Design optimization of wind turbine tower with lattice-tubular hybrid structure using particle swarm algorithm

2016 ◽  
Vol 25 (15) ◽  
pp. 743-758 ◽  
Author(s):  
Junling Chen ◽  
Rongchang Yang ◽  
Renle Ma ◽  
Jinwei Li
Keyword(s):  
Wind Turbine ◽  
Design Optimization ◽  
Particle Swarm ◽  
Hybrid Structure ◽  
Particle Swarm Algorithm ◽  
Wind Turbine Tower ◽  
Swarm Algorithm

scholarly journals Hybrid Wind Turbine Towers Optimization with a Parallel Updated Particle Swarm Algorithm

2021 ◽  
Vol 11 (18) ◽  
pp. 8683
Author(s):  
Zeyu Li ◽  
Hongbing Chen ◽  
Bin Xu ◽  
Hanbin Ge
Keyword(s):  
Particle Swarm Optimization ◽  
Wind Turbine ◽  
Prestressed Concrete ◽  
Particle Swarm ◽  
Particle Swarm Algorithm ◽  
Labor Costs ◽  
Swarm Optimization ◽  
Computation Efficiency ◽  
Wind Turbine Tower ◽  
Wind Turbine Towers

The prestressed concrete–steel hybrid (PCSH) wind turbine tower, characterized by replacing the lower part of the traditional full-height steel tube wind turbine tower with a prestressed concrete (PC) segment, provides a potential alterative solution to transport difficulties and risks associated with traditional steel towers in mountainous areas. This paper proposes an optimization approach with a parallel updated particle swarm optimization (PUPSO) algorithm which aims at minimizing the objective function of the levelized cost of energy (LCOE) of the PCSH wind turbine towers in a life cycle perspective which represents the direct investments, labor costs, machinery costs, and the maintenance costs. Based on the constraints required by relevant specifications and industry standards, the geometry of a PCSH wind turbine tower for a 2 MW wind turbine is optimized using the proposed approach. The dimensions of the PCSH wind turbine tower are treated as optimization variables in the PUPSO algorithm. Results show that the optimized PCSH wind turbine tower can be an economic alternative for wind farms with lower LCOE requirements. In addition, compared with the traditional particle swarm optimization (PSO) algorithm and UPSO algorithm, the proposed PUPSO algorithm can enhance the optimization computation efficiency by about 60–110%.

Dynamic simulation of wind field in three-dimensional display space considering particle swarm algorithm fuzzy logic

2021 ◽  
pp. 1-6
Author(s):  
Honglei Xu ◽  
Linhuan Wang
Keyword(s):  
Fuzzy Logic ◽  
Dynamic Simulation ◽  
Wind Field ◽  
Three Dimensional ◽  
Measurement Data ◽  
Particle Swarm ◽  
Particle Swarm Algorithm ◽  
Three Dimensional Display ◽  
Swarm Algorithm ◽  
Synchronous Measurement

In order to improve the accuracy of dynamic detection of wind field in the three-dimensional display space, system software is carried out on the actual scene and corresponding airborne radar observation information data, and the particle swarm algorithm fuzzy logic algorithm is introduced into the wind field dynamic simulation process in three-dimensional display space, to analyze the error of the filtering result in detail, to process the hurricane Lily Doppler radar measurement data with the optimal adaptive filtering according to the error data. The three-dimensional wind field synchronous measurement data obtained by filtering was compared with three-dimensional wind field synchronous measurement data of the GPS dropsonde in this experiment, the sea surface wind field measurement data of the multi-band microwave radiometer, and the wind field data at aircraft altitude.

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