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Research Article

Low-carbon optimal dispatch of virtual power plant based on time-of-use ladder carbon emission rights exchange mechanism

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Article: 2180688 | Received 09 Dec 2022, Accepted 11 Feb 2023, Published online: 23 Feb 2023

References

  • Cao, Y., Li, Q., Tan, Y., Li, Y., Chen, Y., Shao, X., & Zou, Y. (2018). A comprehensive review of energy internet: basic concept, operation and planning methods, and research prospects. Journal of Modern Power Systems and Clean Energy, 6(3), 399–411. https://doi.org/10.1007/s40565-017-0350-8
  • Chen, D., Liu, F., & Liu, S. (2022). Optimization of virtual power plant scheduling coupling with p2g-ccs and doped with gas hydrogen based on stepped carbon trading. Power System Technology, 46(06), 2042–2054. https://doi.org/10.13335/j.1000-3673.pst.2021.2177
  • Cui, Y., Yan, S., Zhong, W., Wang, Z., Zhang, P., & Zhao, Y. (2020). Optimal thermoelectric dispatching of regional integrated energy system with power-to-gas. Power System Technology, 44(11), 4254–4264. https://doi.org/10.13335/j.1000-3673.pst.2019.2468
  • Gao, Z., Xu, W., Chuanwen, J., Yu, Z., & Zhengyu, W. (2016). Economic analysis of virtual power plants based on bi-level optimization dispatch. Power System Technology, 40(8), 2295–2301. https://doi.org/10.13335/j.1000-3673.pst.2016.08.007
  • Guo, W., Mao, Y., Zhang, X., & Yin, H. (2022). Internal benefit optimization model of gas-thermal power virtual power plant under China's carbon neutral target. Energy Science & Engineering, 10(4), 1227–1239. https://doi.org/10.1002/ese3.1097
  • Guorong, Z., & Xiaran, C. (2017). Future development of energy internet. Proceedings of the EPAE, 37(1), 1–7. https://doi.org/10.16081/j.issn.1006-6047.2017.01.001
  • Hongshang, Z., & Ran, L. (2017). Benefit analysis of optimal schedule of virtual power plant under reward-punishment mechanism. Power System Technology, 41(9), 2840–2846. https://doi.org/10.13335/j.1000-3673.pst.2017.0907
  • Hua, P., Zuofang, L., Qiangzhong, X., Fang, Z., & Yuhan, X. (2020). Economic dispatch of wind/pv/gas/storage virtural power plant based on time-of-use power price. Proceedings of the AESS, 41(8), 115–122. https://doi.org/10.19912/j.0254-0096.2020.08.016
  • Hübler, M., & Löschel, A. (2013). The EU decarbonisation roadmap 2050-what way to walk? Energy Policy, 55, 190–207. https://doi.org/10.1016/j.enpol.2012.11.054
  • Hui, S., Xuanxuan, F., Shubo, H., Feixiang, P., Jinsong, L., & Changhai, S. (2022). Internal and external coordination biddingstrategy of virtual power plant participating in day-ahead power market. Power System Technology, 46(04|4), 1248–1262. https://doi.org/10.13335/j.1000-3673.pst.2021.1819
  • Ji, X., Li, Y., Yu, Y., & Fan, S. (2018). Optimal dispatching and game analysis of power grid considering demand response and pumped storage. Systems Science & Control Engineering, 6(3), 270–277. https://doi.org/10.1080/21642583.2018.1553074
  • Jie, Y., Zhang, X., Yong, T., Chen, R., & Li, J. (2019). Low carbon power dispatch strategy for regional integrated virtual power plants under the constraint of environmental impact assessment. Ekoloji, 28(107), 1411–1416.
  • Jizhen, L., Mingyang, L., Fang, F., & Yuguang, N. (2014). Review on virtual power plants. Proceedings of the CSEE, 34(29), 5103–5111. https://doi.org/10.13334/j.0258-8013.pcsee.2014.29.012
  • Li, L., Ye, F., Li, Y., & Chang, C.-T. (2019). How will the Chinese certified emission reduction scheme save cost for the national carbon trading system? Journal of Environmental Management, 244, 99–109. https://doi.org/10.1016/j.jenvman.2019.04.100
  • Liu, L., Chen, C., Zhao, Y., & Zhao, E. (2015). China’s carbon-emissions trading: Overview, challenges and future. Renewable and Sustainable Energy Reviews, 49, 254–266. https://doi.org/10.1016/j.rser.2015.04.076
  • Liu, Z., Zheng, W., Qi, F., Wang, L., Zou, B., Wen, F., & Xue, Y. (2018). Optimal dispatch of a virtual power plant considering demand response and carbon trading. Energies, 11(6), 1488. https://doi.org/10.3390/en11061488
  • Nafkha-Tayari, W., Ben Elghali, S., Heydarian-Forushani, E., & Benbouzid, M. (2022). Virtual power plants optimization issue: A comprehensive review on methods, solutions, and prospects. Energies, 15(10), 3607. https://doi.org/10.3390/en15103607
  • Naval, N., & Yusta, J. M. (2021). Virtual power plant models and electricity markets-a review. Renewable and Sustainable Energy Reviews, 149, 111393. https://doi.org/10.1016/j.rser.2021.111393
  • NNEC Monitoring & Center E. W. (2022, May 25). Evaluation and analysis of national new energy power consumption in the first quarter of 2022. https://www.candela.cn/21c08c79b1/.
  • Pandžić, H., Kuzle, I., & Capuder, T. (2013). Virtual power plant mid-term dispatch optimization. Applied Energy, 101, 134–141. https://doi.org/10.1016/j.apenergy.2012.05.039
  • Peng, F., Hu, S., Fan, X., Sun, H., Zhou, W., Guo, F., & Song, W. (2021). Sequential coalition formation for wind-thermal combined bidding. Energy, 236, 121475. https://doi.org/10.1016/j.energy.2021.121475
  • Pudjianto, D., Ramsay, C., & Strbac, G. (2007). Virtual power plant and system integration of distributed energy resources. IET Renewable Power Generation, 1(1), 10–16. https://doi.org/10.1049/iet-rpg:20060023
  • Shabanzadeh, M., Sheikh-El-Eslami, M.-K., & Haghifam, M.-R. (2015). The design of a riskhedging tool for virtual power plants via robust optimization approach. Applied Energy, 155, 766–777. https://doi.org/10.1016/j.apenergy.2015.06.059
  • Wenlue, D., Qun, W., & Li, Y. (2015). Coordination dispatching model of virtual power plant and distribution company with wind and water. Automation of Electric Power Systems, 9, 75–81.
  • Xin, A., Shupeng, Z., & Yuequn, Z. (2016). Study on time of use pricing of user side considering wind power uncertainty. Power System Technology, 40(5), 1529–1535. https://doi.org/10.13335/j.1000-3673.pst.2016.05.035
  • Zhou, B., Zhang, K., Chan, K. W., Li, C., Lu, X., Bu, S., & Gao, X. (2020). Optimal coordination of electric vehicles for virtual power plants with dynamic communication spectrum allocation. IEEE Transactions on Industrial Informatics, 17(1), 450–462. doi:10.1109/TII.2020.2986883