SONG Wenwen,GUO Jie,LI Yaling,et al.Characteristics of Maximum Power Load and its Relationship with Meteorological Factors during Summer in Chengdu Power Grid[J].Journal of Chengdu University of Information Technology,2021,36(03):336-341.[doi:10.16836/j.cnki.jcuit.2021.03.016]
成都电网夏季最大电力负荷变化特征及其与气象要素的关系
- Title:
- Characteristics of Maximum Power Load and its Relationship with Meteorological Factors during Summer in Chengdu Power Grid
- 文章编号:
- 2096-1618(2021)03-0336-06
- Keywords:
- meteorology; applied meteorology; maximum power load; meteorological elements; correlation analysis; forecast model
- 分类号:
- P427.31+5
- 文献标志码:
- A
- 摘要:
- 为研究成都电网最大电力负荷变化特征及与气象要素的关系,利用2013-2017年逐日最大电力负荷资料及同期气象资料,采用最小二乘法分离气象电力负荷,分析其与气象因子的关系,并采用多元逐步回归法建立夏季最大电力负荷预测模型,对预测结果进行检验。结果表明:2013-2017年成都电网逐日最大电力负荷具有逐年增长的趋势; 月变化显示夏季最大电力负荷达到高峰; 最大电力负荷具有显著的周效应,周一至周三最大电力负荷逐渐增大,周四、周五减小,休息日中周日最大电力负荷最小; 节假日期间日最大电力负荷明显减小。气象电力负荷与当日气温相关性最大。建立的3类预测模型中,利用夏季逐日气象负荷和当日气象要素建立的日预报模型的预测效果较好。
- Abstract:
- By using the daily maximum power load data and meteorological data in Chengdu power grid during 2013-2017, the variation characteristics of maximum power load in Chengdu power grid and its relationship with meteorological elements was analyzed. The meteorological power load was separated from maximum power load by using least square method, and the relationships between meteorological power load and meteorological factors were analyzed. The prediction model of summer maximum power load was established by using multiple stepwise regression method, and the predicted results were verified. The results showed that the daily maximum power load in Chengdu area had a growth trend year by year during 2013-2017. The monthly variation indicated the maximum power load had a peak value in summer. The maximum power load had significant weekly effect, which meant the maximum power load increased from Monday to Wednesday, and decreased from Thursday to Friday, and the lowest value was on Sunday. The daily maximum power load decreased significantly during festival and holidays. The meteorological power load had the most significant relationship with air temperature. The daily prediction model based on summer daily meteorological power load and meteorological factors had the best result in the three types of prediction models.
参考文献/References:
[1] Le Comte D M,Warren H E.Modeling the Impact of Summer Temperatures on National Electricity Consumption[J].Journal of Applied Meteorology,1981,20(12):1415-1419.
[2] BolzernP,Fronza G,Brusasca G.Temperature Effects on the Winter Daily Electric Load[J].Journal of Applied Meteorology,1982,21(2):241-242.
[3] Lee K,Baek H J,Cho C H.The Estimation of Base Temperature for Heating and Cooling Degree-Days for South Korea[J].Journal of Applied Meteorology and Climatology,2014,53(2):300-309.
[4] Robert G.Quayle,Henry F.Diaz. Heating Degree Day Data Applied to Residential Heating Energy Consumption[J].Journal of applied meteorology,1979,19(19):241-246.
[5] Downton M W,Stewart T R,Miller K A.Estimating Historical Heating and Cooling Needs.Per Capita Degree Days[J].Journal of Applied Meteorology,1988,27(1):84-90.
[6] 张晓云,刘月琨,肖健,等.天津市6-9月气温与供电量的关系分析[J].气象与环境学报,2009,25(3):62-65.
[7] 胡江林,陈正洪,洪斌,等.华中电网日负荷与气象因子的关系[J].气象,2002,28(3):14-18.
[8] 张海东,孙照渤,郑艳,等.温度变化对南京城市电力负荷的影响[J].大气科学学报,2009,32(4):536-542.
[9] 张自银,马京津,雷杨娜.北京市夏季电力负荷逐日变率与气象因子关系[J].应用气象学报,2011,22(6):760-765.
[10] 杜彩月,张国平,刘玉巧,等.许昌市供电量与气象要素相关分析[J].气象与环境科学,2007,30(4):85-87.
