Research Of Power System Load Model Based on Improved Genetic Programming

被引：0
作者：
Wang, Jun [1 ]
Zhang, Jian [1 ]
机构：
[1] Zhengzhou Univ, Sch Elect Engn, Zhengzhou 450000, Peoples R China
来源：
PROCEEDINGS OF THE 2016 INTERNATIONAL CONFERENCE ON CIVIL, TRANSPORTATION AND ENVIRONMENT | 2016年 / 78卷
关键词：
power system; load model; genetic programming; automatic modeling;
D O I：
暂无
中图分类号：
T [工业技术];
学科分类号：
08 ;
摘要：
The model of the power system load has an important impact on power flow calculation, stability analysis. Compared with the traditional load modeling method to determine the structure further identification of the model parameters, using the genetic programming to load modeling do not have to preset the model structure. It automatically generates a different function from the input and output variables. According to their fitness looking for the most accurate fit function. In this paper, using the improved method of GP to load modeling. Precision and efficiency has been improved by optimize the adaptation of the calculation process. The effectiveness and feasibility of the improved genetic programming method is verified by compare with the traditional load modeling method.
引用
收藏
页码：768 / 771
页数：4
相关论文
共 50 条
  • [21] Research on Short-term Load Forecasting of Power System Based on Deep Learning
    Li, Lei
    Jia, Kunlin
    PROCEEDINGS OF 2024 INTERNATIONAL CONFERENCE ON POWER ELECTRONICS AND ARTIFICIAL INTELLIGENCE, PEAI 2024, 2024, : 251 - 255
  • [22] Research on Recognition and Correction of Power System Load Singular Data Based on Wavelet Analysis
    Hong, Chao
    Ye, Xiangshu
    PROCEEDINGS OF THE 2017 7TH INTERNATIONAL CONFERENCE ON EDUCATION, MANAGEMENT, COMPUTER AND SOCIETY (EMCS 2017), 2017, 61 : 2229 - 2234
  • [23] A High Precision Comprehensive Evaluation Method for Flood Disaster Loss Based on Improved Genetic Programming
    ZHOU Yuliang 1)
    JournalofOceanUniversityofChina, 2006, (04) : 322 - 326
  • [24] A high precision comprehensive evaluation method for flood disaster loss based on improved genetic programming
    Yuliang Zhou
    Guihua Lu
    Juliang Jin
    Fang Tong
    Ping Zhou
    Journal of Ocean University of China, 2006, 5 (4) : 322 - 326
  • [25] Short-Term Load Forecasting Based on Improved Gene Expression Programming
    Yin, Jinliang
    Huo, Limin
    Guo, Lirui
    Hu, Jie
    2008 7TH WORLD CONGRESS ON INTELLIGENT CONTROL AND AUTOMATION, VOLS 1-23, 2008, : 5647 - 5650
  • [26] Nonlinear speech coding model based on genetic programming
    Wu, Xiaojun
    Yang, Zhanzhong
    APPLIED SOFT COMPUTING, 2013, 13 (07) : 3314 - 3323
  • [27] A Behavioral Model for Lithium Batteries based on Genetic Programming
    Di Capua, G.
    Oliva, N.
    Milano, F.
    Bourelly, C.
    Porpora, F.
    Maffucci, A.
    Femia, N.
    2023 IEEE INTERNATIONAL SYMPOSIUM ON CIRCUITS AND SYSTEMS, ISCAS, 2023,
  • [28] Hammerstein model identification method based on genetic programming
    Hatanaka, T
    Uosaki, K
    PROCEEDINGS OF THE 2001 CONGRESS ON EVOLUTIONARY COMPUTATION, VOLS 1 AND 2, 2001, : 1430 - 1435
  • [29] Improved Genetic Programming Algorithm for RCMPSP
    Chen H.
    Ding G.
    Zhang J.
    Yan K.
    Zhongguo Jixie Gongcheng/China Mechanical Engineering, 2021, 32 (10): : 1213 - 1221
  • [30] Research on UAV Adaptive Control Method Based on Genetic Programming
    Feng, Qi
    Yu, Jianyu
    2021 PROCEEDINGS OF THE 40TH CHINESE CONTROL CONFERENCE (CCC), 2021, : 2150 - 2154
12345