Modelling and Optimisation for a Coordinated interconnected multi-terminal DC transmission infrastructure for integration of offshore wind energy

Project Description:

As renewables are becoming major contributors to the UK’s energy supply, the power grid is experiencing new challenges, as the current power system was not designed for decentralised intermittent energy resources. One potential solution is the development of “supergrids” – a new type of network topology which is based on multi-terminal High Voltage DC links overlaid on top of AC links, for facilitating interconnection between multiple resources (i.e. wind farms) at a large-scale and in bulk, in a flexible, reliable, and controllable manner. The supergrid concept can also be used to provide connections between multiple regions (e.g. neighbouring countries wind farms) to maximise resource utilisation. An example of a supergrid implementation is the proposed North Sea Wind Power Hub (NSWPH) which proposes to build an interconnector hub in the middle of North Sea to facilitate connection of wind power assets of multiple countries to maximise resource utilisation in line with the EU sustainable energy goals.

The supergrid concept takes advantage of the extra flexibility and controllability of VSC-based HVDC systems. These systems are being implemented successfully for point to point connections, however, there is still much to be done in modelling of a fully flexible interconnected multi-terminal DC system, and its optimal operation for purposes of power control from interconnected offshore wind farms. In this project, therefore, a control framework for optimal coordinated operation of VSC converters in a complex multiterminal DC system for linking offshore wind farms will be investigated. This work will extend on Durham’s existing work in implementing universal models for optimum operational planning purposes in future large-scale offshore wind farms which take advantage of the extra flexibility and controllability of multi-terminal HVDC links. The work will begin by developing a generalised modelling framework for modelling AC and DC components related to the underlying electrical interconnection infrastructure used for linking multiple wind farms together. The models are then used to develop exemplar power systems linking multiple offshore wind farms using HVDC supergrids for purposes of short-term optimum operational planning. To this end, provisions of power flow control and voltage control as well as network ancillary services (e.g. frequency regulation) by the offshore wind assets are analysed.

Methodology

This work will involve developing advanced computational models for power systems including models that are suitable for solving optimal power flow problem. Models will be developed for VSC-based HVDC links which could be used to form multi-terminal supergrids for connecting multiple wind farms. The optimal power flow problem is a complex nonlinear optimisation problem which can be quite tasking for especially larger scale systems and as such one of the main methodological contributions in this project is to develop suitable approximations such as linearisation methods for reducing the computational expenditure of the optimal power flow problem and at the same time maintain its tractability when scaled up for larger systems.

The project will also involve implementation of a suitable day-ahead operational planning framework by solving multiple instances of optimal power flow problem to plan the operation of offshore wind farms within a specific planning timescale (say 24 hours). The planning framework is then implemented to multiple wind farms connected via a multi-terminal HVDC supergrid to provide better power regulation and a more stable, reliable operation even after emergencies such as loss of supply in a specific region. These added flexibilities of operation are necessary for a sustainable growth and integration of offshore wind resource in the future for example in the UK in line with National Grid’s Future Energy Scenarios (FES) projections.