Intelligent Optimal Mechanical Sensorless Control of Variable-Speed Wind Energy Systems Considering System Uncertainties

考虑系统不确定性的变速风能系统智能最优无机械传感器控制（NSF提案ID: 0901218）本研究的目的是开发变速风能系统的智能最优无机械传感器控制。该方法是：(1)开发基于神经网络的实时风速和风向估计器以及风力机轴转速估计器；(2)开发基于自适应临界设计的风力机监控控制器；(3)通过进化群智能算法优化估计器和控制器的参数；(4)使用该控制器对风能系统进行稳定性分析。(5)通过仿真和硬件实现验证建模和控制框架和方法。智力优势：该项目将深入研究生物启发设计原理的应用，以智能的方式处理高度随机、不确定和复杂的过程，例如风能转换。通过建模、控制、稳定性分析、仿真和硬件实现，该项目将促进我们对仿生建模、控制和优化技术的理解，以提高可负担、可靠和可持续的风力发电的可用性。更广泛的影响：该项目的结果将通过降低成本、提高风能系统的效率、动态性能和可靠性，进一步利用风能的好处。这些对于实现供应全国20%的目标至关重要。我们用风力发电。将开发新的课程。将支持本科生和至少一名女研究生参与本项目的各项任务。通过与内布拉斯加州风能应用中心的合作？该项目将使农村K-12学校的教师和学生参与能源教育。

Intelligent Optimal Mechanical Sensorless Control of Variable-Speed Wind Energy Systems Considering System Uncertainties(NSF Proposal ID: 0901218)The objective of this research is to develop intelligent optimal mechanical sensorless control for variable-speed wind energy systems. The approach is to (1) develop a neural-network-based, real-time wind speed and direction estimator and turbine shaft speed estimator, (2) develop an adaptive critic design-based supervisory wind turbine controller, (3) optimize the parameters of the estimators and controller by evolutionary swarm intelligence algorithms, (4) perform a stability analysis for the wind energy systems with the controller, and (5) verify the modeling and control framework and methodology by simulations and hardware implementations.Intellectual Merit: This project will investigate in depth the use of bio-inspired design principles to handle highly stochastic, uncertain, and complex processes, e.g., wind energy conversion, in an intelligent way. Through modeling, control, stability analysis, simulation, and hardware implementation, this project will advance our understanding of bio-inspired modeling, control, and optimization technologies for improving the availability of affordable, reliable, and sustainable electricity from wind.Broader Impacts: This outcome of this project will further exploit the benefits of wind power by reducing the cost and improving the efficiency, dynamic performance, and reliability of wind energy systems. These are essential to reaching the goal of supplying 20% of the nation?s electricity by wind. New courses will be developed. Undergraduates and at least one female graduate student will be supported to work on various tasks of this project. Through the collaboration with the Nebraska Wind Applications Center?s Wind for Schools Program, this project will engage rural K-12 school teachers and students in energy education.