Sizing and control of a Hybrid hydro-battery-flywheel storage system for frequency regulation services

Energy security and environmental challenges are some of the drivers for increasing the electricity generation from non-programmable Renewable Energy Source (RES), adding pressure to the grid, especially if located in weakly connected (or isolated) islands, like Sardinia. Variable-speed Pumped Storage Hydro Power (PSHP) can offer a high degree of flex ibility in providing ancillary services (namely primary and secondary regulations), but due to the hydromechanical nature of the equipment, sudden variations in the power output cause wear and tear. Other energy storage devices can not compete with PSHP in terms of energy and power availability. This work aims to assess the potential benefits derived from the hybridization of a PSHP with Battery Energy Storage System (BESS) and Flywheel Energy Storage System (FESS) in providing frequency regulation services to the grid of the Sardinia Island (Italy). The focus of the study tries to cross both the plant owner point of view, whose aim is to have a smooth PSHP operation and the economic incentive to hybridize the plant, and the Transmission System Operator’s, whose aim is to have a fast reacting plant that better stabilizes the grid frequency. This is done by simulations of a detailed dynamic model of the PSHP, whose hydraulic machine has been characterized from real experimental data, the BESS and the FESS. Moreover, two power management strategies are presented, based on different criteria, to effectively coordinate the devices making up the Hybrid Energy Storage System (HESS). First the simulations are performed open-loop, to assess the impact of various combinations of installed BESS and FESS powers over the wear and tear of the equipment. Later the model is used in an optimization procedure to find the combination of installed BESS and FESS powers and the respective controlparameters that would guarantee the maximum economic return at the end of the investment life. Last, the model is included into a Sardinian power system model and simulated in a future scenario with high RES penetration, assessing the plant capabilities to effectively contain and restore the frequency. Results show that there is not a catch-all solution in terms of hybridization and that a trade-off must be made between the plant owner’s urge to smoothly operate the plant in order to reduce the equipment degradation, and the TSO’s objective to have fast responsive plants providing high quality frequency regulation services. If on one hand open-loop simulations show that the hybridization reduce the main wear and tear indicators, on the other the optimal hybrid system limits the plant ability to contain the frequency excursions in closed-loop simulations, as the optimization problem was formulated over the plant owner’s interests. The results show that there much potential for frequency stabilization and wear and tear reduction, but more techno-economic data is required to fully investigate the benefits of this configuration.Energy security and environmental challenges are some of the drivers for increasing the electricity generation from non-programmable Renewable Energy Source (RES), adding pressure to the grid, especially if located in weakly connected (or isolated) islands, like Sardinia. Variable-speed Pumped Storage Hydro Power (PSHP) can offer a high degree of flex ibility in providing ancillary services (namely primary and secondary regulations), but due to the hydromechanical nature of the equipment, sudden variations in the power output cause wear and tear. Other energy storage devices can not compete with PSHP in terms of energy and power availability. This work aims to assess the potential benefits derived from the hybridization of a PSHP with Battery Energy Storage System (BESS) and Flywheel Energy Storage System (FESS) in providing frequency regulation services to the grid of the Sardinia Island (Italy). The focus of the study tries to cross both the plant owner point of view, whose aim is to have a smooth PSHP operation and the economic incentive to hybridize the plant, and the Transmission System Operator’s, whose aim is to have a fast reacting plant that better stabilizes the grid frequency. This is done by simulations of a detailed dynamic model of the PSHP, whose hydraulic machine has been characterized from real experimental data, the BESS and the FESS. Moreover, two power management strategies are presented, based on different criteria, to effectively coordinate the devices making up the Hybrid Energy Storage System (HESS). First the simulations are performed open-loop, to assess the impact of various combinations of installed BESS and FESS powers over the wear and tear of the equipment. Later the model is used in an optimization procedure to find the combination of installed BESS and FESS powers and the respective controlparameters that would guarantee the maximum economic return at the end of the investment life. Last, the model is included into a Sardinian power system model and simulated in a future scenario with high RES penetration, assessing the plant capabilities to effectively contain and restore the frequency. Results show that there is not a catch-all solution in terms of hybridization and that a trade-off must be made between the plant owner’s urge to smoothly operate the plant in order to reduce the equipment degradation, and the TSO’s objective to have fast responsive plants providing high quality frequency regulation services. If on one hand open-loop simulations show that the hybridization reduce the main wear and tear indicators, on the other the optimal hybrid system limits the plant ability to contain the frequency excursions in closed-loop simulations, as the optimization problem was formulated over the plant owner’s interests. The results show that there much potential for frequency stabilization and wear and tear reduction, but more techno-economic data is required to fully investigate the benefits of this configuration

