Application of Music Based Harmony Search Algorithm for Transmission Loss Allocation in Electricity Markets

Application of meta-heuristic techniques to engineering optimization problems has proved to be an efficient tool. In transaction based electricity markets transmission losses must be allocated among transactions rather than the individual buses as in case of pool based markets. In this paper an attempt is made to apply Music Based Harmonic Search Algorithm (MBHSA) for the allocation of transmission losses among transactions in electricity markets. Transmission loss can be easily allocated among transactions using the values of transaction coefficients. In the proposed method optimal values of transaction co-efficients are found as an optimization problem using MBHSA. Proposed method is tested with IEEE 24 bus reliability test system with multiple transaction sets and the test results are compared with the existing technique in the literature. The method can also be extended for reactive power loss allocation if reactive power transactions are generated according to the real power transaction amounts.

[1]  P. V. Satyaramesh,et al.  Usage-based transmission loss allocation under open access in deregulated power systems , 2010 .

[2]  R. Haque,et al.  An artificial neural network based transmission loss allocation for bilateral contracts , 2005, Canadian Conference on Electrical and Computer Engineering, 2005..

[3]  Thukaram Dhadbanjan,et al.  Estimation of Least Loss Power Contracts in a Deregulated Environment , 2010 .

[4]  Zong Woo Geem,et al.  A New Heuristic Optimization Algorithm: Harmony Search , 2001, Simul..

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

[6]  F. Galiana,et al.  Allocation of transmission losses to bilateral contracts in a competitive environment , 2000 .

[7]  Garng Huang,et al.  Transaction based power flow analysis for transmission utilization allocation , 2001, 2001 Power Engineering Society Summer Meeting. Conference Proceedings (Cat. No.01CH37262).

[8]  Mowen Lu,et al.  A novel nucleolus-based loss allocation method in bilateral electricity markets , 2006 .

[9]  A. Conejo,et al.  Transmission Loss Allocation: A Comparison of Different Practical Algorithms , 2002, IEEE Power Engineering Review.

[10]  K. Lee,et al.  A new meta-heuristic algorithm for continuous engineering optimization: harmony search theory and practice , 2005 .

[11]  Zong Woo Geem,et al.  Music-Inspired Harmony Search Algorithm , 2009 .

[12]  He Xu,et al.  Harmony Search Optimization Algorithm: Application to a Reconfigurable Mobile Robot Prototype , 2010, Recent Advances In Harmony Search Algorithm.

[13]  Mohammad Shahidehpour,et al.  The IEEE Reliability Test System-1996. A report prepared by the Reliability Test System Task Force of the Application of Probability Methods Subcommittee , 1999 .

[14]  Loi Lei Lai,et al.  Power System Restructuring and Deregulation , 2001 .

[15]  L. Lai.  Power system restructuring and deregulation : trading, perfomance and information technology , 2001 .

[16]  Ali Abur,et al.  A unified transmission loss allocation method , 2007 .

[17]  George Gross,et al.  A physical-flow-based approach to allocating transmission losses in a transaction framework , 2000 .

[18]  Sydulu Maheswarapu,et al.  A Music Based Harmony Search (MBHS) approach to Optimal Power Flow with reactive power loss optimization , 2010, 2010 IEEE International Conference on Power and Energy.

[19]  S. K. Panda,et al.  Improved Harmony Search algorithm based optimal design of the brushless DC wheel motor , 2010, 2010 IEEE International Conference on Sustainable Energy Technologies (ICSET).

[20]  G. K. Deekshit,et al.  Transmission loss allocation in a multiple transaction framework , 2012 .