Dynamic reconfiguration of active distribution network considering electric vehicle charging demand under real-time electricity price

Yingliang Li; Boxu Bai

doi:10.1117/12.2689324

10 August 2023 Dynamic reconfiguration of active distribution network considering electric vehicle charging demand under real-time electricity price

Yingliang Li, Boxu Bai

Author Affiliations +

Proceedings Volume 12748, 5th International Conference on Information Science, Electrical, and Automation Engineering (ISEAE 2023); 1274837 (2023) https://doi.org/10.1117/12.2689324
Event: 5th International Conference on Information Science, Electrical and Automation Engineering (ISEAE 2023), 2023, Wuhan, China

Abstract

In the future, with the large-scale integration of distributed generation (DG) and electric vehicle (EV), due to the dual uncertainty of time and space, it is bound to pose new challenges to the economic and safe operation of urban distribution network. As one of the important means of power grid optimization, distribution network reconfiguration can dynamically adjust the power grid structure according to the spatial and temporal changes of EV charging load. Therefore, in order to improve the economy and safety of urban distribution network operation, this paper proposes a dynamic reconfiguration model of active distribution network considering EV charging demand under the guidance of real-time electricity price. At the same time, the reconfiguration period is divided based on the peak-valley membership degree. The ratio of active network loss at each moment of the system and the operating loss cost after the introduction of time-of-use electricity price is used as the operation index, and the reconstruction period is reasonably divided by the change rate of membership degree. The demand response (DR) mechanism is introduced before the reconfiguration, and the active distribution network reconfiguration model with the minimum operating loss cost is established. The model is solved by the improved binary particle swarm optimization algorithm. Finally, a case study of a city's traffic network and an improved IEEE33 node coupling system is carried out to verify that the time-sharing reconstruction method in this paper can effectively deal with the influence of DG output, EV charging and other factors on the urban distribution network, and improve the economy and safety of the overall distribution network operation.

Citation Download Citation

Yingliang Li and Boxu Bai "Dynamic reconfiguration of active distribution network considering electric vehicle charging demand under real-time electricity price", Proc. SPIE 12748, 5th International Conference on Information Science, Electrical, and Automation Engineering (ISEAE 2023), 1274837 (10 August 2023); https://doi.org/10.1117/12.2689324

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KEYWORDS

Switches

Power grids

Safety

Photovoltaics

Switching

Particle swarm optimization

Reconstruction algorithms

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