Paradigm and Paradox in Topology Control of Power Grids

Corrective Transmission Switching can be used by the grid operator to relieve line overloading and voltage violations, improve system reliability, and reduce system losses. Power grid optimization by means of line switching is typically formulated as a mixed integer programming problem (MIP). Such problems are known to be computationally intractable, and accordingly, a number of heuristic approaches to grid topology reconfiguration have been proposed in the power systems literature. By means of some low order examples (3-bus systems), it is shown that within a reasonably large class of “greedy” heuristics, none can be found that perform better than the others across all grid topologies. Despite this cautionary tale, statistical evidence based on a large number of simulations using IEEE 118-bus systems indicates that among three heuristics, a globally greedy heuristic is the most computationally intensive, but has the best chance of reducing generation costs while enforcing N-1 connectivity. It is argued that, among all iterative methods, the locally optimal switches at each stage have a better chance in not only approximating a global optimal solution but also greatly limiting the number of lines that are switched.

[1]  Shuai Wang,et al.  Kirchhoff-Braess phenomena in DC electric networks , 2016, 2016 IEEE 55th Conference on Decision and Control (CDC).

[2]  U. Fincke,et al.  Improved methods for calculating vectors of short length in a lattice , 1985 .

[3]  Shuai Wang,et al.  Power Grid Decomposition Based on Vertex Cut Sets and Its Applications to Topology Control and Power Trading , 2018, 2018 IEEE Conference on Decision and Control (CDC).

[4]  Shuai Wang,et al.  A Novel Decomposition for Control of DC Circuits and Grid Models with Heterogeneous Energy Sources , 2018, 2018 Annual American Control Conference (ACC).

[5]  Milad Soroush,et al.  Accuracies of Optimal Transmission Switching Heuristics Based on DCOPF and ACOPF , 2014, IEEE Transactions on Power Systems.

[6]  Aleksandr Rudkevich,et al.  On fast transmission topology control heuristics , 2011, 2011 IEEE Power and Energy Society General Meeting.

[7]  R D Zimmerman,et al.  MATPOWER: Steady-State Operations, Planning, and Analysis Tools for Power Systems Research and Education , 2011, IEEE Transactions on Power Systems.

[8]  H. Kellerer,et al.  Introduction to NP-Completeness of Knapsack Problems , 2004 .

[9]  Shuai Wang,et al.  The Kirchhoff-Braess paradox and its implications for smart microgrids , 2015, 2015 54th IEEE Conference on Decision and Control (CDC).

[10]  Katta G. Murty,et al.  Some NP-complete problems in quadratic and nonlinear programming , 1987, Math. Program..

[11]  R.P. O'Neill,et al.  Optimal Transmission Switching With Contingency Analysis , 2010, IEEE Transactions on Power Systems.

[12]  Chuin-Shan Chen,et al.  Energy loss reduction by critical switches , 1993 .

[13]  M. Ferris,et al.  Optimal Transmission Switching , 2008, IEEE Transactions on Power Systems.

[14]  A. Cha,et al.  Fast Heuristics for Transmission-Line Switching , 2012, IEEE Transactions on Power Systems.