Dynamic forecasting, optimization and real-time energy management of gridable vehicle – a review


  • Abdilaziz J. Alshareef Department of Electrical and Computer Engineering (ECE), King Abdulaziz University, Jeddah, Saudi Arabia
  • Ahmed Saber Operation Technology, Inc. Irvine, CA, USA
  • Ibrahim M. Mehedi Department of Electrical and Computer Engineering (ECE), Center of Excellence in Intelligent Engineering Systems (CEIES), King Abdulaziz University, Jeddah, Saudi Arabia https://orcid.org/0000-0001-8073-9750


Smart grid; renewable energy; vehicle grid; optimization; dynamic forecasting


This paper investigates the concept of the new generation smart power grid that includes gridable vehicles and renewable energy sources. Here it is analyzed the feasibility of developing a real-time dynamic stochastic optimization approach that will result in a combined cost-emission reduction by the maximum utilization of clean energy sources. The concept in this paper is look at a gridable vehicle (GV) as a small portable power plant (SP3) and a smart parking lot (Smart Park) as a virtual power plant (VPP). After an extensive investigation of existing literature review, it is recommended that a dynamic stochastic optimization (DSO) approach can be used to automatically schedule and coordinate non-stationary sources to get full benefits of renewable energy sources (RESs) such that (1) load demand can be leveled; (2) cost and emission will be reduced; (3) reserve and reliability of a smart grid can be increased when millions of new loads, e.g., GVs, are to be integrated.

DOI: http://doi.org/10.5281/zenodo.3928791