A receding horizon approach for the power flow management with renewable energy and energ storage systems

Optimal operation of energy grids integrated with renewable energy sources (RES) and energy storage systems (ESS) is challenging due to intermittencies in generation and dynamics of the storage. This investigation presents a multi-period alternate current optimal power flow (ACOPF) algorithm for reducing the grid operating cost. The proposed approach uses a receding horizon strategy that solves a non-linear optimization problem during each period by using forecasts and storage dynamics. As a result, the proposed algorithm can optimize the grid operations considering the intermittent renewable generation and storage dynamics. The multi-period ACOPF is illustrated on a Norwegian distribution network with 85 buses and our results illustrate the suitability of the multi-period approach to optimize the grid operations with RES and ESS.

[1]  A. R. Wallace,et al.  Optimal power flow evaluation of distribution network capacity for the connection of distributed generation , 2005 .

[2]  L. Glielmo,et al.  Multi-objective optimization for environmental/economic microgrid scheduling , 2012, 2012 IEEE International Conference on Cyber Technology in Automation, Control, and Intelligent Systems (CYBER).

[3]  Evangelos Rikos,et al.  Use of model predictive control for experimental microgrid optimization , 2014 .

[4]  Luigi Glielmo,et al.  Optimal Power Flow model with energy storage, an extension towards large integration of renewable energy sources. , 2014 .

[5]  Wadaed Uturbey,et al.  Interruptible load management assessment via dynamic optimal power flow , 2003, 2003 IEEE Bologna Power Tech Conference Proceedings,.

[6]  B. J. Cory,et al.  A study of the homogeneous algorithm for dynamic economic dispatch with network constraints and transmission losses , 2000 .

[7]  Hiroshi Sasaki,et al.  Large scale hydrothermal optimal power flow problems based on interior point nonlinear programming , 2000 .

[8]  Haoming Fu.  Online Algorithms and Optimal Offline Algorithms for Dynamic Optimal Power Flow , 2014 .

[9]  Ufuk Topcu,et al.  A simple optimal power flow model with energy storage , 2010, 49th IEEE Conference on Decision and Control (CDC).

[10]  A. G. Expósito,et al.  Power system state estimation : theory and implementation , 2004 .

[11]  Antonio Simoes Costa,et al.  Energy and ancillary service dispatch through dynamic optimal power flow , 2003, 2003 IEEE Bologna Power Tech Conference Proceedings,.

[12]  Aouss Gabash,et al.  Active-Reactive Optimal Power Flow in Distribution Networks With Embedded Generation and Battery Storage , 2012, IEEE Transactions on Power Systems.

[13]  D. Chattopadhyay,et al.  Interruptible load management using optimal power flow analysis , 1996 .

[14]  Felix Wu,et al.  Network Observability: Identification of Observable Islands and Measurement Placement , 1985, IEEE Transactions on Power Apparatus and Systems.

[15]  Ian A. Hiskens,et al.  Model-Predictive Cascade Mitigation in Electric Power Systems With Storage and Renewables—Part I: Theory and Implementation , 2015, IEEE Transactions on Power Systems.

[16]  Ignacio Hernando-Gil,et al.  Optimal Power Flow for Maximizing Network Benefits From Demand-Side Management , 2014, IEEE Transactions on Power Systems.

[17]  Ferial El-Hawary,et al.  Minimum emissions power flow , 1994 .

[18]  M. E. El-Hawary,et al.  The Hydrothermal Optimal Load Flow, A Practical Formulation and Solution Techniques Using Newton's Approach , 1986, IEEE Transactions on Power Systems.

[19]  Steffen Rebennack,et al.  Optimal power flow: a bibliographic survey II , 2012, Energy Systems.

[20]  Ian A. Hiskens,et al.  Model-Predictive Cascade Mitigation in Electric Power Systems With Storage and Renewables—Part II: Case-Study , 2015, IEEE Transactions on Power Systems.

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

[22]  David Macii,et al.  On the Role of Phasor Measurement Units for Distribution System State Estimation , 2014, 2014 IEEE Workshop on Environmental, Energy, and Structural Monitoring Systems Proceedings.

[23]  Evangelos Rikos,et al.  A Model Predictive Control Approach to Microgrid Operation Optimization , 2014, IEEE Transactions on Control Systems Technology.