由于数据变化规律的多样性,中期电力负荷的波动有着不同于短期、长期负荷的特点。基于电力系统复杂性的研究视角,重点讨论了中期负荷预测过程中模型的不确定性、参数的时变特性以及负荷波动的周期性规律。根据中期负荷的数据特性,建立了基于非参数修匀的半参数模型,定义了函数区间的划分粒度以及模型权重的求解方法,提出了基于可变区间权重的动态预测方法,给出了基于经验模态分解和波动能量分析的噪声序列提取、检验方法。试验研究结果表明,气候因素对用电消耗的影响最大,经济因素次之;从选取的指标来看,不同时期的影响因素对于模型的解释能力是时变的;所提方法能够对电力负荷进行精确的多粒度、多维度分析,进而掌握其局部变化规律,可有效用于电力系统中期负荷预测。
Due to the diversity of data variation, the fluctuations characteristic of the medium-term power load is different from short-term and long-term power load. Based on the view of electric power system complexity, the mid-term power load forecasting problem is discussed, including the forecasting model uncertainty, parameter time-varying characteristics and the periodic law of load fluctuation. According to the features of mid-term power load, a semi-parametric model based on nonparametric smoothing is built, and the division of the function interval is defined. After that, a new dynamic prediction method is put forward based on variable interval. Combined with the ensemble empirical mode decomposition algorithm and wave energy test, the noise sequence analysis and separation method is presented. The study shows that, climatic factor have the greatest impact on the electricity consumption, while economic factor has less impact on it. In different forecast periods, the explanatory of factors to the forecasting model varies over time. As the proposed semi-parametric model can be used for accurate multi-dimensional and multi-granularity analysis of electricity load, then grasp the variation, it can be efficiently used for mid-term load forecasting.
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