Doctor of Philosophy, The Ohio State University, 2022, Electrical and Computer Engineering

Due to the increased penetration of inverter-based resources (IBRs) in bulk power system (BPS) networks, to conduct interconnection studies, generic dynamic mod- els of the second-generation renewable energy system models were developed by the Western Electricity Coordinating Council (WECC) Renewable Energy Modeling Task Force. The dynamic models have been extensively implemented in various power system simulation software packages, and the block diagram representation of the dynamic models is widely present in various technical reports and literature. However, there is a gap between the mathematical model and knowledge of key parameters for the second-generation renewable energy system dynamic models. The complex nonlinear nature of the dynamic models makes it highly challenging for the transmission planning engineers to identify the key parameters when the IBRs are subjected to large-scale voltage and frequency disturbances. This is needed to ensure grid stability under contingencies. For instance, the Type 3 wind turbine generator (WTG-3) model consists of 7 modules with 118 user-defined parameters, interfaced through 26 states and 9 control flags to facilitate the plant operation in different control modes. Thus, this work presents a methodology for the key parameter identification in non- linear models of power systems. The proposed methodology is applied to identify the key parameters of the transmission-scale IBRs (solar PV power plants, wind power plants, and battery energy storage system plants) dynamic models using proposed global sensitivity analysis techniques. It fills up the gap regarding the requirement of the mathematical model and knowledge of key parameters. In contrast to the state-of-the-art methods, the proposed modified Morris, modified Sobol', and modified eFAST sensitivity analysis techniques do not linearize the dynamic models of IBRs around an operating point, providing critical insights into the large-signal stability analysis. The (open full item for complete abstract)

Committee: Mahesh Illindala Dr. (Advisor); Xin Feng Dr. (Committee Member); Jin Wang Dr. (Committee Member); Antonio Conejo Dr. (Committee Member) Subjects: Electrical Engineering; Energy

Master of Science, The Ohio State University, 2020, Mechanical Engineering

The increasing penetration of renewable sources of energy has resulted in an increased likelihood of power over-generation and ramp rate requirements at the electricity supplier end. By incorporating temporally varying costs of electricity provided to the customer, the grid supplier may choose to offer demand-response programs that encourage the customer to defer high load activities to periods of low grid load, effectively overcoming these challenges and increasing machine life. Smart homes optimally activate appliances at the appropriate time with an objective to minimize load at high-price periods, so that at the user end, the total electricity price is lowered. The work presented in this thesis focuses first on the development of models for energy demand and generation associated with electric vehicle (EV) charging and solar power generation, and their integration in an existing residential energy modeling framework. For this enhanced residential power demand model, machine learning (ML) techniques are used to develop a prediction of the user activities for single-resident and multi-resident households. The predicted power demand can be integrated into the smart home algorithm to enhance the optimal activation of appliances to minimize electricity cost and inconvenience.

Committee: Stephanie Stockar (Advisor); Manoj Srinivasan (Committee Member) Subjects: Alternative Energy; Artificial Intelligence; Energy; Engineering; Mechanical Engineering

Doctor of Engineering, Cleveland State University, 2017, Washkewicz College of Engineering

High Intensity Laser Power Beaming is a wireless power transmission technology developed at the Industrial Space Systems Laboratory from 2005 through 2010, in collaboration with the Air Force Research Laboratory to enable remote optical `refueling' of airborne electric micro unmanned air vehicles. Continuous tracking of these air vehicles with high intensity lasers while in-flight for tens of minutes to recharge the on-board battery system is not operationally practical; hence the recharge time must be minimized. This dissertation presents the development and system design optimization of a hybrid electrical energy storage system as a solution to this practical limitation. The solution is based on the development of a high energy density integrated system to capture and store pulsed energy. The system makes use of ultracapacitors to capture the energy at rapid charge rates, while lithium-ion batteries provide the long-term energy density, in order to maximize the duration of operations and minimize the mass requirements. A design tool employing a genetic algorithm global optimizer was developed to select the front-end ultracapacitor elements. The simulation model and results demonstrate the feasibility of the solution. The hybrid energy storage system is also optimized at the system-level for maximum end-to-end power transfer efficiency. System response optimization results and corresponding sensitivity analysis results are presented. Lastly, the ultrafast supply/extended energy storage system is generalized for other applications such as high-power commercial, industrial, and aerospace applications.

