Control System Design, Analysis, and Simulation of a Photovoltaic Inverter for Unbalanced Load Compensation in a Microgrid

This thesis presents a control scheme for a single-stage three-phase Photovoltaic (PV) converter with negative sequence load current compensation. In this thesis a dual virtual impedance active damping technique for an LCL filter is proposed to address the issue of LCL filter resonance. Both inverter-side current and the capacitor current are used in the feedback loop. Using both signals provides higher DC rejection than using capacitor current alone. The proposed active damping scheme results in a faster transient response and higher damping ratio than can be obtained using inverter-side current alone. The feedback gains can be calculated to achieve a specified damping level. A method of determining the gains of the Proportional and Resonant current controller based on frequency response characteristics is presented. For a specified set of gain and phase margins, the controller gains can be calculated explicitly. Furthermore, a modification is proposed to prevent windup in the resonator. A numerically compensated Half-Cycle Discrete Fourier Transform (HCDFT) method is developed to calculate the negative sequence component of the load current. The numerical compensation allows the HCDFT to accurately estimate the fundamental component of the load current under off-nominal frequency conditions. The proposed HCDFT method is shown to have a quick settling time that is comparable to that obtained with conventional sequence compensation techniques as well as immunity to harmonics in the input signal. The effect of unbalance compensation on the PV power output depending on the irradiance and the operational region on the power-voltage curve is examined. Analysis of the DC link voltage ripple shows the region of operation on the P-V curve affects the amplitude of the DC link voltage ripple during negative sequence compensation. The proposed control scheme is validated by simulation in the Matlab/Simulink® environment. The proposed control scheme is tested in the presence of excessive current imbalance, unbalanced feeder impedances, and non-linear loads. The results have shown that the proposed control scheme can improve power quality in a hybrid PV-diesel microgrid by reducing both voltage and current imbalance while simultaneously converting real power from a PV array

NETWORKED MICROGRID OPTIMIZATION AND ENERGY MANAGEMENT

Military vehicles possess attributes consistent with a microgrid, containing electrical energy generation, storage, government furnished equipment (GFE), and the ability to share these capabilities via interconnection. Many military vehicles have significant energy storage capacity to satisfy silent watch requirements, making them particularly well-suited to share their energy storage capabilities with stationary microgrids for more efficient energy management. Further, the energy generation capacity and the fuel consumption rate of the vehicles are comparable to standard diesel generators, for certain scenarios, the use of the vehicles could result in more efficient operation. Energy management of a microgrid is an open area of research especially in generation constrained scenarios where shedding of low-priority loads may be required. Typical metrics used to assess the effectiveness of an energy management strategy or policy include fuel consumption, electrical storage energy requirements, or the net exergy destruction. When considering a military outpost consisting of a stationary microgrid and a set of vehicles, the metrics used for managing the network become more complex. For example, the metrics used to manage a vehicle’s onboard equipment while on patrol may include fuel consumption, the acoustic signature, and the heat signature. Now consider that the vehicles are parked at an outpost and participating in vehicle-to-grid power-sharing and control. The metrics used to manage the grid assets may now include fuel consumption, the electrical storage’s state of charge, frequency regulation, load prioritization, and load dispatching. The focus of this work is to develop energy management and control strategies that allow a set of diverse assets to be controlled, yielding optimal operation. The provided policies result in both short-term and long-term optimal control of the electrical generation assets. The contributions of this work were: (1) development of a methodology to generate a time-varying electrical load based on (1) a U.S. Army-relevant event schedule and (2) a set of meteorological conditions, resulting in a scenario rich environment suitable for modeling and control of hybrid AC/DC tactical military microgrids, (2) the development of a multi-tiered hierarchical control architecture, suitable for development of both short and long term optimal energy management strategies for hybrid electric microgrids, and (3) the development of blending strategies capable of blending a diverse set of heterogeneous assets with multiple competing objective functions. This work could be extended to include a more diverse set of energy generation assets, found within future energy networks