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Development of an application for local Micro Grid sizing and optimization

 
: Kandalam, Sai Chamanth Swarup
: Balischewski, Stephan

:
Volltext urn:nbn:de:0011-n-5928827 (2.4 MByte PDF)
MD5 Fingerprint: 0d0161b7854ddbaa264b60e258bcb9e3
Erstellt am: 27.6.2020


Magdeburg, 2019, IX, 88 S.
Magdeburg, Univ., Master Thesis, 2019
Englisch
Master Thesis, Elektronische Publikation
Fraunhofer IFF ()

Abstract
The mobility sector especially the one involving electrified fleet of vehicles accounts for significant proportion of overall energy consumption in a household. However, Electric vehicles (EVs) are still falling short of expectations, due to higher investments and shorter range of those cars. Furthermore, the additional load from charging infrastructure is causing higher load flows. Therefore, to make full use of extraordinary economic & environmental benefits from the Electric vehicles, congestion management is necessary. Smart grid with necessary renewable energy sources (RES) & storage facilities is one way of addressing the issue. Deploying of energy storage system (ESS) to store the sporadic energy generated from the Photovoltaic system (PVS) would add to significant improvement of congestion caused. However, the uncontrolled charging strategy of electric vehicle might still exploit the load consumption from distribution networks creating imbalance by overloading at specific point in time. Moreover, optimized utilization of renewables & reducing the overall consumption encourages the users to invest in nature friendly vehicles.
This thesis aims at studying the impact of Electric vehicles, their mobility patterns, respective size impact on smart grid with energy management system of household with renewables. Real time optimization and sizing of local micro grid consisting of PVS, ESS & Electric Vehicle battery using “particle swarm optimization algorithm” (PSO) was implemented. This coordinates the charging & discharging of specifics with ultimate goal of drawing the minimum energy from grid improving the demand side management of the user & the electric vehicle‘s the penetration level in distribution network. Thereby concealing the issues of overloading the local micro grid and charging infrastructure. It was observed that there is no impact of vehicle departure time and season of the year as long as the average distance is same throughout the year but significant impact of the size of EV on optimum size of Energy Storage System.

: http://publica.fraunhofer.de/dokumente/N-592882.html