Abstract
Combining conventional and unconventional generations with hard forecasting properties and consumption variability has made the task of fitting large amounts of wind generation into unit commitment procedures very challenging. In this context, massive integration of electric vehicles in the electric systems, is expected. This paper aims at evaluating the adequacy of a generating system taking into account the electric vehicles and high wind power integration level in its energy mix. This study was conducted on the European project MERGE framework, and the results have shown that the generating system evaluated is reliable. Nevertheless, the simulations carried out for scenarios with adverse weather conditions (dry years) have revealed specific circumstances that might jeopardize the system adequacy. © 2014 IEEE.

Abstract
This paper presents a new algorithm to estimate the optimal importance sampling (IS) probability distribution in generating capacity reliability (GCR) problems. The proposed approach results from a combination of the cross-entropy (CE) concepts with the standard analytical GCR assessment. A mathematical analysis of the CE equations is carried out to demonstrate that the optimal change of measure or distortion can be obtained by simply dividing the annualized GCR indices for two different configurations of the generating system. Under these hypotheses, a straightforward algorithm based on fast Fourier transform is proposed to systematically obtain the optimal distorted unavailabilities for all generating units in the system. The accuracy and computational performance of the proposed approach are compared with the standard CE optimization process using different generating systems. The IEEE-RTS 79, IEEE-RTS 96, and two configurations of the Brazilian South-Southeastern system are all used for this purpose.

Abstract
This work presents a risk analysis performed to stationary Li-ion batteries within the framework of the STABALID project. The risk analysis had as main objective analysing the variety of hazards and dangerous situations that might be experienced by the battery during its life cycle and providing useful information on how to prevent or manage those undesired events. The first task of the risk analysis was the identification of all the hazards (or risks) that may arise during the battery life cycle. Afterwards, the hazards identified were mapped in the different stages of the battery life cycle and two analyses were performed for each stage: an internal problem analysis and an external peril analysis. For both, the dangerous phenomena and the undesirable events resulting from each hazard was evaluated in terms of probability of occurrence and severity. Then, a risk assessment was carried out according to a predefined risk matrix and a preliminary set of risk mitigation measures were proposed to reduce their probability of occurrence and/or their severity level. The results obtained show that it is possible to reduce the probability of occurrence/severity of all the risks associated to the battery life cycle to acceptable or tolerable levels.

Abstract
The Unit Commitment (UC) problem consists on the day-ahead scheduling of thermal generation units. The scheduling process is based on a forecast for the demand, which adds uncertainty to the decision of starting or shutting down units. With the increasing penetration of renewable energy sources, namely wind power, the level of uncertainty is such that deterministic UC approaches that rely uniquely on point forecasts are no longer appropriate. The UC approach reported in this paper considers a stochastic formulation and includes constraints for the technical limits of thermal generation units, like ramp-rates and minimum and maximum power output, and also for the power flow equations by integrating the DC model in the optimization process. The objective is to assess the ability of the stochastic UC approach to decrease the expected value of load shedding and wind power loss when compared to the deterministic UC approach. A case study based on IEEE-RTS 79 system, which has 24 buses and 32 thermal generation units, for two different penetrations of wind power and a 24-hour horizon is carried out. The computational performance of the methodology proposed is also discussed to show that considerable performance gains without compromising the robustness of the stochastic UC approach can be achieved.

Abstract
Generally, the more Renewable Energy Sources (RES) in generation mix the more complex is the problem of reliability assessment of generating systems, mainly because of the variability and uncertainty of generating capacity. These short-term concerns have been seen as a way of controlling the amount of spinning reserve, providing operators with information on operation system risks. For the medium and long-term assessment, such short-term concerns should be accounted for the system performance [1,2], assuring that investment options will result in more robust and flexible generating configurations that are consequently more secure. In order to deal with the spinning reserve needs, this work proposes the use of a risk based technique, Value-at-Risk and Conditional Value at-Risk, to assist the planners of the Electric Power Systems (EPS) as regards the design of the flexibility of generating systems. This methodology was applied in the IEEE-RTS-96 HW producing adequate results.

Abstract
Currently, it is an ordinary procedure to restrict the use of renewables, mainly wind power, to accommodate a more stable set of generating units (e.g.: thermal units) to supply the load. The purpose of this paper is to discuss particular aspects from the adequacy and security evaluation of generation and transmission (G&T) system that must be revised due to the massive integration of wind power in the present and future energy systems. By running a sequential Monte Carlo simulation (SMCS) algorithm it is possible to assess the system adequacy identifying possible security constrains. The demonstration cases are based on the modified IEEE-RTS 79 system and a small planned configuration for a real G&T system, typically radial. The results extracted from the case studies illustrate that the impact resulting from the massive integration of renewable sources should not be assessed from the adequacy evaluation perspective without considering system security issues.