DocumentCode :
2026130
Title :
Advanced simulation tool for the optimal management of photovoltaic generation in combined systems
Author :
Bourry, Franck ; Ha, Duy Long
Author_Institution :
Lab. for Solar Syst. (L2S), Nat. Inst. for Solar Energy (INES), Le Bourget du Lac, France
fYear :
2013
fDate :
16-20 June 2013
Firstpage :
1
Lastpage :
6
Abstract :
Photovoltaic generation is characterized by a low predictability, a high variability and a low controllability. Consequently, photovoltaic systems may be combined with energy storage devices, controllable loads or conventional sources in order to reduce the critical impacts related to their large scale integration into power systems. Such combinations lead to a need of energy management tools. This paper presents the development of a generic simulation tool for the energy management of combined power systems including photovoltaic generation. The developed software is named M2C, standing for Multi-Models Multi-Components. In this paper, the authors present the objectives and the proposed approach adopted for the development of M2C. Example of simulations carried out with M2C are shown for three case studies: a 50 electrical vehicle fleet combined with a PV system, a combined PV-storage plant connected to the grid and a stand-alone hybrid power plant including PV systems, diesel gensets and storage for supplying a village load.
Keywords :
energy management systems; hybrid power systems; photovoltaic power systems; power grids; power system simulation; M2C software; PV system; advanced simulation tool; combined PV-storage plant; combined power systems; controllable loads; diesel gensets; electrical vehicle fleet; energy management; energy management tools; energy storage devices; large scale power system integration; multimodel multicomponents; optimal photovoltaic generation management; stand-alone hybrid power plant; Computational modeling; Electric vehicles; Energy management; Libraries; Load modeling; Production; Software; electric vehicles; energy management; energy storage systems; model predictive control; optimization; photovoltaic systems; simulation;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
PowerTech (POWERTECH), 2013 IEEE Grenoble
Conference_Location :
Grenoble
Type :
conf
DOI :
10.1109/PTC.2013.6652469
Filename :
6652469
Link To Document :
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