Transmission loss and load flow allocations via genetic algorithm technique

Transmission loss and load flow allocations become important issues under deregulation system. Due to nonlinear nature of power flow, tracing the loss and power flow through the mesh network becomes more complicated. Since the complexity of electricity transmission system, it is not straightforward to determine the contribution of particular generator to a particular line loss and/ or load. This paper will discuss load flow and loss allocation using Genetic Algorithm (GA) technique. GA is one of the optimization techniques that apply natural phenomena, viz. genetic inheritance and Darwinian strive for survival. Transmission loss and load flow allocations problem will be treated as an optimization problem. In this paper, Ward-Hale 6-bus test system will be used to demonstrate the effectiveness of the technique and validated by IEEE 30-bus test system. Comparison with other method is also given.

[1]  John H. Holland,et al.  Adaptation in Natural and Artificial Systems: An Introductory Analysis with Applications to Biology, Control, and Artificial Intelligence , 1992 .

[2]  Randy L. Haupt,et al.  Practical Genetic Algorithms , 1998 .

[3]  Hadi Saadat,et al.  Power System Analysis , 1998 .

[4]  Jen-Hao Teng,et al.  Power flow and loss allocation for deregulated transmission systems , 2005 .

[5]  David E. Goldberg,et al.  Genetic Algorithms in Search Optimization and Machine Learning , 1988 .

[6]  Enrique Acha,et al.  FACTS: Modelling and Simulation in Power Networks , 2004 .

[7]  Sobhy M. Abdelkader Transmission loss allocation in a deregulated electrical energy market , 2006 .

[8]  J. Bialek,et al.  Tracing the generators' output , 1996 .

[9]  Xiaodong Yin,et al.  Investigations On Solving the Load Flow Problem By Genetic Algorithms , 1991 .

[10]  S.A. Soman,et al.  Optimization approach to real power tracing: an application to transmission fixed cost allocation , 2006, IEEE Transactions on Power Systems.

[11]  J. B. Ward,et al.  Digital Computer Solution of Power-Flow Problems [includes discussion] , 1956, Transactions of the American Institute of Electrical Engineers. Part III: Power Apparatus and Systems.

[12]  H. Shareef,et al.  Identification of source to sink relationship in deregulated power systems using artificial neural network , 2007, 2007 International Power Engineering Conference (IPEC 2007).

[13]  Hadi Saadat,et al.  Power Systems Analysis , 2002 .

[14]  Goran Strbac,et al.  Contributions of individual generators to loads and flows , 1997 .