What is it about?
the effectiveness of sustainable sources is inherently limited by their unpredictable nature and environmental variables, leading to significant fluctuations in energy production levels. The introduction of hybrid renewable energy systems (HRES) has emerged as a necessary solution to counteract the instability observed in singleenergy configurations. These hybrid systems amalgamate wind, solar, diesel, and storage elements, facilitating a cost-effective and consistent supply of electricity supply 1、What are the goals of capacity optimization and how to balance them 2、The existing algorithm is improved and compared with other popular algorithms, and the optimal result is obtained
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Why is it important?
1、The economic, environmental, and reliability objectives of renewable energy system microgrids are balanced using a weighted objective function approach. 2、To improve the convergence speed of the algorithm in the early stage, the Golden Sinusoidal Strategy and Levy Flight Strategy are introduced, partially avoiding the algorithm from falling into local optima. In the later iterations, the algorithm's global search ability is enhanced by introducing a dynamic reverse learning strategy, effectively preventing it from getting stuck in local optima.
Perspectives
Writing this article was a great pleasure as it has co-authors with whom I have had long standing collaborations.
Jia Lu
Taiyuan Institute Of Technology
Read the Original
This page is a summary of: Capacity optimization of independent hybrid renewable energy system under different operational strategies based on improved gray wolf algorithm, AIP Advances, May 2024, American Institute of Physics,
DOI: 10.1063/5.0198446.
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