[11] 林小红,夏丽花,黄美金,等.福州市夏季电力气象等级预测模型初探[J].气象科技,2006,34(6):774-777.
[12] 罗慧,巢清尘,李奇,等.气象要素在电力负荷预测中的应用[J].气象,2005,31(6):15-18.
[13] 罗森波,纪忠萍,马煜华,等.2002-2004年广东电力负荷的变化特征及预测[J].热带气象学报,2007,23(2):153-161.
[14] 钟利华,周绍毅,李勇,等.广西电网电力负荷变化特征与气温的关系及其预测[J].气象研究与应用,2007,28(1):56-63.
[15] 叶殿秀,张培群,赵珊珊,等.北京夏季日最大电力负荷预报模型建立方法探讨[J].气候与环境研究,2013,18(6):804-810.
相似文献/References:
[1]廖洪涛,肖天贵,魏 微,等.东亚梅雨季低频波波包传播特征[J].成都信息工程大学学报,2019,(02):143.[doi:10.16836/j.cnki.jcuit.2019.02.008]
LIAO Hongtao,XIAO Tiangui,WEI Wei,et al.Low Frequency Wave Packet Propagation
Characteristics in East Asian Meiyu Season[J].Journal of Chengdu University of Information Technology,2019,(03):143.[doi:10.16836/j.cnki.jcuit.2019.02.008]
[2]王雨歌,郑佳锋,朱克云,等.一次西南涡过程的云-降水毫米波云雷达回波特征分析[J].成都信息工程大学学报,2019,(02):172.[doi:10.16836/j.cnki.jcuit.2019.02.011]
WANG Yuge,ZHENG Jiafeng,ZHU Keyun,et al.Analysis of Cloud-Precipitation Echo Characteristics of a Southwest Vortex[J].Journal of Chengdu University of Information Technology,2019,(03):172.[doi:10.16836/j.cnki.jcuit.2019.02.011]
[3]青 泉,罗 辉,陈刚毅.基于L波段秒级探空数据V-3θ图形的四川盆地暴雨预报模型研究[J].成都信息工程大学学报,2019,(02):186.[doi:10.16836/j.cnki.jcuit.2019.02.013]
QING Quan,LUO Hui,CHEN Gangyi.Forecasting Model of Torrential Rain in Sichuan Basin based on V-3θ
Structural Graphs of L-Band Second Level Sounding Data[J].Journal of Chengdu University of Information Technology,2019,(03):186.[doi:10.16836/j.cnki.jcuit.2019.02.013]
[4]吴秋月,华 维,申 辉,等.基于湿位涡与螺旋度的一次西南低涡强降水分析[J].成都信息工程大学学报,2019,(01):63.[doi:10.16836/j.cnki.jcuit.2019.01.013]
WU Qiuyue,HUA Wei,SHEN Hui,et al.Diagnostic Analysis of a Southwest Vortex Rainstormbased on Moist Potential Vorticity and Helicity[J].Journal of Chengdu University of Information Technology,2019,(03):63.[doi:10.16836/j.cnki.jcuit.2019.01.013]
[5]李潇濛,赵琳娜,肖天贵,等.2000-2015年青藏高原切变线统计特征分析[J].成都信息工程大学学报,2018,(01):91.[doi:10.16836/j.cnki.jcuit.2018.01.016]
LI Xiao-meng,ZHAO Lin-na,XIAO Tian-gui,et al.Statistical Characteristics Analysis of the Shear Linein the Qinghai-Tibet Plateau from 2000 to 2015[J].Journal of Chengdu University of Information Technology,2018,(03):91.[doi:10.16836/j.cnki.jcuit.2018.01.016]
[6]喻乙耽,马振峰,范广洲.华西秋雨气候特征分析[J].成都信息工程大学学报,2018,(02):164.[doi:10.16836/j.cnki.jcuit.2018.02.011]
YU Yi-dan,MA Zhen-feng,FAN Guang-zhou.The Analysis of Climatic Feature of Autumn Rainfall in West China[J].Journal of Chengdu University of Information Technology,2018,(03):164.[doi:10.16836/j.cnki.jcuit.2018.02.011]
[7]孙康慧,巩远发.20世纪70年代末云南省雨季降水的突变及原因分析[J].成都信息工程大学学报,2018,(02):177.[doi:10.16836/j.cnki.jcuit.2018.02.012]
