A platform for research: civil engineering, architecture and urbanism
A platform for research: civil engineering, architecture and urbanism
Wind farm layout optimization using PSO and GIS
A new optimum wind farm layout method was discussed in the project, the author combined Particle Swarm Optimization (PSO) algorithm and Geographic Information System (GIS) to optimize wind farm layout. The optimization standard is on the basis of minimizing the cost of energy (COE) and maximizing turbine power generation by considering the wake effects. The method applied a realistic wind farm location and terrain surface roughness information that was obtained by GIS into PSO algorithm to generate an optimum wind farm layout. PSO mainly focus on the net generated energy model, which is calculated by considering the single wind turbine, which is loss of production because of wake decay influence, and it can handle with different terrains which has different surface roughness and different number of turbine. Three case studies were constructed to test the method. Pre-post optimization results showed that COE decreased 70%, and energy output increased 226%.
Wind farm layout optimization using PSO and GIS
A new optimum wind farm layout method was discussed in the project, the author combined Particle Swarm Optimization (PSO) algorithm and Geographic Information System (GIS) to optimize wind farm layout. The optimization standard is on the basis of minimizing the cost of energy (COE) and maximizing turbine power generation by considering the wake effects. The method applied a realistic wind farm location and terrain surface roughness information that was obtained by GIS into PSO algorithm to generate an optimum wind farm layout. PSO mainly focus on the net generated energy model, which is calculated by considering the single wind turbine, which is loss of production because of wake decay influence, and it can handle with different terrains which has different surface roughness and different number of turbine. Three case studies were constructed to test the method. Pre-post optimization results showed that COE decreased 70%, and energy output increased 226%.
Wind farm layout optimization using PSO and GIS
Yang, Lian (author)
2014-12-01
Miscellaneous
Electronic Resource
English
DDC:
690
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