Analysis of optimal wind power integration capacity based on the scenario tree construction method

Određivanje optimalnog integrativnog kapaciteta energije vjetra velike vjetroelektrane postalo je važno pitanje kod planiranja i rada energetskog postrojenja. Razumni integrativni kapacitet energije vjetra može poboljšati korištenje energije vjetra i uštedjeti na ulaganju za izgradnju vjetroelektrane. U ovom je radu prikazan matematički model za određivanje optimalnog integrativnog kapaciteta vjetroelektrane uzimajući maksimalizaciju čiste dobiti godišnje proizvodnje vjetroelektrane kao objektivnu funkciju, a potrebe osiguranja kao ograničenja modela. Metoda konstrukcije stabla scenarija predložena je zbog bavljenja nesistematskim karakteristikama energije vjetra tijekom jedne godine na temelju teorije vjerojatnosti. Predloženi su principi diskretizacije vjerojatnoće raspodjele brzine vjetra i postupci konstrukcije stabla scenarija energije vjetra. Primijenjen je algoritam hijerarhijske optimalizacije koji kombinira algoritam optimalizacije roja w-čestica i algoritam društveno emocionalne optimalizacije za rješenje modela optimalizacije u ovom radu. Predloženi se model primijenio u istraživanju učinaka izazvanih varijacijom faktora povezanih s rezultatima optimalnog integrativnog kapaciteta energije vjetra. Daju se detaljni postupci u dobivanju rješenja. Točnost modela i valjanost algoritama verificirani su prema simulaciji na sustavu IEEE-30 čvorova.The determination of the optimal wind power integration capacity of a large-scale wind farm has become an important issue in power system operation and planning. Reasonable wind power integration capacity can improve the wind energy utilization and save investment for wind farm construction. This paper builds a mathematical model for determining wind farm optimal integration capacity by taking the maximization of the wind farm annual generation net benefits the objective function and the security operation requirements as the model constraints. The scenario tree construction method is proposed to deal with the random characteristics of wind power in one year based on the probability theory. The discretization principles of wind speed probability distribution and the scenario tree construction processes of wind power are proposed. Hierarchical optimization algorithm combining w-particle swarm optimization algorithm and social emotional optimization algorithm is used to solve the optimization model in this paper. The effects caused by the variation of factors correlated with the optimal wind power integration capacity results are investigated using the proposed model. The detailed solution steps are given. The correctness of the model and the validity of the algorithms for solving are verified according to the simulation on the IEEE-30 nodes system

Analysis of optimal wind power integration capacity based on the scenario tree construction method

Određivanje optimalnog integrativnog kapaciteta energije vjetra velike vjetroelektrane postalo je važno pitanje kod planiranja i rada energetskog postrojenja. Razumni integrativni kapacitet energije vjetra može poboljšati korištenje energije vjetra i uštedjeti na ulaganju za izgradnju vjetroelektrane. U ovom je radu prikazan matematički model za određivanje optimalnog integrativnog kapaciteta vjetroelektrane uzimajući maksimalizaciju čiste dobiti godišnje proizvodnje vjetroelektrane kao objektivnu funkciju, a potrebe osiguranja kao ograničenja modela. Metoda konstrukcije stabla scenarija predložena je zbog bavljenja nesistematskim karakteristikama energije vjetra tijekom jedne godine na temelju teorije vjerojatnosti. Predloženi su principi diskretizacije vjerojatnoće raspodjele brzine vjetra i postupci konstrukcije stabla scenarija energije vjetra. Primijenjen je algoritam hijerarhijske optimalizacije koji kombinira algoritam optimalizacije roja w-čestica i algoritam društveno emocionalne optimalizacije za rješenje modela optimalizacije u ovom radu. Predloženi se model primijenio u istraživanju učinaka izazvanih varijacijom faktora povezanih s rezultatima optimalnog integrativnog kapaciteta energije vjetra. Daju se detaljni postupci u dobivanju rješenja. Točnost modela i valjanost algoritama verificirani su prema simulaciji na sustavu IEEE-30 čvorova.The determination of the optimal wind power integration capacity of a large-scale wind farm has become an important issue in power system operation and planning. Reasonable wind power integration capacity can improve the wind energy utilization and save investment for wind farm construction. This paper builds a mathematical model for determining wind farm optimal integration capacity by taking the maximization of the wind farm annual generation net benefits the objective function and the security operation requirements as the model constraints. The scenario tree construction method is proposed to deal with the random characteristics of wind power in one year based on the probability theory. The discretization principles of wind speed probability distribution and the scenario tree construction processes of wind power are proposed. Hierarchical optimization algorithm combining w-particle swarm optimization algorithm and social emotional optimization algorithm is used to solve the optimization model in this paper. The effects caused by the variation of factors correlated with the optimal wind power integration capacity results are investigated using the proposed model. The detailed solution steps are given. The correctness of the model and the validity of the algorithms for solving are verified according to the simulation on the IEEE-30 nodes system

