王宝, 叶彬, 石雪梅, 牛振振. 基于用电结构变动的省级电网长期负荷特性预测[J]. 现代电力, 2015, 32(3): 54-59.
引用本文: 王宝, 叶彬, 石雪梅, 牛振振. 基于用电结构变动的省级电网长期负荷特性预测[J]. 现代电力, 2015, 32(3): 54-59.
WANG Bao, YE Bin, SHI Xuemei, NIU Zhenzhen. Long-term Load Characteristic Forecast of Provincial Power Grid Based on Electricity Structure Changes[J]. Modern Electric Power, 2015, 32(3): 54-59.
Citation: WANG Bao, YE Bin, SHI Xuemei, NIU Zhenzhen. Long-term Load Characteristic Forecast of Provincial Power Grid Based on Electricity Structure Changes[J]. Modern Electric Power, 2015, 32(3): 54-59.

基于用电结构变动的省级电网长期负荷特性预测

Long-term Load Characteristic Forecast of Provincial Power Grid Based on Electricity Structure Changes

  • 摘要: 准确把握省级电网长期负荷特性发展趋势,可使电网规划更具前瞻性和合理性。通过充分分析地区负荷特性变动主要影响因素,识别出经济与用电结构因素是长期负荷特性变动的关键影响因素,据此构建了基于用电结构变动的省级电网长期负荷特性预测模型及其校核方法,以安徽省为例,对2020和2030年全省四季典型日负荷率和峰谷差率进行了预测,并以欧美发达国家和上海市为参考对预测结果进行了校核。结果表明该长期负荷特性预测模型的合理性和有效性,为电力市场分析与电网规划人员准确掌握地区长期负荷特性变动趋势提供了一定的参考。

     

    Abstract: Accurately mastering the development trend on long-term load characteristic of provincial power grid can effectively guide the prospect and rationality of power grid planning. It is identified through the fully analyzing on main influencing factors of the change in regional load characteristic that economic and electricity structures are the key factors influencing the change in regional long-term load characteristic. Then a forecasting model and its check method for long-term load characteristic of provincial power grid based on the change in electricity structure are built. By taking Anhui province as an instance, the load ratio and peak-valley ratio of each typical day at all seasons in 2020 and 2030 are predicted, and the forecast results are verified by taking that of European and American developed countries and Shanghai municipality as the reference. Results verify the rationality and effectiveness of this long-term load characteristic forecasting model, which can provide certain reference value for electricity market analysts and operators to master the variation trend of long-term load characteristic accurately.

     

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