Advertisement

Frontiers in Energy

, Volume 12, Issue 4, pp 569–581 | Cite as

Optimal dispatch of multi energy system using power-to-gas technology considering flexible load on user side

  • Zi Ling
  • Xiu YangEmail author
  • Zilin Li
Research Article
  • 8 Downloads

Abstract

The relation between power-to-gas technology (P2G) and energy interconnection becomes increasingly close. Meanwhile, the participation of flexible load on user side in system optimization has attracted much attention as an efficient approach to relieve the contradiction between energy supply and energy demand. Based on the concept of energy hub, according to its series characteristic, this paper established a generic multi-energy system model using the P2G technology. The characteristic of flexible load on user side was considered and optimal dispatch analysis was made, so as to reduce the cost, to reasonably dispatch the flexible load, to reduce the discharge, to enhance the new energy output, and to increase the power-to-gas conversion efficiency. Finally, a concrete analysis was made on the optimal dispatch result of the multi-energy system using the P2G technology considering flexible load on user side in the calculating example, and optimal dispatch of the system was verified via four different scenarios. The results indicate that cooperative dispatch of multi-energy system using the P2G technology considering flexible load on user side is the most economic, and can make a contribution to absorption of new energy and P2G conversion. In this way, environmental effects and safe and stable operation of the system can be guaranteed.

Keywords

multi-energy system energy hub series characteristic optimal dispatch flexible load 

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

Notes

Acknowledgements

This work was financially supported by the local capacity construction plan of Shanghai Municipal Science and Technology Commission (No. 16020500900).

