Homotopy Method for Finding the Global Solution of Post-contingency Optimal Power Flow

The goal of optimal power flow (OPF) is to find a minimum cost production of committed generating units while satisfying technical constraints of the power system. To ensure robustness of the network, the system must be able to find new operating points within the technical limits in the event of component failures such as line and generator outages. However, finding an optimal, or even a feasible, preventive/corrective action may be difficult due to the innate nonconvexity of the problem. With the goal of finding a global solution to the post-contingency OPF problem of a stressed network, e.g. a network with a line outage, we apply a homotopy method to the problem. By parametrizing the constraint set, we define a series of optimization problems to represent a gradual outage and iteratively solve these problems using local search. Under the condition that the global minimum of the OPF problem for the base-case is attainable, we find theoretical guarantees to ensure that the OPF problem for the contingency scenario will also converge to its global minimum. We show that this convergence is dependent on the geometry of the homotopy path. The effectiveness of the proposed approach is demonstrated on Polish networks.

[1]  Steven H. Low,et al.  Branch Flow Model: Relaxations and Convexification—Part I , 2012, IEEE Transactions on Power Systems.

[2]  Dinesh Manocha,et al.  SOLVING SYSTEMS OF POLYNOMIAL EQUATIONS , 2002 .

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

[4]  L. Watson Numerical linear algebra aspects of globally convergent homotopy methods , 1986 .

[5]  Jean Charles Gilbert,et al.  Application of the Moment-SOS Approach to Global Optimization of the OPF Problem , 2013, IEEE Transactions on Power Systems.

[6]  Victor Hinojosa,et al.  Preventive Security-Constrained DCOPF Formulation Using Power Transmission Distribution Factors and Line Outage Distribution Factors , 2018, Energies.

[7]  Venkataramana Ajjarapu,et al.  The continuation power flow: a tool for steady state voltage stability analysis , 1991 .

[8]  A. B. Poore,et al.  The expanded Lagrangian system for constrained optimization problems , 1988 .

[9]  Gabriela Hug,et al.  Robust Convergence of Power Flow Using TX Stepping Method with Equivalent Circuit Formulation , 2018, 2018 Power Systems Computation Conference (PSCC).

[10]  Dianne P. O'Leary,et al.  Homotopy optimization methods for global optimization. , 2005 .

[11]  Santanu S. Dey,et al.  Matrix minor reformulation and SOCP-based spatial branch-and-cut method for the AC optimal power flow problem , 2017, Math. Program. Comput..

[12]  D. Bernstein,et al.  Homotopy Approaches to the H2 Reduced Order Model Problem , 1991 .

[13]  M. B. Cain,et al.  History of Optimal Power Flow and Formulations , 2012 .

[14]  Javad Lavaei,et al.  Geometry of Power Flows and Optimization in Distribution Networks , 2012, IEEE Transactions on Power Systems.

[15]  Javad Lavaei,et al.  Homotopy Method for Finding the Global Solution of Post-contingency Optimal Power Flow , 2020, 2020 American Control Conference (ACC).

[16]  Konstantin Turitsyn,et al.  Numerical polynomial homotopy continuation method to locate all the power flow solutions , 2014, 1408.2732.

[17]  Henrik Sandberg,et al.  A Survey of Distributed Optimization and Control Algorithms for Electric Power Systems , 2017, IEEE Transactions on Smart Grid.

[18]  Hossein Mobahi,et al.  A Theoretical Analysis of Optimization by Gaussian Continuation , 2015, AAAI.

[19]  Alper Atamtürk,et al.  A spatial branch-and-cut method for nonconvex QCQP with bounded complex variables , 2016, Math. Program..

[20]  J. Lavaei,et al.  Conic Relaxations of Power System Optimization : Theory and Algorithms , 2019 .

[21]  J. Yorke,et al.  Finding zeroes of maps: homotopy methods that are constructive with probability one , 1978 .

[22]  L. Watson,et al.  Modern homotopy methods in optimization , 1989 .

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

[24]  Ian A. Hiskens,et al.  Sparsity-Exploiting Moment-Based Relaxations of the Optimal Power Flow Problem , 2014, IEEE Transactions on Power Systems.

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

[26]  Javad Lavaei,et al.  Convex Relaxation for Optimal Power Flow Problem: Mesh Networks , 2015, IEEE Transactions on Power Systems.

[27]  J. Lavaei,et al.  Damping With Varying Regularization in Optimal Decentralized Control , 2022, IEEE Transactions on Control of Network Systems.

[28]  Konstantin S. Turitsyn,et al.  Simple certificate of solvability of power flow equations for distribution systems , 2015, 2015 IEEE Power & Energy Society General Meeting.

[29]  Laurent El Ghaoui,et al.  An Homotopy Algorithm for the Lasso with Online Observations , 2008, NIPS.