-Stochastic generation, i.e. electrical power production by an uncontrolled primary energy source, is expected to play an important role in future power systems. A new power system structure is created due to the largescale implementation of this small-scale, distributed, nondispatchable generation; the 'horizontally operated' system. Modelling methodologies that can deal with the operational uncertainty introduced by these power units should be used for analyzing the impact of this generation to the system. In this contribution, the principles for this modelling are presented, based on the decoupling of the single stochastic generator behavior (marginal distribution-stochastic unit capacity) from the concurrent behavior of the stochastic generators (stochastic dependence structure-stochastic system dispatch). Subsequently, the Stochastic Bounds Methodology is applied to model the extreme power contribution of the stochastic generation to the system, based on two new sampling concepts (comonotonicity-countermonotonicity). The application of this methodology to the power system leads to the definition of clusters of positively correlated stochastic generators and the combination of different clusters based on the sampling concepts. The stochastic decomposition and clustering concepts presented in this contribution give the basis for the application of new uncertainty analysis techniques, for the modelling of the stochastic generation in power systems.

Abstract-In this paper it is shown that the Mayr-type arc models can be used to describe the arc behavior before current zero exactly. Based on this analysis the different types of 'modified' Mayr arc models can be explained. As a result of the theory, an improved Mayr-type arc model -with a constant time parameter and a cooling power which is dependent on the electrical power input -is introduced and used to reproduce current zero measurements successfully.

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Abstract-Analytical expressions are derived to gain insight in the operating principles of phase shifting transformers (PSTs) in a highly meshed grid. To this extent, the dc load flow algorithm is adapted to account for such devices. This leads to a linear expression for the relation between PST settings and the active power flow in the lines. Based on these equations, the total transfer capacity (TTC) can be described mathematically, which allows for optimization. Furthermore, the linear least squares method is used to distribute a cross-border transport evenly over the interconnectors. Both criteria are demonstrated by two examples.Index Terms-dc load flow, load flow control, phase shifting transformer, total transfer capacity.