Study On The Evaluation Method Of Wind Curtailment Power Of Wind Farm

Power grid showing the emergence of wind power peak shaving, tidal flow, is due to peak shaving and grid constraint problem, along with growing of wind power installed scale in recent years. Due to operation of multiple wind farms in power grid, how to "open, fair and just" arrangements of wind farm in power grid peak shaving, adjusting the trend of the current and realizing reasonable planning of power grid has become facing new problems for dispatch specialty, while evaluating of wind curtailment power will be an important indicator of this work area. So, proposing two novel wind curtailment power statistical methods:"wind tower", "wind tower neural network method" in this paper, which can solve the problem of statistical difficulty in evaluating wind curtailment power of wind farm in China in a certain extent, mastering accurately wind curtailment power of wind farm is of great guiding significance to realize recycle of wind curtailment power, reasonable planning of power grid and " Three Public " dispatch of wind power.First of all, in order to get the relationship between wind speed and power, regarding Bei Si Jia Zi wind farm of Liaoning Chaoyang Beipiao as the research object in this paper, studying the statistical regularities changes of wind speed and wind power of the wind farm according to the wind farm wind tower actual measuring history data and wind farm wind power history running data, determine wind speed data and power data, lay the data foundation for wind curtailment power evaluation model.Secondly, in order to forecast a good wind speed, established the physical model of wind speed, using wind profiler method and analytical method based on potential flow theory, extrapolated from wind tower wind speed obtained wind speed of every wind turbine hub height. In order to obtain the exact relationship of wind speed-power. Obtained every wind turbine wind speed data and corresponding wind turbine output power data by extrapolating, using maximum value method, method of bean and method of maximum probability to build model and simulate for actual measured power curve of every wind turbine respectively, and three methods were compared and analyzed, simulation results show that the maximum probability method can reflect measured wind speed-power curve model likely, best effect are obtained. To achieve the theoretical basis for realization of wind curtailment power evaluation model of wind tower.Then, have studied "Tower Method", which is calculating theory generating power of wind farm in the corresponding period, according to the actual measured tower data and actual measured power curve of each unit, and then obtain the wind curtailment power; Studied the wind tower neural network method, according to the wind speed and wind direction history data of wind tower actual measuring of different height, combined with historical actual measuring power data of every wind turbine, establishing neural network model, and sample data is inputted into the neural network model, to obtain theory power, and obtained wind curtailment power; Studied model machine method and area integral method, which is used to count wind curtailment power size, statistical accuracy of the two methods are analyzed and evaluated; described the advantages and disadvantages of the above four methods in detail, and made four kinds of statistical methods of wind curtailment power data table.Last, according to the wind farm micro meteorological analysis of wind farm, draw the conclusion:the "Tower Method" and " Machine Model Method " both are close to the wind farm theory power relatively, can reflect the wind farm wind curtailment power size well, "Tower Method" performance the better effect, while wind tower of neural network method has certain reference value in the low speed wind power curtailment assessment, solving the problem of China's wind curtailment power statistics that is difficult in a certain extent, providing a deep theoretical foundation and basis for domestic subsequent wind power wind curtailment project development.