Distributed Multiple Agent System Based Online Optimal Reactive Power Control for Smart Grids

Under high penetration of renewable energy resources, more and more reactive power control devices are integrated into power grids. The large-scale deployment of these devices requires upgrading existing reactive power control solutions. To improve energy efficiency and voltage profiles of the power grids under different operating conditions, this paper proposes a fully distributed multiple agent system based optimal reactive control solution. To update its control setting, a reactive controller only needs information measured locally or obtained from its neighboring buses. The updating rules of the subgradient based algorithm are derived under mild assumptions. The solution is able to provide comparable steady state performance as that of centralized optimization solutions. Due to the simplicity of communication topology and the reduced amount of data to process, the solution can provide timely response to changes of operating conditions. Simulation studies with power systems of different sizes demonstrate the effectiveness of proposed control solution.

[1]  Naum Zuselevich Shor,et al.  Minimization Methods for Non-Differentiable Functions , 1985, Springer Series in Computational Mathematics.

[2]  A. Gomez-Exposito,et al.  Finding Improved Local Minima of Power System Optimization Problems by Interior-Point Methods , 2002, IEEE Power Engineering Review.

[3]  S. Granville.  Optimal reactive dispatch through interior point methods , 1994 .

[4]  Fang Liu,et al.  A hybrid genetic algorithm-interior point method for optimal reactive power flow , 2006, IEEE Transactions on Power Systems.

[5]  Xin Wang,et al.  Distributed Subgradient-Based Coordination of Multiple Renewable Generators in a Microgrid , 2014, IEEE Transactions on Power Systems.

[6]  Wei Zhang,et al.  Multiagent-Based Reinforcement Learning for Optimal Reactive Power Dispatch , 2012, IEEE Transactions on Systems, Man, and Cybernetics, Part C (Applications and Reviews).

[7]  M. J. H. Sterling,et al.  Optimum Dispatch of Active and Reactive Generation by Quadratic Programming , 1973 .

[8]  Takeshi Nagata,et al.  A multi-agent based distributed reactive power control method , 2009 .

[9]  Wenxin Liu,et al.  Novel Multiagent Based Load Restoration Algorithm for Microgrids , 2011, IEEE Transactions on Smart Grid.

[10]  Alfredo Vaccaro,et al.  A Decentralized and Cooperative Architecture for Optimal Voltage Regulation in Smart Grids , 2011, IEEE Transactions on Industrial Electronics.

[11]  M. Innorta,et al.  Feasibility Study for an Energy Management System Intelligent Alarm Processor , 1986, IEEE Power Engineering Review.

[12]  Wenxin Liu,et al.  Stable Multi-Agent-Based Load Shedding Algorithm for Power Systems , 2011, IEEE Transactions on Power Systems.

[13]  B. Bhattacharyya,et al.  Sensitivity based Evolutionary algorithms for Reactive Power Dispatch , 2009, 2009 International Conference on Power Systems.

[14]  B. Zhao,et al.  A multiagent-based particle swarm optimization approach for optimal reactive power dispatch , 2005, IEEE Transactions on Power Systems.

[15]  T. Kulworawanichpong,et al.  Multi-Agent Based Optimal Power Flow Solution , 2012, 2012 Asia-Pacific Power and Energy Engineering Conference.

[16]  A. Augugliaro,et al.  Voltage regulation and power losses minimization in automated distribution networks by an evolutionary multiobjective approach , 2004, IEEE Transactions on Power Systems.

[17]  L.C.P. da Suva,et al.  A method for transmission loss allocation based on sensitivity theory , 2006, 2006 IEEE Power Engineering Society General Meeting.

[18]  Barbara Messing,et al.  An Introduction to MultiAgent Systems , 2002, Künstliche Intell..

[19]  D. Kirschen,et al.  A Survey of Frequency and Voltage Control Ancillary Services—Part I: Technical Features , 2007, IEEE Transactions on Power Systems.

[20]  Felix F. Wu,et al.  A Two-stage Approach To Solving Large-scale Optimal Power Flows , 1979 .

[21]  Yong Zhang,et al.  A Real-time Hierarchical and Distributed Control Scheme for Reactive Power Optimization in Multi-area Power Systems , 2005, 2005 IEEE/PES Transmission & Distribution Conference & Exposition: Asia and Pacific.

[22]  H. Yoshida,et al.  A particle swarm optimization for reactive power and voltage control considering voltage security assessment , 1999, 2001 IEEE Power Engineering Society Winter Meeting. Conference Proceedings (Cat. No.01CH37194).

[23]  Sergio Barbarossa,et al.  Decentralized Maximum-Likelihood Estimation for Sensor Networks Composed of Nonlinearly Coupled Dynamical Systems , 2006, IEEE Transactions on Signal Processing.

[24]  C. M. Shen,et al.  Power-system load scheduling with security constraints using dual linear programming , 1970 .

[25]  G. Lambert-Torres,et al.  Increasing the loadability of power systems through optimal-local-control actions , 2004, IEEE Transactions on Power Systems.

[26]  T. Nagata,et al.  A multi-agent based distributed reactive power control method , 2009, 2009 IEEE Power & Energy Society General Meeting.

[27]  Michael Chertkov,et al.  Options for Control of Reactive Power by Distributed Photovoltaic Generators , 2010, Proceedings of the IEEE.

[28]  James H. Taylor,et al.  On-line optimal reactive power flow by energy loss minimization , 1996, Proceedings of 35th IEEE Conference on Decision and Control.

[29]  K. Vaisakh,et al.  Optimal reactive power allocation using PSO-DV hybrid algorithm , 2008, 2008 Annual IEEE India Conference.

[30]  K. C. Mamandur,et al.  Optimal Control of Reactive Power flow for Improvements in Voltage Profiles and for Real Power Loss Minimization , 1981, IEEE Transactions on Power Apparatus and Systems.

[31]  S. Barbarossa.  SELF-ORGANIZING SENSOR NETWORKS WITH INFORMATION PROPAGATION BASED ON MUTUAL COUPLING OF DYNAMIC SYSTEMS , 2005 .

[32]  S. de la Torre,et al.  On the convexity of the system loss function , 2005, IEEE Transactions on Power Systems.

[33]  Asuman E. Ozdaglar,et al.  Distributed Subgradient Methods for Convex Optimization Over Random Networks , 2011, IEEE Transactions on Automatic Control.

[34]  Shin-Yeu Lin,et al.  Distributed Optimal Power Flow With Discrete Control Variables of Large Distributed Power Systems , 2008, IEEE Transactions on Power Systems.

[35]  M. Moallem,et al.  Multi-agent control system for real-time adaptive VVO/CVR in Smart Substation , 2012, 2012 IEEE Electrical Power and Energy Conference.