Researh on dynamic time-sharing tariff orderly charging strategy based on NSGA2 in PV-Storage-Charging stations

• Published in: Electric power systems research Vol. 225; p. 109784
• Main Authors: Zhaoyun, Zhang, linjun, Lv, Xinghua, Wang
• Format: Journal Article
• Language: English
• Published: Elsevier B.V 01.12.2023
• Subjects: Dynamic time-of-use tariffs; NSGA2; Photovoltaic(PV) -Storage-Charging stations; NSGA2; Photovoltaic(PV) -Storage-Charging stations; Dynamic time-of-use tariffs
• ISSN: 0378-7796; 1873-2046
• DOI: 10.1016/j.epsr.2023.109784

•Optimization for the orderly charging problem of optical storage charging stations in commercial areas from the point of view of charging stations.•Propose to adopt a stepped dynamic time-sharing tariff for orderly charging guidance by changing the service charges.•It is proposed to determine the local optimal solution by distance and to jump out the local optimal solution in optimization by improving the elite strategy and neighborhood search strategy.•The effects of different ordered charging strategies are compared and the results reflect the necessity of the methodology of this paper. The emergence of photovoltaic storage charging stations in commercial areas has effectively mitigated the issues of indirect carbon emissions and grid overload caused by electric vehicle charging loads. However, due to the rapid charging mode of the stations and the behavioral characteristics of commercial area users, improper guidance or inadequate guidance methods may lead to the phenomena of "abandoning light for real" and significant fluctuations in grid loads. To address these challenges, this paper analyzes real data from commercial area charging stations and proposes a tiered dynamic time-of-day pricing strategy, which is optimized using an improved Non-dominated Sorting Genetic Algorithm 2（NSGA2）. Simulation results demonstrate that the adoption of dynamic time-of-day pricing can effectively address photovoltaic integration issues, reduce user charging costs, enhance charging station profits, and achieve peak shaving and valley filling for grid loads.