Design, analysis, operation, and advanced control of hybrid renewable energy systems

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University of Delaware
Because using non-renewable energy systems (e.g., coal-powered cogeneration power plants) to generate electricity is an unsustainable, environmentally hazardous practice, it is important to develop cost-effective and reliable renewable energy systems, such as photovoltaics (PVs), wind turbines (WTs), and fuel cells (FCs). Non-renewable energy systems, however, are currently less expensive than individual renewable energy systems (IRESs). Furthermore, IRESs based on intermittent natural resources (e.g., solar irradiance and wind) are incapable of meeting continuous energy demands. Such shortcomings can be mitigated by judiciously combining two or more complementary IRESs to form a hybrid renewable energy system (HRES). Although previous research efforts focused on the design, operation, and control of HRESs has proven useful, no prior HRES research endeavor has taken a systematic and comprehensive approach towards establishing guidelines by which HRESs should be designed, operated, and controlled. The overall goal of this dissertation, therefore, is to establish the principles governing the design, operation, and control of HRESs resulting in cost-effective and reliable energy solutions for stationary and mobile applications. The first empirical part of this dissertation focuses on HRES equipment selection and sizing using an economic and feasibility analysis. We determined that HRES components and their sizes should be rationally selected using knowledge of component costs, availability of renewable energy resources, and expected power demands of the application. To demonstrate this statement, we ascertained the economically preferred and feasible renewable energy system types and sizes for a range of average annual wind speed, average annual solar irradiance, power demand and minimum renewable fraction. We found that under some combinations of these variables HRESs are less expensive than IRESs and grid-supplied energy. This result has a significant implication for renewable energy systems becoming increasingly ubiquitous. After HRES type and sizes are selected, it is necessary to determined how the components are arranged and what control systems are best for coordinating the entire system to meet a set of operating objectives (typically satisfy a power demand while storing excess power for later use). This was demonstrated by way of a case study involving the design, control, and economics of a University of Delaware FC/battery bus retrofitted with a roof-installed PV array. The preferred arrangement of HRES components is the FC in series with the battery (the FC is committed to maintaining a desired battery state of charge (SOC) while the battery meets the majority of the bus power demand) while the PV array is used to assist the battery in meeting the bus power demand, with excess PV power being used to charge the battery. Simulation results indicate that under a variety of operating conditions, a PID control strategy is best for enabling the bus to satisfy required power demands and maintain a desired battery SOC. An economic analysis of the PV investment necessary to realize the HRES design objectives indicates that the investment will pay for itself in Newark, DE, establishing the economic viability of the proposed addition of a PV array to the existing University of Delaware FC/battery bus. Although the performance of standard controllers for HRESs is generally satisfactory, operating objectives can be met more reliably and efficiently when information-rich data is used to coordinate HRES component. Two such data-driven control paradigms were developed in separate case studies. In the first case study, we developed and evaluated a method for reconfiguration of control loops in decentralized control schemes using directed spectral decomposition of collected process data. This technique was applied to a stirred mixing tank process and was shown to improve control performance under changing operating conditions. The second case study, which involved data-driven centralized control, establishes a method for adaptive data-driven MPC of a PV/WT/FC/battery/electrolyzer HRES for a single-family home using measured disturbance prediction and model adaptation. This procedure was shown to enable the HRES to better track a power demand setpoint, resulting in increased system reliability and efficiency. Finally, a PV/WT/battery HRES called an OMNi-Charger, which is intended for small-scale (~1 W) remote power applications) was experimentally validated under varying power demand, wind speed, and solar irradiance during controlled and field tests. The OMNi-Charger controller—a simple state controller that enacts a prespecified control action depending on the current state or operating conditions of the system—was shown to enable the OMNi-Charger to meet varying power demands nearly instantaneously and consistently despite rapid and unknown fluctuations in wind speed and solar irradiance. Although the OMNi-Charger warrants some future investigation, the device should prove useful as a cell phone charging station or a power source for lighted ocean buoys.