Predicting the Extreme Loads in Power Production of Large Wind Turbines Using an Improved PSO Algorithm

Abstract

Predicting the extreme loads in power production for the preliminary-design of large-scale wind turbine blade is both important and time consuming. In this paper, a simplified method, called Particle Swarm Optimization-Extreme Load Prediction Model (PSO-ELPM), is developed to quickly assess the extreme loads. This method considers the extreme loads solution as an optimal problem. The rotor speed, wind speed, pitch angle, yaw angle, and azimuth angle are selected as design variables. The constraint conditions are obtained by considering the influence of the aeroelastic property and control system of the wind turbine. An improved PSO algorithm is applied. A 1.5 MW and a 2.0 MW wind turbine are chosen to validate the method. The results show that the extreme root load errors between PSO-ELPM and FOCUS are less than 10%, while PSO-ELPM needs much less computational cost than FOCUS. The distribution of flapwise bending moments are close to the results of FOCUS. By analyzing the loads, we find that the extreme flapwise bending moment of the blade root in chord coordinate (CMF_ROOT) is largely reduced because of the control system, with the extreme edgewise bending moment of the blade root in chord coordinate (CME_ROOT) almost unchanged. Furthermore, higher rotor speed and smaller pitch angle will generate larger extreme bending moments at the blade root.

Reptile Search Algorithm Considering Different Flight Heights to Solve Engineering Optimization Design Problems

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“…(2) Wilcoxon rank sum and Friedman tests are used to analyze the statistical data. (3) The FRSA is applied to solve three constrained optimization problems in mechanical fields and compared with ten SOTA algorithms.…”

“…With the deeper exploration of natural laws by humans, more and more practical problems have emerged in fields such as control [ 1 , 2 ], manufacturing [ 3 , 4 ], economics [ 5 , 6 ], and physics [ 7 ]. Most of these problems have characteristics such as a large scale, multiple constraints, and discontinuity [ 8 ].…”

Special Issue on “Wind Energy Conversion Systems”

“…There are four papers dealing with various aspects of the wind turbine systems; they are, respectively, related to system design, control system upgrade, wind turbine power curve representation, as well as a hydraulic wind turbine with an energy storage system. The paper "Predicting the Extreme Loads in Power Production of Large Wind Turbines Using an Improved PSO Algorithm" [6] proposed a simplified method to assess the extreme loads of a wind turbine, which could predict the extreme loads for the preliminary-design of large-scale wind turbine blade. The method uses the optimisation method to treat extreme loads with rotor speed, wind speed, pitch angle, yaw angle, and azimuth angle as design variables.…”

Optimization Design of Wind Turbine Blade Based on an Improved Particle Swarm Optimization Algorithm Combined with Non‐Gaussian Distribution

“…PSO algorithm has also been applied to the optimal design of different wind turbine blades [4][5][6]. Liao et al [7] adopted an improved PSO algorithm to optimize the blade extreme load. Based on multidisciplinary optimization theory, the PSO algorithm was applied by Ceruti [8] to optimize the geometry of small wind turbine blades to obtain the optimal chord distribution and airfoil.…”