Optimal sizing of reliable hybrid renewable energy system considered various load types

Hakimi, S. M.; Moghaddas-Tafreshi, S. M.; HassanzadehFard, H.

doi:doi:10.1063/1.3655372

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Journal of Renewable and Sustainable Energy / Volume 3 / Issue 6 / REVIEW ARTICLES

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J. Renewable Sustainable Energy 3, 062701 (2011); http://dx.doi.org/10.1063/1.3655372 (18 pages)

Optimal sizing of reliable hybrid renewable energy system considered various load types

S. M. Hakimi, S. M. Moghaddas-Tafreshi, and H. HassanzadehFard

Faculty of Electrical Engineering, Khajeh Nasir Toosi University, Tehran, Iran

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(Received 22 June 2011; accepted 23 September 2011; published online 7 November 2011)

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Abstract

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Citing Articles (1)

Article Objects (25)

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In this paper, a novel intelligent method is applied to the problem of sizing in a hybrid power system such that the demand of residential area is met. This study is performed for Kahnouj area in south-east Iran. It is to mention that there are many similar regions around the world with this typical situation that can be expanded. The system consist of fuel cells, some wind units, some electrolyzers, a reformer, an anaerobic reactor, and some hydrogen tanks. The system is assumed to be stand-alone and uses the biomass as an available energy resource. System costs involve investments, replacement, and operation and maintenance as well as loss of load costs. Prices are all empirical and components are commercially available. In this study, we consider load growth and different types of load profile for their system. In this village, four types of loads exist such as residential, agricultural, industrial, and official loads. Also we consider load growth for the loads. Particle swarm optimization algorithm is used for optimal sizing of system’s components.

Article Outline

INTRODUCTION
DESCRIPTION OF THE HYBRID SYSTEM COMPONENTS
1. Wind turbine
2. Fuel cell
3. Electrolyzer
4. Anaerobic reactor
5. Reformer
6. Hydrogen tank
7. Power converter
DESCRIPTION OF THE HYBRID SYSTEM
1. Generation meets demand
2. Over generation
3. Over demand
SYSTEM COST
1. Net present cost
2. The objective function
PARTICLE SWARM OPTIMIZATION
1. Optimization procedure
CONSIDERING GRAPH OF DIFFERENT TYPE OF LOADS IN MICRO-GRID
1. System operation strategy during loss of power
LOAD GROWTH
SIMULATION RESULTS
CONCLUSION

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KEYWORDS and PACS

Keywords

fuel cell power plants, hybrid power systems, maintenance engineering, particle swarm optimisation, wind turbines

PACS

88.50.G-

Wind turbines
02.60.Pn

Numerical optimization
88.30.G-

Fuel cell systems

ARTICLE DATA

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http://dx.doi.org/10.1063/1.3655372

PUBLICATION DATA

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1941-7012 (online)

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American Institute of Physics

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