Metformin: a modulator of bevacizumab activity in cancer? A case report.

Recurrent type I endometrial cancer ((EC)) has poor prognosis and demands novel therapeutic approaches. Bevacizumab, a VEGF-A neutralizing monoclonal antibody, has shown clinical activity in this setting. To our knowledge, however, although some diabetic cancer patients treated with bevacizumab may also take metformin, whether metformin modulates response to anti-VEGF therapy has not yet been investigated. Here, we report the case of a patient with advanced (EC) treated, among other drugs, with bevacizumab in combination with metformin. The patient affected by relapsed (EC) G3 type 1, presented in march 2010 with liver, lungs and mediastinic metastases. After six cycles of paclitaxel and cisplatin she underwent partial response. Later on, she had disease progression notwithstanding administration of multiple lines of chemotherapy. In march 2013, due to brain metastases with coma, she began steroid therapy with development of secondary diabetes. At this time, administration of Bevacizumab plus Metformin improved her performance status. CT scans performed in this time window showed reduced radiologic density of the lung and mediastinic lesions and of liver disease, suggestive of increased tumor necrosis. Strong F-18-FDG uptake by PET imaging along with high levels of monocarboxylate transporter 4 and lack of liver kinase B1 expression in liver metastasis, highlighted metabolic features previously associated with response to anti-VEGF therapy and phenformin in preclinical models. However, clinical benefit was transitory and was followed by rapid and fatal disease progression. These findingsalbeit limited to a single casesuggest that tumors lacking LKB1 expression and/or endowed with an highly glycolytic phenotype might develop large necrotic areas following combined treatment with metformin plus bevacizumab. As metformin is widely used among diabetes patients as well as in ongoing clinical trials in cancer patients, these results deserve further clinical investigation

A New ELISA Using the ANANAS Technology Showing High Sensitivity to diagnose the Bovine Rhinotracheitis from Individual Sera to Pooled Milk

Diagnostic tests for veterinary surveillance programs should be efficient, easy to use and, possibly, economical. In this context, classic Enzyme linked ImmunoSorbent Assay (ELISA) remains the most common analytical platform employed for serological analyses. The analysis of pooled samples instead of individual ones is a common procedure that permits to certify, with one single test, entire herds as "disease-free". However, diagnostic tests for pooled samples need to be particularly sensitive, especially when the levels of disease markers are low, as in the case of anti-BoHV1 antibodies in milk as markers of Infectious Bovine Rhinotracheitis (IBR) disease. The avidin-nucleic-acid-nanoassembly (ANANAS) is a novel kind of signal amplification platform for immunodiagnostics based on colloidal poly-avidin nanoparticles that, using model analytes, was shown to strongly increase ELISA test performance as compared to monomeric avidin. Here, for the first time, we applied the ANANAS reagent integration in a real diagnostic context. The monoclonal 1G10 anti-bovine IgG1 antibody was biotinylated and integrated with the ANANAS reagents for indirect IBR diagnosis from pooled milk mimicking tank samples from herds with IBR prevalence between 1 to 8%. The sensitivity and specificity of the ANANAS integrated method was compared to that of a classic test based on the same 1G10 antibody directly linked to horseradish peroxidase, and a commercial IDEXX kit recently introduced in the market. ANANAS integration increased by 5-fold the sensitivity of the 1G10 mAb-based conventional ELISA without loosing specificity. When compared to the commercial kit, the 1G10-ANANAS integrated method was capable to detect the presence of anti-BHV1 antibodies from bulk milk of gE antibody positive animals with 2-fold higher sensitivity and similar specificity. The results demonstrate the potentials of this new amplification technology, which permits improving current classic ELISA sensitivity limits without the need for new hardware investments

