Optimal Fast Control and Scheduling of Power Distribution System Using Integrated Receding Horizon Control and Convex Conic Programming

In this paper, a convex optimal power flow (OPF) formulation integrated within receding horizon control (RHC) architecture using second-order conic programming (SOCP) is proposed. The main advantages of the proposed method are 1) global optimal scheduling with faster computation time; 2) dynamic models with online control within optimization routine; and 3) integration of uncertain resources and measurements. The effectiveness of this method is evaluated using modified IEEE 32-bus and IEEE 119-bus distribution test systems considering network constraints such as energy market interactions, storage dynamics, and uncertain model of wind generation. The efficiency of the proposed method compared to RHC ac optimal power flow (RHC-ACOPF) is also evaluated using real-time simulator. The results show that the proposed method outperforms the RHC-ACOPF and guarantees global optimal solution. The proposed method also provides effective usage of energy storage system since dynamic modeling of energy storage within the optimization algorithm is possible using RHC integration.

[1]  Steven H. Low,et al.  Branch Flow Model: Relaxations and Convexification—Part II , 2012 .

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

[3]  K. Pandya,et al.  A SURVEY OF OPTIMAL POWER FLOW , 2008 .

[4]  Kameshwar Poolla,et al.  Real-time scheduling of deferrable electric loads , 2012, 2012 American Control Conference (ACC).

[5]  Sukumar Kamalasadan,et al.  Real-time optimization of distribution system considering interaction between markets , 2013, 2013 IEEE Industry Applications Society Annual Meeting.

[6]  R. Adapa,et al.  A review of selected optimal power flow literature to 1993. I. Nonlinear and quadratic programming approaches , 1999 .

[7]  K. Mani Chandy,et al.  Inverter VAR control for distribution systems with renewables , 2011, 2011 IEEE International Conference on Smart Grid Communications (SmartGridComm).

[8]  Stephen P. Boyd,et al.  Message Passing for Dynamic Network Energy Management , 2012, ArXiv.

[9]  Georgios B. Giannakis,et al.  Distributed Optimal Power Flow for Smart Microgrids , 2012, IEEE Transactions on Smart Grid.

[10]  F. S. Hover,et al.  Convex Models of Distribution System Reconfiguration , 2012, IEEE Transactions on Power Systems.

[11]  Felix F. Wu,et al.  Network Reconfiguration in Distribution Systems for Loss Reduction and Load Balancing , 1989, IEEE Power Engineering Review.

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

[13]  Paul J. Werbos,et al.  Computational Intelligence for the Smart Grid-History, Challenges, and Opportunities , 2011, IEEE Computational Intelligence Magazine.

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

[15]  Gareth Harrison,et al.  A Receding-Horizon OPF for Active Network Management , 2013 .

[16]  Zhengcai Fu,et al.  An improved TS algorithm for loss-minimum reconfiguration in large-scale distribution systems , 2007 .

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

[18]  Francisco D. Galiana,et al.  A survey of the optimal power flow literature , 1991 .

[19]  James A. Momoh,et al.  Smart grid design for efficient and flexible power networks operation and control , 2009, 2009 IEEE/PES Power Systems Conference and Exposition.

[20]  Alberto Bemporad,et al.  Stochastic MPC for real-time market-based optimal power dispatch , 2011, IEEE Conference on Decision and Control and European Control Conference.

[21]  Steven H. Low,et al.  Optimal inverter VAR control in distribution systems with high PV penetration , 2011, 2012 IEEE Power and Energy Society General Meeting.

[22]  R. Adapa,et al.  A review of selected optimal power flow literature to 1993. II. Newton, linear programming and interior point methods , 1999 .

[23]  Joshua A. Taylor,et al.  Conic optimization of electric power systems , 2011 .

[24]  Sukumar Kamalasadan,et al.  Real-time optimal scheduling of smart power distribution systems using integrated receding horizon control and convex conic programming , 2014, 2014 IEEE Industry Application Society Annual Meeting.

[25]  M. E. Baran,et al.  Optimal sizing of capacitors placed on a radial distribution system , 1989 .

[26]  R. C. Dugan,et al.  Distribution System Analysis and the Future Smart Grid , 2011, IEEE Transactions on Industry Applications.

[27]  Yang Wang,et al.  Code generation for receding horizon control , 2010, 2010 IEEE International Symposium on Computer-Aided Control System Design.

[28]  Meysam Doostizadeh,et al.  Day-ahead scheduling of an active distribution network considering energy and reserve markets , 2013 .

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