Optimization of a PV/wind micro-grid for rural housing electrification using a hybrid iterative/genetic algorithm: Case study of Kuala Terengganu, Malaysia

Tamer Khatib, Azah Mohamed, Kamaruzzaman Sopian

Research output: Contribution to journalArticle

96 Citations (Scopus)

Abstract

This paper presents an optimization for hybrid PV/wind system based on loss of load probability (LLP) and system cost. This paper is divided into three main parts: optimization of PV array, wind turbine and battery, optimum PV array tilt angle and optimization of the inverter size. Firstly, the optimization performed is aimed to select the optimal capacities of the PV array and wind turbine that give minimum system cost. However, the optimization was done using a hybrid iterative/genetic algorithm. The iterative part of the proposed algorithm is applied to generate a set of possible configurations for the proposed system, while the genetic algorithm is applied to find the optimum configuration. Secondly, a model for optimizing the tilt angle of the PV array is presented based on the Liu and Jordan model. Finally, an iterative method for optimizing the inverter size in the proposed system is presented. The results showed that the optimum sizes of the PV array (C A), wind turbine (C s) and storage battery (C B) are 1.1411, 0.7159, and 0.550, respectively, while the optimum inverter's size (Rs) is 1.37. Lastly, by applying the calculated monthly optimum tilt angle, the collected yield of the PV array is increased by 7.96%.

Original languageEnglish
Pages (from-to)321-331
Number of pages11
JournalEnergy and Buildings
Volume47
DOIs
Publication statusPublished - Apr 2012

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Genetic algorithms
Wind turbines
Loss of load probability
Iterative methods
Costs

Keywords

  • Inverter size
  • Micro-grid
  • Optimization of PV systems
  • Optimum tilt angle
  • PV/wind systems

ASJC Scopus subject areas

  • Civil and Structural Engineering
  • Building and Construction
  • Mechanical Engineering
  • Electrical and Electronic Engineering

Cite this

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title = "Optimization of a PV/wind micro-grid for rural housing electrification using a hybrid iterative/genetic algorithm: Case study of Kuala Terengganu, Malaysia",
abstract = "This paper presents an optimization for hybrid PV/wind system based on loss of load probability (LLP) and system cost. This paper is divided into three main parts: optimization of PV array, wind turbine and battery, optimum PV array tilt angle and optimization of the inverter size. Firstly, the optimization performed is aimed to select the optimal capacities of the PV array and wind turbine that give minimum system cost. However, the optimization was done using a hybrid iterative/genetic algorithm. The iterative part of the proposed algorithm is applied to generate a set of possible configurations for the proposed system, while the genetic algorithm is applied to find the optimum configuration. Secondly, a model for optimizing the tilt angle of the PV array is presented based on the Liu and Jordan model. Finally, an iterative method for optimizing the inverter size in the proposed system is presented. The results showed that the optimum sizes of the PV array (C A), wind turbine (C s) and storage battery (C B) are 1.1411, 0.7159, and 0.550, respectively, while the optimum inverter's size (Rs) is 1.37. Lastly, by applying the calculated monthly optimum tilt angle, the collected yield of the PV array is increased by 7.96{\%}.",
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AB - This paper presents an optimization for hybrid PV/wind system based on loss of load probability (LLP) and system cost. This paper is divided into three main parts: optimization of PV array, wind turbine and battery, optimum PV array tilt angle and optimization of the inverter size. Firstly, the optimization performed is aimed to select the optimal capacities of the PV array and wind turbine that give minimum system cost. However, the optimization was done using a hybrid iterative/genetic algorithm. The iterative part of the proposed algorithm is applied to generate a set of possible configurations for the proposed system, while the genetic algorithm is applied to find the optimum configuration. Secondly, a model for optimizing the tilt angle of the PV array is presented based on the Liu and Jordan model. Finally, an iterative method for optimizing the inverter size in the proposed system is presented. The results showed that the optimum sizes of the PV array (C A), wind turbine (C s) and storage battery (C B) are 1.1411, 0.7159, and 0.550, respectively, while the optimum inverter's size (Rs) is 1.37. Lastly, by applying the calculated monthly optimum tilt angle, the collected yield of the PV array is increased by 7.96%.

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