Parallel Sequential Monte Carlo for Efficient Density Combination: The DeCo MATLAB Toolbox

This paper presents the Matlab package DeCo (Density Combination) which is based on the paper by Billio et al. (2013) where a constructive Bayesian approach is presented for combining predictive densities originating from different models or other sources of information. The combination weights are time-varying and may depend on past predictive forecasting performances and other learning mechanisms. The core algorithm is the function DeCo which applies banks of parallel Sequential Monte Carlo algorithms to filter the time-varying combination weights. The DeCo procedure has been implemented both for standard CPU computing and for Graphical Process Unit (GPU) parallel computing. For the GPU implementation we use the Matlab parallel computing toolbox and show how to use General Purposes GPU computing almost effortless. This GPU implementation comes with a speed up of the execution time up to seventy times compared to a standard CPU Matlab implementation on a multicore CPU. We show the use of the package and the computational gain of the GPU version, through some simulation experiments and empirical application

A fully coupled computational fluid dynamics – agent-based model of atherosclerotic plaque development: Multiscale modeling framework and parameter sensitivity analysis

Background: Peripheral Artery Disease (PAD) is an atherosclerotic disorder that leads to impaired lumen patency through intimal hyperplasia and the build-up of plaques, mainly localized in areas of disturbed flow. Computational models can provide valuable insights in the pathogenesis of atherosclerosis and act as a predictive tool to optimize current interventional techniques. Our hypothesis is that a reliable predictive model must include the atherosclerosis development history. Accordingly, we developed a multiscale modeling framework of atherosclerosis that replicates the hemodynamic-driven arterial wall remodeling and plaque formation. Methods: The framework was based on the coupling of Computational Fluid Dynamics (CFD) simulations with an Agent-Based Model (ABM). The CFD simulation computed the hemodynamics in a 3D artery model, while 2D ABMs simulated cell, Extracellular Matrix (ECM) and lipid dynamics in multiple vessel cross-sections. A sensitivity analysis was also performed to evaluate the oscillation of the ABM output to variations in the inputs and to identify the most influencing ABM parameters. Results: Our multiscale model qualitatively replicated both the physiologic and pathologic arterial configuration, capturing histological-like features. The ABM outputs were mostly driven by cell and ECM dynamics, largely affecting the lumen area. A subset of parameters was found to affect the final lipid core size, without influencing cell/ECM or lumen area trends. Conclusion: The fully coupled CFD-ABM framework described atherosclerotic morphological and compositional changes triggered by a disturbed hemodynamics

correction on the stability of manganese tris β diketonate complexes as redox mediators in dsscs

Correction for 'On the stability of manganese tris(β-diketonate) complexes as redox mediators in DSSCs' by Stefano Carli et al., Phys. Chem. Chem. Phys., 2016, 18, 5949–5956

An agent-based model of cardiac allograft vasculopathy: toward a better understanding of chronic rejection dynamics

