An enhanced multiobjective particle swarm optimisation algorithm for optimum utilisation of hybrid renewable energy systems

被引：0
|
作者：
Suresh, M. [1 ]
Meenakumari, R. [1 ]
Panchal, Hitesh [2 ]
Priya, V. [3 ]
El Agouz, El Sayed [4 ]
Israr, Mohammad [5 ]
机构：
[1] Department of Electrical and Electronics Engineering, Kongu Engineering College, Perundurai, India
[2] Department of Mechanical Engineering, Government Engineering College, Patan, India
[3] Department of Computer Science and Engineering, Mahendra Institute of Technology, Tiruchengode, India
[4] Department of Mechanical Power Engineering, Faculty of Engineering, Tanta University, Tanta, Egypt
[5] Department of Mechanical Engineering, Sur University College, Sur, Oman
来源：
International Journal of Ambient Energy | 2022年 / 43卷 / 01期
关键词：
Wind - Multiobjective optimization - Particle swarm optimization (PSO) - Electric batteries - Electric power systems - Renewable energy resources - Costs - Genetic algorithms - Diesel engines - Investments - Meteorology - Digital storage;
D O I：
暂无
中图分类号：
学科分类号：
摘要：
Journal article (JA)
引用
收藏
页码：2540 / 2548
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