Convergence Analysis of the Incremental Cost Consensus Algorithm Under Different Communication Network Topologies in a Smart Grid

In a smart grid, effective distributed control algorithms could be embedded in distributed controllers to properly allocate electrical power among connected buses autonomously. By selecting the incremental cost of each generation unit as the consensus variable, the incremental cost consensus (ICC) algorithm is able to solve the conventional centralized economic dispatch problem in a distributed manner. The mathematical formulation of the algorithm has been presented in this paper. The results of several case studies have also been presented to show that the difference between network topologies will influence the convergence rate of the ICC algorithm.

[1]  Javad Lavaei,et al.  On quantized consensus by means of gossip algorithm - Part II: Convergence time , 2009, 2009 American Control Conference.

[2]  R. Srikant,et al.  Quantized Consensus , 2006, 2006 IEEE International Symposium on Information Theory.

[3]  A. Gibbons Algorithmic Graph Theory , 1985 .

[4]  Randal W. Beard,et al.  Distributed Consensus in Multi-vehicle Cooperative Control - Theory and Applications , 2007, Communications and Control Engineering.

[5]  Zwe-Lee Gaing,et al.  Particle swarm optimization to solving the economic dispatch considering the generator constraints , 2003 .

[6]  Seif Haridi,et al.  Distributed Algorithms , 1992, Lecture Notes in Computer Science.

[7]  Anastasios G. Bakirtzis,et al.  Genetic algorithm solution to the economic dispatch problem , 1994 .

[8]  A Q Huang,et al.  The Future Renewable Electric Energy Delivery and Management (FREEDM) System: The Energy Internet , 2011, Proceedings of the IEEE.

[9]  Richard M. Murray,et al.  Consensus problems in networks of agents with switching topology and time-delays , 2004, IEEE Transactions on Automatic Control.

[10]  Mo-Yuen Chow,et al.  Networked Control System: Overview and Research Trends , 2010, IEEE Transactions on Industrial Electronics.

[11]  Mo-Yuen Chow,et al.  Incremental cost consensus algorithm in a smart grid environment , 2011, 2011 IEEE Power and Energy Society General Meeting.

[12]  Reza Olfati-Saber,et al.  Consensus and Cooperation in Networked Multi-Agent Systems , 2007, Proceedings of the IEEE.

[13]  Geir E. Dullerud,et al.  Distributed control design for spatially interconnected systems , 2003, IEEE Trans. Autom. Control..

[14]  E.M. Atkins,et al.  A survey of consensus problems in multi-agent coordination , 2005, Proceedings of the 2005, American Control Conference, 2005..

[15]  G. L. Viviani,et al.  Hierarchical Economic Dispatch for Piecewise Quadratic Cost Functions , 1984, IEEE Transactions on Power Apparatus and Systems.

[16]  Dick Duffey,et al.  Power Generation , 1932, Transactions of the American Institute of Electrical Engineers.

[17]  L. Conradt,et al.  Consensus decision making in animals. , 2005, Trends in ecology & evolution.

[18]  John N. Tsitsiklis,et al.  Parallel and distributed computation , 1989 .

[19]  Richard M. Murray,et al.  INFORMATION FLOW AND COOPERATIVE CONTROL OF VEHICLE FORMATIONS , 2002 .

[20]  Jong-Bae Park,et al.  An Improved Particle Swarm Optimization for Nonconvex Economic Dispatch Problems , 2010 .

[21]  Jong-Bae Park,et al.  An Improved Particle Swarm Optimization for Nonconvex Economic Dispatch Problems , 2010, IEEE Transactions on Power Systems.