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Photovoltaic and Wind Turbine Integration Applying Cuckoo Search for Probabilistic Reliable Optimal Placement

Author

Listed:
  • R. A. Swief

    (Faculty of Engineering, Ain Shams University, 11566 Cairo, Egypt)

  • T. S. Abdel-Salam

    (Faculty of Engineering, Ain Shams University, 11566 Cairo, Egypt)

  • Noha H. El-Amary

    (Arab Academy for Science, Technology and Maritime Transport (AASTMT), 2033 Cairo, Egypt)

Abstract

This paper presents an efficient Cuckoo Search Optimization technique to improve the reliability of electrical power systems. Various reliability objective indices such as Energy Not Supplied, System Average Interruption Frequency Index, System Average Interruption, and Duration Index are the main indices indicating reliability. The Cuckoo Search Optimization (CSO) technique is applied to optimally place the protection devices, install the distributed generators, and to determine the size of distributed generators in radial feeders for reliability improvement. Distributed generator affects reliability and system power losses and voltage profile. The volatility behaviour for both photovoltaic cells and the wind turbine farms affect the values and the selection of protection devices and distributed generators allocation. To improve reliability, the reconfiguration will take place before installing both protection devices and distributed generators. Assessment of consumer power system reliability is a vital part of distribution system behaviour and development. Distribution system reliability calculation will be relayed on probabilistic reliability indices, which can expect the disruption profile of a distribution system based on the volatility behaviour of added generators and load behaviour. The validity of the anticipated algorithm has been tested using a standard IEEE 69 bus system.

Suggested Citation

  • R. A. Swief & T. S. Abdel-Salam & Noha H. El-Amary, 2018. "Photovoltaic and Wind Turbine Integration Applying Cuckoo Search for Probabilistic Reliable Optimal Placement," Energies, MDPI, vol. 11(1), pages 1-17, January.
    • Handle: RePEc:gam:jeners:v:11:y:2018:i:1:p:139-:d:125726
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    Citations

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    Cited by:

    1. Gang Zhou & Jianxun Shi & Bingjing Chen & Zhongyi Qi & Licheng Wang, 2023. "Risk Assessment of Power Supply Security Considering Optimal Load Shedding in Extreme Precipitation Scenarios," Energies, MDPI, vol. 16(18), pages 1-17, September.
    2. Ziad M. Ali & Ibrahim Mohamed Diaaeldin & Shady H. E. Abdel Aleem & Ahmed El-Rafei & Almoataz Y. Abdelaziz & Francisco Jurado, 2020. "Scenario-Based Network Reconfiguration and Renewable Energy Resources Integration in Large-Scale Distribution Systems Considering Parameters Uncertainty," Mathematics, MDPI, vol. 9(1), pages 1-31, December.

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