新能源电力系统中的分布式光伏净负荷预测

doi:10.16183/j.cnki.jsjtu.2021.244

摘要/Abstract

摘要：

为响应碳达峰、碳中和的需求,构建一套完整的“源-网-荷-储”的新能源电力系统,提出了一种基于Hamiltonian Monte Carlo推断深度高斯过程(HMCDGP)算法的分布式光伏净负荷预测模型.首先,分别使用直接预测和间接预测两种形式对预测模型的精度进行实验并得到点预测结果;其次,使用所提出的模型进行概率预测实验并得到区间预测结果;最后,通过以澳洲电网记录的300户净负荷数据为基础的对比实验验证所提模型的优越性.在得到准确的净负荷概率预测后,可以通过电力调度充分利用光伏产出,减少化石能源使用,从而减少碳排放.

关键词: 净负荷概率预测, 光伏产出, 深度高斯过程, 点预测, 区间预测

Abstract:

To respond to the demand of achieving carbon peaking and carbon neutrality goals, and to construct a complete “source-grid-load-storage” new energy power system, a distributed photovoltaic net load forecasting model based on Hamiltonian Monte Carlo inference for deep Gaussian processes (HMCDGP) is proposed. First, direct and indirect forecasting methods are used to examine the accuracy of the proposed model and to obtain spot forecasting results. Then, the proposed model is used to perform probability forecasting experiments and produce interval prediction results. Finally, the superiority of the proposed model is verified through the comparative experiments based on the net load data of 300 households recorded by Australia Grid. After obtaining the exact net load probabilistic forecasting results, the photovoltaic production can be fully utilized via power dispatch, which can reduce the use of fossil energy and further reduce the carbon emission.

Key words: net load forecasting, photovoltaic production, deep Gaussian process, point forecasting, interval prediction

中图分类号:

TM615
TM715

廖启术, 胡维昊, 曹迪, 黄琦, 陈哲. 新能源电力系统中的分布式光伏净负荷预测[J]. 上海交通大学学报, 2021, 55(12): 1520-1531.

LIAO Qishu, HU Weihao, CAO Di, HUANG Qi, CHEN Zhe. Distributed Photovoltaic Net Load Forecasting in New Energy Power Systems[J]. Journal of Shanghai Jiao Tong University, 2021, 55(12): 1520-1531.

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方法	RMSE		MAE		NRMSD
方法	间接	直接	间接	直接	间接	直接
BPN	35.00	35.74	20.22	21.19	0.109	0.111
QR	33.53	33.52	22.06	21.75	0.104	0.104
SVR	32.52	31.42	19.38	20.80	0.100	0.098
LR	31.14	31.04	21.35	22.41	0.096	0.096
SGP	31.34	31.49	20.83	21.05	0.097	0.098
HMCDGP	28.65	28.12	18.67	19.01	0.089	0.087

方法	夏季			冬季
方法	RMSE	MAE	NRMSD	RMSE	MAE	NRMSD
BPN	35.740	21.185	0.1109	41.267	29.484	0.1369
QR	33.522	21.751	0.1040	39.462	25.219	0.1309
SGP	31.490	21.047	0.0977	34.702	24.657	0.1151
SVR	31.424	20.804	0.0975	35.929	25.718	0.1192
LR	31.044	22.411	0.0963	36.272	27.598	0.1203
HMCDGP	28.124	19.014	0.0872	33.950	24.646	0.1126

方法	夏季		冬季
方法	Q^b	Q^a/%	Q^b	Q^a/%
QR	7.533	22.56	12.428	26.18
SGP	8.326	23.17	9.500	28.91
HMCDGP	6.803	19.57	8.712	24.92

方法	Q^a=90%	Q^a=80%	Q^a=70%	Q^a=60%
QR	29.44	22.56	18.09	14.34
SGP	29.51	23.17	18.77	15.32
HMCDGP	25.06	19.57	15.82	12.79