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A problem of concern in the deregulated electricity market is to obtain a global power quality (PQ) index for the supply and load side to estimate the cost of PQ in order to include it in the contracts between customers and utility companies. Existing PQ indices are usually isolated and lack the cost impact of bad PQ. This study presents an intelligent method based on artificial neural network (ANN) and fuzzy logic to obtain a quantitative global index for PQ evaluation and pricing in competitive electricity market. Taking into account the cost of PQ phenomena with their relative weights in this index, it can be used as a PQ measure in electricity tariffs by utility companies. Although individual cost assignments used in this study are subject to approximation, once the assignments are made, the calculation is consistent and gives a useful and unique measure of quality of electricity for both supply side and customer side. The proposed algorithm has been implemented on real measured data of a distribution network. The results show the capability of this method to obtain an accurate measure for PQ evaluation and pricing.