SUN Kang-hui,GONG Yuan-fa.Abrupt Change of Precipitation in Rainy Season in YunnanProvince in Late 1970s and its Cause Analysis[J].Journal of Chengdu University of Information Technology,2018,(03):177.[doi:10.16836/j.cnki.jcuit.2018.02.012]
[8]吴树炎,顾建峰,刘海文,等.高原冬季雪深与重庆夏季降水的年际关系研究[J].成都信息工程大学学报,2018,(02):184.[doi:10.16836/j.cnki.jcuit.2018.02.013]
WU Shu-yan,GU Jian-feng,LIU Hai-wen,et al.Interannual Relationship between Winter Snow Depth over TibetanPlateau and Summer Precipitation over Chongqing[J].Journal of Chengdu University of Information Technology,2018,(03):184.[doi:10.16836/j.cnki.jcuit.2018.02.013]
[9]朱 莉,张腾飞,李华宏,等.云南一次短时强降水过程的中尺度特征及成因分析[J].成都信息工程大学学报,2018,(03):335.[doi:10.16836/j.cnki.jcuit.2018.03.017]
ZHU Li,ZHANG Teng-fei,LI Hua-hong,et al.Analysis on Meso-scale Features and Forming Reasons of a Short TimeIntensive Precipitation Case in Yunnan Province[J].Journal of Chengdu University of Information Technology,2018,(03):335.[doi:10.16836/j.cnki.jcuit.2018.03.017]
[10]李筱杨,朱克云,程 溢,等.吉林玉米生长期土壤水分规律分析[J].成都信息工程大学学报,2018,(03):344.[doi:10.16836/j.cnki.jcuit.2018.03.018]
LI Xiao-yang,ZHU Ke-yun,CHENG Yi,et al.Analysis of Soil Moisture Regularity in Jilin Maize Growing Period[J].Journal of Chengdu University of Information Technology,2018,(03):344.[doi:10.16836/j.cnki.jcuit.2018.03.018]
[11]魏 凡,李 超.利用气象雷达信息划设雷暴飞行限制区的方法研究[J].成都信息工程大学学报,2018,(02):205.[doi:10.16836/j.cnki.jcuit.2018.02.016]
WEI Fan,LI Chao.Study on the Method of Setting Up Limited Flying area ofThunderstorm by Using Weather Radar Information[J].Journal of Chengdu University of Information Technology,2018,(03):205.[doi:10.16836/j.cnki.jcuit.2018.02.016]
[12]邹 璐sup>,肖国杰,黎跃浩.近54 a云南西北地区极端降水频数和强度特征[J].成都信息工程大学学报,2016,(05):531.
ZOU Lu,XIAO Guo-jie,LI Yue-hao.Analysis on the Frequency And Intensity of Extreme Precipitation
in the Northwest Yunnan during Last 54 Years[J].Journal of Chengdu University of Information Technology,2016,(03):531.
[13]张天峰,王位泰,张洪芬,等.一次城市内涝暴雨特征及强度公式验证分析[J].成都信息工程大学学报,2017,(02):226.[doi:10.16836/j.cnki.jcuit.2017.02.018]
ZHANG Tian-feng,WANG Wei-tai,ZHANG Hong-fen,et al.The Analysis of a Storm Rainfall in Urban Water-logging
and Validation of the Strength Formula[J].Journal of Chengdu University of Information Technology,2017,(03):226.[doi:10.16836/j.cnki.jcuit.2017.02.018]
[14]卢会国,张 捷,蒋娟萍,等.四川盆地极端降水演变特征及拟合[J].成都信息工程大学学报,2021,36(04):404.[doi:10.16836/j.cnki.jcuit.2021.04.010]
LU Huiguo,ZHANG Jie,JIANG Juanping,et al.The Research of Observation Data Correction based on Convex Optimization Theory[J].Journal of Chengdu University of Information Technology,2021,36(03):404.[doi:10.16836/j.cnki.jcuit.2021.04.010]
备注/Memo
收稿日期:2020-04-28
基金项目:高原与盆地暴雨旱涝灾害四川省重点实验室科技发展基金资助项目(省重实验室2018-重点-03、省重实验室2018-青年-10)