1.Key Laboratory of Distributed Energy Storage and Microgrid of Hebei Province (North China Electric Power University), Baoding 071003, China;2.State Key Laboratory of Alternate Electrical Power System with Renewable Energy Sources (North China Electric Power University), Baoding 071003, China;3.State Grid Hebei Electric Power Co., Ltd., Shijiazhuang 050000, China
According to the waveform feature of the aggregated power for electric water heaters (EWHs), a short-term interval prediction method is proposed, which considers the ramp characteristic and interval optimization. Firstly, in view of the uncertainty of load power for EWH, a combinatorial point prediction model with high-precision considering multi-source heterogeneous characteristics of the sample distribution is presented, which combines with ensemble empirical mode decomposition (EEMD), principal component analysis (PCA) and multi-kernel relevant vector machine (MKRVM). Secondly, to obtain a narrower prediction interval with the expected prediction coverage, the evaluation indices of the interval prediction coverage, interval average width, and cumulative width deviation are combined to design an improved prediction interval optimization method integrating the kernel density estimation (KDE) and particle swarm optimization, which enhances the performance of MKRVM-KDE in interval structure and avoids the randomness in parameter selection. Finally, the aggregated power data of EWH is used to verify the effectiveness of the approach. The results show that the prediction method has high prediction accuracy and better clarity, and it can also provide prediction intervals with high quality.
This work is supported by the Key Special Project of National Key R&D Program of China “International Scientific and Technological Innovation Cooperation Between Governments/Scientific and Technological Innovation Cooperation Between Hong Kong, Macao and Taiwan” (No. 2018YFE0122200) and State Grid Corporation of China (No. KJGW2018-014).
|||YU Yang, QUAN Li, JIA Yulong, et al. Interval Prediction of Aggregated Power for Electric Water Heaters Considering Ramp Characteristic and Prediction Interval Optimization[J]. Automation of Electric Power Systems,2021,45(1):88-96. DOI:10.7500/AEPS20191022006|