Convex power flow models for scalable electricity market modelling

Optimal power flow problems and market clearing approaches are converging: cost-optimal scheduling of loads and generators should be performed while taking the grid’s physics and operational envelopes into account. Within the SmartNet project, the idea is to consider the grid’s physical behaviour in market clearing approaches. Taking the physics of power flow into account, while managing solution times, demands pragmatic approaches. Convex relaxation and linear approximation are two such approaches to manage computational tractability. This work gives an overview of recent OPF formulations, and their relaxations and approximations. The hierarchy of the approaches is detailed, as well as the loss of properties resulting from the relaxation process.

[1]  Stephen P. Boyd,et al.  A rank minimization heuristic with application to minimum order system approximation , 2001, Proceedings of the 2001 American Control Conference. (Cat. No.01CH37148).

[2]  Jean B. Lasserre,et al.  Global Optimization with Polynomials and the Problem of Moments , 2000, SIAM J. Optim..

[3]  Ian A. Hiskens,et al.  Moment-based relaxation of the optimal power flow problem , 2013, 2014 Power Systems Computation Conference.

[4]  Carleton Coffrin,et al.  The QC relaxation: A theoretical and computational study on optimal power flow , 2016, 2017 IEEE Power & Energy Society General Meeting.

[5]  Masakazu Kojima,et al.  Second Order Cone Programming Relaxation of a Positive Semidefinite Constraint , 2003, Optim. Methods Softw..

[6]  M. E. Baran,et al.  Optimal capacitor placement on radial distribution systems , 1989 .

[7]  R. Jabr Radial distribution load flow using conic programming , 2006, IEEE Transactions on Power Systems.

[8]  Eilyan Bitar,et al.  A rank minimization algorithm to enhance semidefinite relaxations of Optimal Power Flow , 2013, 2013 51st Annual Allerton Conference on Communication, Control, and Computing (Allerton).

[9]  Pascal Van Hentenryck,et al.  Network flow and copper plate relaxations for AC transmission systems , 2015, 2016 Power Systems Computation Conference (PSCC).

[10]  M. Er Quadratic optimization problems in robust beamforming , 1990 .

[11]  K. Fujisawa,et al.  Semidefinite programming for optimal power flow problems , 2008 .

[12]  Arkadi Nemirovski,et al.  On Polyhedral Approximations of the Second-Order Cone , 2001, Math. Oper. Res..

[13]  O. Alsaç,et al.  DC Power Flow Revisited , 2009, IEEE Transactions on Power Systems.

[14]  Pascal Van Hentenryck,et al.  The QC Relaxation: Theoretical and Computational Results on Optimal Power Flow , 2015, ArXiv.

[15]  Steven H. Low,et al.  Convex Relaxation of Optimal Power Flow—Part I: Formulations and Equivalence , 2014, IEEE Transactions on Control of Network Systems.

[16]  Santanu S. Dey,et al.  Strong SOCP Relaxations for the Optimal Power Flow Problem , 2015, Oper. Res..

[17]  Santanu S. Dey,et al.  Strong SOCP Relaxations for Optimal Power Flow , 2015 .

[18]  Paul A. Trodden,et al.  Local Solutions of the Optimal Power Flow Problem , 2013, IEEE Transactions on Power Systems.

[19]  Pascal Van Hentenryck,et al.  Convex quadratic relaxations for mixed-integer nonlinear programs in power systems , 2016, Mathematical Programming Computation.