Dynamic Modeling and Control of Hybrid Power Systems

包括传统发电和可再生能源的电力系统被称为混合电力系统。加拿大有数百个偏远孤立的柴油社区，许多人生活在离网的地方。每个偏远社区和孤立的家庭都可以使用更有效的混合动力系统来满足电力需求。混合动力系统的最优规模取决于系统组件的配置和成本分析。由于风力发电机组、光伏发电系统、储能系统、备用发电机和负载等组成部分的非线性功率特性，混合电力系统的分析和设计非常复杂。混合动力系统还需要最优动态控制器和监控控制器，并且可能涉及交流和直流总线。提出的研究计划的目标是为小型混合动力系统开发新的预测模型和最优控制系统和组件。该研究将集成小型风力涡轮机、光伏太阳能电池、电池和发电机的子系统级模型，开发混合动力系统的新动态模型。根据混合动力系统模型的仿真结果设计系统控制器。更具体地说，该研究项目将开发和确定：(1)确定混合动力系统的降阶动态模型的新方法，该模型可以比现有模型更快地模拟；(2)智能控制方式，包括监控控制器和超低功耗数据记录仪；(3)针对混合动力系统提出了一种新的线性变参数控制器和模糊监控控制器，并确定了最佳运行策略；(4)为偏远家庭提供分布式电池存储和可再生能源的低压纳米电网，包括动态和监控控制器，以实现最佳运行。该研究将开发一种在混合电力系统中，当变流器工作在同步和异步切换模式时，消除变流器之间循环电流的方法。同时，为小型远程混合动力系统的可靠性分析提供了一种新的方法。新型超低功耗控制器和数据记录仪的低阶建模和设计具有创新性，因为它们将对混合动力系统的仿真技术和幻影损耗产生积极影响。提出的纳米电网研究将设计一种新的监控控制器，并解决其相关的转换器问题。拟议的研究计划将导致混合动力系统，他们的设计，控制，仪表，数据记录和可靠性分析的新知识。这项研究将加强加拿大对可再生能源的采用，从而有助于实现其减少排放的承诺，并改善居住在偏远北部社区的人们的生活。这项研究还将培训10名混合可再生能源系统的研究生，从而为加拿大的可再生能源行业开发所需的HQP。

Power systems that include conventional generation and renewable energy sources are called hybrid power systems. Canada has hundreds of remote isolated diesel-powered communities and many people live off-grid. Each remote community and isolated home can potentially use a more effective hybrid power system to supply power needs. The optimal sizing of a hybrid power system depends on the configuration of system components and cost analysis. The analysis and design of hybrid power systems is complex because of the nonlinear power characteristics of the components, e.g., wind turbine, PV system, energy storage, backup generator, and the load. Hybrid power systems also require optimal dynamic and supervisory controllers and may involve AC as well as a DC bus. The objectives of the proposed research program are to develop new predictive models and optimal control systems and components for small hybrid power systems. This research will integrate subsystem level models of small wind turbines, photovoltaic solar cells, batteries, and generators to develop new dynamic models of hybrid power systems. System controllers will be designed with the simulation results of hybrid power system models. More specifically, the research program will develop and identify: (1) new methods to determine a reduced order dynamic model of hybrid power systems that could be simulated more quickly than existing models; (2) intelligent control methods including supervisory controllers and ultra-low power data loggers; (3) a new linear parameter varying controller and a fuzzy supervisory controller for hybrid power systems and determine the best operational strategy; and (4) a low voltage nano-grid to power remote houses with distributed battery storage and renewable sources including a dynamic and supervisory controller for optimal operation. The research will develop a method to eliminate circulating currents between converters in hybrid power systems when such converters are working in synchronous and asynchronous switching modes. Also, it aims to develop a new method for reliability analysis of small remote hybrid power systems. The reduced order modeling and design of new ultra-low power controllers and data loggers are innovative since they will positively impact simulation techniques and phantom losses in hybrid power systems. The proposed research on a nano-grid will design a new supervisory controller and resolve its associated converters issues. The proposed research program will lead to new knowledge on hybrid power systems, their design, control, instrumentation, data logging, and reliability analysis. The research will enhance the adoption of renewable energy in Canada thereby helping to meet its commitment to reduce emissions and improves the lives of people living in remote northern communities. This research will also train ten graduate students on hybrid renewable power systems, hence developing the needed HQP for the renewable energy industry in Canada.