Abstract
Microgrids are the basic building cells of a smart grid. They are assumed to be established at the low voltage distribution level, where distributed energy sources, storage devices, controllable loads, and electric vehicles are integrated and need to be properly managed. The microgrid cell is a very flexible system that can be operated connected to the main power network or autonomously, in a controlled and coordinated way. When operating in islanded mode, the MG relies on local energy storage to ensure the balance between generations and loads. However, when operating isolated from the main grid, the MG is more sensitive to power quality issues such as voltage unbalance, caused by the connection of single-phase loads and sources. In order to improve the MG emergency operation conditions, the EV should be envisaged as an active and flexible entity, providing to the MG additional distributed load or storage capacity under the vehicle-to-grid (V2G) concept. This chapter reviews the MG architecture considering EV and focuses on the impact of their active participation on the MG frequency regulation in emergency conditions (namely in islanding operating mode). Voltage unbalance issues during MG autonomous operation and the need for adopting voltage balancing mechanisms in specific power electronic interfaces are also discussed. © Springer India 2014.

Abstract
The challenge of resilience for High Performance Computing applications is significant for future extreme scale systems. These systems will experience unprecedented rates of faults and errors as they will be constructed from massive numbers of components that are inherently less reliable than those available today. While the use of redundant computing can provide detection and possible correction of errors, its system-wide use in future extreme-scale HPC systems will incur considerable overheads to application performance. In this paper, we present a framework that provides application level fault detection based on redundant multithreading. In previous work, we demonstrated an adaptive approach based on a language level directive. The computation contained in the programmer directive is executed by duplicate threads. In concert with a runtime system, the redundant multithreading is enabled opportunistically to provide fault detection at more reasonable overheads to application performance. The lazy fault detection approach presented in this work seeks to further optimize the use of redundancy by prioritizing the application's primary computation over the fault detection. Our approach relaxes the requirement that the redundant threads synchronize and compare results immediately. We show that lazy error detection is feasible and yields lower time to solution over adaptive RMT for a range of scientific computational kernels. We also explore a thread-to-core assignment strategy that seeks to reduce the interference between the redundant threads. © 2014 IEEE.

Abstract

Abstract
METRIC (TM) is a satellite-based surface energy balance model aimed at estimating and mapping crop evapotranspiration (ET). It has been applied to a large range of vegetation types, mostly annual crops. When applied to anisotropic woody canopies, such as olive orchards, extensions are required to algorithms for estimating the leaf area index (LAI), surface temperature, and momentum roughness length (Z(om)). The computation of the radiometric surface temperature needs to consider a three-source condition, thus differentiating the temperature of the canopy (T-c), of the shaded ground surface (T-shadow), and of the sunlit ground surface (T-sunlit). The estimation of the Z(om) for tall and incomplete cover is based upon the LAI and crop height using the Perrier equation. The LAI, Zorn, and temperature derived from METRIC after these adjustments were tested against field collected data with good results. The application of METRIC to a two year set of Landsat images to estimate ET of a super-intensive olive orchard in Southern Portugal produced good ET estimates that compared well with ground-based ET. The analysis of METRIC performance showed a quantitative improvement of ET estimates when applying the three-source condition for temperature estimation, as well as the Z(om) computation with the Perrier equation. Results show that METRIC can be used operationally to estimate and mapping ET of super-intensive olive orchards aiming at improving irrigation water use and management.

Abstract
A control chart based on the quantile function to monitor the shape parameter of a Weibull distribution is proposed and its performance is analyzed by Monte Carlo simulation. The importance of monitoring the shape parameter even when the other parameters of the Weibull distribution are assumed known is further enhanced, together with motivating examples. © 2014 Proceedings of COMPSTAT 2014 - 21st International Conference on Computational Statistics. All rights reserved.

Abstract
In cloud computing environments, data storage systems often rely on optimistic replication to provide good performance and availability even in the presence of failures or network partitions. In this scenario, it is important to be able to accurately and efficiently identify updates executed concurrently. Current approaches to causality tracking in optimistic replication have problems with concurrent updates: they either (1) do not scale, as they require replicas to maintain information that grows linearly with the number of writes or unique clients; (2) lose information about causality, either by removing entries from client-id based version vectors or using server-id based version vectors, which cause false conflicts. We propose a new logical clock mechanism and a logical clock framework that together support a traditional key-value store API, while capturing causality in an accurate and scalable way, avoiding false conflicts. It maintains concise information per data replica, only linear on the number of replica servers, and allows data replicas to be compared and merged linear with the number of replica servers and versions.