In a zonal market, the transmission system operator (TSO) has to compute the transfer limits among areas in advance (weeks or months) with respect to the day-ahead market session. The computation of such limits is usually made starting from some reference scenarios: this choice is arbitrary and has a strong influence on the results of the market. In this paper, a new probabilistic approach is developed to reduce such arbitrariness. A Monte Carlo method is applied to sample many different reference scenarios (in terms of generation patterns) to be adopted for the total transfer capacity (TTC) computation. Eventually, the probability density function of the TTC values is built. The proposed procedure allows the TSO to evaluate, for each possible choice of the TTC limit among areas, the maximum probability of congestion in a market framework, thus selecting the limit corresponding to the acceptable risk level. The new methodology is applied to the Italian system
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Berizzi et al. (2007) studied this question.
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