Incremental cost consensus algorithm in a smart grid environment

In a next generation power system, effective distributed control algorithms could be embedded in distributed controllers to properly allocate electrical power among connected buses autonomously. In this paper, we present a novel approach to solve the economic dispatch problem. By selecting the incremental cost of each generation unit as the consensus variable, the algorithm is able to solve the conventional centralized control problem in a distributed manner. The row-stochastic matrices have been used to indicate the different topologies of distribution systems and their configuration properties, such as convergence speeds. The simulation results of several case studies are provided to verify the algorithm.

[1]  Philip G. Hill,et al.  Power generation , 1927, Journal of the A.I.E.E..

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

[3]  T. P. Hughes,et al.  Networks of Power: Electrification in Western Society, 1880-1930. , 1985 .

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

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

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

[7]  Fan Chung,et al.  Spectral Graph Theory , 1996 .

[8]  G. Sheblé,et al.  Power generation operation and control — 2nd edition , 1996 .

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

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

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

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

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

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

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

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

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

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

[19]  G. Heydt,et al.  Architecture of a smart microgrid distributed operating system , 2011, 2011 IEEE/PES Power Systems Conference and Exposition.