THE APPLICATION OF LSM FOR LONG-TERM FORECASTING OF SPECIFIC FUEL CONSUMPTION BY THE ENERGY SYSTEM OF UZBEKISTAN

D. Losev
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Abstract

The article considers the possibility of using the least squares method (LSM) for long-term forecasting of the parameters of the regime of electric power systems. There is presented least squares method for predicting the parameters of the regime of electric power systems. It is shown that, based on the least-squares method, it is possible to obtain prognostic equations, aswell as coefficients of approximating functions necessary for the formation of these equations. The results of the analysis of the comparison of linear, hyperbolic, logarithmic, exponential and quadratic functions on the use of LSMs to predict specific fuel consumption are presented. Analytical studies are based on statistical data on specific fuel consumption for the period 1990-2016 years by the power system of Uzbekistan. There is shown that the statistical data was divided into training and control samples, when performing an analysis of comparisons of algebraic functions. The training sample, which based on prediction equations are obtained using algebraic functions of various types. The criterion of the least squares method, which is according for using the statistical data of the control sample in the obtained prognostic functions, the standard deviations are found. In the end, there has drawn conclusions, based on the obtained results.
LSM在乌兹别克斯坦能源系统比燃料消耗长期预测中的应用
本文考虑了用最小二乘法对电力系统状态参数进行长期预测的可能性。提出了预测电力系统状态参数的最小二乘方法。结果表明,基于最小二乘法,可以得到预测方程,以及形成这些方程所需的近似函数的系数。给出了线性函数、双曲函数、对数函数、指数函数和二次函数对lsm预测比油耗的比较分析结果。分析研究基于乌兹别克斯坦电力系统1990年至2016年期间特定燃料消耗的统计数据。有表明,统计数据分为训练样本和控制样本,在进行代数函数的分析比较时。利用不同类型的代数函数得到基于预测方程的训练样本。最小二乘法的判据是根据在得到的预测函数中使用控制样本的统计数据,找出标准差。最后,根据所得结果,得出结论。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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