Mutation particle swarm optimization algorithm for solving the optimal operation model of thermal power plants

2014 ◽  
Vol 6 (4) ◽  
pp. 043118 ◽  
Author(s):  
Shi Biao ◽  
Hu Chang hua ◽  
Yu Xin hua ◽  
He Chuan
Keyword(s):  
Particle Swarm Optimization ◽  
Optimization Algorithm ◽  
Power Plants ◽  
Particle Swarm Optimization Algorithm ◽  
Thermal Power ◽  
Particle Swarm ◽  
Optimal Operation ◽  
Thermal Power Plants ◽  
Operation Model ◽  
Swarm Optimization

scholarly journals An Improved Bare Bone Multi-Objective Particle Swarm Optimization Algorithm for Solar Thermal Power Plants

Energies ◽  
2019 ◽  
Vol 12 (23) ◽  
pp. 4480
Author(s):  
Qun Niu ◽  
Han Wang ◽  
Ziyuan Sun ◽  
Zhile Yang
Keyword(s):  
Power Generation ◽  
Particle Swarm Optimization ◽  
Optimization Algorithm ◽  
Particle Swarm Optimization Algorithm ◽  
Thermal Power ◽  
Particle Swarm ◽  
Swarm Optimization ◽  
Multi Objective ◽  
Solar Thermal Power ◽  
Bare Bone

Solar energy has many advantages, such as being abundant, clean and environmentally friendly. Solar power generation has been widely deployed worldwide as an important form of renewable energy. The solar thermal power generation is one of a few popular forms to utilize solar energy, yet its modelling is a complicated problem. In this paper, an improved bare bone multi-objective particle swarm optimization algorithm (IBBMOPSO) is proposed based on the bare bone multi-objective particle swarm optimization algorithm (BBMOPSO). The algorithm is first tested on a set of benchmark problems, confirming its efficacy and the convergency speed. Then, it is applied to optimize two typical solar power generation systems including the solar Stirling power generation and the solar Brayton power generation; the results show that the proposed algorithm outperforms other algorithms for multi-objective optimization problems.

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