Optimal Thermal Unit Commitment Integrated with Renewable Energy Sources Using Advanced Particle Swarm Optimization

2009 ◽  
Vol 4 (5) ◽  
pp. 609-617 ◽  
Author(s):  
Shantanu Chakraborty ◽  
Tomonobu Senjyu ◽  
Ahmed Yousuf Saber ◽  
Atsushi Yona ◽  
Toshihisa Funabashi
Keyword(s):  
Particle Swarm Optimization ◽  
Renewable Energy ◽  
Unit Commitment ◽  
Renewable Energy Sources ◽  
Particle Swarm ◽  
Energy Sources ◽  
Thermal Unit ◽  
Swarm Optimization

Control-Based Maximum Power Point Tracking for a Grid-Connected Hybrid Renewable Energy System Optimized by Particle Swarm Optimization

2021 ◽  
pp. 353-384
Author(s):  
Mouna Ben Smida ◽  
Anis Sakly ◽  
Sundarapandian Vaidyanathan ◽  
Ahmad Taher Azar
Keyword(s):  
Particle Swarm Optimization ◽  
Renewable Energy ◽  
Renewable Energy Sources ◽  
Particle Swarm ◽  
Energy System ◽  
Energy Sources ◽  
Swarm Optimization ◽  
Hybrid Renewable Energy System ◽  
Renewable Energy System ◽  
Hybrid Renewable Energy

There has been a great deal of interest in renewable energy sources for electricity generation, particularly for photovoltaic and wind generators. These energy resources have enormous potential and can meet the current global demand for energy. Despite the obvious advantages of renewable energy sources, they have significant disadvantages, such as the discontinuity of their generation, due to their heavy dependence on weather and climate change, which affects their effectiveness in the conversion of renewable energy. Faced with this conflict, it is essential to optimize the performance of renewable systems in order to increase their efficiency. Several unconventional approaches to optimization have been developed in the literature. In this chapter, the management of a hybrid renewable energy system is optimized by intelligent approach based on particle swarm optimization comprising a shaded photovoltaic generator and a wind generator.

Control-Based Maximum Power Point Tracking for a Grid-Connected Hybrid Renewable Energy System Optimized by Particle Swarm Optimization

2018 ◽  
pp. 58-89 ◽  
Author(s):  
Mouna Ben Smida ◽  
Anis Sakly ◽  
Sundarapandian Vaidyanathan ◽  
Ahmad Taher Azar
Keyword(s):  
Particle Swarm Optimization ◽  
Renewable Energy ◽  
Renewable Energy Sources ◽  
Particle Swarm ◽  
Energy System ◽  
Energy Sources ◽  
Swarm Optimization ◽  
Hybrid Renewable Energy System ◽  
Renewable Energy System ◽  
Hybrid Renewable Energy

There has been a great deal of interest in renewable energy sources for electricity generation, particularly for photovoltaic and wind generators. These energy resources have enormous potential and can meet the current global demand for energy. Despite the obvious advantages of renewable energy sources, they have significant disadvantages, such as the discontinuity of their generation, due to their heavy dependence on weather and climate change, which affects their effectiveness in the conversion of renewable energy. Faced with this conflict, it is essential to optimize the performance of renewable systems in order to increase their efficiency. Several unconventional approaches to optimization have been developed in the literature. In this chapter, the management of a hybrid renewable energy system is optimized by intelligent approach based on particle swarm optimization comprising a shaded photovoltaic generator and a wind generator.

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