Adaptive load shedding for an industrial petroleum cogeneration system

被引:21
|
作者
Hsu, Cheng-Ting [2 ]
Chuang, Hui-Jen [1 ]
Chen, Chao-Shun [3 ]
机构
[1] Kao Yuan Univ, Dept Elect Engn, Kaohsiung, Taiwan
[2] So Taiwan Univ, Dept Elect Engn, Tainan, Taiwan
[3] I Shou Univ, Dept Elect Engn, Kaohsiung, Taiwan
关键词
Load shedding; Artificial neural networks; Cogeneration;
D O I
10.1016/j.eswa.2011.04.204
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
This paper presents the design of adaptive load-shedding strategy by executing the artificial neural network (ANN) and transient stability analysis for an Industrial cogeneration facility. To prepare the training data set for ANN, the transient stability analysis has been performed to solve the minimum load shedding for various operation scenarios without causing tripping problem of cogeneration units. Various training algorithms have been adopted and incorporated into the back-propagation learning algorithm for the feed-forward neural networks. By selecting the total power generation, total load demand and frequency decay rate as the input neurons of the ANN, the minimum amount of load shedding is determined to maintain the stability of power system. To demonstrate the effectiveness of the ANN minimum load-shedding scheme, the traditional method and the present load shedding schemes of the selected cogeneration system are also applied for comparison and verification of the proposed methodology. (C) 2011 Elsevier Ltd. All rights reserved.
引用
收藏
页码:13967 / 13974
页数:8
相关论文
共 50 条
  • [41] Adaptive neuro-fuzzy inference system based under-frequency load shedding for Tamil Nadu
    K. Paul Joshua
    J. Mohanalin
    S. T. Jaya Christa
    The Journal of Supercomputing, 2020, 76 : 4184 - 4198
  • [42] Adaptive neuro-fuzzy inference system based under-frequency load shedding for Tamil Nadu
    Joshua, K. Paul
    Mohanalin, J.
    Christa, S. T. Jaya
    JOURNAL OF SUPERCOMPUTING, 2020, 76 (06): : 4184 - 4198
  • [43] A Continuous Multistage Load Shedding Algorithm for Industrial Processes Based on Metaheuristic Optimization
    Baiceanu, Florin-Constantin
    Ivanov, Ovidiu
    Beniuga, Razvan-Constantin
    Neagu, Bogdan-Constantin
    Nemes, Ciprian-Mircea
    MATHEMATICS, 2023, 11 (12)
  • [44] Intelligent Electrical Load Shedding in Heavily Loaded Industrial Establishments with a Case Study
    Kucuk, Selahattin
    2018 5TH INTERNATIONAL CONFERENCE ON ELECTRICAL AND ELECTRONIC ENGINEERING (ICEEE), 2018, : 463 - 467
  • [45] Methodology for generating thermal and electric load profiles for designing a cogeneration system
    Huamani, M. M.
    Orlando, A. F.
    ENERGY AND BUILDINGS, 2007, 39 (09) : 1003 - 1010
  • [46] Adaptive Wide-Area Load Shedding Scheme Based on the Sink and Source Concept to Preserve Power System Stability
    Bekhradian, Reza
    Sanaye-Pasand, Majid
    Mahari, Arash
    IEEE SYSTEMS JOURNAL, 2023, 17 (01): : 503 - 512
  • [47] A new approach for islanding management in PV system using frequency modulation technique and simple adaptive load shedding algorithm
    Naoussi, Serge Raoul Dzonde
    Tsobze, Saatong Kenfack
    Kenne, Godpromesse
    SN APPLIED SCIENCES, 2019, 1 (12):
  • [48] A new approach for islanding management in PV system using frequency modulation technique and simple adaptive load shedding algorithm
    Serge Raoul Dzonde Naoussi
    Saatong Kenfack Tsobzé
    Godpromesse Kenne
    SN Applied Sciences, 2019, 1
  • [49] Adaptive Load Shedding for Grid Emergency Control via Deep Reinforcement Learning
    Zhang, Ying
    Yue, Meng
    Wang, Jianhui
    2021 IEEE POWER & ENERGY SOCIETY GENERAL MEETING (PESGM), 2021,
  • [50] Underfrequency Load Shedding Strategy With an Adaptive Variation Capability for Multi-Microgrids
    Chen, Ran
    Xu, Hanping
    Zhou, Li
    Cai, Jie
    Xiong, Chuanyu
    Zhou, Yingbo
    Zhang, Xuefei
    Dong, Qingguo
    Wang, Can
    Yang, Nan
    IEEE ACCESS, 2023, 11 : 17294 - 17304