Research on Analysis and Forecast of Power Demand Based on Changli Network

被引：0

作者：

Li Ying ^{[1
]}

Liu Qihui ^{[1
]}

Li Chao ^{[2
]}

机构：

[1] North China Elect Power Univ, Sch Elect & Engn, Beijing, Peoples R China

[2] Shi Jiazhuang Power Supply Co, Dept Substn & Operat, Shijiazhuang, Peoples R China

来源：

2011 ASIA-PACIFIC POWER AND ENERGY ENGINEERING CONFERENCE (APPEEC) | 2011年

关键词：

power demand forcasting; distribution network planning; grey system theory; maximum load;

D O I：

暂无

中图分类号：

TE [石油、天然气工业]; TK [能源与动力工程];

学科分类号：

0807 ; 0820 ;

摘要：

In this paper, based on the use of electric power in history and the economic development in future, from the geographical area, voltage level, the view of industry point, load cycle and other aspects, we summed up the characteristics of the power demand forecasting of Changli. Then based on the comprehensive analysis of these characteristics, we decided to use the power demand forecasting method based on grey system theory to predict the short term power demand and use the average annual growth rate method to predict the medium term power demand. According to the research on the electricity and the historical load data of changli power grid, we analyzed the characteristics of Changli's distribution network. Finally we predicted the power and maximum load of Changli from 2010 to 2015 by the forecasting method based on the grey system theory and average annual growth rate method.

引用

页数：4

共 50 条

[1] Research on Investment Demand Forecast of Power Grid Based on Grey System Theory
Li, Hui
Wang, Yongli
Peng, Dong
Wang, Zhidong
Ma, Yuze
Zhang, Fuli
Zhao, Lang
Xue, Yawei
2019 5TH INTERNATIONAL CONFERENCE ON ENERGY MATERIALS AND ENVIRONMENT ENGINEERING, 2019, 295
[2] Aggregated Electric Vehicle Fast-Charging Power Demand Analysis and Forecast Based on LSTM Neural Network
Chang, Munseok
Bae, Sungwoo
Cha, Gilhwan
Yoo, Jaehyun
SUSTAINABILITY, 2021, 13 (24)
[3] Artificial Neural Network Based Short Term Power Demand Forecast for Smart Grid
Kulkarni, Sonali N.
Shingare, Prashant
2018 IEEE CONFERENCE ON TECHNOLOGIES FOR SUSTAINABILITY (SUSTECH), 2018, : 1 - 7
[4] Bus Network Planning Based on Traffic Demand Forecast
Fang, Weizhou
Xu, Weixiang
SIXTH INTERNATIONAL CONFERENCE ON ELECTROMECHANICAL CONTROL TECHNOLOGY AND TRANSPORTATION (ICECTT 2021), 2022, 12081
[5] Research and Application of Urban Logistics Demand Forecast Based on Radial Basic Function Neural Network
Gao, Meijuan
Feng, Qian
Tian, Jingwen
PROCEEDINGS OF THE FIRST INTERNATIONAL WORKSHOP ON EDUCATION TECHNOLOGY AND COMPUTER SCIENCE, VOL II, 2009, : 853 - +
[6] Research on Demand Forecast of Project Materials Based on Classifier
Gao, Jun-jun
Tian, Peng-peng
Hong, Fang-hua
3RD INTERNATIONAL CONFERENCE ON ECONOMICS AND MANAGEMENT (ICEM 2016), 2016, : 387 - 393
[7] The Forecast Research of Enterprise Logistics Cost Based on Neural Network Analysis
Yun, Hong
Zhang, Yan
INTERNATIONAL CONFERENCE ON ENGINEERING AND BUSINESS MANAGEMENT (EBM2011), VOLS 1-6, 2011, : 1047 - 1050
[8] Research on Demand Forecast of Human Resource Post Structure in Power Enterprise
Zhao, Jian
Liu, Hao-jie
Qi, Jin-chang
2ND INTERNATIONAL CONFERENCE ON EDUCATION, MANAGEMENT AND SYSTEMS ENGINEERING (EMSE 2017), 2017, : 387 - 390
[9] Research on Power Demand Forecasting of Beijing Based on Regression Analysis
Dai, Shuyu
Li, Yan
Niu, Dongxiao
PROCEEDINGS OF THE 2017 7TH INTERNATIONAL CONFERENCE ON MECHATRONICS, COMPUTER AND EDUCATION INFORMATIONIZATION (MCEI 2017), 2017, 75 : 255 - 259
[10] The forecast of power demand cycle turning points based on ARMA
Yang, ShuXia
WKDD: 2009 SECOND INTERNATIONAL WORKSHOP ON KNOWLEDGE DISCOVERY AND DATA MINING, PROCEEDINGS, 2009, : 308 - 311

← 1 2 3 4 5 →