CONTROL STRATEGIES OF DC MICROGRID TO ENABLE A MORE WIDE-SCALE ADOPTION
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Microgrids are gaining popularity in part for their ability to support increased penetration of distributed renewable energy sources, aiming to meet energy demand and overcome global warming concerns. DC microgrid, though appears promising, introduces many challenges in the design of control systems in order to ensure a reliable, secure and economical operation. To enable a wider adoption of DC microgrid, this dissertation examines to combine the characteristics and advantages of model predictive control (MPC) and distributed droop control into a hierarchy and fully autonomous control of the DC microgrid. In addition, new maximum power point tracking technique (MPPT) for solar power and active power decoupling technique for the inverter are presented to improve the efficiency and reliability of the DC microgrid. With the purpose of eliminating the oscillation around the maximum power point (MPP), an improved MPPT technique was proposed by adding a steady state MPP determination algorithm after the adaptive perturb and observe method. This control method is proved independent with the environmental conditions and has much smaller oscillations around the MPP compared to existing ones. Therefore, it helps increase the energy harvest efficiency of the DC microgrid with less continuous DC power ripple. A novel hierarchy strategy consisting of two control loops is proposed to the DC microgrid in study, which is composed of two PV boost converters, two battery bi-directional converters and one multi-level packed-u-cell inverter with grid connected. The primary loop task is the control of each energy unit in the DC microgrid based on model predictive current control. Compared with traditional PI controllers, MPC speeds up the control loop since it predicts error before the switching signal is applied to the converter. It is also free of tuning through the minimization of a flexible user-defined cost function. Thus, the proposed primary loop enables the system to be expandable by adding additional energy generation units without affecting the existing ones. Moreover, the maximum power point tracking and battery energy management of each energy unit are included in this loop. The proposed MPC also achieves unity power factor, low grid current total harmonics distortion. The secondary loop based on the proposed autonomous droop control identifies the operation modes for each converter: current source converter (CSC) or voltage source converter (VSC). To reduce the dependence on the high bandwidth communication line, the DC bus voltage is utilized as the trigger signal to the change of operation modes. With the sacrifice of small variations of bus voltage, a fully autonomous control can be realized. The proposed distributed droop control of different unit converters also eliminates the potential conflicts when more than two converters compete for the VSC mode. Single-phase inverter systems in the DC microgrid have low frequency power ripple, which adversely affects the system reliability and performance. A power decoupling circuit based on the proposed dual buck converters are proposed to address the challenges. The topology is free of shoot-through and deadtime concern and the control is independent with that of the main power stage circuit, which makes the design simpler and more reliable. Moreover, the design of both PI and MPC controllers are discussed and compared. While, both methods present satisfied decoupling performances on the system, the proposed MPC is simpler to be implemented. In conclusion, the DC microgrid may be more widely adopted in the future with the proposed control strategies to address the current challenges that hinder its further development.
Maximum Power Point Tracking
Model Predictive Control
Renewable Energy Sources
Battery Storage System
Active Power Decoupling.
Xiao, Shunlong (2018). CONTROL STRATEGIES OF DC MICROGRID TO ENABLE A MORE WIDE-SCALE ADOPTION. Doctoral dissertation, Texas A & M University. Available electronically from
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