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的柴油发电社区，许多人生活在离网状态。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。混合动力系统的最佳规模取决于系统组件的配置和成本分析。混合动力系统的分析和设计是复杂的，因为组件的非线性功率特性，例如，风力涡轮机、光伏系统、能量存储、备用发电机和负载。混合动力系统还需要最佳的动态和监控控制器，并且可能涉及AC和DC总线。拟议的研究计划的目标是开发新的预测模型和最优控制系统和组件的小型混合动力系统。本研究将整合小型风力涡轮机、光伏太阳能电池、蓄电池和发电机的子系统级模型，以开发新的混合动力系统动态模型。系统控制器的设计将与混合动力系统模型的仿真结果。更具体地说，该研究计划将开发和确定：（1）新的方法来确定一个降阶动态模型的混合动力系统，可以更快地模拟比现有的模型;（2）智能控制方法，包括监督控制器和超低功耗数据记录器;（3）提出了一种新的混合电力系统线性变参数控制器和模糊监督控制器，并确定了最佳运行策略;以及（4）用分布式电池存储和可再生能源为远程房屋供电的低压纳米电网，包括用于最佳操作的动态和监督控制器。本研究将发展一种方法，以消除在混合电力系统中的转换器之间的环流时，这样的转换器工作在同步和异步开关模式。此外，它旨在开发一种新的方法，为小型远程混合电力系统的可靠性分析。新型超低功耗控制器和数据记录器的降阶建模和设计具有创新性，因为它们将对混合电力系统中的仿真技术和幻象损耗产生积极影响。拟议的纳米电网研究将设计一个新的监督控制器，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，其设计，控制，仪表，数据记录和可靠性分析的新知识。这项研究将促进加拿大采用可再生能源，从而有助于实现其减少排放的承诺，改善生活在偏远北方社区的人们的生活。这项研究还将培训10名研究生混合可再生能源系统，从而为加拿大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.*****