SPRIXIN's Precise Power Forecasting Installs a ＂Strong Heart＂ for the Power System

Time：2022-03-14 Source：SPRIXIN

Power forecasting of new energy is of great significance to the operation of the power system. Accurate prediction of wind power and photovoltaic power generation can not only provide a reliable basis for the grid to make dispatching and generation plans to keep it stable, safe, and economic, but also reduce the cost and improve the revenue of the power generation companies. The accuracy of power forecasting is hence the key to determining whether new energy can be grid-friendly.

It is shown that in recent years, China's research on power forecasting has made great progress in technology and accuracy. We can now meet the increasingly stringent technical assessments and requirements, allow large-scale new energy to be connected to the power grid in a friendlier way, and realize reliable power supply, efficient consumption, and safe operation of the power system, making new energy more predictable, controllable, and schedulable.

SPRIXIN has been focusing on the research of new energy power forecasting systems for more than ten years and has accumulated rich experience in developing and applicating the systems. Widely implemented in large PV power plants, and on/offshore wind power farms, SPRIXIN's power forecasting system reflects prominent compatibility, adaptability, and grid accessibility. Even under strict local grid connection conditions and various index assessments, we can accomplish high-precision modeling that achieves accurate predictions in extreme environments and complex terrains.

Taking a wind farm built in the mountains as an example, due to its complex terrain, local microclimates are prone to occur, resulting in large differences in the power generation of wind turbines at different locations. The effective coverage of a single weather station, however, is not comprehensive enough for the mesoscale numerical weather prediction to take into consideration the local microclimate in detail, elevating the difficulty of power forecasting. SPRIXIN has effectively eliminated local microclimate fluctuations with micrometeorology and computational fluid dynamics (CFD), greatly reducing the forecast deviation of critical meteorological factors such as wind speed. In addition, we achieved high-resolution weather forecasting using data assimilation, ensemble forecasting, and multi-model integrated forecasting technologies. Moreover, through advanced intelligent algorithms, we have made perceivable and predictable the conversion process of each wind turbine from wind to electricity.

The reason why SPRIXIN can maximize the accuracy of power forecasting is that we constantly study new technologies in the aspects of modeling, algorithms, and meteorology, and master the use of various numerical weather prediction models to predict multiple possibilities of future weather.
Among them, ensembled numerical weather prediction + segmental modeling technology breaks the traditional method of single modeling and single numerical weather prediction. The new method enriches the forecast results from the model and reduces the forecast bias through integrated forecasting of multiple data sources such as topography, measured data, equipment status, and numerical weather forecasting. Furthermore, it can forecast by region using algorithms such as neural networks to model in segments, which improves the match between the model and the real situations of the power plants, leading to high-accuracy ultra-short-term, short-term, and medium-term power forecasts.

During global new energy development, whether it is centralized or decentralized wind farms and distributed photovoltaic power stations, they all have promising potential for future development. The application of accurate power forecasting systems is therefore extremely crucial. SPRIXIN's high-accuracy power forecasting system is like a ‘strong heart’ of the new energy power plants, providing technical support for the safe, stable, and economical operation of the new energy power system.