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An optimal fuzzy PI controller to capture the maximum power for variable-speed wind turbines

机译:捕获变速风力涡轮机最大功率的最佳模糊PI控制器

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Wind energy conversion systems can work by fixed and variable speed using the power electronic converters. The variable-speed type is more desirable because of its ability to achieve maximum efficiency at all wind speeds. The main operational region for wind turbines according to wind speed is divided into partial load and full load. In the partial-load region, the main goal is to maximize the power captured from the wind. This goal can be achieved by controlling the generator torque such that the optimal tip speed ratio is tracked. Since the wind turbine systems are nonlinear in nature and due to modeling uncertainties, this goal is difficult to be achieved in practice. The proportional-integral (PI) controller, due to its robustness and simplicity, is very often used in practical applications, but finding its optimal gains is a challenging task. In this paper, to cope with nonlinearities and at the same time modeling uncertainties of wind turbines, a PI torque controller is proposed such that its optimal gains are derived via a novel scheme based on particle swarm optimization algorithm and fuzzy logic theory. The proposed method is applied to a 5-MW wind turbine model. The simulation results show the effectiveness of the proposed method in capturing maximum power in the partial-load region while coping well with nonlinearities and uncertainties.
机译:风能转换系统可以使用功率电子转换器以固定和变速运行。变速类型是更理想的,因为它能够在所有风速下实现最大效率。根据风速,风力涡轮机的主要运行区域分为部分负荷和全负荷。在部分负载区域,主要目标是使从风中捕获的功率最大化。该目标可以通过控制发电机转矩以跟踪最佳叶尖速比来实现。由于风力涡轮机系统本质上是非线性的并且由于建模的不确定性,因此在实践中很难实现该目标。比例积分(PI)控制器由于其鲁棒性和简单性,经常在实际应用中使用,但是要找到其最佳增益是一项艰巨的任务。为了解决非线性问题,同时对风力发电机的建模不确定性进行了研究,提出了一种基于粒子群优化算法和模糊逻辑理论的PI转矩控制器,通过一种新颖的方案来推导其最优增益。所提出的方法被应用于5-MW风力涡轮机模型。仿真结果表明,该方法在克服部分非线性和不确定性的同时,可有效捕获部分负载区域的最大功率。

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