MicroRNA 19a replacement partially rescues fin and cardiac defects in zebrafish model of Holt Oram syndrome

Holt-Oram Syndrome (HOS) is an autosomal dominant heart-hand syndrome caused by mutations in the TBX5 gene, a transcription factor capable of regulating hundreds of cardiac-specific genes through complex transcriptional networks. Here we show that, in zebrafish, modulation of a single miRNA is sufficient to rescue the morphogenetic defects generated by HOS. The analysis of miRNA-seq profiling revealed a decreased expression of miR-19a in Tbx5-depleted zebrafish embryos compared to the wild type. We revealed that the transcription of the miR-17-92 cluster, which harbors miR-19a, is induced by Tbx5 and that a defined dosage of miR-19a is essential for the correct development of the heart. Importantly, we highlighted that miR-19a replacement is able to rescue cardiac and pectoral fin defects and to increase the viability of HOS zebrafish embryos. We further observed that miR-19a replacement shifts the global gene expression profile of HOS-like zebrafish embryos towards the wild type condition, confirming the ability of miR-19a to rescue the Tbx5 phenotype. In conclusion our data demonstrate the importance of Tbx5/miR-19a regulatory circuit in heart development and provide a proof of principle that morphogenetic defects associated with HOS can be rescued by transient miRNA modulation

Online security assessment with load and renewable generation uncertainty: The iTesla project approach

The secure integration of renewable generation into modern power systems requires an appropriate assessment of the security of the system in real-time. The uncertainty associated with renewable power makes it impossible to tackle this problem via a brute-force approach, i.e. it is not possible to run detailed online static or dynamic simulations for all possible security problems and realizations of load and renewable power. Intelligent approaches for online security assessment with forecast uncertainty modeling are being sought to better handle contingency events. This paper reports the platform developed within the iTesla project for online static and dynamic security assessment. This innovative and open-source computational platform is composed of several modules such as detailed static and dynamic simulation, machine learning, forecast uncertainty representation and optimization tools to not only filter contingencies but also to provide the best control actions to avoid possible unsecure situations. Based on High Performance Computing (HPC), the iTesla platform was tested in the French network for a specific security problem: overload of transmission circuits. The results obtained show that forecast uncertainty representation is of the utmost importance, since from apparently secure forecast network states, it is possible to obtain unsecure situations that need to be tackled in advance by the system operator

Open access simulation toolbox for the grid connection of offshore wind farms using multi-terminal HVDC networks

Decarbonisation of the European electricity system can become dauntingly costly due to transmission and distribution network issues arising from the integration of intermittent renewable generation sources. It is expected that wind energy will be the principal renewable source by 2050 and, as such, a number of initiatives in the academia and in the industry are being carried out to propose solutions to best accommodate the wind resource. This paper presents work carried out by DEMO 1 partners within the EU FP7 project BEST PATHS. A MATLAB/Simulink toolbox consisting of the necessary building blocks for the simulation and integration of offshore wind farms using enabling technologies such as multiterminal high-voltage direct-current grids is presented. To illustrate the toolbox capabilities, a number of system topologies is studied. System performance is assessed and measured against a set of key performance indicators. To ensure knowledge dissemination, the toolbox has been made available as open access in the BEST PATHS project website

An Efficient Method to Take into Account Forecast Uncertainties in Large Scale Probabilistic Power Flow

The simulation of uncertainties due to renewable and load forecasts is becoming more and more important in security assessment analyses performed on large scale networks. This paper presents an efficient method to account for forecast uncertainties in probabilistic power flow (PPF) applications, based on the combination of PCA (Principal Component Analysis) and PEM (Point Estimate Method), in the context of operational planning studies applied to large scale AC grids. The benchmark against the conventional PEM method applied to large power system models shows that the proposed method assures high speed up ratios, preserving a good accuracy of the marginal distributions of the outputs

Probabilistic assessment of Net Transfer Capacity considering forecast uncertainties

In transmission system planning, researchers propose methods to assess the effect of uncertainties of power system operating condition due to forecasting errors of intermittent generation and loads. In particular probabilistic power flow methods are used to calculate the probability distributions of the voltages and the branch currents, starting from the distributions of power injections/absorptions. These uncertainties play a key role in the operational planning of power systems, as certain configurations of load and intermittent generation can cause security problems. This paper aims to propose a probabilistic methodology to assess Net Transfer Capacity (NTC) among network areas, which quantifies forecast error uncertainties by applying the Point Estimate Method (PEM) combined with Third Order Polynomial Normal (TPN) Transformation. This approach is compared with a conventional NTC assessment technique and has been tested on an IEEE test system

A Risk-Based Methodology and Tool Combining Threat Analysis and Power System Security Assessment

A thorough investigation of power system security requires the analysis of the vulnerabilities to natural and man-related threats which potentially trigger multiple contingencies. In particular, extreme weather events are becoming more and more frequent due to climate changes and often cause large load disruptions on the system, thus the support for security enhancement gets tricky. Exploiting data coming from forecasting systems in a security assessment environment can help assess the risk of operating power systems subject to the disturbances provoked by the weather event itself. In this context, the paper proposes a security assessment methodology, based on an updated definition of risk suitable for power system risk evaluations. Big data analytics can be useful to get an accurate model for weather-related threats. The relevant software (SW) platform integrates the security assessment methodology with prediction systems which provide short term forecasts of the threats affecting the system. The application results on a real wet snow threat scenario in the Italian High Voltage grid demonstrate the effectiveness of the proposed approach with respect to conventional security approaches, by complementing the conventional "N - 1" security criterion and exploiting big data to link the security assessment phase to the analysis of incumbent threat

Benchmarking and Validation of Cascading Failure Analysis Tools

Cascading failure in electric power systems is a complicated problem for which a variety of models, software tools, and analytical tools have been proposed but are difficult to verify. Benchmarking and validation are necessary to understand how closely a particular modeling method corresponds to reality, what engineering conclusions may be drawn from a particular tool, and what improvements need to be made to the tool in order to reach valid conclusions. The community needs to develop the test cases tailored to cascading that are central to practical benchmarking and validation. In this paper, the IEEE PES working group on cascading failure reviews and synthesizes how benchmarking and validation can be done for cascading failure analysis, summarizes and reviews the cascading test cases that are available to the international community, and makes recommendations for improving the state of the art