Wind turbine technology is well known around the globe as an eco-friendly and effective renewable power source. However, this technology often faces reliability problems due to structural vibration. This study proposes a smart semi-active vibration control system using Magnetorheological (MR) dampers where feedback controllers are optimized with nature-inspired algorithms. Proportional integral derivative (PID) and Proportional integral (PI) controllers are designed to achieve the optimal desired force and current input for MR the damper. PID control parameters are optimized using an Ant colony optimization (ACO) algorithm. The effectiveness of the ACO algorithm is validated by comparing its performance with Ziegler-Nichols (Z-N) and particle swarm optimization (PSO). The placement of the MR damper on the tower is also investigated to ensure structural balance and optimal desired force from the MR damper. The simulation results show that the proposed semi-active PID-ACO control strategy can significantly reduce vibration on the wind turbine tower under different frequencies (i.e., 67%, 73%, 79% and 34.4% at 2 Hz, 3 Hz, 4.6 Hz and 6 Hz, respectively) and amplitudes (i.e. 50%, 58% and 67% for 50 N, 80 N, and 100 N, respectively). In this study, the simulation model is validated with an experimental study in terms of natural frequency, mode shape and uncontrolled response at the 1st mode. The proposed PID-ACO control strategy and optimal MR damper position is also implemented on a lab-scaled wind turbine tower model. The results show that the vibration reduction rate is 66% and 73% in the experimental and simulation study, respectively, at the 1st mode.
The forest canopy affects the water entering the forest ecosystem by intercepting rainfall. This is especially pertinent in forests that depend on rainfall for their ecological water needs, quantifying and simulating interception losses provide critical insights into their ecological hydrological processes. In the semi-arid areas of the Loess Plateau, afforestation has become an effective ecological restoration measure. However, the rainfall interception process of these plantations is still unclear. To quantify and model the canopy interception of these plantations, we conducted a two-year rainfall redistribution measurement experiment in three typical plantations, including a deciduous broadleaf plantation (Robinia pseudoacacia) and two evergreen coniferous plantations (Platycladus orientalis and Pinus tabuliformis). Based on this, the revised Gash model was used to simulate their interception losses, and the model applicability across varying rainfall types was further compared and verified. The experiment clarified the rainfall redistribution in the three plantations, and the proportions of throughfall to gross rainfall in Robinia pseudoacacia, Platycladus orientalis, and Pinus tabuliformis were 84.8%, 70.4%, and 75.6%; corresponding, the stemflow proportions were 2.0%, 2.2%, and 1.8%; the interception losses were 13.2%, 27.4%, and 22.6%, respectively. The dominant rainfall pattern during the experiment was characterized by low-amounts, moderate-intensity, and short-duration, during which the highest interception proportions across the three plantations were observed. We used the Penman-Monteith equation and the regression method, respectively, to estimate the canopy average evaporation rate of the revised Gash model, finding that the latter provides a closer match to the measured cumulative interception (NSE >0.7). When simulating interception under the three rainfall patterns, the model with the regression method better simulated the cumulative interception and event-scale interception for Platycladus orientalis and Pinus tabuliformis plantations under the dominant rainfall pattern. The results contribute valuable information to assess the impact of forest rainfall interception on regional hydrologic processes. 相似文献
