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Modelling and forecasting of Jiangsu's total electricity consumption using the novel grey multivariable model

机译:基于新型灰色多变量模型的江苏省总用电量建模与预测

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Electricity demand prediction plays an important role in the policy makings and plans for the governments, energy sector investors and other relevant stakeholders. Although there exist several forecasting techniques, selection of the most appropriate technique is of great importance. One of the forecasting techniques which has proved successful in prediction is GM(1, N). In order to clarify the interaction mechanism of driving variables and improve the accuracy of the model, a new model which is based on the development trend of multiple driving variables, abbreviated as TMGM (1, N), is proposed. Firstly, a new forecast model of the development trend of the driving variables is established in order to make better use of the interaction mechanism of the driving variables. On the basis of that, the new grey model TMGM (1, N) is constructed. Meanwhile, the solution to the model parameters are derived on the least square method. And the time response formula is solved by the convolution integral to make up the defects of the solving method of traditional model GM(1, N). Finally, a real application about the forecast of the total electricity consumption in Jiangsu Province is used to demonstrate the feasibility and practicability of the TMGM(1, N) model. The results indicate the superiority of TMGM(1, N) model when compared with GM(1, N) model and TGM(1, N) model.
机译:电力需求预测在政府,能源部门投资者和其他相关利益相关者的政策制定和计划中起着重要作用。尽管存在几种预测技术,但是选择最合适的技术非常重要。 GM(1,N)是预测成功的一种预测技术。为了阐明驱动变量的相互作用机理,提高模型的准确性,提出了一种基于多个驱动变量发展趋势的新模型,简称为TMGM(1,N)。首先,建立驱动变量发展趋势的新预测模型,以更好地利用驱动变量的相互作用机理。在此基础上,构造了新的灰色模型TMGM(1,N)。同时,采用最小二乘法推导模型参数。通过卷积积分求解时间响应公式,弥补了传统模型GM(1,N)求解方法的缺陷。最后,通过对江苏省总用电量预测的实际应用,证明了TMGM(1,N)模型的可行性和实用性。结果表明,与GM(1,N)模型和TGM(1,N)模型相比,TMGM(1,N)模型具有优越性。

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