Hybrid Wind Turbine Towers Optimization with a Parallel Updated Particle Swarm Algorithm
Source abstract
Abstract
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%.
Source: crossref · Quality: baseline
Research context
OpenAlex topics: Wind Energy Research and Development · Topology Optimization in Engineering · Structural Health Monitoring Techniques
SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.
Affiliations
College of Civil Engineering, Hunan University, Changsha 410082, China
School of Civil and Resource Engineering, University of Science and Technology Beijing, Beijing 100083, China
College of Civil Engineering, Huaqiao University, Xiamen 361021, China
Key Laboratory for Intelligent Infrastructure and Monitoring of Fujian Province, Huaqiao University, Xiamen 361021, China
Department of Civil Engineering, Meijo University, Nagoya 468-8502, Japan
Funding
National Natural Science Foundation of China · Scientific Research Funds of Huaqiao University · International Science and Technology Cooperation and Exchange Fund Projects of Ministry of Science and Technology of China
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