1.Department of Electrical Engineering, Tsinghua University, Beijing 100084, China;2.State Key Laboratory of Power System and Generation Equipment, Tsinghua University, Beijing 100084, China
This paper aims to improve the accuracy of ultra-short-term prediction of photovoltaic power in small fluctuation scenarios such as the clear sky or thin cloud. Although, the diurnal and annual periodicity of solar radiation makes the photovoltaic power series have deterministic components, the detailed parameters of power stations and local weather change with time and are difficult to obtain. To this end, this paper proposes a modified clear-sky power calculation model that only depends on a few parameters. On this basis, a prediction algorithm updating parameters online is constructed to predict the power of a photovoltaic power station in the next four hours under the small fluctuation weather. The test is performed by using data from a power station in Jilin province. The results show that the clear-sky power curve obtained by the proposed model can accurately fit the power station output under the small fluctuation weather. The photovoltaic prediction results based on the updating parameters online can reduce the prediction error to about 3.78% in the fourth hour under small fluctuation weather, which makes up for the deficiency that the error of adjacent sunny method is more than 5% or even 10% in some scenarios. The proposed method not only improves the accuracy of ultra-short-term prediction of photovoltaic power under small fluctuation weather but also provides a more accurate stabilization benchmark for complex weather conditions.
This work is supported by National Key R&D Program of China (No. 2018YFB0904200) and State Grid Corporation of China (No. SGLNDKOOKJJS1800266).
|||MA Yuan, ZHANG Xuemin, ZHEN Zhao, et al. Ultra-short-term Photovoltaic Power Prediction Based on Modified Clear-sky Model[J/OL]. Automation of Electric Power Systems, http://doi. org/10.7500/AEPS20200227003.|