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

Authors

  • 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

Keywords:

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

Abstract

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

Published

2020-07-02