Demand flexibility enabled by virtual energy storage to improve renewable energy penetration

The increasing resort to renewable energy distributed generation, which is needed to mitigate anthropogenic CO2 emissions, leads to challenges concerning the proper operation of electric distribution systems. As a result of the intrinsic nature of Renewable Energy Sources (RESs), this generation shows a high volatility and a low predictability that make the balancing of energy production and consumption difficult. At the same time, the electrification of new energy‐intensive sectors (such as heating) is expected. This complex scenario paves the way for new sources of flexibility that will have more and more relevance in the coming years. This paper analyses how the electrification of the heating system, combined with an electric flexibility utilisation module, can be used to mitigate the problems related to the fluctuating production of RES. By using Power‐to‐Heat (P2H) technologies, buildings are able to store the overproduction of RES in the form of thermal energy for end‐use according to the principle of the so‐called Virtual Energy Storage (VES). A context‐aware demand flexibility extraction based on the VES model and the flexibility upscale and utilisation on district‐level through grid simulation and energy flow optimisation is presented in the paper. The involved modules have been developed within the PLANET (PLAnning and operational tools for optimising energy flows and synergies between energy NETworks) H2020 European project and interact under a unified co‐simulation framework with the PLANET Decision Support System (DSS) for the analysis of multi‐energy scenarios. DSS has been used to simulate a realistic future energy scenario, according to which the imbalance problems triggered by RES overproduction are mitigated with the optimal exploitation of the demand flexibility enabled by VES

Co-simulation Management Algorithm for Distribution System Operation with Real-Time Simulator

This article presents a co-simulation framework consistent with the real-time simulation for operational analysis of electrical distribution networks. Realtime simulators have become a fundamental tool for testing and optimising control strategies in a safe and controlled environment. The proposed methodology outlines the steps required for setting up, controlling, and monitoring an electrical grid using a real-time simulator. The framework proposes the use of the Message Queuing Telemetry Transport communication between the electrical grid module and an external coordinator. An algorithm based on the Python programming language is proposed to manage the real-time simulation, create the grid topology, and communicate with the external coordinator. The implementation of the electrical network and the validation of the real-time simulator network are also presented. The article concludes that the proposed framework can improve the performance and flexibility of co-simulation for studies on the penetration of power electronics-based renewable sources

Organically modified hydrotalcite for compounding and spinning of polyethylene nanocomposites

Organically modified hydrotalcite is a recent class of organoclay based on layered double hydroxides (LDH), which is anionically modified with environmental friendly ligands such as fatty acids. In this paper the influence of hydrotalcite compounded/dispersed by means of two different processes for production of plates and fibers of polyolefin nanocomposites will be compared. A polyethylene matrix, suitable for fiber production, was firstly compounded with various amounts of hydrotalcite in the range of 0.5–5% by weight, and then compression moulded in plates whose thermomechanical properties were evaluated. Similar compositions were processed by using a co-rotating twin screw extruder in order to directly produce melt-spun fibers. The incorporation of clay into both bulk and fiber nanocomposites enhanced the thermal stability and induced heterogeneous nucleation of polyethylene crystals. Hydrotalcite manifested a satisfactory dispersion into the polymer matrix, and hence positively affected the mechanical properties in term of an increase of both Young’s modulus and tensile strength. Tenacity of nanocomposite as spun fibers was increased up to 30% with respect to the neat polymer. Moreover, the addition of LDH filler induced an increase of the tensile modulus of drawn fibers from 5.0 GPa (neat HDPE) up to 5.6–5.8 GPa

[The therapy of symptomatic and/or complicated dysontogenetic liver cysts].

Congenital hepatic cysts are a frequent disease, symptomatic in the 16-18\% of the cases. The authors report a review of the literature of the last 20 years about 135 treated surgically patients with symptomatic and/or complicated hepatic cysts. They analyse the different models of treatment both surgical and conservative, referring in special way about the alcoholization of the cysts. The authors finally report their personal experience about eight cases

Preoperative and intraoperative staging in gastric cancer.

Non disponibil

Role-Oriented Code Generation in an Engine for Solving Hyperbolic PDE Systems

The development of a high performance PDE solver requires the combined expertise of interdisciplinary teams with respect to application domain, numerical scheme and low-level optimization. In this paper, we present how the ExaHyPE engine facilitates the collaboration of such teams by isolating three roles: application, algorithms, and optimization expert. We thus support team members in letting them focus on their own area of expertise while integrating their contributions into an HPC production code. Inspired by web application development practices, ExaHyPE relies on two custom code generation modules, the Toolkit and the Kernel Generator, which follow a Model-View-Controller architectural pattern on top of the Jinja2 template engine library. Using Jinja2's templates to abstract the critical components of the engine and generated glue code, we isolate the application development from the engine. The template language also allows us to define and use custom template macros that isolate low-level optimizations from the numerical scheme described in the templates. We present three use cases, each focusing on one of our user roles, showcasing how the design of the code generation modules allows to easily expand the solver schemes to support novel demands from applications, to add optimized algorithmic schemes (with reduced memory footprint, e.g.), or provide improved low-level SIMD vectorization support.Comment: SC19 SE-HE