DocumentCode :
2027147
Title :
Deterministic optimal power flow for smart grid short-term predictive energy management
Author :
Benoit, Clementine ; Mercier, Aurelien ; Besanger, Yvon ; Wurtz, Frederic
Author_Institution :
G2Elab, Grenoble Inst. of Technol., Grenoble, France
fYear :
2013
fDate :
16-20 June 2013
Firstpage :
1
Lastpage :
7
Abstract :
This paper investigates a formulation of the Optimal Power Flow (OPF) problem, which aims to find the predictive optimal operational state of a low voltage smart grid. The optimization problem includes distributed generations (DG), distributed storage (DS), and smart buildings. Active and reactive power management is done through DG and DS control, and soft load shedding. It takes into account networks constraints, through a full AC power flow calculation. The low-voltage distribution network is modeled as a three-phased four-wire system. Several objective functions are described. Finally, a case study is solved using KNITRO [1], a robust and efficient solver for large, nonlinear and constrained problems, after being modeled in GAMS [2].
Keywords :
distributed power generation; energy management systems; home automation; load flow control; load shedding; optimal control; optimisation; power distribution control; smart power grids; DG control; DS control; GAMS; active power management; deterministic OPF; distributed generation; distributed storage; distribution network; optimal power flow; optimization problem; predictive energy management; reactive power management; smart building; smart grid; soft load shedding; wire system; Energy management; Equations; Low voltage; Mathematical model; Optimization; Reactive power; Wires; Demand-side energy management; Distribution Management System; Low Voltage Smart grid; Optimal Power Flow; Predictive energy management; deterministic optimization;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
PowerTech (POWERTECH), 2013 IEEE Grenoble
Conference_Location :
Grenoble
Type :
conf
DOI :
10.1109/PTC.2013.6652502
Filename :
6652502
Link To Document :
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