Optimal Control in a Cooperative Network of Smart Power Grids

The possibility to store energy, to exchange power and information on demand and production among grids allows us to achieve an active distribution which is of major interest for cooperative smart power grids, that are grids which can forecast demand and production and are able to exchange power in order to enhance the quality of the service. In this paper, a model to support optimal decisions in a network of cooperative grids is formalized as an original discrete and centralized problem here defined as cooperative network of smart power grids (CNSPG) problem. In the CNSPG problem, the control variables are the instantaneous flows of power in the network of grids, which can be obtained from the solution of a linear quadratic Gaussian problem on a fixed time horizon. A simple case study showing the enhancement which may be obtained from the introduction of direct connections among microgrids according to a lattice network is shown and finally discussed.

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

[2]  Debora Coll-Mayor,et al.  Future intelligent power grids: Analysis of the vision in the European Union and the United States , 2007 .

[3]  A. T. Holen,et al.  Operation planning of hydrogen storage connected to wind power operating in a power market , 2006, IEEE Transactions on Energy Conversion.

[4]  A. T. Holen,et al.  A Norwegian case study on the production of hydrogen from wind power , 2007 .

[5]  M.P.F. Hommelberg,et al.  Distributed Control Concepts using Multi-Agent technology and Automatic Markets: An indispensable feature of smart power grids , 2007, 2007 IEEE Power Engineering Society General Meeting.

[6]  John S. Anagnostopoulos,et al.  Pumping station design for a pumped-storage wind-hydro power plant , 2007 .

[7]  T R Ender,et al.  A Framework for Portfolio Management of Renewable Hybrid Energy Sources , 2008, IEEE Systems Journal.

[8]  Shrisha Rao,et al.  Simulation and Pricing Mechanism Analysis of a Solar-Powered Electrical Microgrid , 2010, IEEE Systems Journal.

[9]  J. R. McDonald,et al.  Adaptive intelligent power systems: Active distribution networks☆ , 2008 .

[10]  Carlo Bruni,et al.  Some results about the optimal LQG tracking problem , 2001 .

[11]  Ian A. Hiskens,et al.  Operation and Control of Electrical Power Systems , 2008 .

[12]  Magnus Korpaas,et al.  Operation and sizing of energy storage for wind power plants in a market system , 2003 .

[13]  K. C. Divya,et al.  Battery Energy Storage Technology for power systems-An overview , 2009 .

[14]  Anna Scaglione,et al.  Generating Statistically Correct Random Topologies for Testing Smart Grid Communication and Control Networks , 2010, IEEE Transactions on Smart Grid.

[15]  Federico Silvestro,et al.  Short-Term Scheduling and Control of Active Distribution Systems With High Penetration of Renewable Resources , 2010, IEEE Systems Journal.

[16]  Manuel A. Matos,et al.  Assessing the contribution of microgrids to the reliability of distribution networks , 2009 .

[17]  Anurag K. Srivastava,et al.  Controls for microgrids with storage: Review, challenges, and research needs , 2010 .

[18]  John D. Kueck,et al.  Distribution System of the Future , 2003 .

[19]  Michela Robba,et al.  A Dynamic Decision Model for the Real-Time Control of Hybrid Renewable Energy Production Systems , 2010, IEEE Systems Journal.

[20]  José L. Bernal-Agustín,et al.  Hourly energy management for grid-connected wind–hydrogen systems , 2008 .

[21]  P. Ramanathan A Statcom-Control Scheme for Grid Connected Wind Energy System for Power Quality Improvement , 2014 .

[22]  P. Whittle Risk-Sensitive Optimal Control , 1990 .