This work presents an extensive review of hierarchical control strategies that provide effective and robust control for a DC microgrid. DC microgrid is an efficient, scalable and reliable solution for electrification in remote areas and needs a reliable control scheme such as hierarchical control. The hierarchical control strategy is divided into three layers namely primary, secondary and tertiary based on their functionality. In this study, different methods of primary control for current and voltage regulation, secondary control for error-correction in voltage and current, power sharing in a microgrid and microgrid clusters and tertiary control for power and energy management with a primary focus on minimal power loss and operational cost in a DC microgrid system are reviewed in-depth. Along with this, the advantages and limitations of various control structures like centralised, decentralised, distributed are discussed in this study. After a comparative study of all control strategies, the optimum control schemes from the author's point of view are also presented.

At the High Luminosity Large Hadron Collider (HL-LHC), traditional track reconstruction techniques that are critical for physics analysis will need to be upgraded to scale with track density. Quantum annealing has shown promise in its ability to solve combinatorial optimization problems amidst an ongoing effort to establish evidence of a quantum speedup. As a step towards exploiting such potential speedup, we investigate a track reconstruction approach by adapting the existing geometric Denby-Peterson (Hopfield) network method to the quantum annealing framework for HL-LHC conditions. We develop additional techniques to embed the problem onto existing and near-term quantum annealing hardware. Results using simulated annealing and quantum annealing with the D-Wave 2X system on the TrackML open dataset are presented, demonstrating the successful application of a quantum annealing algorithm to the track reconstruction challenge. We find that combinatorial optimization problems can effectively reconstruct tracks, suggesting possible applications for fast hardware-specific implementations at the HL-LHC while leaving open the possibility of a quantum speedup for tracking.

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