DocumentCode :
634041
Title :
A dynamic GA-based approach for optimal short-term operation of a micro-grid
Author :
Bashari, Masoud ; Salamati, Mahmoud ; Tavakkolinia, Mohamad ; Rahimi-Kian, Ashkan
Author_Institution :
Sch. of ECE, Univ. of Tehran, Tehran, Iran
fYear :
2013
fDate :
14-16 May 2013
Firstpage :
1
Lastpage :
5
Abstract :
This paper presents a dynamic non-linear model of a micro-grid and then applies the GA algorithm to optimally manage the short-term operation of the studied micro-grid. The original calculus of variations method has been modified and augmented with GA-algorithm to solve non-linear optimal control problems, such as the optimal short-term operation of a micro-grid with nonlinear dynamics. To validate the proposed dynamic model of the selected micro-grid and to evaluate the accuracy and performance of the developed GA-based optimization algorithm a simulation case study is presented and the obtained results are analyzed and compared with the simplified LQR problem using the Lagrange Multipliers (LM) theory(where the nonlinearity of the micro-grid model is ignored). The simulation results clearly show the superiority of the proposed method in this paper versus the original LQR modeling and optimization using the LM theory.
Keywords :
distributed power generation; genetic algorithms; GA-based optimization algorithm; LM theory; LQR problem; Lagrange multiplier theory; dynamic GA-based approach; dynamic nonlinear model; microgrid model; nonlinear optimal control problems; optimal short-term operation; variations method; Batteries; Educational institutions; Equations; Generators; Heuristic algorithms; Mathematical model; Optimization; LQR; calculus of variation; frequency and voltage control; genetic algorithm; micro-grid modeling; optimal short-term operation;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Electrical Engineering (ICEE), 2013 21st Iranian Conference on
Conference_Location :
Mashhad
Type :
conf
DOI :
10.1109/IranianCEE.2013.6599530
Filename :
6599530
Link To Document :
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