Analysis of a multi-objective hybrid system to generate power in different environmental conditions based on improved the Barnacles Mating Optimizer Algorithm

Autor: Guangli Fan, Meng Li, Xinxiao Chen, Xiaolei Dong, Kittisak Jermsittiparsert
Jazyk: angličtina
Rok vydání: 2021
Předmět:
Zdroj: Energy Reports, Vol 7, Iss , Pp 2950-2961 (2021)
Druh dokumentu: article
ISSN: 2352-4847
DOI: 10.1016/j.egyr.2021.05.023
Popis: Industrial development, increased demand for energy, limited fossil fuels, and the prevention of environmental damage have led to the use of renewable energy to produce power. The combined system includes renewable wind and solar energy systems or other renewable energy. The hybrid system has been widely used in recent decades to provide energy. In this research, an optimal integrated system has been used to generate electricity. The proposed system includes wind, hydropower, and photovoltaic systems. to estimate the maximum power generation and reduce fluctuations in electricity generation, three proposed algorithms have been used and three common solutions have been applied to solve the optimization problem. The performance of the combined system in different weather conditions has also been assessed. The results showed that among the three proposed algorithms, the model improved the Barnacles Mating Optimizer Algorithm (IBMO) has the best distribution and convergence. Among the three common solutions, a common solution has the most logical solution to the optimization problem. And among the different hydrological conditions, the highest electricity generation is related to the wet season. the most important role in the hybrid system related the hydropower so that despite the reduction of electricity produced in the wind and photovoltaic power plants, the hydropower plant compensates for the drop in production of these systems and causes the production flow to continue.
Databáze: Directory of Open Access Journals