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机械无传感器控制(国家自然科学基金提案ID：0901218)本研究的目的是开发变速风能系统的智能最优机械无传感器控制。该方法是：(1)开发基于神经网络的实时风速和风向估计器和涡轮轴速度估计器，(2)开发基于自适应批评设计的监督风力机控制器，(3)用进化群智能算法优化估值器和控制器的参数，(4)用控制器进行风能系统的稳定性分析，(5)通过仿真和硬件实现验证建模和控制框架和方法。风能转换，以一种智能的方式。通过建模、控制、稳定性分析、仿真和硬件实现，该项目将增进我们对仿生建模、控制和优化技术的理解，以提高负担得起、可靠和可持续的风电可用性。广泛影响：该项目的成果将通过降低风能系统的成本、提高风能系统的效率、动态性能和可靠性来进一步开发风电的好处。这些对于实现全国20%的风电供应目标至关重要--S。将开发新的课程。本科生和至少一名女研究生将被支持从事这个项目的各种任务。通过与内布拉斯加州风能应用中心-S学校风能项目的合作，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.