Epidemiological and genomic characteristics of global mcr-positive Escherichia coli isolates

ObjectiveThe worldwide dissemination of colistin-resistant Escherichia coli (E. coli) endangers public health. This study aimed to better understand the global genomic epidemiology of E. coli isolates carrying mobilized colistin resistance (mcr) genes, providing information to assist in infection and prevention.MethodsEscherichia coli genomes were downloaded from NCBI, and mcr was detected using BLASTP. Per software was used to extract information on hosts, resources, collection data, and countries of origin from GenBank. Sequence types (STs), prevalence of plasmids, antimicrobial resistance genes (ARG), and virulence factors (VF) in these genomes were analyzed. Statistical analyses were performed to assess the relationships between mcr, ARGs, plasmids, and STs.ResultsIn total, 778 mcr-positive isolates were identified. Four mcr variants were detected, with mcr-1 (86.1%) being the most widespread, followed by mcr-9 (5.7%), mcr-5 (4.4%), and mcr-3 (3.0%). Multiple ARGs were identified, with blaCTX–M (53.3%), fosA (28.8%), qnr (26.1%), blaNDM (19.8%), and aac (6’)-Ib-cr (14.5%) being the most common. Overall, 239 distinct STs were identified, of which ST10 (13.8%) was the most prevalent. A total of 113 different VFs were found, terC (99.9%) and gad (83.0%) were most frequently detected. Twenty types of plasmids were identified; IncFIB (64.1%), IncX (42.3%), and IncX (42.3%) were the most common replicons. IncI2 and IncX4 were frequently detected in mcr-1-positive isolates, whereas IncFII, IncI1-I, and IncHI2 were dominant plasmids in mcr-3, mcr-5, and mcr-9-positive isolates, respectively. A higher frequency of ARGs and VFs was observed among ST156 and ST131 isolates.ConclusionOur data indicated that more than half of the mcr-positive E. coli strains carried endemic ARGs and VFs. ST10 and ST156 isolates deserved further attention, given the rapid transmission of ST10 and the convergence of ARGs and VFs in ST156

Correlation between Arctic river discharge and sea ice formation in Laptev Sea using sea surface salinity from SMOS satellite

European Geosciences Union (EGU) General Assembly 2020, 4-8 May 2020During the last 3 decades, the Arctic rivers have increased their discharge around 10%, mainly due to the increase of the global atmospheric temperature. The increase of the river discharge carries higher loads of dissolved organic matter (DOM) and suspended matter (SM) entering to the Arctic Ocean. This results in increased absorption of solar energy in the mixed layer, which can potentially contribute to the general sea ice retreat. Observation based studies (e.g. Bauch et al., 2013) showed correlation between river water discharge and local sea ice melting on the Laptev sea shelf due to the change on the ocean heat. Previous studies are based with a limited number of observations, both in space and in time. Thanks to the ESA SMOS (Soil Moisture and Ocean Salinity) and NASA SMAP (Soil Moisture Active Passive) missions we have daily the sea surface salinity (SSS) maps from the Arctic, which permit to observe the salinity variations due to the river discharges. The Arctic sea surface salinity products obtained from SMOS measurements have been improved considerable by the Barcelona Expert Center (BEC) team thanks to the project Arctic+Salinity, funded by ESA. The new version of the product (v3) covers the years from 2011 up to 2018, have a spatial resolution of 25km and are daily maps with 9 day averages. The Arctic+ SSS maps provide a better description of the salinity gradients and a better effective spatial resolution than the previous versions of the Arctic product, so the salinity fronts are better resolved. The quality assessment of the Arctic+SSS product is challenging because, in this region, there are scarce number of in-situ measurements. The high effective spatial resolution of the Arctic+ SSS maps will permit to study for the first time scientific physical processes that occurs in the Arctic. We will explore if a correlation between the Lena and Ob rivers discharge with the sea ice melting and freeze up is observed with satellite data, as already stated with in-situ measurements by Bauch et al. 2013. Salinity and sea ice thickness maps from SMOS and sea ice concentration from OSISAF will be used in this study. Bauch, D.,Hölemann, J. , Nikulina, A. , Wegner, C., Janout, M., Timokhov, L. and Kassens, H. (2013): Correlation of river water and local sea-ice melting on the Laptev Sea shelf (Siberian Arctic) , Journal of Geophysical Research C: Oceans, 118 (1), pp. 550-561 . doi: 10.1002/jgrc.2007

