Designing reward and penalty scheme in performancebased regulation for electric distribution companies


A reward and penalty scheme (RPS) in performance-based mostly regulation (PBR) penalises companies for providing poor reliability and rewards them for providing smart reliability. During this study, an algorithm is presented to get the parameters of RPS for every electric company by using data envelopment analysis (DEA) and fuzzy c-means clustering (FCM). This algorithm is based on system average interruption length index (SAIDI) and customers?? worth of interruptions. FCM algorithm is applied to search out similar distribution firms and cluster corporations into completely different clusters. The most effective performer in each cluster is utilised as a benchmark for alternative corporations and DEA is used to set a top quality target for every electrical distribution company. The performance of the proposed algorithm is demonstrated in a case study to design RPS for Iranian electricity distribution corporations. The results of the algorithm embody DEA efficiency score, parameters of RPS and money risk assessment.

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