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In this paper, we analysed the growing penetration of generating units from renewable energy sources in transmission power systems. Among the possible effects of the interaction of distributed generation (DG) with transmission systems, we considered the abnormal operating conditions caused by short circuits in the transmission systems and the resulting voltage sags that occur in the network. A systematic method is presented for analysing the voltage sag behaviour of any transmission system in which large DG units are connected to the transmission system by means of High Voltage/Medium Voltage (HV/MV) stations. The method proposed for obtaining the voltage sags is the fault position method (FPM), from which we derived a graphical visualization of the during-fault voltage (DFV) matrix as a valuable tool to obtain an immediate measure of the propagation of voltage sags in the network. The results obtained were based on a portion of a real transmission system. The system that we considered is an actual portion of the Italian transmission system, and all of the quantities we used were obtained from the data of the Transmission system operator (TSO). [ABSTRACT FROM AUTHOR]

A new short-term probabilistic forecasting method is proposed to predict the probability density function of the hourly active power generated by a photovoltaic system. Firstly, the probability density function of the hourly clearness index is forecasted making use of a Bayesian auto regressive time series model; the model takes into account the dependence of the solar radiation on some meteorological variables, such as the cloud cover and humidity. Then, a Monte Carlo simulation procedure is used to evaluate the predictive probability density function of the hourly active power by applying the photovoltaic system model to the random sampling of the clearness index distribution. A numerical application demonstrates the effectiveness and advantages of the proposed forecasting method. [ABSTRACT FROM AUTHOR]

This paper presents a probabilistic model for supporting the process of decision making about the value of new lighting systems in existing road tunnels when some data and parameters are affected by uncertainty. The proposed model, which we have called Probabilistic Energy Screening of Tunnel (PrEST), accounts for both the technical performance and the economic objectives of the new lighting systems. The technical performance is described on an adequate (x, y) plane that was defined by two indices. The first index measured the consumption of electricity per kilometre of tunnel lengths; the second index measured the performance of the lighting systems per unit of illuminated area. The economic results were measured by the net present value of the savings and by the payback period. Both the terms account for initial capital investments, energy and maintenance costs. PrEST was applied to two real road tunnels in service in Italy showing that the statistics of the results can support a final decision in function of the business strategy. [ABSTRACT FROM AUTHOR]