Abstract
This study presents an integrated approach for reliability planning and risk estimation in active distribution systems. By incorporating the use of accurate reliability equivalents for different medium voltage/low voltage networks and load subsectors, a probabilistic methodology is proposed to capture both power quality and reliability aspects in power system planning, which potentially avoids the underestimation of system's performance at bulk supply points. A 'time to restore supply' concept, based on security of supply legislation, is introduced to quantify the effect of different network functionalities such as the use of backup supply or automatic/manual reconfiguration schemes. The range of annual reliability indices reported by 14 network operators in the UK is also used for the validation of reliability results, which allows estimating the risk of interruption times above the regulator-imposed limits. Accordingly, conventional reliability assessment procedures are extended in this study by analysing a meshed urban distribution network through the application of a time-sequential Monte Carlo simulation. The proposed methodology also acknowledges the use of time-varying fault probabilities and empirical load profiles for a more realistic estimation of customer interruptions. A decision-making approach is shown by assessing the impact of several network actions on the accuracy of reliability performance results.

Abstract
The estimation of the tail index is a central topic in extreme value analysis. We consider a geometric-type estimator for the tail index and study its asymptotic properties. We propose here two asymptotic equivalent bias-corrected geometric-type estimators and establish the corresponding asymptotic behaviour. We also apply the suggested estimators to construct asymptotic confidence intervals for this tail parameter. Some simulations in order to illustrate the finite sample behaviour of the proposed estimators are provided.

Abstract
This paper presents a modified negative selection algorithm for the diagnosis of disturbance in distribution electrical systems. This study analyzes voltage disturbances and high-impedance faults, based on three phase current and voltage electric measures, which are obtained at the substations. The principal application is to support operation decision aid during faults, as well as to supervise the protection system. To evaluate the performance of the proposed method, simulations were executed using the EMTP software for a distribution test system containing 134 bus. The results obtained were compared with the specialized literature.

Abstract
This paper reports the research that was developed to predict biding curves submitted by generation players to the Market Operator of the Iberian Electricity Market. In this scope, we used a data set based on publicly available information from the website of the Market Operator to develop a two-step ANN prediction model. The first step involves the prediction of the amount of energy bidden at zero price and the second ANN predicts the parameters of the equation of the line that better approximates the remaining bid curve. The tests were done using information of a large generation player but this approach can be replicated to other players so that the individual predicted curves can be composed in order to obtain the aggregated selling curve for each hour of the next day.

Abstract
Load profiles are a crucial tool for power system planning and operation, and also in several operations of electricity markets. This article proposes a new methodology for the determination of load profiles based on a two-step approach. The first phase employs a neural network autoencoder to reduce the dimensionality of the input vectors. The second phase is a clustering process based on the Kohonen Self- Organizing Maps, to identify cohesive consumers' classes. The implemented approach produces classes based on load diagrams and, simultaneously, a class identification based on consumers' billing data.

Abstract
The operation of remote and isolated or islanded power systems is often very challenging because of their small system inertia. Moreover, economic and environmental pressure has led to an increasing renewable power penetration, particularly in wind generation and solar photovoltaics (PV). Simultaneously, significant technological progress has been made in terms of control capability of grid assets [generators, controllable loads such as electric vehicles (EVs), and energy storage systems], mostly exploiting the capabilities of power ?electronics. In this context, several advanced control solutions can be implemented, supporting and improving the robustness of the operation in terms of fast frequency and voltage control responses. In this article, the Portuguese islands are taken as a case study. Within the Madeira archipelago (Porto Santo and Madeira islands), two approaches were envisioned. For Porto Santo Island, the main goal is the sizing of a flywheel energy storage system (FESS) to avoid frequency stability problems. For Madeira Island, the objective relies on the exploitation of hydro resources through the quantification of the technical benefits resulting from variable speed hydro pumping stations that are able to provide primary frequency regulation services in the pump operation mode. In addition, this article also addresses the benefits of introducing EVs in Flores Island in the Azores Archipelago. Finally, to support the development of innovative technological solutions for this type of power system, a laboratory setup based on scaled test systems was also set up and is described. A set of applications was specifically developed for such autonomous power systems. The laboratorial infrastructure allowed the testing of ?solutions and prototypes for hardware and software modules related to those applications. © 2013 IEEE.