Generation Reliability Evaluation in Deregulated Power Systems Using Game Theory and Neural Networks


Deregulation policy has caused some changes in the concepts of power systems reliability assessment and enhancement. In the present research, generation reliability is considered, and a method for its assessment is proposed using Game Theory (GT) and Neural Networks (NN). Also, due to the stochastic behavior of power markets and generators’ forced outages, Monte Carlo Simulation (MCS) is used for reliability evaluation. Generation reliability focuses merely on the interaction between generation complex and load. Therefore, in the research, based on the behavior of players in the market and using GT, two outcomes are considered: cooperation and non-cooperation. The proposed method is assessed on IEEE-Reliability Test System with satisfactory results. Loss of Load Expectation (LOLE) is used as the reliability index and the results show generation reliability in cooperation market is better than non-cooperation outcome.

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H. Haroonabadi and H. Barati, "Generation Reliability Evaluation in Deregulated Power Systems Using Game Theory and Neural Networks," Smart Grid and Renewable Energy, Vol. 3 No. 2, 2012, pp. 89-95. doi: 10.4236/sgre.2012.32013.

Conflicts of Interest

The authors declare no conflicts of interest.


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