A new graph theory based loss allocation framework for bilateral power market using diakoptics

Abstract Deregulation and privatization of power market worldwide has forced to identify the different ancillary services and the service providers so that all the services can be priced properly. Active power loss is a component that can never be avoided and constitutes a considerable part of economy. Hence, identification of the sources of active power loss is very important. In deregulated power market bilateral power trading plays a very important role where the amount of power and the flow path between the transacting generators and loads are fixed beforehand. But the power flow rarely follows contracted path, it flows according to physical property of the network. Graph theory based loss allocation methods are based on power flow paths and hence are more reliable. But proper transaction based power flow is not available and it makes graph theory based loss allocation for bilateral market a complex task. Present paper applies diakoptics algorithm to find out the loop flows that is the deviation from contracted path for each bilateral transaction which in turn allows finding out the loss allocated to any transaction. Diakoptics is a general concept in which larger problems are solved by dividing the larger problem into smaller problems and then finding out the overall solution by considering the solutions of each smaller problem together. The proposed method is applied to different test systems and results are discussed in detail.

[1]  G.T. Heydt,et al.  Modification to Contribution Factor Formula for Unscheduled Flows , 2008, IEEE Transactions on Power Systems.

[2]  Ying Yu,et al.  A Reachability Matrix Based Power Flow Tracing Method for Transmission Loss Allocation , 2013, 2013 7th Asia Modelling Symposium.

[3]  S.M. Abdelkader Transmission Loss Allocation Through Complex Power Flow Tracing , 2007, IEEE Transactions on Power Systems.

[4]  S. Cvijic,et al.  Optimal clustering for efficient computations of contingency effects in large regional power systems , 2012, 2012 IEEE Power and Energy Society General Meeting.

[5]  Rao Liu,et al.  Transmission Loss Allocation Based on Circuit Theories and Orthogonal Projection , 2009, IEEE Transactions on Power Systems.

[6]  Antonio J. Conejo,et al.  Z-Bus Loss Allocation , 2001 .

[7]  Marija D. Ilic,et al.  Part I: A New Framework for Modeling and Tracing of Bilateral Transactions and the Corresponding Loop Flows in Multi-Control Area Power Networks , 2014, IEEE Transactions on Power Systems.

[8]  S. Sivanagaraju,et al.  Power flow tracing by graph method using BFS technique , 2012, 2012 International Conference on Advances in Power Conversion and Energy Technologies (APCET).

[9]  M. Ilic,et al.  A graph-theoretic approach to modeling network effects of phase shifters on active power loop flows , 2012, 2012 North American Power Symposium (NAPS).

[10]  E. Bompard,et al.  Modeling Bilateral Electricity Markets: A Complex Network Approach , 2008, IEEE Transactions on Power Systems.

[11]  Fushuan Wen,et al.  Bilateral transaction bargaining between independent utilities under incomplete information , 2001 .

[12]  S M Abdelkader Characterization of Transmission Losses , 2011, IEEE Transactions on Power Systems.

[13]  Haili Song,et al.  Nash Equilibrium Bidding Strategies in a Bilateral Electricity Market , 2002, IEEE Power Engineering Review.

[14]  H. H. Happ,et al.  Piecewise methods and applications to power systems , 1980 .

[15]  A. Gomez Exposito,et al.  Fair allocation of transmission power losses , 2000 .

[16]  Janusz Bialek,et al.  Topological generation and load distribution factors for supplement charge allocation in transmission open access , 1997 .

[17]  Marija D. Ilic,et al.  Area-level reduction of wheeling loop flows in regional power networks , 2012, 2012 3rd IEEE PES Innovative Smart Grid Technologies Europe (ISGT Europe).

[18]  Wenyuan Li,et al.  Analytical model and algorithm for tracing active power flow based on extended incidence matrix , 2009 .