Optimal Charging Algorithm Based on Receding Horizon Framework for Electric Two-wheeler Charging Stations | Zendy

Van Nguyen Ngoc | Zendy; Duc Nguyen Huu | Zendy

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Optimal Charging Algorithm Based on Receding Horizon Framework for Electric Two-wheeler Charging Stations

Author(s) -

Van Nguyen Ngoc,

Duc Nguyen Huu

Publication year - 2025

Publication title -

ieee access

Language(s) - English

Resource type - Magazines

SCImago Journal Rank - 0.587

H-Index - 127

eISSN - 2169-3536

DOI - 10.1109/access.2025.3591193

Subject(s) - aerospace , bioengineering , communication, networking and broadcast technologies , components, circuits, devices and systems , computing and processing , engineered materials, dielectrics and plasmas , engineering profession , fields, waves and electromagnetics , general topics for engineers , geoscience , nuclear engineering , photonics and electrooptics , power, energy and industry applications , robotics and control systems , signal processing and analysis , transportation

In Vietnam urban traffic, electric two-wheelers have emerged as a potential alternative to gasoline-powered motorcycles. Thus, charging infrastructure for electric two-wheelers is being in the front line of research and development. Moreover, high rooftop power potential and the encouragement of self-generation-self-consumption propel the need for photovoltaic-integrated charging solutions which in turn might pose technical challenges relating to optimal charging operation. In this work, an optimal real-time scheduling algorithm for photovoltaic-integrated electric two-wheeler charging stations is proposed. The algorithm aims at improving the total load profile as well as load leveling, peak shaving and valley filling. By leveraging receding horizon framework combined with grouping approach, the proposed algorithm can effectively perform optimal scheduling while covering the uncertainties of arrival/ departure and energy level variation of vehicles. The effectiveness of the algorithm is verified and analyzed through various case studies and operation scenarios.

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