基于元胞自动机技术的农村中长期负荷预测方法

Rural medium-long-term load forecasting method based on cellular automata technology

针对农村用电负荷分布不均、多样性强,难以准确预测的问题,在考虑农村发展规划、经济、人口等影响负荷变化因素的基础上,提出了一种基于元胞自动机技术的农村中长期负荷预测方法。根据农村用电用途和特点,对农村负荷进行分类;按照台区供电范围内地块利用性质以及地块上负荷分布特点,定义了农村地块功能,利用最小二乘法得到不同功能地块的历史负荷密度曲线;在此基础上,结合农村发展规划、经济及自然条件等引起农村负荷密度和地块功能变化的影响因素,利用历史数据训练门控循环单元负荷密度模型,并利用元胞自动机技术预测地块变化信息;根据地块变化信息和历史负荷密度曲线,利用门控循环单元网络模型预测负荷密度,进而得到农村中长期负荷的预测结果;以某农村为例,验证了所提策略的可行性和有效性。

Aiming at the problem that the rural load distribution is uneven,the diversity is strong,and it is difficult to predict accurately,on the basis of considering the factors of the rural development planning,economy,population and other factors,the medium-long-term load forecasting method of a rural area based on cellular automata technology and machine learning is proposed in this paper.Firstly,according to the use and characteristics of the rural electricity load,the rural load is classified.Then,according to the nature of land use in the power supply scope of station area and the distribution characteristics of the load on the block,the function of the rural land is defined,and the least squares method(LSM)is used to obtain the historical load density curve of different functions.On this basis,combined with the factors of the rural development planning,economic and natural conditions,etc.,historical data is used to train the gated loop unit load density model,and the cellular automata technology is used to predict change information of the land block.Moreover,based on change information of the land block and historical load density curve,the gated loop unit network model is used to predict the load density,and then,the rural medium-long-term load forecast results are obtained.Finally,taking a rural area as an example,the feasibility and effectiveness of the proposed strategy are verified.