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, Available online , doi: 10.16516/j.ceec.2024-358
Abstract:
Introduction The analysis of limited icing capacity of wind turbine in cold wave weather is difficult to predict, resulting in inaccurate wind power prediction and insufficient decision-making basis for wind power dispatching. Method Through the prediction model of the limited icing capacity of wind turbine, the limited icing capacity of wind turbine in extreme cold wave weather process in Guangxi was analyzed and summarized by using conventional meteorological observation data, wind turbine shutdown actual data and numerical model data. Result The results show that the reference value and accuracy of icing prediction are effectively improved by integrating the numerical prediction products with the actual data of limited icing capacity and applying regression analysis for real-time correction. In addition, the icing prediction model can effectively respond to the strong cold air system southward affecting the Guangxi wind farm, but the response to the turning weather is insufficient, and the prediction result is larger than the actual data. At the same time, the numerical model prediction results have amplitude deviation and phase deviation, and the predicted value is larger than the actual value in this process. In terms of prediction effect, the model performs better in air temperature prediction than relative humidity and wind speed prediction, and the prediction effect of meteorological elements in high altitude areas is generally better than that in low altitude areas. Conclusion Based on the above conclusions, some suggestions are put forward, such as strengthening the early warning and prediction ability of cold wave, carrying out the upgrading and transformation of icing capacity prediction system, so as to improve the prediction accuracy of the limited icing capacity of wind turbine in extreme cold wave weather.
, Available online , doi: 10.16516/j.ceec.2024-334
Abstract:
Introduction The implementation of carbon neutrality and carbon peaking policies has promoted the rapid development of wind power, a clean energy source. In recent years, extreme weather and climate events occur frequently, and with the large-scale production and grid connection of wind power, the issue of meteorological disasters in wind farms caused by extreme weather has become more prominent. Extreme weather not only poses severe challenges to wind power development, but may also affect the grid stability and reliability of power supply. Therefore, it is necessary to deeply understand the mechanism of how extreme weather affects wind power development, and take effective prevention and response measures to ensure the healthy and safe development of the wind power industry. Method By reviewing the recently published literature on meteorological disasters in wind farms, the paper classified the high-impact weather affecting wind power development into two major categories: extreme weather and adverse weather. It summarized the impacts of extreme weather such as typhoon, strong wind, lightning, rainstorm, sandstorm, cryogenic freezing and high temperature, as well as adverse weather such as calm breeze wind, salt spray and sea fog, on wind farm planning, resource assessment, survey and design, installation construction, infrastructure, wind power output and wind power prediction during the planning and design, construction, and operation stage of wind farm. Result In the planning and design stage, it is necessary to identify and assess the risks of high-impact weather, and carry out scientific macro and micro site selection. In the construction stage, rainstorm, cryogenic freezing and so on can affect transportation and delay the construction period; strong winds, heavy rain and so on affect hoisting and cause operational risks; sea fog, lightning and so on may affect the safety of offshore wind power construction. In the production and operation stage, high-impact weather can lead to large-scale shutdown of wind farms and loss of output, and even threaten the safe and stable operation of the power grid. Except for tropical cyclones of a certain intensity, other high-impact weather events are not conducive to wind power output. The frequent occurrence of high-impact weather leads to a reduction in the accuracy of wind power forecasting. Conclusion Finally, measures to cope with high-impact weather are proposed, including strengthening emergency management and high-impact weather monitoring and early warning, considering the impact of high-impact weather on wind power forecasting, and strengthening the construction of energy storage system.
