AUTHOR=Yang Wenqiang , Peng Zhanlei , Feng Wei , Menhas Muhammad Ilyas 

TITLE=A Novel Real-Coded Genetic Algorithm for Dynamic Economic Dispatch Integrating Plug-In Electric Vehicles

JOURNAL=Frontiers in Energy Research

VOLUME=Volume 9 - 2021

YEAR=2021

URL=https://www.frontiersin.org/journals/energy-research/articles/10.3389/fenrg.2021.706782

DOI=10.3389/fenrg.2021.706782

ISSN=2296-598X

ABSTRACT=Massive popularity of plug-in electric vehicles (PEVs) may bring considerable opportunities and challenges to the power grid. The scenario highly is depended on whether PEVs can be effectively managed. Dynamic economic dispatch (DED), considering valve-point effects and transmission losses, is a complex constrained optimization problem with non-smooth, non-linear and non-convex characteristics. High efficient DED method provides a powerful tool in both power system scheduling and PEVs charging coordination. In this paper, firstly, PEVs are integrated into the DED problem, which can carry out orderly charge and discharge management to improve the quality of the grid. To tackle this, a novel real-coded genetic algorithm (RCGA) namely dimension-by-dimension mutation based on feature intervals (GADMFI), is proposed to enhance the exploitation and exploration of conventional RCGAs. Thirdly, a simple and efficient constrain handling method is proposed for infeasible solution for DED. Finally, the proposed method is compared with the current literatures on 6 cases with 3 scenarios, including only thermal units, units with disorderly PEVs and units with orderly PEVs. The proposed GADMFI shows outstanding advantages on solving the DED with/without PEVs problem, obtaining the effect of cutting peaks and filling valleys on the DED with orderly PEVs problem