References

  1. 1.
    Wang K, Yu J, Yu Y, Qian Y R, Zeng D Z, Guo S, Xiang Y,Wu J S. A survey on energy internet: architecture, approach, and emerging technologies. IEEE Systems Journal, 2018, 35(5):130–139Google Scholar
  2. 2.
    Geidl M, Koeppel G, Favre-Perrod P, Klockl B, Andersson G, Frohlich K. Energy hubs for the future. IEEE Power & Energy Magazine, 2007, 5(1): 24–30Google Scholar
  3. 3.
    Zhang X, Shahidehpour M, Alabdulwahab A, Abusorrah A. Optimal expansion planning of energy hub with multiple energy infrastructures. IEEE Transactions on Smart Grid, 2015, 6(5): 2302–2311Google Scholar
  4. 4.
    Ma T F, Wu J Y, Hao L L. Energy flow calculation and integrated simulation of micro-energy grid with combined cooling, heating and power. Automation of Electric Power Systems, 2016, 40(23): 22–27 (in Chinese)Google Scholar
  5. 5.
    Bozchalui M C, Hashmi S A, Hassen H, Canizares C A, Bhattacharya K. Optimal operation of residential energy hubs in smart grids. IEEE Transactions on Smart Grid, 2012, 3(4): 1755–1766Google Scholar
  6. 6.
    Wang Y, Zhao J,Wen F, Xue Y. Market equilibrium of multi-energy system with power-to-gas functions. Automation of Electric Power Systems, 2015, 39(21): 1–10 (in Chinese)Google Scholar
  7. 7.
    Li Y, Liu W, Zhao J H. Optimal dispatch of combined electricitygas-heat energy systems with power-to-gas devices and benefit analysis of wind power accommodation. Power System Technology, 2016, 40(12): 3680–3689 (in Chinese)Google Scholar
  8. 8.
    Huang G, Liu W J, Wen F S. Collaborative planning of integrated electricity and natural gas energy systems with power-to-gas stations. Electric Power Construction, 2016, 37(09): 1–13 (in Chinese)Google Scholar
  9. 9.
    Dong S, Wang C F, Liang J. Multi-objective optimal day ahead dispatch of integrated energy system considering power-to-gas operational cost. Automation of Electric Power Systems, 2018, 42 (11): 8–15 (in Chinese)Google Scholar
  10. 10.
    Wang Y J, Dong Z Y, Xu Y. Enabling large-scale energy storage and renewable energy grid connectivity: a power-to-gas approach. Proceedings of the CSEE, 2015, 35(14): 3586–3595 (in Chinese)Google Scholar
  11. 11.
    Wei Z N, Zhang S, Sun G Q, Zang H X, Chen S. Power-to-gas considered peak load shifting research for integrated electricity and natural gas energy systems. Proceedings of the CSEE, 2017, 37(16): 4601–4609 (in Chinese)Google Scholar
  12. 12.
    Du L, Su L, Chen H H. Multi-index evaluation of integrated energy system with P2G planning. Electric Power Automation Equipment, 2017, 37(06): 110–116 (in Chinese)Google Scholar
  13. 13.
    Wang Y N, Xu X Y, Yan Z,Wang S,Wu Z H. Optimizing operation of integrated electrical and gas network with power-to-gas process. Modern Electric power, 2017, 34(04): 1–7 (in Chinese)Google Scholar
  14. 14.
    Yang H, Zhang J, Qiu J, Zhang S, Lai M, Dong Z Y. A practical pricing approach to smart grid demand response based on load classification. IEEE Transactions on Smart Grid, 2018, 9(1):179–190Google Scholar
  15. 15.
    Wang K, Yao J, Yao L, Yang S, Yong T. Survey of research on flexible loads scheduling technologies. Automation of Electric Power Systems, 2014, 38(20): 127–135 (in Chinese)Google Scholar
  16. 16.
    Fu Y, Jiang Y, Li Z K, Wei C. Optimal economic dispatch for microgrid considering shiftable loads. Proceedings of the CSEE, 2014, 34(16): 2612–2620 (in Chinese)Google Scholar
  17. 17.
    He S, Zheng Y, Cai X, Wu X, Shi S. Optimal operation for demand side management based on load-storage microgrid. Automation of Electric Power Systems, 2015, 39(19): 15–20 (in Chinese)Google Scholar
  18. 18.
    Shun H E, Zheng Y, Cai X, Wu X D, Shi S. Receding-horizon optimization for microgrid energy management. Power System Technology, 2014, 38(09): 2349–2355 (in Chinese)Google Scholar
  19. 19.
    Zhang H, Wen F, Zhang C, Meng J, Lin G. Operation optimization model of home energy hubs considering comfort level of customers. Automation of Electric Power Systems, 2016, 40(20): 32–39 (in Chinese)Google Scholar
  20. 20.
    Chen Z, Wang D, Jia H, Wang W, Guo B. Research on optimal dayahead economic dispatching strategy for microgrid considering P2G and multi-source energy storage system. Proceedings of the CSEE, 2017, 37(11): 3067–3077 (in Chinese)Google Scholar
  21. 21.
    Salehimaleh M, Akbarimajd AValipour, K, Dejamkhooy A. Generalized modeling and optimal management of energy hub based electricity, heat and cooling demands. Energy, 2018, 159: 669–685Google Scholar
  22. 22.
    Sun Q, Zhao M, Chen Y, Ma D. Optimal energy flow of multiple energy systems in energy internet. Proceedings of the CSEE, 2017, 37(06): 1590–1599 (in Chinese)Google Scholar
  23. 23.
    Chen L, Xu F, Wang X, Min Y, Ding M. Implementation and effect of thermal storage in improving wind power accommodation. Proceedings of the CSEE, 2015, 35(17): 4283–4290 (in Chinese)Google Scholar
  24. 24.
    Gu W, Lu S, Wang J, Yin X, Zhang C. Modeling of the heating network for multi-district integrated energy system and its operation optimization. Proceedings of the CSEE, 2017, 37(05): 1305–1316 (in Chinese)Google Scholar
  25. 25.
    Chen J, Yang X, Zhu L, Zhang M X. Genetic algorithm based economic operation optimization of a combined heat and power microgrid. Power System Protection and Control, 2013, 41(8): 7–15 (in Chinese)Google Scholar

Copyright information

© Higher Education Press and Springer-Verlag GmbH Germany, part of Springer Nature 2018

Authors and Affiliations

  1. 1.College of Electric EngineeringShanghai University of Electric PowerShanghaiChina

Personalised recommendations