a submerged permeable breakwater under the impact of extreme waves is relatively few. In addition, wave focusing has been widely used to generate extreme waves in the past few decades. Hence, as a necessary supplement to the previous research work, the hydrodynamic performance of a submerged permeable breakwater under the impacts of focused wave groups was numerically studied by using a nonhydrostatic numerical wave model (NHWAVE). The influences of several main factors, such as the incident significant wave height, water depth, wave peak period, porosity of the breakwater (n), and the side slope angle of the breakwater, were considered. It is expected that the results of this study will further strengthen the research on the hydrodynamic characteristics of a submerged permeable breakwater under extreme wave conditions.

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