Abstract
The inclusion and arrangement of protection devices within the LV distribution network often neglected. By exemption of protection devices during network modelling, may result in overestimation of reliability performances. Detail network representation of UK LV residential model is used to assess network reliability performance. The analytical and improved Monte-Carlo Simulation (MCS) approaches are used to estimate system-related reliability indices.

Abstract
Last decade has witnessed the birth and dissemination of microgeneration (MG) in most EU countries. MG growth and diffusion in LV networks are expected to continue in the next decade. At the same time, the interest on energy storage systems (ESS) applications to power systems has been intensifying in the last years, following some major technological achievements that improved ESS abilities and decreased their price. This article analyzes the impacts of MG and ESS dissemination in LV networks' losses. The central goal is to estimate the global impact on the Portuguese LV distribution system. For that purpose, a set of empirical studies was carried out over a set of representative networks, in which different MG and ESS scenarios were considered. The extrapolation of the results to the global LV points out to a loss reduction potential of more than 15%.

Abstract
In the beginning of the Iberian Electricity Market (MIBEL), in 2006, the Portuguese regulator created a new tariff scheme, aiming at responding to the new market competition environment. At the same time, the regulator intended to improve consumers' awareness and incentivize renewables generation. After one decade, this policy may be considered successful, as it led to a good level of transparency (all tariff costs are clear and public) and renewables production had increased considerably. However, this strategy has brought other less positive aspects. One of them is the attractiveness of the tariff system in terms of energy savings. In fact, the test cases present in this article demonstrate that the current tariff scheme does not stimulate energy efficiency. Other complementary studies are performed to illustrate the impact of the tariff structure design on the potential energy savings.

Abstract

Abstract
This paper addresses a critical analysis of the impact of the wind ramp events with unforeseen magnitude in power systems at the very short term, modeling the response of the operational reserve against this type of phenomenon. A multi-objective approach is adopted, and the properties of the Pareto-optimal fronts are analyzed in cost versus risk, represented by a worst scenario of load curtailment. To complete this critical analysis, a study about the usage of the reserve in the event of wind power ramps is performed. A case study is used to compare the numerical results of the models based on stochastic programming and models that take a risk analysis view in the system with high level of wind power. Wind power uncertainty is represented by scenarios qualified by probabilities. The results show that the reliability reserve may not be adequate to accommodate unforeseen wind ramps and therefore the system may be at risk.

Abstract
Short-term load forecasting plays an important role to the operation of electric systems, as a key parameter for planning maintenances and to support the decision making process on the purchase and sale of electric power. A particular case in this respect is the consumption forecasting on special days, which can be a complex task as it presents unusual load behavior, when compared to regular working days. Moreover, its reduced number of samples makes it hard to properly train and validate more complex and nonlinear prediction algorithms. This paper tackles this problem by proposing a new approach to improve the accuracy of the predictions amidst existing special days, employing an Information Theoretic Learning Mean Shift algorithm for pattern discovery, classifying and densifying the available scarce consumption data. The paper describes how this methodology was applied to an electrical load forecasting problem in the northern region of Brazil, improving the previously obtained accuracy held by the power company.