A simulation setup for analyzing mitigation methods for reducing the impact of extensive EV penetration in the distribution network

IEEE PES Innovative Smart Grid Technologies Europe, pp. 01–05

Abstract

The growth of Electric Vehicles (EV) penetration into the distribution network around the world is expected to reduce greenhouse gas emissions from the transportation sector. Simultaneously transportation electrification is becoming a point of concern for power utilities and Distribution System Operators (DSO). Because of this, a simulation framework to understand the system conditions with extensive EV penetration, from the perspective of DSO, is needed. For this purpose, the modified CIGRE-MV 14-node test distribution network was modeled and simulated using the real-time open-source simulator, Dynamic Phasor Simulator (DPSim). It offers features such as Common Information Model import, realtime capability, and interfaces for communication with other simulators. This makes the simulator an ideal choice for performing real-time power flow simulation studies and controller hardware-in-the-loop simulations. The power flow data is communicated to the Power Management (PM) algorithm for analysis with the help of the lightweight Message Queuing Telemetry Transport (MQTT) protocol. This setup is demonstrated by applying it for analyzing the impacts of increasing penetration levels of EVs in the network that results in critical loading conditions during the peak-load hours. The anticipated impact is addressed by power injections from the Battery Energy Storage System (BESS) determined and initiated by the PM algorithm.

Authors 5

1. Ugyen Chophel

   King Mongkut's University of Technology North Bangkok

   Affiliation as printed

   Thai-German Graduate School of Engineering (TGGS) King Mongkut's University of Technology North Bangkok (KMUTNB), Bangkok, Thailand

2. Charukeshi Joglekar Aachen Institute for Automation of Complex Power Systems (ACS) E.ON ERC -

   RWTH Aachen University

   Affiliation as printed

   Institute for Automation of Complex Power Systems (ACS) E.ON ERC - RWTH Aachen University, Aachen, Germany

3. Ferdinanda Ponci Aachen ACS E.ON ERC -

   RWTH Aachen University

   Affiliation as printed

   ACS E.ON ERC - RWTH Aachen University, Aachen, Germany

4. Wijarn Wangdee

   King Mongkut's University of Technology North Bangkok

   Affiliation as printed

   TGGS KMUTNB, Bangkok, Thailand

5. Antonello Monti Aachen ACS E.ON ERC -

   RWTH Aachen University

   Affiliation as printed

   ACS E.ON ERC - RWTH Aachen University, Aachen, Germany