DocumentCode :
2195478
Title :
Swine Influenza Model Based Optimization for operation management of Micro-Grid
Author :
Sharma, Sharmistha ; Bhattacharjee, Subhadeep ; Bhattacharya, Aniruddha
Author_Institution :
Department of Electrical Engineering, National Institute of Technology, Agartala, India
fYear :
2015
fDate :
24-25 Jan. 2015
Firstpage :
1
Lastpage :
6
Abstract :
In recent years, many modern power grids and energy management systems focused their attention to derive an optimal operational planning with regard to energy costs minimization of Micro-Grid (MG) and better utilization of Renewable Energy Sources (RES) such as wind and solar. Size of Battery Energy Storage (BES) plays an important role in the operation management of MG. In this paper a cost-based formulation has been performed to minimize total operation cost of MG considering optimal size of BES under various constraints such as, power capacity of Distributed Generators (DGs), power and energy capacity of BES, charge/discharge efficiency of BES, operating reserve and load demand satisfaction. Swine Influenza Model Based Optimization with Quarantine (SIMBO-Q) has been applied here to solve the operation management problem of MG and simulation results establish that SIMBO-Q algorithm outperforms several existing optimization techniques like Genetic Algorithm (GA), Particle Swarm Optimization (PSO), Bat Algorithm (BA) and Improved Bat Algorithm (IBA) in terms quality of solution and computational efficiency.
Keywords :
Energy storage; Influenza; Maintenance engineering; Optimization; Power generation; Sociology; Statistics; battery energy storage; distributed generation; micro-grid; operation management; swine influenza model based optimization with quarantine;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Electrical, Electronics, Signals, Communication and Optimization (EESCO), 2015 International Conference on
Conference_Location :
Visakhapatnam, India
Print_ISBN :
978-1-4799-7676-8
Type :
conf
DOI :
10.1109/EESCO.2015.7253848
Filename :
7253848
Link To Document :
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