AC optimal power flow in the presence of renewable sources and uncertain loads

The increasing penetration of renewable energy resources, paired with the fact that load can vary significantly, introduce a high degree of uncertainty in the behavior of modern power grids. Given that classical dispatch solutions are "rigid," their performance in such an uncertain environment is in general far from optimal. For this reason, in this paper, we consider AC optimal power flow (AC-OPF) problems in the presence of uncertain loads and (uncertain) renewable energy generators. The goal of AC-OPF design is to guarantee that controllable generation is dispatched at minimum cost, while satisfying constraints on generation and transmission for "almost all" realizations of the uncertainty. We propose an approach based on a randomized technique recently developed, named "scenario with certificates", which allows to tackle the problem without assuming any a-priori dependence of the voltages in the network on the uncertain generators/loads. The proposed solution can exploit the usually available probabilistic description of the uncertainty and variability, and provides solutions with a-priori probabilistic guarantees on the risk of violating the constraints on generation and transmission.

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

[2]  Michael Chertkov,et al.  Chance-Constrained Optimal Power Flow: Risk-Aware Network Control under Uncertainty , 2012, SIAM Rev..

[3]  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.

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

[5]  James A. Momoh,et al.  Improved interior point method for OPF problems , 1999 .

[6]  Aouss Gabash,et al.  A Framework for Real-Time Optimal Power Flow under Wind Energy Penetration , 2017, EEEIC 2017.

[7]  Yi Guo,et al.  Data-Based Distributionally Robust Stochastic Optimal Power Flow—Part I: Methodologies , 2018, IEEE Transactions on Power Systems.

[8]  Göran Andersson,et al.  Chance-Constrained AC Optimal Power Flow: Reformulations and Efficient Algorithms , 2017, IEEE Transactions on Power Systems.

[9]  Scott Backhaus,et al.  A robust approach to chance constrained optimal power flow with renewable generation , 2017 .

[10]  Qing-Guo Wang,et al.  Sequential Randomized Algorithms for Convex Optimization in the Presence of Uncertainty , 2013, IEEE Transactions on Automatic Control.

[11]  Von Estorff Ulrik,et al.  Strategic Energy Technology Plan Study on Energy Education and Training in Europe , 2014 .

[12]  K. Pearson Contributions to the Mathematical Theory of Evolution. II. Skew Variation in Homogeneous Material , 1895 .

[13]  Emilio Gómez-Lázaro,et al.  Wind Power Forecasting Error Distributions : An International Comparison , 2012 .

[14]  Weijun Xie,et al.  Distributionally Robust Chance Constrained Optimal Power Flow with Renewables: A Conic Reformulation , 2018, IEEE Transactions on Power Systems.

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

[16]  B.K. Johnson Extraneous and false load flow solutions , 1977, IEEE Transactions on Power Apparatus and Systems.

[17]  Daniel Bienstock,et al.  Strong NP-hardness of AC power flows feasibility , 2019, Oper. Res. Lett..

[18]  Rabih A. Jabr,et al.  Adjustable Robust OPF With Renewable Energy Sources , 2013, IEEE Transactions on Power Systems.

[19]  Steven H. Low,et al.  Convex Relaxation of Optimal Power Flow—Part II: Exactness , 2014, IEEE Transactions on Control of Network Systems.

[20]  J.A.P. Lopes,et al.  On the optimization of the daily operation of a wind-hydro power plant , 2004, IEEE Transactions on Power Systems.

[21]  Bri-Mathias Hodge,et al.  Short-Term Load Forecast Error Distributions and Implications for Renewable Integration Studies , 2013, 2013 IEEE Green Technologies Conference (GreenTech).

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

[23]  Andrew J. Korsak,et al.  On the Question of Uniqueness of Stable Load-Flow Solutions , 1972 .

[24]  Yasumasa Fujisaki,et al.  Randomized solution for robust optimal power flow , 2014, 53rd IEEE Conference on Decision and Control.

[25]  Hui Zhang,et al.  Chance Constrained Programming for Optimal Power Flow Under Uncertainty , 2011, IEEE Transactions on Power Systems.