Cardiac allograft vasculopathy (CAV) is a coronary artery disease affecting 50% of heart transplant (HTx) recipients, and it is the major cause of graft loss. CAV is driven by the interplay of immunological and non-immunological factors, setting off a cascade of events promoting endothelial damage and vascular dysfunction. The etiology and evolution of tissue pathology are largely unknown, making disease management challenging. So far, in vivo models, mostly mouse-based, have been widely used to study CAV, but they are resource-consuming, pose many ethical issues, and allow limited investigation of time points and important biomechanical measurements. Recently, agent-based models (ABMs) proved to be valid computational tools for deciphering mechanobiological mechanisms driving vascular adaptation processes at the cell/tissue level, augmenting cost-effective in vivo lab-based experiments, at the same time guaranteeing richness in observation time points and low consumption of resources. We hypothesize that integrating ABMs with lab-based experiments can aid in vivo research by overcoming those limitations. Accordingly, this work proposes a bidimensional ABM of CAV in a mouse coronary artery cross-section, simulating the arterial wall response to two distinct stimuli: inflammation and hemodynamic disturbances, the latter considered in terms of low wall shear stress (WSS). These stimuli trigger i) inflammatory cell activation and ii) exacerbated vascular cell activities. Moreover, an extensive analysis was performed to investigate the ABM sensitivity to the driving parameters and inputs and gain insights into the ABM working mechanisms. The ABM was able to effectively replicate a 4-week CAV initiation and progression, characterized by lumen area decrease due to progressive intimal thickening in regions exposed to high inflammation and low WSS. Moreover, the parameter and input sensitivity analysis highlighted that the inflammatory-related events rather than the WSS predominantly drive CAV, corroborating the inflammatory nature of the vasculopathy. The proof-of-concept model proposed herein demonstrated its potential in deepening the pathology knowledge and supporting the in vivo analysis of CAV

Interband characterization and electronic transport control of nanoscaled GeTe/Sb2_2Te3_3 superlattices

The extraordinary electronic and optical properties of the crystal-to-amorphous transition in phase-change materials led to important developments in memory applications. A promising outlook is offered by nanoscaling such phase-change structures. Following this research line, we study the interband optical transmission spectra of nanoscaled GeTe/Sb$_2$Te$_3$ chalcogenide superlattice films. We determine, for films with varying stacking sequence and growth methods, the density and scattering time of the free electrons, and the characteristics of the valence-to-conduction transition. It is found that the free electron density decreases with increasing GeTe content, for sub-layer thickness below $\sim$3 nm. A simple band model analysis suggests that GeTe and Sb$_2$Te$_3$ layers mix, forming a standard GeSbTe alloy buffer layer. We show that it is possible to control the electronic transport properties of the films by properly choosing the deposition layer thickness and we derive a model for arbitrary film stacks

Relationship between hemodynamics and in-stent restenosis in femoral arteries

Although percutaneous transluminal angioplasty with stenting is one of the preferred treatments of lower extremity peripheral artery disease, this procedure suffers from a 66% 1-year primary patency rate. The unfavorable outcome is mostly attributable to in-stent restenosis, an inflammatory-driven arterial response, characterized by excessive smooth muscle cell proliferative and synthetic activity ultimately leading to lumen re-narrowing. The etiology of in-stent restenosis is multifactorial, involving different systemic, biological and biomechanical drivers. Among the biomechanical factors, a key role has been recognized to the stent-induced hemodynamic alteration, influencing smooth muscle cell activity both directly and through endothelium-dependent mechanisms. In this scenario, computational fluid dynamics simulations of stented femoral arteries allowed quantifying the local hemodynamics and identifying wall shear stress-based hemodynamic predictors of in-stent restenosis. This contributed to enhance the current knowledge of the fluid dynamic-related mechanisms of post-stenting lumen remodeling. However, given the multiscale and multifactorial nature of in-stent restenosis, multiscale mechanobiological modeling relating the intervention-induced mechanical stimuli to the complex network of biological events has recently emerged as a fundamental approach to decipher the underlying pathological pathways. This involves the analysis of interactions, cause-effect relationships, feedback mechanisms and cascade signaling pathways across different spatial and temporal scales, thus allowing tracking the effect of the interventioninduced perturbation to the molecular, cellular and finally tissue response. The present chapter examines the state-of-the-art of computational fluid dynamics studies of in-stent restenosis in femoral arteries and provides an overview on the emerging field of multiscale mechanobiological modeling of arterial adaptation following endovascular procedures