Research on Medium and Long Term Power Load Forecasting Considering Intelligent Power Utilization

被引:0
|
作者
Jiang Haoran [1 ]
Chen Xinru [1 ]
Li Yang [1 ]
Feng Xiaofeng [2 ]
Lu Shixiang [2 ]
Lin Guoying [2 ]
机构
[1] Southeast Univ, Sch Elect Engn, Nanjing 210096, Jiangsu, Peoples R China
[2] Guangdong Power Grid Co, Elect Power Res Inst, Guangzhou, Guangdong, Peoples R China
关键词
Intelligent power utilization; Medium and long term load forecasting; Electricity consumption behavior; Electric vehicle; Smart air conditioner;
D O I
暂无
中图分类号
TM [电工技术]; TN [电子技术、通信技术];
学科分类号
0808 ; 0809 ;
摘要
with the economic and social development of China, intelligent power utilization is getting increasing common in the daily lives of residents, while the types of electricity equipment are becoming various significantly. Furthermore, the electricity consumption behavior of different types of users are diverse. The load characteristics may change, such as peak load transferring, peak and valley differently increasing, and even peak on peak load at the same time. The intelligent power utilization can make scientific and rational use of electrical equipment, so that the electricity consumption can be reduced, which also brings a challenge to load forecasting. Based on the research of intelligent power utilization, this article employed a probability distribution model to fit the users' behavior, and established corresponding load models to characterize its interaction with the power grid. After that, based on the prospect-gray theory, a medium long term load forecasting method considering intelligent power utilization was proposed and analyzed by examples. Finally, this paper used MATLAB to get the power load forecasting result and analyze the influence of intelligent power utilization on the total power load.
引用
收藏
页码:2938 / 2942
页数:5
相关论文
共 50 条
  • [1] Long Term Intelligent Load Forecasting Method Considering the Expectation of Power Market Transaction
    Xu, Wei-ting
    Wang, Yun-ling
    Li, Ting
    Tang, Quan
    Zhang, Jin-fang
    Shen, Li
    Zhu, Mi
    [J]. 2017 29TH CHINESE CONTROL AND DECISION CONFERENCE (CCDC), 2017, : 2310 - 2315
  • [2] A New Medium and Long-Term Power Load Forecasting Method Considering Policy Factors
    Zhang, Bo
    Zhao, Xiaohan
    Dou, Zhenhai
    Liu, Lianxin
    [J]. IEEE ACCESS, 2021, 9 : 160021 - 160034
  • [3] A New Medium and Long-Term Power Load Forecasting Method Considering Policy Factors
    Zhang, Bo
    Zhao, Xiaohan
    Dou, Zhenhai
    Liu, Lianxin
    [J]. IEEE Access, 2021, 9 : 160021 - 160034
  • [4] Medium-long term load forecasting method considering industry correlation for power management
    Jiang, Yuxuan
    Huang, Qingqing
    Zhang, Kunming
    Lin, Zhian
    Zhang, Tianhan
    Hu, Xuetao
    Liu, Shengyuan
    Jiang, Cenxi
    Yang, Li
    Lin, Zhenzhi
    [J]. ENERGY REPORTS, 2021, 7 (07) : 1231 - 1238
  • [5] 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
  • [6] Research on Intelligent Forecasting Method of Medium and Long-term Electricity Load
    Wang Deji
    Lian Jie
    Xie Junming
    [J]. PROCEEDINGS OF THE 31ST CHINESE CONTROL CONFERENCE, 2012, : 3928 - 3931
  • [7] Study on Medium and Long Term Power Load Forecasting Based on Combination Forecasting Model
    Feng, Yue
    [J]. 3RD INTERNATIONAL CONFERENCE ON APPLIED ENGINEERING, 2016, 51 : 859 - 864
  • [8] Medium and Long Term Power Load Forecasting Based on Stacked-GRU
    Yang, Zheng
    Cui, Jing
    Zhang, Qiangjian
    Yin, Chunlin
    Yang, Li
    Qiu, Pengfeng
    Hu, Kai
    Yang, Junwen
    [J]. Strategic Planning for Energy and the Environment, 2022, 41 (04) : 363 - 378
  • [9] Research on Medium-long Term Power Load Forecasting Method Based on Load Decomposition and Big Data Technology
    Chen, Panfeng
    Cheng, Haozhong
    Yao, Yingbei
    Li, Xuan
    Zhang, Jianping
    Yang, Zonglin
    [J]. 2018 INTERNATIONAL CONFERENCE ON SMART GRID AND ELECTRICAL AUTOMATION (ICSGEA), 2018, : 50 - 54
  • [10] A new intelligent hybrid forecasting method for power load considering uncertainty
    Fan, Guo-Feng
    Han, Ying-Ying
    Wang, Jing-Jing
    Jia, Hao-Li
    Peng, Li-Ling
    Huang, Hsin-Pou
    Hong, Wei-Chiang
    [J]. KNOWLEDGE-BASED SYSTEMS, 2023, 280