Control, Modulation, and Protection Strategies for Modular Multilevel Converters in Smart AC and DC Grids Applications

• Author / Creator

  Ghazanfari, Amin

• The technical viability of the modular multilevel converter (MMC) technology for a wide range of applications from low- to high-voltage systems has resulted in the rapid deployment of these converters in smart ac and dc grids. The features that MMCs offer, including common dc-link, modularity, voltage scalability, superior harmonic performance, and low switching losses, account for this increasing interest. However, difficulties associated with the operation and control of the MMC, such as unbalanced submodule (SM) capacitor voltages, lack of coordination or malfunction of the MMC components, and fault occurrence in the dc link and/or ac grid demand special attention. This research work presents a new sensorless capacitor voltage balancing strategy for MMCs to effectively balance SM capacitor voltages in a wide range of switching frequencies. The proposed hierarchical permutation cyclic coding (PCC) method is developed to evenly distribute the switching gate signals among the SMs of each arm. In addition to improving reliability and computational resources, the hierarchical PCC algorithm is decoupled from other standard control loops in MMCs. A new SM circuit is designed to facilitate fault-tolerant capability for MMCs under various internal and external faults. The proposed SM circuit can be simply integrated into conventional half bridge-based MMCs by using a switching signal adapter. A fully modular structure, enhanced internal fault management, external fault-handling capability, and ease of expandability are the key features of the designed SM circuit. For fault-tolerant operation, a supervisory algorithm including monitoring and decision-making units is devised to detect and identify faults by analyzing the circulating currents and SM capacitor voltages. The supervisory algorithm distinguishes a fault occurring in SMs from those occurring in sensors. Fast fault identification and robust postfault restoration are the main features of the proposed fault-tolerant framework. The technical feasibility of the proposed strategies for MMCs in various applications is investigated. To supply a wide range of rapidly varying plug-in and wireless electric vehicles (EVs) in dc parking lots, a resilient decentralized control framework is developed to give the system plug-and-play (PnP) capability. The PnP decentralized controller guarantees precise power dc and oscillatory components management among different assets. It also ensures seamless operation mode transition without the need for communication among assets. For smart dc homes, a decentralized cooperative control (DCC) method along with a fault segment identification (FSI) scheme is designed to achieve the control and protection objectives by using only local measurements. The DCC method ensures accurate current sharing, dc bus voltage regulation, and fast restoration after the fault clearance. The main objective of the FSI scheme is to quickly identify and isolate the faulty segment to protect the sensitive power electronic components in the dc home from the high-fault current. Extensive case studies, based on time-domain simulations using the Matlab/Simulink and PSCAD/EMTDC, are provided to evaluate the performance of the proposed schemes when the MMC is subject to various disturbances, e.g., load change, component failure, unbalanced load, and grid fault conditions. Furthermore, real-time studies are conducted in a hardware-in-the-loop (HIL) setup to verify the feasibility and resilience of the proposed schemes. This research will be the key for control and protection methodology development of MMCs and will lay the foundation for the future smart infrastructure.

• Subjects / Keywords

  • Capacitor Voltage Balancing
  • Modular Multilevel Converter (MMC)
  • Electric Vehicle (EV)
  • Protection
  • Smart Building
  • Monitoring
  • Controls
  • Resilient Framework
  • DC Distribution Systems
  • Fault Identification
  • Smart Grid

• Graduation date

  Fall 2017

• Type of Item

  Thesis

• Degree

  Doctor of Philosophy

• DOI

  https://doi.org/10.7939/R3BV7B87B

• License

  This thesis is made available by the University of Alberta Libraries with permission of the copyright owner solely for non-commercial purposes. This thesis, or any portion thereof, may not otherwise be copied or reproduced without the written consent of the copyright owner, except to the extent permitted by Canadian copyright law.