Invited Session Thu.1.MA 550

Thursday, 10:30 - 12:00 h, Room: MA 550

Cluster 18: Optimization in energy systems [...]

Gas and electricity networks


Chair: Alexander Martin



Thursday, 10:30 - 10:55 h, Room: MA 550, Talk 1

Robert Schwarz
Gas network design with integrated optimization of topology and dimensioning


Natural gas is transported through networks of pipelines from sources
to sinks. Given the geographical locations of these points together
with nominated amounts of flow, we solve the problem of building the
cost-optimal network able to satisfy all demands within the feasible
pressure bounds. The decisions include both the selection of arcs
where pipelines are built, as well as the choice of suitable diameters
out of a set of discrete values with associated cost factors. Because
of the nonconvex, nonlinear relationship between the flow rate and the
pressure loss along the pipes, the diameters do not correspond
directly to flow capacities. This leads to a MINLP formulation of the
problem, which is solved using outer approximation and spatial
branching. The discrete diameter choice is exploited to reformulate
certain subproblems as MILPs after variable fixations during the
branch and bound process. We present some preliminary computational
results and discuss some possible extensions of the model.



Thursday, 11:30 - 11:55 h, Room: MA 550, Talk 3

Ken Mckinnon
An MINLP approach to islanding electricity networks

Coauthors: Waqquas Bukhsh, Andreas Grothey, Paul Trodden


Intentional islanding is attracting an increasing amount of attention as a means of preventing large-scale blackouts in electricity transmission networks. In this talk, a mathematical formulation for islanding is presented, in which suspected unhealthy components of the network are isolated while the load shed is minimized. To achieve balanced, feasible islands, nonlinear AC power flow equations should be included, resulting in an MINLP problem. In the proposed MILP formulation, these terms are approximated by piecewise linear functions. The approach is demonstrated by results on test networks.


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