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On Control and Optimization of DC Microgrids

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2017, Doctor of Philosophy, Ohio State University, Electrical and Computer Engineering.
The power system is provisioned to evolve into a smart grid that is greener, safer, and more efficient. DC microgrid, a new form of distribution system and an emerging electrical network on ships/airplanes/electronic devices, has risen to prominence as an important building block of the future grid and many other applications. With proper operation and coordination, DC microgrids can exploit the flexibility in generation as well as consumption units, which have been standing unresponsive for decades, to approach a more robust and efficient grid such that every component in a power grid can reach its full potential to vibrantly participate in grid services. This dissertation presents systematic approaches to solve DC microgrid control and optimization problems that are usually marked by challenges like uncertainty, nonlinearity, tractability, and structural constraint issues. First, it is well known that when a DC microgrid is operated in island mode, the stability critical power balance is shadowed by uncertain and volatile generation and consumption. We propose a robust stability framework containing a set of sufficient conditions to provide provable stability guarantee for such systems. We then further investigate into robust control design to improve the performance of the system. In view of the physical communication structures that commonly exist in a microgrid, decentralized/distributed controllers are recognized to be more applicable in practice for their limited reliance on information transmissions. Nevertheless, with the communication structural constraints, the decentralized/distributed control design problem is NP-hard in general, and an ill-designed controller may as well render an originally operative system unstable. We propose an algorithm to design a structurally constrained controller in such a way that it can guarantee a design direction with provable improving performance. Second, for DC microgrids that are in grid-connected mode, the power imbalance can be compensated automatically by switching power from grid-connected units. Taking advantage of it, with proper energy management a DC microgrid is able to act as a valuable energy asset with an optimized switching power profile to provide various grid services. The challenge of the problem lies in that the switching power is still uncertain due to the integration of various renewable resources and random loads in a DC microgrid. To counteract this, we propose a chance constrained programming framework, which transforms energy management problems with uncertainty into deterministic convex problems. At last, in this dissertation we use realistic simulation case studies as well as hardware-in-the-loop testing to verify the effectiveness of the work.
Wei Zhang (Advisor)
Giorgio Rizzoni (Advisor)
Antonio Conejo (Committee Member)
Mahesh Illindala (Committee Member)
Andrej Rotter (Other)
129 p.

Recommended Citations

Citations

  • Liu, J. (2017). On Control and Optimization of DC Microgrids [Doctoral dissertation, Ohio State University]. OhioLINK Electronic Theses and Dissertations Center. http://rave.ohiolink.edu/etdc/view?acc_num=osu1512049527948171

    APA Style (7th edition)

  • Liu, Jianzhe. On Control and Optimization of DC Microgrids. 2017. Ohio State University, Doctoral dissertation. OhioLINK Electronic Theses and Dissertations Center, http://rave.ohiolink.edu/etdc/view?acc_num=osu1512049527948171.

    MLA Style (8th edition)

  • Liu, Jianzhe. "On Control and Optimization of DC Microgrids." Doctoral dissertation, Ohio State University, 2017. http://rave.ohiolink.edu/etdc/view?acc_num=osu1512049527948171

    Chicago Manual of Style (17th edition)