Abstract
Acoustic emission monitoring is often used in the diagnosis of electrical and mechanical incipient faults in high voltage apparatus. A great number of methods are available for condition monitoring and diagnosis of power transformer insulation, but only a few can take direct measurements inside a transformer. Partial discharges are a major source of insulation failure in power transformers and their detection can be achieved through the associated acoustic emissions. This paper reports the development of two sensing head configurations based on extrinsic and intrinsic fiber Fabry-Perot interferometers for the detection of incipient faults in oil-filled power transformers. These sensors can be placed inside the transformer tank without affecting the insulation integrity, improving fault detection and location. The performances of the sensing heads are characterized and compared with the situations where it operates in air, water and oil and promising results are obtained, which will allow the industrial development of practical solutions.

Abstract
This work presents a model to evaluate the Distribution System Dynamic De-adaptation respecting its planning for a given period of Tariff Control. The starting point for modeling is brought about by the results from a multi-criteria method based on Fuzzy Dynamic Programming and on Analytic Hierarchy Processes applied in a mid/short-term horizon (stage 1). Then, the decision-making activities using the Hierarchy Analytical Processes will allow defining, for a Control of System De-adaptation (stage 2). a Vector to evaluate the System Dynamic Adaptation. It is directly associated to an eventual series of inbalances that take place during its evolution.

Abstract
This paper presents a new and efficient methodology for distribution network reconfiguration integrated with optimal power flow (OPF) based on a Benders decomposition approach. The objective minimizes power losses, load balancing among feeders, and is subject to constraints: capacity limit of branches, minimum and maximum power limits of substations or distributed generators, minimum deviation of bus voltages, and radial optimal operation of networks. A specific approach of the Generalized Benders decomposition algorithm is applied to solve the problem. The formulation can be embedded under two stages: the first one is the Master problem and is formulated as a mixed integer nonlinear programming problem. This stage determines the radial topology of the distribution network. The second stage is the Slave problem and is formulated as a nonlinear programming problem. This stage is used to determine the feasibility of the Master problem solution by means of an OPF and provides information to formulate the linear Benders cuts that connect both problems. The model is programmed in the General Algebraic Modeling System. The effectiveness of the proposal is demonstrated through three examples extracted from the literature.

Abstract
The integration of large shares of wind generation in power systems requires the development of new algorithms and forecasting tools for making decisions in the operational domain taking into account wind generation forecast uncertainties. One of these decisions regards operating reserve requirements to meet load and wind variations. The aim of this paper is therefore to address this issue from a risk evaluation perspective, showing that it is possible to describe the consequences of each possible reserve level through a set of risk indices useful for decision-making. The new reserve management tool described in this paper is intended to support the Transmission System Operator (TSO) in defining on-line the operating reserve needs for the daily and intraday markets. Decision strategies like setting an acceptable risk level or finding a compromise between economic issues and the risk of loss of load are explored. A case-study based on the Portuguese power system demonstrates the usefulness and efficiency of the tool.

Abstract
Reserve definition is a compromise between economic issues (additional capacity costs) and reliability (risk of loss of load due to outages of the generators), generally approached by deterministic criteria (e.g. the percentage rule defined by UCTE in Europe) and probabilistic methods like PJM (Pennsylvania-New Jersey, Maryland) and its enhancements, based on the concept of risk. With wind power generation increasing in power systems worldwide, these operational issues gain a renewed interest due to the volatile nature of this kind of energy. The aim of this paper is therefore to address this issue from a risk evaluation point of view, showing that it is possible to extend classical probabilistic methods to this new situation, by introducing a detailed Markov model of wind parks that accounts both for machine failures and different wind power levels. This evaluation, where wind generation fluctuation and uncertainty is included, can be helpful for transmission system operators (TSO). when defining the reserve requirements for the next hours. In fact, the results obtained for the risk can be used by TSO to check if the reserve levels that results from traditional deterministic rules are acceptable or need to be increased.

Abstract
This paper presents an application of probabilistic methodologies to evaluate the reserve requirements of generating systems with a large penetration of renewable energy sources. The idea is to investigate the behavior of reliability indices, including those from the well-being analysis, when the major portion of the renewable sources comes from wind power and other intermittent sources. A new simulation process to address operating reserve adequacy is introduced, and the correspondent reliability indices are observed. Case Studies on the Portuguese and Spanish generating systems are presented and discussed.