Open Access

ARTICLE

Energy Management of an Isolated Wind/Photovoltaic Microgrid Using Cuckoo Search Algorithm

Hani Albalawi^1,3, Ahmed M. Kassem², Sherif A. Zaid^1,3,4,*, Abderrahim Lakhouit⁵, Muhammed A. Arshad⁶

1 Department of Electrical Engineering, Faculty of Engineering, University of Tabuk, Tabuk, 47913, Saudi Arabia
2 Department of Electrical Engineering, Faculty of Engineering, Sohag University, Sohag, Egypt
3 Renewable Energy and Energy Efficiency Centre (REEEC), University of Tabuk, Tabuk, 47913, Saudi Arabia
4 Department of Electrical Power, Faculty of Engineering, Cairo University, Cairo, 12613, Egypt
5 Department of Civil Engineering, Faculty of Engineering, University of Tabuk, Tabuk, 47913, Saudi Arabia
6 Sensor Networks and Cellular System Research Centre, University of Tabuk, Saudi Arabia

* Corresponding Author: Sherif A. Zaid. Email:

Intelligent Automation & Soft Computing 2022, 34(3), 2051-2066. https://doi.org/10.32604/iasc.2022.026032

Received 13 December 2021; Accepted 21 February 2022; Issue published 25 May 2022

Abstract

This paper introduces a renewable-energy-based microgrid that includes Photovoltaic (PV) energy and wind energy generation units. Also, an energy storage system is present. The proposed microgrid is loaded with a constant load impedance. To improve the performance of the proposed microgrid, an optimal control algorithm utilizing Cuckoo Search Algorithm (CSA) is adapted. It has many merits such as fast convergence, simple tunning, and high efficiency. Commonly, the PV and wind energies are suitable for supplying loads under normal conditions. However, the energy storage system recovers the excess load demand. The load frequency and voltage are regulated using the CSA optimal controller. The microgrid responses with the introduced optimal controller are measured under step changes in load demand, wind power, and the PV irradiation level. Matlab simulations are carried out to test the proposed system performance. The simulation results showed that the proposed microgrid fed the load with Alternating Current (AC) power of constant amplitude and frequency for all disturbances. Moreover, the required load demand has been perfectly compensated. Moreover, the performance of the storage system is excellent with the unstable wind speed and variable solar irradiation. Also, the results with the optimal CSA controller are compared to those with the Particle Swarm Optimization (PSO) algorithm at the same conditions. It is also found that the optimal CSA controller provides better responses.

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Keywords

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