A Cyber-Physical Systems Approach for Implementing the Receding Horizon Optimal Power Flow in Smart Grids

Two major challenges in securing reliable Optimal Power Flow (OPF) operations are: (i) fluctuations induced due to renewable generators and energy demand, and (ii) interaction and interoperability among the different entities. Addressing these issues requires handling both physical (e.g., power flows) and cyber aspects (computing and communication) of the energy grids, i.e, a cyber-physical systems (CPS) approach is necessitated. First, this investigation proposes a receding horizon control (RHC) based approach for solving OPF to deal with the uncertainties. It uses forecasts on renewable generation and demand and an optimization model solving a predictive control problem to secure energy balance while meeting the network constraints. Second, to handle the interoperability issues, a middleware using common information model (CIM) for exchanging information among applications and the associated profiles are presented. CIM profiles modelling various components and aspects of the RHC based OPF is proposed. In addition, a middleware architecture and services to collect information is discussed. The proposed CPS approach is illustrated in a distribution grid in Steinkjer, Norway having 85 nodes, 700 customers, three hydrogenerators, and various industrial loads. Our results demonstrate the benefits of CPS approach to implement OPF addressing also the interoperability issues.

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

[2]  Ivar Jacobson,et al.  The unified modeling language reference manual , 2010 .

[3]  A. Bose,et al.  GridStat: A Flexible QoS-Managed Data Dissemination Framework for the Power Grid , 2009, IEEE Transactions on Power Delivery.

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

[5]  George J. Pappas,et al.  Smart building: a private cyber-physical system approach , 2015, SWEC@CPSWeek.

[6]  Minyi Guo,et al.  Scheduling Co-Design for Reliability and Energy in Cyber-Physical Systems , 2013, IEEE Transactions on Emerging Topics in Computing.

[7]  Rushikesh K. Joshi,et al.  CIM-Based Connectivity Model for Bus-Branch Topology Extraction and Exchange , 2011, IEEE Transactions on Smart Grid.

[8]  Ahmed Yousuf Saber,et al.  Efficient Utilization of Renewable Energy Sources by Gridable Vehicles in Cyber-Physical Energy Systems , 2010, IEEE Systems Journal.

[9]  Gareth A. Taylor,et al.  Adopting the IEC Common Information Model to Enable Smart Grid Interoperability and Knowledge Representation Processes , 2014 .

[10]  Ankush Sharma,et al.  An Extension of Common Information Model for Power System Multiarea State Estimation , 2017, IEEE Systems Journal.

[11]  Yijia Cao,et al.  Cyber-physical electrical energy systems: challenges and issues , 2015 .

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

[13]  V. S. K. Murthy Balijepalli,et al.  Enablement of Consumer-Oriented Interoperable Systems With Integration of CIM and Green Button Standards , 2013, IEEE Systems Journal.

[14]  Pierluigi Siano,et al.  New Trends in Intelligent Energy Systems–An Industrial Electronics Point of View , 2015, IEEE Transactions on Industrial Electronics.

[15]  José-Fernán Martínez,et al.  Middleware Architectures for the Smart Grid: Survey and Challenges in the Foreseeable Future , 2013 .

[16]  Luigi Glielmo,et al.  A receding horizon approach for the power flow management with renewable energy and energ storage systems , 2015, 2015 AEIT International Annual Conference (AEIT).

[17]  Xiaofeng Wang,et al.  CIM extensions to electrical distribution and CIM XML for the IEEE radial test feeders , 2003 .

[18]  Alfredo Vaccaro,et al.  A Decentralized and Proactive Architecture based on the Cyber Physical System Paradigm for Smart Transmission Grids Modelling, Monitoring and Control , 2016 .

[19]  Siddharth Sridhar,et al.  Cyber–Physical System Security for the Electric Power Grid , 2012, Proceedings of the IEEE.

[20]  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.

[21]  David Villa,et al.  A dynamically reconfigurable architecture for smart grids , 2011, IEEE Transactions on Consumer Electronics.