[26]  Wilsun Xu,et al.  The existence of multiple power flow solutions in unbalanced three-phase circuits , 2002 .

[27]  Rabih A. Jabr,et al.  Robust Multi-Period OPF With Storage and Renewables , 2015, IEEE Transactions on Power Systems.

[28]  Johanna L. Mathieu,et al.  Stochastic Optimal Power Flow with Uncertain Reserves from Demand Response , 2014, 2014 47th Hawaii International Conference on System Sciences.

[29]  Luca Zaccarian,et al.  Robust Linear Static Anti-Windup With Probabilistic Certificates , 2015, IEEE Transactions on Automatic Control.

[30]  M. Perninge,et al.  A Stochastic Optimal Power Flow Problem With Stability Constraints—Part II: The Optimization Problem , 2013, IEEE Transactions on Power Systems.

[31]  R. Yokoyama,et al.  Improved genetic algorithms for optimal power flow under both normal and contingent operation states , 1997 .

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

[33]  V. Quintana,et al.  Improving an interior-point-based OPF by dynamic adjustments of step sizes and tolerances , 1999 .

[34]  M. A. Abido,et al.  Optimal power flow using particle swarm optimization , 2002 .

[35]  Knud D. Andersen,et al.  The Mosek Interior Point Optimizer for Linear Programming: An Implementation of the Homogeneous Algorithm , 2000 .

[36]  Pascal Van Hentenryck,et al.  A Linear-Programming Approximation of AC Power Flows , 2012, INFORMS J. Comput..

[37]  Manfred Morari,et al.  Policy-Based Reserves for Power Systems , 2012, IEEE Transactions on Power Systems.

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

[39]  Maria Vrakopoulou,et al.  Probabilistic security constrained optimal power flow for a mixed HVAC and HVDC grid with stochastic infeed , 2014, 2014 Power Systems Computation Conference.

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

[41]  Bri-Mathias Hodge,et al.  Wind power forecasting error distributions over multiple timescales , 2011, 2011 IEEE Power and Energy Society General Meeting.

[42]  R. H. Lasseter,et al.  Stochastic optimal power flow: formulation and solution , 2000, 2000 Power Engineering Society Summer Meeting (Cat. No.00CH37134).

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

[44]  Johan Löfberg,et al.  YALMIP : a toolbox for modeling and optimization in MATLAB , 2004 .

[45]  Xiaoqing Bai,et al.  A semidefinite programming method with graph partitioning technique for optimal power flow problems , 2011 .

[46]  K. Pearson Contributions to the Mathematical Theory of Evolution , 1894 .

[47]  Florin Capitanescu,et al.  Critical review of recent advances and further developments needed in AC optimal power flow , 2016 .

[48]  Giuseppe Carlo Calafiore,et al.  The scenario approach to robust control design , 2006, IEEE Transactions on Automatic Control.

[49]  John Lygeros,et al.  Stochastic optimal power flow based on conditional value at risk and distributional robustness , 2015 .

[50]  John Lygeros,et al.  Probabilistic guarantees for the N-1 security of systems with wind power generation , 2013 .

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

[52]  William F. Tinney,et al.  Optimal Power Flow Solutions , 1968 .

[53]  J. Carpentier,et al.  Optimal Power Flows , 1979, VSC-FACTS-HVDC.

[54]  John Lygeros,et al.  Probabilistic security-constrained AC optimal power flow , 2013, 2013 IEEE Grenoble Conference.

[55]  Tamás Keviczky,et al.  Tractable reserve scheduling in AC power systems with uncertain wind power generation , 2017, 2017 IEEE 56th Annual Conference on Decision and Control (CDC).

[56]  I. Erlich,et al.  A Stochastic Model for the Optimal Operation of a Wind-Thermal Power System , 2009, IEEE Transactions on Power Systems.

[57]  John Lygeros,et al.  A Probabilistic Framework for Reserve Scheduling and ${\rm N}-1$ Security Assessment of Systems With High Wind Power Penetration , 2013, IEEE Transactions on Power Systems.

[58]  Silvano Martello,et al.  Decision Making under Uncertainty in Electricity Markets , 2015, J. Oper. Res. Soc..