基于B-N数据分解京津唐地区特殊时段对用电需求的冲击效应分析  

Analysis on Impact Effect of Special Time Period on Electricity Demand in Beijing-Tianjin-Tangshan Region Based on B-N Data Decomposition

作　　者：李付强[1] 赵浩然[2] 李娜娜[2] 赵会茹[2] 

机构地区：[1]国家电网华北电网有限公司,北京100053 [2]华北电力大学经济与管理学院,北京102206

出　　处：《陕西电力》2017年第6期55-60,共6页Shanxi Electric Power

基　　金：国家自然科学基金项目资助(71373076);中央高校基本科研业务费专项资金(2017XS106)

摘　　要：在分析2011—2015年春节、五一、十一假期、2015年9月3日的大阅兵,以及2014年11月7—12日的APEC会议等特殊时段对京津唐地区全社会电力需求影响的基础上,运用Beveridge-Nelson(B-N)数据分解模型对特殊时段京津唐地区全社会用电需求时间序列的确定性趋势项、周期项、随机冲击项进行分解,分析了特殊时段对京津唐地区全社会电力需求的冲击效应,得出:大阅兵、APEC会议、春节、五一以及十一假期期间京津唐地区全社会用电量受到较大的负向冲击;确定性趋势项的存在使得京津唐地区全社会电力需求虽然受到特殊事件的负向冲击,但仍保持一定增长趋势;春节假期对京津唐地区全社会电力需求影响最大,使全社会用电量累计减少0.070 6%,"十一"假期的影响居于第二位,"五一"假期对全社会电力需求影响最小。Through the analysis of the electricity consumption in Beijing-Tianjin-Tangshan region affected by Spring Festival, May Day, National Day, APEC meeting and other special festivals during 2011-2015, Beveridge-Nelson （B-N） decomposition method is employed to decompose the electricity consumption data series into deterministic trend term, periodic term, and random impulse term. The impact of special period on electricity demand is analyzed by studying on the random impulse tenn. And some conclusions can be drawn： （1） the special period has a large negative impact on the whole society electricity consumption in Beijing-Tianjin- Tangshan region; （2） although the whole society electricity demand is under large negative impact, the existence of deterministic trend still makes the electricity consumption maintain a certain growth rate; （3） Spring Festival has the greatest impact on electricity demand, which made the electricity consumption reduce by 0.0706%, the National Day ranks the second place, while the May Day has a minimum impact on electricity consumption.

关 键 词：用电需求 特殊时段 随机冲击效应 Beveridge—Nelson(B—N)数据分解法 

分 类 号：TM71[电气工程—电力系统及自动化] F206[经济管理—国民经济]