DocumentCode :
2467598
Title :
Improved load management algorithm for future network requirements
Author :
Hess, Thomas ; Schegner, Peter ; Hable, Matthias
Author_Institution :
Tech. Univ. Dresden, Dresden, Germany
fYear :
213
fDate :
10-13 June 213
Firstpage :
1
Lastpage :
4
Abstract :
With the expected charging characteristic of e-mobility a considerable load peak during the night is expected. Photovoltaic and small wind power systems will further increase the load fluctuations. The paper describes the application of a modified maximum rectangle algorithm to determine the optimal starting times for charging electric cars to realise a flat load curve. The load characteristic of electric cars is similar to night storage heating devices. This allows to use these currently widely spread devices as example for developing and testing methods for optimized load management in low and medium voltage networks. It is shown that the developed optimization algorithm finds solutions close to the global optimum even with a huge number of devices (≈15 000) with low requirements of calculation time (<;1 min).
Keywords :
automobiles; battery powered vehicles; load management; optimisation; photovoltaic power systems; power system management; wind power plants; e-mobility charging characteristics; electric car charging; flat load curve; future network requirement; improved load management algorithm; load fluctuation; medium voltage network; modified maximum rectangle algorithm; night storage heating device; optimization algorithm; photovoltaic power system; small wind power system;
fLanguage :
English
Publisher :
iet
Conference_Titel :
Electricity Distribution (CIRED 2013), 22nd International Conference and Exhibition on
Conference_Location :
Stockholm
Electronic_ISBN :
978-1-84919-732-8
Type :
conf
DOI :
10.1049/cp.2013.0615
Filename :
6683218
Link To Document :
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