Abstract
In this paper, unit commitment and the scheduling problem of plug-in electric vehicles (PEV) under the condition of power grid feedback are jointly considered, formulating a many objective problem. The objectives involve economic and environmental impact, carbon emission as well as the user satisfaction. To solve this multi-objective problem, an improved MOEA/D algorithm is proposed where levy flight is integrated to improve the algorithm performance. The improved MOEA/D algorithm, NSGA-II algorithm and the traditional MOEA/D algorithm are compared. The experimental results show that the improved MOEA/D algorithm is comprehensive optimal in the multi-objective function, which shows the effectiveness of the improved algorithm. Moreover, the four objectives are comprehensively considered to balance the multiple factors in the application.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Similar content being viewed by others
References
Yang, Z., Li, K., Niu, Q., et al.: A novel parallel-series hybrid meta-heuristic method for solving a hybrid unit commitment problem. Knowl.-Based Syst. 134, 13–30 (2017)
Jian, L., Zheng, Y., Shao, Z.: High efficient valley-filling strategy for centralized coordinated charging of large-scale electric vehicles. Appl. Energy 186, 46–55 (2017)
Wang, Y., Yang, Z., Mourshed, M., et al.: Demand side management of plug-in electric vehicles and coordinated unit commitment: a novel parallel competitive swarm optimization method. Energy Convers. Manag. 196, 935–949 (2019)
Li, Y.F., Pedroni, N., Zio, E.: A memetic evolutionary multi-objective optimization method for environmental power unit commitment. IEEE Trans. Power Syst. 28(3), 2660–2669 (2013)
Trivedi, A., Srinivasan, D., Pal, K., et al.: Enhanced multiobjective evolutionary algorithm based on decomposition for solving the unit commitment problem. IEEE Trans. Ind. Inform. 11(6), 1346–1357 (2017)
Shukla, A., Singh, S.N.: Multi-objective unit commitment with renewable energy using hybrid approach. IET Renewable Power Gener. 10(3), 327–338 (2016)
Jian, L.N., Yan, C., et al.: High efficient valley-filling strategy for centralized coordinated charging of large-scale electric vehicles. Appl. Energy 186, 46–55 (2017)
Wu, L., Wang, Y., Yuan, X., et al.: Multiobjective optimization of HEV fuel economy and emissions using the self-adaptive differential evolution algorithm. IEEE Trans. Veh. Technol. 60(6), 2458–2470 (2011)
Zakariazadeh, A., Jadid, S., Siano, P.: Multi-objective scheduling of electric vehicles in smart distribution system. Energy Convers. Manag. 79, 43–53 (2014)
Lokeshgupta, B., Sivasubramani, S.: Multi-objective dynamic economic and emission dispatch with demand side management. Int. J. Electr. Power Energy Syst. 97, 334–343 (2018)
Elsied, M., Oukaour, A., Gualous, H., et al.: Optimal economic and environment operation of micro-grid power systems. Energy Convers. Manag. 122, 182–194 (2016)
Ma, H., Yang, Z., You, P., et al.: Multi-objective biogeography-based optimization for dynamic economic emission load dispatch considering plug-in electric vehicles charging. Energy 135, 101–111 (2017)
Hadayeghparast, S., Shayanfar, H., Farsangi, A.S., et al.: Stochastic multi-objective economic/emission energy management of a microgrid in presence of combined heat and power systems. In: 2019 IEEE/IAS 55th Industrial and Commercial Power Systems Technical Conference. IEEE (2019)
Swief, R.A., Amary, N.H., Kamh, M.Z.: Optimal energy management integrating plug in hybrid vehicle under load and renewable uncertainties. IEEE Access 8, 176895–176904 (2020)
Acknowledgments
This work was supported by the Natural Science Foundation of China (No. 52077213 and 62003332) and Youth Innovation Promotion Association CAS 2021358.
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2021 Springer Nature Singapore Pte Ltd.
About this paper
Cite this paper
Shao, P., Yang, Z., Zhu, X., Zhao, S. (2021). Multi-objective Optimization of Electric Vehicle and Unit Commitment Considering Users Satisfaction: An Improved MOEA/D Algorithm. In: Li, K., Coombs, T., He, J., Tian, Y., Niu, Q., Yang, Z. (eds) Recent Advances in Sustainable Energy and Intelligent Systems. LSMS ICSEE 2021 2021. Communications in Computer and Information Science, vol 1468. Springer, Singapore. https://doi.org/10.1007/978-981-16-7210-1_8
Download citation
DOI: https://doi.org/10.1007/978-981-16-7210-1_8
Published:
Publisher Name: Springer, Singapore
Print ISBN: 978-981-16-7209-5
Online ISBN: 978-981-16-7210-1
eBook Packages: Computer ScienceComputer Science (R0)