Convexification of power flow problem over arbitrary networks

Consider an arbitrary power network with PV and PQ buses, where active powers and voltage magnitudes are known at PV buses, and active and reactive powers are known at PQ buses. The classical power flow (PF) problem aims to find the unknown complex voltages at all buses. This problem is usually solved approximately through linearization or in an asymptotic sense using Newton's method, given that the solution belongs to a good regime containing voltage vectors with small angles. The question arises as to whether the PF problem can be cast as the solution of a convex optimization problem over that regime. The objective of this paper is to show that the answer to the above question is affirmative. More precisely, we propose a class of convex optimization problems with the property that they all solve the PF problem as long as angles are small. Each convex problem proposed in this work is in the form of a semidefinite program (SDP). Associated with each SDP, we explicitly characterize the set of complex voltages that can be recovered via that convex problem. Since there are infinitely many SDP problems, each capable of recovering a potentially different set of voltages, designing a good SDP problem is cast as a convex problem.

[1]  Robert J. Thomas,et al.  MATPOWER's extensible optimal power flow architecture , 2009, 2009 IEEE Power & Energy Society General Meeting.

[2]  Art M. Duval,et al.  Simplicial matrix-tree theorems , 2008, 0802.2576.

[3]  David Tse,et al.  Distributed algorithms for optimal power flow problem , 2011, 2012 IEEE 51st IEEE Conference on Decision and Control (CDC).

[4]  Emmanuel J. Candès,et al.  PhaseLift: Exact and Stable Signal Recovery from Magnitude Measurements via Convex Programming , 2011, ArXiv.

[5]  Pascal Van Hentenryck,et al.  AC-Feasibility on Tree Networks is NP-Hard , 2014, IEEE Transactions on Power Systems.

[6]  Pablo A. Parrilo,et al.  Guaranteed Minimum-Rank Solutions of Linear Matrix Equations via Nuclear Norm Minimization , 2007, SIAM Rev..

[7]  Jesse T. Holzer,et al.  Implementation of a Large-Scale Optimal Power Flow Solver Based on Semidefinite Programming , 2013, IEEE Transactions on Power Systems.

[8]  Javad Lavaei,et al.  Promises of Conic Relaxation for Contingency-Constrained Optimal Power Flow Problem , 2014, IEEE Transactions on Power Systems.

[9]  Abhinav Verma,et al.  Power grid security analysis: an optimization approach , 2010 .

[10]  J. Lavaei,et al.  Physics of power networks makes hard optimization problems easy to solve , 2012, 2012 IEEE Power and Energy Society General Meeting.

[11]  Albert Y. S. Lam,et al.  An Optimal and Distributed Method for Voltage Regulation in Power Distribution Systems , 2012, IEEE Transactions on Power Systems.

[12]  Javad Lavaei Zero duality gap for classical opf problem convexifies fundamental nonlinear power problems , 2011, Proceedings of the 2011 American Control Conference.

[13]  Robert A. W. van Amerongan A general-purpose version of the fast decoupled load flow , 1989 .

[14]  R. Jabr Exploiting Sparsity in SDP Relaxations of the OPF Problem , 2012, IEEE Transactions on Power Systems.

[15]  J. Lavaei,et al.  Convex relaxation for optimal power flow problem: Mesh networks , 2013, 2013 Asilomar Conference on Signals, Systems and Computers.

[16]  S. Low,et al.  Zero Duality Gap in Optimal Power Flow Problem , 2012, IEEE Transactions on Power Systems.

[17]  William F. Tinney,et al.  Power Flow Solution by Newton's Method , 1967 .

[18]  Javad Lavaei,et al.  Low-rank solutions of matrix inequalities with applications to polynomial optimization and matrix completion problems , 2014, 53rd IEEE Conference on Decision and Control.

[19]  Martin S. Andersen,et al.  Reduced-Complexity Semidefinite Relaxations of Optimal Power Flow Problems , 2013, IEEE Transactions on Power Systems.

[20]  R.A.M. VanAmerongen A general-purpose version of the fast decoupled loadflow , 1989 .

[21]  O. Alsac,et al.  Fast Decoupled Load Flow , 1974 .