An assessment of ten ocean reanalyses in the polar regions

Global and regional ocean and sea ice reanalysis products (ORAs) are increasingly used in polar research, but their quality remains to be systematically assessed. To address this, the Polar ORA Intercomparison Project (Polar ORA-IP) has been established following on from the ORA-IP project. Several aspects of ten selected ORAs in the Arctic and Antarctic were addressed by concentrating on comparing their mean states in terms of snow, sea ice, ocean transports and hydrography. Most polar diagnostics were carried out for the first time in such an extensive set of ORAs. For the multi-ORA mean state, we found that deviations from observations were typically smaller than individual ORA anomalies, often attributed to offsetting biases of individual ORAs. The ORA ensemble mean therefore appears to be a useful product and while knowing its main deficiencies and recognising its restrictions, it can be used to gain useful information on the physical state of the polar marine environment.Peer reviewe

Improved BEC SMOS Arctic Sea Surface Salinity product v3.1

17 pages, 13 figures, 1 table.-- Data availability: The product (Martínez et al., 2019) is freely distributed on the BEC (Barcelona Expert Center) web page (http://bec.icm.csic.es/, last access: 25 January 2022) with the DOI number https://doi.org/10.20350/digitalCSIC/12620 (Martínez et al., 2019) and on the Digital CSIC server: https://digital.csic.es/handle/10261/219679 (last access: 25 January 2022). Data can be downloaded from the FTP service: http://bec.icm.csic.es/bec-ftp-service/ (last access: 25 January 2022). The maps are distributed in the standard grid EASE-Grid 2.0, which has a spatial resolution of 25 km. In addition to the product validated in this work (L3 with temporal resolution of 9 d), L3 products having a temporal resolution of 3 and 18 d and the L2 product are available. These Arctic SSS products cover the period from 2011 to 2019.-- This work represents a contribution to the CSIC Thematic Interdisciplinary Platform PTI Teledetect and PolarCSIC. Argo data were collected and made freely available by the International Argo program and the national programs that contribute to it (https://argo.ucsd.edu, https://www.ocean-ops.org, last access: 25 January 2022). The Argo program is part of the Global Ocean Observing SystemMeasuring salinity from space is challenging since the sensitivity of the brightness temperature (TB) to sea surface salinity (SSS) is low (about 0.5 K psu−1), while the SSS range in the open ocean is narrow (about 5 psu, if river discharge areas are not considered). This translates into a high accuracy requirement of the radiometer (about 2–3 K). Moreover, the sensitivity of the TB to SSS at cold waters is even lower (0.3 K psu−1), making the retrieval of the SSS in the cold waters even more challenging. Due to this limitation, the ESA launched a specific initiative in 2019, the Arctic+Salinity project (AO/1-9158/18/I-BG), to produce an enhanced Arctic SSS product with better quality and resolution than the available products. This paper presents the methodologies used to produce the new enhanced Arctic SMOS SSS product (Martínez et al., 2019) . The product consists of 9 d averaged maps in an EASE 2.0 grid of 25 km. The product is freely distributed from the Barcelona Expert Center (BEC, http://bec.icm.csic.es/, last access: 25 January 2022) with the DOI number https://doi.org/10.20350/digitalCSIC/12620 (Martínez et al., 2019). The major change in this new product is its improvement of the effective spatial resolution that permits better monitoring of the mesoscale structures (larger than 50 km), which benefits the river discharge monitoringThis work has been carried out as part of the ESA Arctic+Salinity project (AO/1-9158/18/I-BG), which permitted the production of the database, and the Ministry of Economy and Competitiveness, Spain, through the National R&D Plan under L-BAND project ESP2017-89463-C3-1-R. [...] With the funding support of the ‘Severo Ochoa Centre of Excellence’ accreditation (CEX2019-000928-S), of the Spanish Research Agency (AEI)Peer reviewe

Measuring currents, ice drift, and waves from space: the Sea Surface KInematics Multiscale monitoring (SKIM) concept

We propose a new satellite mission that uses a near-nadir Ka-band Doppler radar to measure surface currents, ice drift and ocean waves at spatial scales of 40?km and more, with snapshots at least every day for latitudes 75 to 82, and every few days otherwise. The use of incidence angles at 6 and 12 degrees allows a measurement of the directional wave spectrum which yields accurate corrections of the wave-induced bias in the current measurements. The instrument principle, algorithm for current velocity and mission performance are presented here. The proposed instrument can reveal features on tropical ocean and marginal ice zone dynamics that are inaccessible to other measurement systems, as well as a global monitoring of the ocean mesoscale that surpasses the capability of today?s nadir altimeters. Measuring ocean wave properties facilitates many applications, from wave-current interactions and air-sea fluxes to the transport and convergence of marine plastic debris and assessment of marine and coastal hazards