Distributed Control of HVDC Transmission Grids

Abstract: Priority access of renewable resources such as offshore wind recommended by Europeanenergy directives, new market models and trading the electric energy among countries leadto new requirements on the operation and expansion of transmission grids. Since AC gridexpansions are limited by legislative issues and long distance transmission capacity, thereis a considerable attention drawn to application of HVDC transmission grids on top of, orin complement to, existing AC power systems. Potential benefits of HVDC transmissiongrids includes the possibility to access remote energy sources thereby increasing renewablepenetration, improving grid security and decreasing congestion in the system. However, thesecure operation of HVDC grids requires a hierarchical control system to manage differentfunctions such as voltage or power flow control. In HVDC grids, the primary control actionto deal with power or DC voltage deviations is communication-free and local which can becarried out by different control schemes such as DC voltage droop control. In addition toprimary local actions, the higher supervisory control actions are needed to guarantee theoptimal operation of HVDC grid.This thesis presents distributed control of an HVDC grid. To this end, three functionsare investigated to be deployed in HVDC supervisory system; coordination of power injectionset-points in the presence of large wind farms, DC slack bus selection and two-stagenetwork topology identification. However, the implementation of supervisory control functionsis linked to the arrangement of system operators; i.e. an individual HVDC operator(central structure) or sharing tasks among AC system operators (distributed structure). Inthis thesis, all three functions are first investigated for the central structure. As main contribution,this thesis presents the distributed solutions for the determined supervisory controlapplications. Furthermore, to study all aspects of proposed algorithms, a co-simulationplatform is introduced.In this thesis, two different distributed algorithms based on Alternating DirectionMethodof Multipliers (ADMM) and Auxiliary Problem Principle (APP) are used to solve coordinationof power injection. However, for distributed implementation of DC slack bus, thechoice of parameters for quantitative ranking of converters is important. These parametersshould be calculated based on local measurements if distributed decision making isdesired. To this end, the short circuit capacity of connected AC grid and power marginof converters are considered for the evaluation of converters to work as slack bus. To estimatethe short circuit capacity as one of the required parameters for selection of DCslack bus, the result of this thesis shows that the recursive least square algorithm can bevery efficiently used. Besides, it is possible to intelligently use a naturally occurring droopresponse in HVDC grids as a local measurement for this estimation algorithm. Regardingthe network topology, a two-stage distributed algorithm is introduced to use the abstractinformation about the neighbouring substation topology to determine the grid connectivity.