State Transition Modeling Method for Optimal Dispatching for Integrated Energy System Based on Cyber-Physical System

被引:1
作者
Yang, Yi [1 ]
Zhang, Peng [1 ]
Wang, Can [1 ]
Zhao, Zhuoli [2 ]
Lai, Loi Lei [2 ]
机构
[1] China Three Gorges Univ, Coll Elect Engn & New Energy, Hubei Prov Key Lab Operat & Control Cascaded Hydro, Yichang, Peoples R China
[2] Guangdong Univ Technol, Sch Automat, Dept Elect Engn, Guangzhou, Peoples R China
基金
中国国家自然科学基金;
关键词
Integrated energy system (IES); cyber-physical system (CPS); state transition; modeling; optimal dispatching; OPTIMAL OPERATION ANALYSIS; POWER-SYSTEMS; OPTIMIZATION;
D O I
10.35833/MPCE.2024.000090
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
The traditional energy hub based model has difficulties in clearly describing the state transition and transition conditions of the energy unit in the integrated energy system (IES). Therefore, this study proposes a state transition modeling method for an IES based on a cyber-physical system (CPS) to optimize the state transition of energy unit in the IES. This method uses the physical, integration, and optimization layers as a three-layer modeling framework. The physical layer is used to describe the physical models of energy units in the IES. In the integration layer, the information flow is integrated into the physical model of energy unit in the IES to establish the state transition model, and the transition conditions between different states of the energy unit are given. The optimization layer aims to minimize the operating cost of the IES and enables the operating state of energy units to be transferred to the target state. Numerical simulations show that, compared with the traditional modeling method, the state transition modeling method based on CPS achieves the observability of the operating state of the energy unit and its state transition in the dispatching cycle, which obtains an optimal state of the energy unit and further reduces the system operating costs.
引用
收藏
页码:1617 / 1630
页数:14
相关论文
共 26 条
  • [1] Performance prediction of micro-CHP systems using simple virtual operating cycles
    Bianchi, M.
    De Pascale, A.
    Melino, F.
    Peretto, A.
    [J]. APPLIED THERMAL ENGINEERING, 2014, 71 (02) : 771 - 779
  • [2] Operational Risk Evaluation of Active Distribution Networks Considering Cyber Contingencies
    Cao, Ge
    Gu, Wei
    Li, Peixin
    Sheng, Wanxing
    Liu, Keyan
    Sun, Lijing
    Cao, Zhihuang
    Pan, Jing
    [J]. IEEE TRANSACTIONS ON INDUSTRIAL INFORMATICS, 2020, 16 (06) : 3849 - 3861
  • [3] Capacity Planning of Energy Hub in Multi-Carrier Energy Networks: A Data-Driven Robust Stochastic Programming Approach
    Cao, Yang
    Wei, Wei
    Wang, Jianhui
    Mei, Shengwei
    Shafie-khah, Miadreza
    Catalao, Joao P. S.
    [J]. IEEE TRANSACTIONS ON SUSTAINABLE ENERGY, 2020, 11 (01) : 3 - 14
  • [4] Energy Circuit-Based Integrated Energy Management System: Theory, Implementation, and Application
    Chen, Binbin
    Guo, Qinglai
    Yin, Guanxiong
    Wang, Bin
    Pan, Zhaoguang
    Chen, Yuwei
    Wu, Wenchuan
    Sun, Hongbin
    [J]. PROCEEDINGS OF THE IEEE, 2022, 110 (12) : 1897 - 1926
  • [5] Comprehensive Evaluation of Electric Power Prediction Models Based on D-S Evidence Theory Combined with Multiple Accuracy Indicators
    Cui, Qiong
    Zhu, Jizhong
    Shu, Jie
    Huang, Lei
    Ma, Zetao
    [J]. JOURNAL OF MODERN POWER SYSTEMS AND CLEAN ENERGY, 2022, 10 (03) : 597 - 605
  • [6] Distributed Resilient Control for Energy Storage Systems in Cyber-Physical Microgrids
    Deng, Chao
    Wang, Yu
    Wen, Changyun
    Xu, Yan
    Lin, Pengfeng
    [J]. IEEE TRANSACTIONS ON INDUSTRIAL INFORMATICS, 2021, 17 (02) : 1331 - 1341
  • [7] Integrated Planning of Cyber-Physical Active Distribution System Considering Multidimensional Uncertainties
    Gao, Hongjun
    Lyu, Xiaodong
    He, Shuaijia
    Wang, Lingfeng
    Wang, Cheng
    Liu, Junyong
    [J]. IEEE TRANSACTIONS ON SMART GRID, 2022, 13 (04) : 3145 - 3159
  • [8] A Lyapunov Optimization-Based Energy Management Strategy for Energy Hub With Energy Router
    Li, Penghua
    Sheng, Wanxing
    Duan, Qing
    Li, Zhen
    Zhu, Cunhao
    Zhang, Xinyu
    [J]. IEEE TRANSACTIONS ON SMART GRID, 2020, 11 (06) : 4860 - 4870
  • [9] Ultra-short-term Interval Prediction of Wind Power Based on Graph Neural Network and Improved Bootstrap Technique
    Liao, Wenlong
    Wang, Shouxiang
    Bak-Jensen, Birgitte
    Pillai, Jayakrishnan Radhakrishna
    Yang, Zhe
    Liu, Kuangpu
    [J]. JOURNAL OF MODERN POWER SYSTEMS AND CLEAN ENERGY, 2023, 11 (04) : 1100 - 1114
  • [10] Intelligent Modeling and Optimization for Smart Energy Hub
    Liu, Tianhao
    Zhang, Dongdong
    Dai, Hang
    Wu, Thomas
    [J]. IEEE TRANSACTIONS ON INDUSTRIAL ELECTRONICS, 2019, 66 (12) : 9898 - 9908