Abstract: A drilling type sidewall coring apparatus, comprising: a main body, a transmission device, a bit mounted on the transmission device, a rack accommodated in the main body, and a plurality of first hydraulic oil cylinders, the transmission device mounted on the rack in a rotatable manner, the first hydraulic oil cylinders mounted on the main body, pistons of the first hydraulic oil cylinders connected with the rack, the telescopic motion of the pistons of the first hydraulic oil cylinders driving the rack to perform radial motion in the main body so as to make the bit protrude or retract from the main body. The electric motor is mounted in the main body and connected with the right angel speed reducer by the soft shaft. The electric motor transmits power by the soft shaft and the right angle speed reducer to drive the bit to rotate, the transmission efficiency is higher.

Abstract: A drilling type sidewall coring apparatus, comprising: a main body, a transmission device, a bit mounted on the transmission device, a rack accommodated in the main body, and a plurality of first hydraulic oil cylinders, the transmission device mounted on the rack in a rotatable manner, the first hydraulic oil cylinders mounted on the main body, pistons of the first hydraulic oil cylinders connected with the rack, the telescopic motion of the pistons of the first hydraulic oil cylinders driving the rack to perform radial motion in the main body so as to make the bit protrude or retract from the main body. The electric motor is mounted in the main body and connected with the right angel speed reducer by the soft shaft. The electric motor transmits power by the soft shaft and the right angle speed reducer to drive the bit to rotate, the transmission efficiency is higher.

Abstract: A method of calculating voltage and power of large-scaled photovoltaic power plant includes following steps. Environment models of varies locations within the photovoltaic power plant are obtained. A photovoltaic display model is established by establishing a photovoltaic cell model, combining the photovoltaic cell model with the environment models, determining a combination of the environmental data on photovoltaic panels and the photovoltaic cell model, and determining a quantitative relationship between a photovoltaic cell power generation state and photovoltaic environment. An inverter model is obtained by modeling inverters connected to photovoltaic cells. A grid-side model is obtained. An electrical energy and voltage forecast model is constructed by integrated the photovoltaic display model, the inverter model, and the grid-side model.

Abstract: A method of computing theoretical power of wind farm based on sample wind turbine method. Historical real-time measured output data of sample wind turbines in the wind farm is statistically analyzed. A theoretical output of the sample wind turbines is analyzed based on a wind power output characteristic and a theoretical output design curve of wind turbine. A theoretical power calculation model of wind farm is constructed based on the historical real-time measured output data of sample wind turbines. A number of wind turbines actually running in real-time is obtained based on real-time information data of wind turbines in the wind farm. An actual operation data of the sample wind turbines is confirmed. The actual operation data is input into the theoretical power calculation model of wind farm. Real-time data of theoretical power of wind farm is output, and an actual operation result of wind farm is comparatively analyzed.

Abstract: A method of calculating theoretical power of wind farm based on extrapolation of anemometer tower data includes following steps. A number of anemometer towers in a wind farm is selected, and analyzing historical data acquired by the number of anemometer towers. An air density is calculated based on the historical data of the number of anemometer towers. A power curve is calibrated based on the historical data of the number of anemometer towers. The power curve is fit based on a wind speed and a wind power of a fan head of each wind turbine based on the historical data. An theoretical power calculation extrapolation model of anemometer tower data is constructed. Real-time anemometer tower wind data and a calibrated air density are inputted into the theoretical power calculation model and calculating the wind power. The theoretical power is obtained.

Abstract: A method of predicating ultra-short-term wind power based on self-learning composite data source includes following steps. Model parameters of an autoregression moving average model are obtained by inputting data. A predication result is obtained by inputting data required by wind power predication into the autoregression moving average model. A post-evaluation is performed to the predication result by analyzing error between the predication result and measured values, and performing model order determination and model parameters estimation again while the error is greater than an allowable maximum error.

Abstract: A method of analyzing wake flow of wind turbine based on multiple wake flow models includes following steps. A number of wake flow model are analyzed. A number of wake flow turbulence models are analyzed based on analysis results of the wake flow models. A number of wake flow combined models are analyzed based on the analysis results of the wake flow turbulence models, and the wind turbine wake flow analysis results of all the wake flow models, wake flow turbulence modes, and wake flow combine models are obtained.