4.6 Article

Optimal, Reliable and Cost-Effective Framework of Photovoltaic-Wind-Battery Energy System Design Considering Outage Concept Using Grey Wolf Optimizer Algorithm-Case Study for Iran

Journal

IEEE ACCESS
Volume 7, Issue -, Pages 182611-182623

Publisher

IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/ACCESS.2019.2958964

Keywords

Hybrid photovoltaic-wind-battery systems; cost/reliability assessment; outage rate; loss of load probability; grey Wolf optimizer

Funding

  1. Ministry of Education (MOE)
  2. Universiti Teknologi Malaysia
  3. Universiti Sriwijaya
  4. [4F828]
  5. [01M44]
  6. [18H10]
  7. [4B345]
  8. [04E54]

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In this paper, an optimal, reliable, and cost-effective framework for designing a renewable hybrid photovoltaic-wind-battery system is presented to minimize the total net present cost (TNPC) and to consider reliability constraint as loss of load probability (LPP) for the city of Ahvaz, Iran, considering the components outage rate (COR). The decision variables include the number of photovoltaic panels, wind turbines, batteries, and the angle of the photovoltaic panel optimized by the grey wolf optimizer (GWO) algorithm. The performance of the proposed method is compared with the particle swarm optimization (PSO) method. The results of a system designed in different combinations with and without considering COR are evaluated. The simulation results confirm that theGWO algorithm is superior to the PSO method by yielding lower TNPC (1.199 M$ for GWO and 1.201 M$ for PSO) and better LPP (0.653% for GWO and 0.655% for PSO) for optimal combination (photovoltaic-battery system). The results also showed that a photovoltaic wind combination is not the most cost-effective and reliable for the Ahvaz region, and the implementation of hybrid systems based on wind power is not cost-effective in this region. In addition, the results showed that considering COR gives the designers of these systems a more accurate view of the cost and reliability. Moreover, considering COR increases the cost of load supply and undermines the load reliability.

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