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| 摘要: |
| 由于电力负荷具有突变性，很多预测方法不能及时反映负荷的突然变化，对于发生转折的数据预测精度不高，而单调的灰色GM（1，1）预测并不能反映相关因素对负荷的影响。提出改进的灰色递阶模型和灰色群模模型，通过对历史数据的优化分段引进了变化的模型参数，同时将社会经济等发展指标引入，很大程度上能解决对数据突变的适应性，并反映相关因素对电力负荷的影响。将上述模型应用于所附实际算例，取得了较好的效果。 |
| 关键词: 电力系统 负荷预测 灰色系统 聚类 预测模型 GM（1,1）模型 |
| DOI： |
| 分类号:TM715 |
| 基金项目: |
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| Study on the improved method for mid-and long-term load forecasting of power system |
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GU Jie SHEN Gang XU Guang hu
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| Abstract: |
| Since the load of power system sometimes changes rapidly, many forecasting methods couldn't reflect the sudden change of power load on time, so the precision is low. Moreover, the simple GM(1,1) model of Grey system couldn't reflect the correlative factors of the load. Two models are introduced: Recursion Grey model and Clustering Grey model. By optimal sectioning the historic data, the varying model parameters are induced. Combined with some social and economic indexes,it can adapt the sudden change of the data and reflect the correlative factors of the power load. Good results are obtained when the two models are applied in the practical examples in the paper. |
| Key words: load forecasting,grey system,recursion,clustering, |