Committee: Hanz Richter Ph.D. (Committee Chair); Taysir Nayfeh Ph.D. (Committee Member); Lili Dong Ph.D. (Committee Member); Majid Rashidi Ph.D. (Committee Member); Petru Fodor Ph.D. (Committee Member) Subjects: Electrical Engineering

Master of Science, University of Akron, 2016, Electrical Engineering

This thesis presents a PV system for single-phase applications. A multilevel DC link (MLDCL) structure and a single-phase H-bridge are used. To regulate the PV voltage, a quasi Z-Source converter is used in each unit of the MLDCL. Several quasi Z-source half-bridge converters are connected in series to produce the required discrete voltage output levels of the MLDCL. A detailed design and analysis are applied to a 180 W single phase stand-alone PV system using three cascaded half-bridge quasi Z-source converters and a 60 Hz H-bridge single-phase inverter. Each quasi Z-source module in the proposed structure has the advantage of having an independent control scheme, so that each unit can effectively achieve maximum power point (MPP) from the individual PV panels. The complete system is simulated using MATLAB/Simulink to verify the proposed concept and the theoretical analysis. In the simulations, the incremental conductance method is used as the Maximum Power Point Tracking (MPPT) scheme. The feasibility of the proposed topology is also confirmed through a 60-W experimental setup. The simulation and experimental results are discussed to verify the analysis. The simulations and experiments also confirm that the quasi Z-source structures allow the use of fewer switches and the use of capacitors with lower voltage ratings than traditional buck/boost or Z-source implementations.

Committee: Malik Elbuluk (Advisor); Yilmaz Sozer (Committee Member); Veillette Robert (Committee Member) Subjects: Electrical Engineering; Engineering

Master of Sciences, Case Western Reserve University, 2016, EECS - Computer and Information Sciences

Solar energy is becoming a more important energy source. With the photovoltaic industry experiencing its unprecedented growth in the past decade, the study of PV modules and their durability and lifetime performance is playing an important role in making solar energy a better, more reliable product. To facilitate PV analytics, a distributed system, called E-CRADLE was developed in 2013. Based on that, a number of improvements have been made forming the E-CRADLE v1.1. The improvements include: a monitoring system, a new database schema for PV data, and an easy way to process PV data. The monitoring system ensures the system is working properly. The new database schema is designed for PV data in a NoSQL database. And its universal design ensures it works with our old data as well as data in the future. The new way to process PV data makes distributed computing power accessible even to non-programmers.

Committee: Guo Qiang Zhang (Committee Chair); Roger French (Committee Co-Chair); Mingguo Hong (Committee Member) Subjects: Materials Science; Systems Design; Technology

Master of Science in Engineering (MSEgr), Wright State University, 2014, Mechanical Engineering

