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Research on Real-Time Optimized Operation and Dispatching Strategy for Integrated Energy System Based on Error Correction

Author

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  • Aidong Zeng

    (School of Electric Power Engineering, Nanjing Institute of Technology, Nanjing 211167, China
    Jiangsu Collaborative Innovation Center for Smart Distribution Network, Nanjing Institute of Technology, Nanjing 211100, China)

  • Sipeng Hao

    (School of Electric Power Engineering, Nanjing Institute of Technology, Nanjing 211167, China
    Jiangsu Collaborative Innovation Center for Smart Distribution Network, Nanjing Institute of Technology, Nanjing 211100, China)

  • Jia Ning

    (School of Electric Power Engineering, Nanjing Institute of Technology, Nanjing 211167, China
    Jiangsu Collaborative Innovation Center for Smart Distribution Network, Nanjing Institute of Technology, Nanjing 211100, China)

  • Qingshan Xu

    (School of Electrical Engineering, Southeast University, Nanjing 210096, China)

  • Ling Jiang

    (Electric Power Research Institute, State Grid Tianjin Electric Power Company, State Grid, Tianjin 300010, China)

Abstract

A real-time error correction operation model for an integrated energy system is proposed in this paper, based on the analysis of the real-time optimized operation structure of an integrated energy system and the characteristics of the system. The model makes real-time corrections to the day-ahead operation strategy of the integrated energy system, to offset forecast errors from the renewable power generation system and multi-energy load system. When unbalanced power occurs in the system due to prediction errors, the model comprehensively considers the total capacity of each energy supply and energy storage equipment, adjustable margin, power climbing speed and adjustment cost, to formulate the droop rate which determines the unbalanced power that each device will undertake at the next time interval, while taking the day-ahead dispatching goals of the system into consideration. The case study shows that the dispatching strategy obtained by the real-time error correction operation model makes the power output change trend of the energy supply equipment consistent with the day-ahead dispatching plan at the next time interval, which ensures the safety, stability and economy of the real-time operation of the integrated energy system.

Suggested Citation

  • Aidong Zeng & Sipeng Hao & Jia Ning & Qingshan Xu & Ling Jiang, 2020. "Research on Real-Time Optimized Operation and Dispatching Strategy for Integrated Energy System Based on Error Correction," Energies, MDPI, vol. 13(11), pages 1-21, June.
  • Handle: RePEc:gam:jeners:v:13:y:2020:i:11:p:2908-:d:368030
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    References listed on IDEAS

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    1. Zheng, C.Y. & Wu, J.Y. & Zhai, X.Q., 2014. "A novel operation strategy for CCHP systems based on minimum distance," Applied Energy, Elsevier, vol. 128(C), pages 325-335.
    2. Kang, Ligai & Yang, Junhong & An, Qingsong & Deng, Shuai & Zhao, Jun & Wang, Hui & Li, Zelin, 2017. "Effects of load following operational strategy on CCHP system with an auxiliary ground source heat pump considering carbon tax and electricity feed in tariff," Applied Energy, Elsevier, vol. 194(C), pages 454-466.
    3. Miao Li & Hailin Mu & Huanan Li, 2013. "Analysis and Assessments of Combined Cooling, Heating and Power Systems in Various Operation Modes for a Building in China, Dalian," Energies, MDPI, vol. 6(5), pages 1-22, May.
    4. Stadler, M. & Kloess, M. & Groissböck, M. & Cardoso, G. & Sharma, R. & Bozchalui, M.C. & Marnay, C., 2013. "Electric storage in California’s commercial buildings," Applied Energy, Elsevier, vol. 104(C), pages 711-722.
    5. Wang, Jiangjiang & Yang, Ying & Mao, Tianzhi & Sui, Jun & Jin, Hongguang, 2015. "Life cycle assessment (LCA) optimization of solar-assisted hybrid CCHP system," Applied Energy, Elsevier, vol. 146(C), pages 38-52.
    6. Olaszi, Balint D. & Ladanyi, Jozsef, 2017. "Comparison of different discharge strategies of grid-connected residential PV systems with energy storage in perspective of optimal battery energy storage system sizing," Renewable and Sustainable Energy Reviews, Elsevier, vol. 75(C), pages 710-718.
    7. Jayasekara, Saliya & Halgamuge, Saman K. & Attalage, Rahula A. & Rajarathne, Rohitha, 2014. "Optimum sizing and tracking of combined cooling heating and power systems for bulk energy consumers," Applied Energy, Elsevier, vol. 118(C), pages 124-134.
    8. Guillermo Rey & Carlos Ulloa & José Luís Míguez & Antón Cacabelos, 2016. "Suitability Assessment of an ICE-Based Micro-CCHP Unit in Different Spanish Climatic Zones: Application of an Experimental Model in Transient Simulation," Energies, MDPI, vol. 9(11), pages 1-13, November.
    9. Dongxiao Niu & Di Pu & Shuyu Dai, 2018. "Ultra-Short-Term Wind-Power Forecasting Based on the Weighted Random Forest Optimized by the Niche Immune Lion Algorithm," Energies, MDPI, vol. 11(5), pages 1-21, April.
    10. Li, Longxi & Yu, Shiwei & Mu, Hailin & Li, Huanan, 2018. "Optimization and evaluation of CCHP systems considering incentive policies under different operation strategies," Energy, Elsevier, vol. 162(C), pages 825-840.
    11. Xu, Xiandong & Jin, Xiaolong & Jia, Hongjie & Yu, Xiaodan & Li, Kang, 2015. "Hierarchical management for integrated community energy systems," Applied Energy, Elsevier, vol. 160(C), pages 231-243.
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