A framework for day-ahead optimal charging scheduling of electric vehicles providing route mapping: Kowloon case study

With the ever-increasing growth of electric vehicles (EV)s in power industry, their significance as a flexible load has increased drastically. On other hand, uncontrolled charging these can cause serious problems grid, such peak demand, decrease life expectancy transformers and result, an increase costs EVs for EV owners. In this paper, framework day-ahead optimal is proposed which through optimization active reactive exchange at each time interval, could prevent mentioned above same benefit owners network operators simultaneously. Furthermore, taking into account effective factors on electrical energy consumption driving pattern owners, route mapping algorithm developed based framework, so to provide with better services. The simulations are carried out using hybrid interior-point approach, traffic geographic data collected from city Kowloon standard IEEE 33 bus system used. simulation results show that integrating reduce loss during hours EVs’ presence selling price electricity by 24.93% 33.6%, respectively comparison mode. Also, average 2.97% mode compared