Long and Medium Term Power Load Forecasting Based on a Combination Model of GMDH, PSO and LSSVM

被引：0

作者：

Long Jinlian ^{[1
]}

Zhang Yufen ^{[1
]}

Lu Jiaxuan ^{[2
]}

机构：

[1] Guizhou Univ, Coll Elect Engn, Guiyang 550025, Guizhou, Peoples R China

[2] Guizhou Univ, Coll Big Data & Informat Engn, Guiyang 550025, Guizhou, Peoples R China

来源：

2017 29TH CHINESE CONTROL AND DECISION CONFERENCE (CCDC) | 2017年

关键词：

power load forecasting; Group Method of Data Handing (GMDH); Particle Swarm Optimization (PSO); Least Squares Support Vector Machine (LSSVM);

D O I：

暂无

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

In this paper, a new method based on Group Method of Data Handling (GMDH), Improved Particle Swarm Optimization (PSO), and Least Squares Support Vector Machine (LSSVM) is proposed to solve the problem in power load forecasting, which is difficult to determine the input node and model parameters of minimum support vector machine (LSSVM) modeling. The specific method is as follows: firstly, the authors use the GMDH algorithm to obtain the input variables of the LSSVM modeling. Secondly, the adaptive mutation PSO algorithm is analyzed to optimize the parameters of the LSSVM model, and then the trained LSSVM model is utilized to predict the test samples. Furthermore, a real case about the actual load of a certain city from the year 2008 to 2013 is analyzed, and the power load in 2014, 2015 were forecast. The simulation results verify that the forecasting accuracy has been improved obviously.

引用

页码：964 / 969

页数：6

共 50 条

[11] Medium and Long-term Power Load Forecasting based on the Thought of Big Data
Zheng, Feng Xian
Ting, Zhang Ting
Jun, Li Hong
Bin, Per Zhao
[J]. PROCEEDINGS OF THE 2016 INTERNATIONAL CONFERENCE ON EDUCATION, MANAGEMENT, COMPUTER AND SOCIETY, 2016, 37 : 1312 - 1316
[12] Medium and Long-Term Electric Power Planning Load Forecasting Based on Variable Weights Gray Model
Song, Da
Liu, Xiaobo
[J]. PROCEEDINGS OF THE 5TH INTERNATIONAL CONFERENCE ON ELECTRICAL ENGINEERING AND AUTOMATIC CONTROL, 2016, 367 : 137 - 144
[13] Power load combination forecasting based on triangular fuzzy discrete difference equation forecasting model and PSO-SVR
Liu, Jinpei
Wang, Piao
Huang, Yanyan
Wu, Peng
Xu, Qin
Chen, Huayou
[J]. JOURNAL OF INTELLIGENT & FUZZY SYSTEMS, 2019, 36 (06) : 5889 - 5898
[14] Medium- and Long-Term Power Load Forecasting Method Based on LTC-RNN Model
Deng, Bin
Zhang, Nan
Wang, Jiang
Ge, Leijiao
[J]. Tianjin Daxue Xuebao (Ziran Kexue yu Gongcheng Jishu Ban)/Journal of Tianjin University Science and Technology, 2022, 55 (10): : 1026 - 1033
[15] Application of Improved Particle Swarm Optimization Algorithm in Medium and Long Term power Load Combination Forecasting
Zhang, Shuguo
Su, Yang
[J]. Proceedings of the 2016 2nd International Conference on Economics, Management Engineering and Education Technology (ICEMEET 2016), 2016, 87 : 32 - 35
[16] A Combined Model Based on EOBL-CSSA-LSSVM for Power Load Forecasting
Wang, Xinheng
Gao, Xiaojin
Wang, Zuoxun
Ma, Chunrui
Song, Zengxu
[J]. SYMMETRY-BASEL, 2021, 13 (09):
[17] Study on medium and long term power load forecasting in cold regions
Li, Jian
Jiang, Zhenhuan
[J]. PROGRESS IN CIVIL ENGINEERING, PTS 1-4, 2012, 170-173 : 3472 - 3477
[18] Medium-long power load forecasting based on improved Grey BP model
Lie, Xiaoxia
Zhang, Peijun
[J]. PROCEEDINGS OF THE FIRST INTERNATIONAL WORKSHOP ON EDUCATION TECHNOLOGY AND COMPUTER SCIENCE, VOL II, 2009, : 366 - +
[19] Short-Term Power Load Forecasting Model Design Based on EMD-PSO-GRU
Zhang, Weihao
Wang, Ting
[J]. SCIENTIFIC PROGRAMMING, 2022, 2022
[20] Research on Medium and Long Term Power Load Forecasting Considering Intelligent Power Utilization
Jiang Haoran
Chen Xinru
Li Yang
Feng Xiaofeng
Lu Shixiang
Lin Guoying
[J]. 2018 CHINA INTERNATIONAL CONFERENCE ON ELECTRICITY DISTRIBUTION (CICED), 2018, : 2938 - 2942

← 1 2 3 4 5 →