| Mid-term forecasting of real-time load based on Prophet algorithm and Blending integrated learning |
| 投稿时间：2023-04-04 修订日期：2023-06-29 |
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| English Abstract: |
| The current medium-term load forecasting generally doesn’t consider the real-time state of the load. However, the characteristics of load data such as nonlinearity, seasonality, randomness and temporality will influence the medium-term forecasting of real-time load. A framework for mid-term forecasting of real-time load is constructed. The Prophet algorithm is adopted to extract the seasonal component of the load data. The Blending integrated learning is adopted for the rolling forecasting of non-seasonal component of the load data. The seasonal and non-seasonal components are combined to synthesize the real-time data of mid-term load. The effectiveness and stability of the model are verified by Irish Power System. |
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| English and key words:load forecasting Prophet algorithm Blending integrated learning seasonality |
| 基金项目:中国南方电网重点科技项目(支撑多能互补园区规划的能效数据挖掘技术研究项目)(GDKJXM20202019) |
| DOI：10.16081/j.epae.202308025 |
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