Agriculture is a significant measure of an economy for a number of countries in the world. Currently, the agriculture sector relies heavily on conventional sources of energy for irrigation and other purposes. When, considering factors such as increasing costs of fossil fuels and extending new power lines, especially to remote locations where grid electricity is either inaccessible or expensive, a solar PV (photovoltaic) irrigation system can be an effective choice for irrigating farmland. Solar power eliminates the need to run electrical power lines to remote agriculture locations, which quickly turns the monetary equation in favor of solar irrigation over grid-powered irrigation. In addition, the cost of delivering fossil fuels to remote locations can be expensive. Solar power is ideal for agricultural irrigation, as most irrigation is required when the sun is shining brightly. Consequently, a PV powered irrigation system is a promising technology that could help meet the irrigation needs of remote agricultural. The two major goals of this research are to get an existing solar PV irrigation system working and to acquire experimental data using this system under various operating conditions. This research work is built upon a series of three senior design projects. These three senior design projects were to design and construct a solar irrigation system, an instrumentation system for this solar irrigation system, and a single axis solar translator. Specifically this thesis work entailed getting the instrumentation system to work properly, writing a LabVIEW program to automatically acquire data from installed sensors, integrating all three of these senior design projects into one PV irrigation system, getting the PV irrigation system installed on the roof of the Russ Engineering Building, and collecting a large amount of data on the system. All have been accomplished successfully. The PV irrigation system work presented in this thesis use two 224 watt PV modu (open full item for complete abstract)

Committee: James Menart Ph.D. (Advisor); Rory Roberts Ph.D. (Committee Member); Zifeng Yang Ph.D. (Committee Member) Subjects: Alternative Energy; Energy; Engineering; Mechanical Engineering

MS, University of Cincinnati, 2008, Engineering : Electrical Engineering

The majority of commercially available electrical energy is generated through the burning of fossil fuels. This process introduces carbon into the atmosphere and thus contributes to a growing environmental crisis. Carbon-neutral energy sources such as photovoltaic panels provide a viable alternative to energy consumers. However, designing a residential photovoltaic generation and storage system is currently an intimidating problem to anyone without a background in electronics. An intuitive method of residential photovoltaic system simulation and analysis would allow an average homeowner to properly design such a system while considering its potential costs and benefits.The current work focuses on development of a photovoltaic system simulation using MATLAB and Simulink. Commercially available photovoltaic system components were modeled and included in this simulation. Seasonal weather conditions and their effects on power generation were taken into account. Typical household loads were modeled. Various system topologies were explored and comparative cost/benefit system analyses were performed.

Committee: Fred Beyette PhD (Committee Chair); Hal Carter PhD (Committee Member); Arthur Helmicki PhD (Committee Member) Subjects: Electrical Engineering; Engineering; Systems Design

Doctor of Philosophy, The Ohio State University, 2011, Electrical and Computer Engineering

This dissertation presents a hybrid large scale system model of a DC microgrid, its input to state stability analysis and an optimal control algorithm for load side energy management. The theoretical principles of hybrid large scale system modeling, stability, and optimal control for stochastic systems are applied to DC microgrid designed for a photovoltaic based charging station at a workplace parking garage. The example DC microgrid has two energy sources (renewable energy source and power grid) and many plug-in electric vehicle (PEV) charging stations. Stochastic inputs to the system are solar power and charging demand of the PEVs and the control inputs are the vehicle charging power and duration. The hybrid large scale system model of the DC microgrid is developed in state space form to model the large number of DC-DC converters and discrete changes in the system configurations caused by actions of a supervisory controller and converter operating modes. Stability analysis of the model using the Gersgorin principle, an eigenvalue inclusion theorem and connective stability principles provide design guidelines and conditions on interconnection properties. Necessary conditions for the large scale system stability are provided using eigenvalue analysis. The input to state stability analysis is performed using Lyapunov theory for hybrid systems to provide constraints on the dwell time of the switching signal. The optimization problem is structured as an inventory control problem and solved using dynamic programming with stochastic inputs to find the charging power of all the vehicles at each time step. A simple but realistic rule based algorithm is developed to distribute the total charging power among available vehicles. The control algorithm schedules PEV charging power to maximize the use of solar energy, reduce energy taken from the grid, and satisfy the charging demand of all vehicles within the switching constraints. Finally, this research is accompanied by th (open full item for complete abstract)

Committee: Stephen Yurkovich PhD (Advisor); Giorgio Rizzoni PhD (Committee Member); Jin Wang PhD (Committee Member) Subjects: Alternative Energy; Economics; Electrical Engineering; Energy