New Technical Achievement! SPRIXIN’s Early Warning Platform of Abnormal Weather Now Available

Time：2022-04-21 Source：SPRIXIN

How to ensure that large-scale new energy power is safely connected to the grid for efficient transmission and use is now the core issue for the steady development of new energy. The accurate forecast of new energy power generation has hence become a good recipe whose accuracy, however, is keen to the accuracy of the weather forecast. On top of optimizing numerical weather forecasting, the demand for accurate forecasting under abnormal weather is also imminent.

Taking into consideration the influence of extreme weather on the accuracy of power forecasting, SPRIXIN developed the Early Warning Platform of Abnormal Weather. The platform’s results of the occurrence of abnormal weather are calculated by our model algorithm whose main input data includes abnormal weather forecasts and early warnings, real-time weather conditions nowcasts, numerical weather forecasts, historical meteorological data, etc. The results together with optimization are then applied to power forecasting to rationally adjust the power forecast values so that the prediction results can adapt to abnormal weather conditions.

Weather Source Upgrade: The Technological Backbone
The numerical weather forecast data used by the standard power forecasting system of many power plants is relatively flat, making it difficult to forecast short-term weather data such as strong winds and low temperatures. There is no direct forecast result of the corresponding parameters for abnormal weather conditions such as cloudy, sandy dust, haze, and snowfall that can affect irradiance. Therefore, for those wind and solar plants in areas with frequent abnormal weather which can very likely cause problems such as wind turbine cut-outs and huge deviations between actual and forecasted photovoltaic output, the efficiency of the power generation of these power plants will be greatly affected and thus harm the safety and stability of the power grid.

To this end, SPRIXIN's Early Warning Platform of Abnormal Weather introduces more information on the weather state than ordinary numerical weather forecasting does and adopts persistent non-numerical abnormal weather sources including smog, dust, heavy rain, snowfall, etc. from our partner institutions specializing in meteorological research for abnormal disasters. The status forecast of the platform is then completed through the meteorological early warning mechanism, and the forecast results are adjusted in the duration of the status.

Seizing Timeliness: The Product's Core
For nowcasting, there should be new requirements for timeliness. Technical experts at SPRIXIN suggest that the near numerical weather forecast pay more attention to the hourly forecast data in the next 4 to 12 hours provided by new energy power plants to ensure the forecast accuracy under near real-time and abnormal weather conditions. Furthermore, factors such as local meteorological conditions and topography of the power plants should also be considered when obtaining on-site historical meteorological data to optimize and supplement the model input to guarantee more accurate early warning results.

Innovation and Research: The Universal Tools for Problem-Solving
SPRIXIN’s Early Warning Platform of Abnormal Weather gets its early warning results through the prediction model and sets warning limits for different power plants to make early warning responses when the abnormal weather conditions reach the corresponding limit.
The wind power prediction model considers the fan cut-outs under the conditions of strong wind, low temperature, and ice-covered blades.
The solar power prediction model considers the decline of irradiance in conditions like snow-covered/snow-melt, hazy/sandy photovoltaic panel, etc.

In short, as the new energy industry develops and the demand for high-accuracy power forecasting grows, the early warning of abnormal weather is an unavoidable topic for such weather could directly affect the normal operation and power generation of new energy power plants.

Based on research and practical experiences, the technology experts of SPRIXIN innovatively combine abnormal weather and near real-time weather forecasts to finally launch the Early Warning Platform of Abnormal Weather. For new energy power plants, the platform can effectively improve the forecast accuracy of power generation under abnormal weather, and help them plan in advance thus reducing losses; for the power grid, it can maintain the stability and improve the resilience of the grid, reducing the safety risks when dispatching and operating, and improving the grid’s the ability to consume new energy. The innovative technology of SPRIXIN has overcome the difficulty of accurate forecasting of power generation, and we will be actively promoting the sustainable development of both the environment and the new energy industry with expertise.