Using the advanced DMS functions to handle the impact of plug-in Electric vehicles on distribution networks
Paper in proceeding, 2014

Integration of Electric vehicles and their impact on power system have been a major topic within smart grid initiatives. It is proven that managing larger amount of loads in form of plug-in Electric vehicles (PEV) is a challenge for operation of low and medium voltage distribution network. The main objective of this paper is to discuss the usage of 'Integrated Volt/Var Optimization' function (which is one of main advanced distribution management system (DMS) functions) for handling the larger share of PEV load and reducing their impact on operation of Distribution System (DS). For this purpose, we propose a method for evaluating the impact of PEV charging on steady state operating condition of DS and identifying its possible capacity limitations in case of significant penetration of PEVs. We have applied a stochastic modeling for base EV load and have examined several different scenarios based on charging power and penetration level of PEVs to compare uncontrolled charging with base operation conditions. By presenting the results from our developed Volt/Var Optimization (VVO) engine, it is concluded that DMS functions can support handling of these new operating conditions for DSOs. A real distribution network in south western part of Sweden is used as test system for this study while a set of realistic load profile has been created based on real driving pattern (using the results of national survey from Swedish traffic authority) and actual base load for one year. In this work, the VVO function have been implemented in General Algebraic Modeling System (GAMS) by using a single mixed integer linear programming (MILP) model for the volt-var problem. The results of optimization are system loss and voltage profile along the network in comparison with 'base-case' solution.

Mixed Integer Linear Programming (MILP)

Volt/Var Optimization (VVO)

Distribution systems

Electric vehicle

Plug-in hybrid

Smart Grid

Energy management

Author

S. Rahimi

ABB Sweden

University of Genoa

K. Zhu

ABB Sweden

S. Massucco

University of Genoa

F. Silvestro

University of Genoa

David Steen

Chalmers, Energy and Environment, Electric Power Engineering

2014 IEEE International Electric Vehicle Conference, IEVC 2014


978-147996075-0 (ISBN)

Subject Categories

Transport Systems and Logistics

DOI

10.1109/IEVC.2014.7056127

More information

Latest update

10/9/2021