Optimal scheduling of Distributed Energy Resources connected to Electricity Distribution Networks using Robust Mixed-Integer Second Order Cone Programming
Eng. D. Thesis.Tackling climate change is a global emergency, driving the electricity sector to
go through rapid changes, including the increasing reliance on local generating
assets, called distributed energy resources (DER). DER range from onsite energy
storage systems, to gas or diesel generators, and renewable generators, but could
also include other forms of generation such as electric vehicles with vehicle-to-grid
capabilities. This PhD proposes a model to optimally schedule DER connected
to radial distribution networks, which can form an active distribution network or a
microgrid, aiming at delivering improvements in operational cost, security of supply
and environmental sustainability. This is mathematically formulated using robust
mixed-integer second-order cone programming. The proposed model takes into
account an accurate power flow model for radial networks and a robust approach
to deal with uncertainty in the market price, the electricity demand, the renewable
generation, and the time and duration of a scheduled interruption from the main grid
when DER form part of a microgrid. Computational experiments support the suitability
of the proposed model, in a number of case studies informed by real-world data
and operational scenarios. This research concludes the following. Firstly, that it is
important to account for detailed modelling of network losses in operational decisions
of such systems, as they profoundly affect both the cost and the network’s operating
state and conditions. Secondly, that the robust approach used in this thesis in order to
deal with uncertainty allows distribution system and/or microgrid operators to manage
trade-offs between the level of the aforementioned uncertainties they are willing to
tolerate, and the operational cost of network assets. Benefits of using the proposed
model include, reduction of the operational cost, and mitigation of technical constraint
violations in actual conditions. The proposed model can be used by a range of
stakeholders including, microgrid operators, distribution system operators, and DER
owners.Newcastle University, Engineering and
Physical Sciences Research Council (EPSRC
