The features of the new electricity market with the presence of many different operators lead to a new interest in the congestion management. The changes to the market-clearing point schedules required by the presence of bottlenecks in the electric grid can be strongly reduced if flexible ac transmission system (FACTS) devices are suitably installed in the transmission system with the aim of redistributing real and reactive power flows. Their optimal setting and operation mode can be determined by the use of customized security-constrained optimal power flow (SCOPF) programs. This paper deals with the use of FACTS devices as control variables in a compact and reduced SCOPF formulation, focusing on the definition of their control regions and on a new procedure implemented to find a global solution without sticking on local minima. The application of the new SCOPF procedure to a real system is also presented.Index Terms-Linear approximation, load flow control, optimization methods, power generation dispatch, power systems.

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

This paper describes a procedure developed by the authors with the aim to evaluate the capability of Medium Voltage (MV) busses to accept power injection from dispersed generators and to support the distribution system operators in facing the growing penetration of dispersed generation, especially due to Renewable Energy Sources (RES).\ud This simple procedure simulates an increasing power injection at every bus of the considered sample and checks the violation of operating limits in order to determine the maximum admissible nodal injection. The procedure is applied to a huge network data set, corresponding to real Italian MV grids and representing a significant subset (6%) of the system. Results presented in this paper could be a robust and statistically significant background for technical and economic considerations about the limits for\ud penetration of dispersed generation in the Italian system

With the introduction of the Power Exchange, one of the most critical issues to be faced by a Transmission System Operator (TSO) is to take into account the transmission constraints in a simplified market model. The zonal approach represents a suitable solution, since its mechanism can be easily understood by all the operators; on the other side, it requires to establish a priori the relevant transmission constraints. However, in a meshed network, this solution results in some problems in the management of the system, mainly because the Transmission Capability (TTC) value is deeply influenced by both demand and generation patterns. In order to face this problem, coupling the clearing process with an on-line TTC evaluation tool would represent the best solution, allowing the full exploitation of the transmission facilities. Since all the methods already\ud proposed in the technical literature are not suitable for on-line applications due to their huge computation time, a new approach is proposed. An Artificial Neural Network (ANN) is used to estimate the TTC in real time: once the proposed model has been trained, it is adopted for a real time update of the TTC between two market areas, with respect to the actual market results, in order to increase the market efficiency and to reduce the associated congestion costs

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