51 research outputs found
Distributed control of reactive power flow in a radial distribution circuit with high photovoltaic penetration
We show how distributed control of reactive power can serve to regulate
voltage and minimize resistive losses in a distribution circuit that includes a
significant level of photovoltaic (PV) generation. To demonstrate the
technique, we consider a radial distribution circuit with a single branch
consisting of sequentially-arranged residential-scale loads that consume both
real and reactive power. In parallel, some loads also have PV generation
capability. We postulate that the inverters associated with each PV system are
also capable of limited reactive power generation or consumption, and we seek
to find the optimal dispatch of each inverter's reactive power to both maintain
the voltage within an acceptable range and minimize the resistive losses over
the entire circuit. We assume the complex impedance of the distribution circuit
links and the instantaneous load and PV generation at each load are known. We
compare the results of the optimal dispatch with a suboptimal local scheme that
does not require any communication. On our model distribution circuit, we
illustrate the feasibility of high levels of PV penetration and a significant
(20% or higher) reduction in losses.Comment: 6 pages, 5 figures
Options for Control of Reactive Power by Distributed Photovoltaic Generators
High penetration levels of distributed photovoltaic(PV) generation on an
electrical distribution circuit present several challenges and opportunities
for distribution utilities. Rapidly varying irradiance conditions may cause
voltage sags and swells that cannot be compensated by slowly responding utility
equipment resulting in a degradation of power quality. Although not permitted
under current standards for interconnection of distributed generation,
fast-reacting, VAR-capable PV inverters may provide the necessary reactive
power injection or consumption to maintain voltage regulation under difficult
transient conditions. As side benefit, the control of reactive power injection
at each PV inverter provides an opportunity and a new tool for distribution
utilities to optimize the performance of distribution circuits, e.g. by
minimizing thermal losses. We discuss and compare via simulation various design
options for control systems to manage the reactive power generated by these
inverters. An important design decision that weighs on the speed and quality of
communication required is whether the control should be centralized or
distributed (i.e. local). In general, we find that local control schemes are
capable for maintaining voltage within acceptable bounds. We consider the
benefits of choosing different local variables on which to control and how the
control system can be continuously tuned between robust voltage control,
suitable for daytime operation when circuit conditions can change rapidly, and
loss minimization better suited for nighttime operation.Comment: 8 pages, 8 figure
Local Control of Reactive Power by Distributed Photovoltaic Generators
High penetration levels of distributed photovoltaic (PV) generation on an
electrical distribution circuit may severely degrade power quality due to
voltage sags and swells caused by rapidly varying PV generation during cloud
transients coupled with the slow response of existing utility compensation and
regulation equipment. Although not permitted under current standards for
interconnection of distributed generation, fast-reacting, VAR-capable PV
inverters may provide the necessary reactive power injection or consumption to
maintain voltage regulation under difficult transient conditions. As side
benefit, the control of reactive power injection at each PV inverter provides
an opportunity and a new tool for distribution utilities to optimize the
performance of distribution circuits, e.g. by minimizing thermal losses. We
suggest a local control scheme that dispatches reactive power from each PV
inverter based on local instantaneous measurements of the real and reactive
components of the consumed power and the real power generated by the PVs. Using
one adjustable parameter per circuit, we balance the requirements on power
quality and desire to minimize thermal losses. Numerical analysis of two
exemplary systems, with comparable total PV generation albeit a different
spatial distribution, show how to adjust the optimization parameter depending
on the goal. Overall, this local scheme shows excellent performance; it's
capable of guaranteeing acceptable power quality and achieving significant
saving in thermal losses in various situations even when the renewable
generation in excess of the circuit own load, i.e. feeding power back to the
higher-level system.Comment: 6 pages, 5 figures, submitted to IEEE SmartGridComm 201
Design strategies for the self-assembly of polyhedral shells
The control over the self-assembly of complex structures is a long-standing
challenge of material science, especially at the colloidal scale, as the
desired assembly pathway is often kinetically derailed by the formation of
amorphous aggregates. Here we investigate in detail the problem of the
self-assembly of the three Archimedean shells with five contact points per
vertex, i.e. the icosahedron, the snub cube, and the snub dodecahedron. We use
patchy particles with five interaction sites (or patches) as model for the
building blocks, and recast the assembly problem as a Boolean satisfiability
problem (SAT) for the patch-patch interactions. This allows us to find
effective designs for all targets, and to selectively suppress unwanted
structures. By tuning the geometrical arrangement and the specific interactions
of the patches, we demonstrate that lowering the symmetry of the building
blocks reduces the number of competing structures, which in turn can
considerably increase the yield of the target structure. These results cement
SAT-assembly as an invaluable tool to solve inverse design problems.Comment: 21 pages, 10 figure
Complex+:Aided Decision-Making for the Study of Protein Complexes
Proteins are the chief effectors of cell biology and their functions are typically carried out in the context of multi-protein assemblies; large collections of such interacting protein assemblies are often referred to as interactomes. Knowing the constituents of protein complexes is therefore important for investigating their molecular biology. Many experimental methods are capable of producing data of use for detecting and inferring the existence of physiological protein complexes. Each method has associated pros and cons, affecting the potential quality and utility of the data. Numerous informatic resources exist for the curation, integration, retrieval, and processing of protein interactions data. While each resource may possess different merits, none are definitive and few are wieldy, potentially limiting their effective use by non-experts. In addition, contemporary analyses suggest that we may still be decades away from a comprehensive map of a human protein interactome. Taken together, we are currently unable to maximally impact and improve biomedicine from a protein interactome perspective textendash motivating the development of experimental and computational techniques that help investigators to address these limitations. Here, we present a resource intended to assist investigators in (i) navigating the cumulative knowledge concerning protein complexes and (ii) forming hypotheses concerning protein interactions that may yet lack conclusive evidence, thus (iii) directing future experiments to address knowledge gaps. To achieve this, we integrated multiple data-types/different properties of protein interactions from multiple sources and after applying various methods of regularization, compared the protein interaction networks computed to those available in the EMBL-EBI Complex Portal, a manually curated, gold-standard catalog of macromolecular complexes. As a result, our resource provides investigators with reliable curation of bona fide and candidate physical interactors of their protein or complex of interest, prompting due scrutiny and further validation when needed. We believe this information will empower a wider range of experimentalists to conduct focused protein interaction studies and to better select research strategies that explicitly target missing information
SAT-assembly: A new approach for designing self-assembling systems
We propose a general framework for solving inverse self-assembly problems,
i.e. designing interactions between elementary units such that they assemble
spontaneously into a predetermined structure. Our approach uses patchy
particles as building blocks, where the different units bind at specific
interaction sites (the patches), and we exploit the possibility of having
mixtures with several components. The interaction rules between the patches is
determined by transforming the combinatorial problem into a Boolean
satisfiability problem (SAT) which searches for solutions where all bonds are
formed in the target structure. Additional conditions, such as the
non-satisfiability of competing structures (e.g. metastable states) can be
imposed, allowing to effectively design the assembly path in order to avoid
kinetic traps. We demonstrate this approach by designing and numerically
simulating a cubic diamond structure from four particle species that assembles
without competition from other polymorphs, including the hexagonal structure.Comment: 12 pages, 4 figure
Phenotype bias determines how natural RNA structures occupy the morphospace of all possible shapes
The relative prominence of developmental bias versus natural selection is a long standing controversy in evolutionary biology. Here we demonstrate quantitatively that developmental bias is the primary explanation for the occupation of the morphospace of RNA secondary structure (SS) shapes. By using the RNAshapes method to define coarse-grained SS classes, we can measure the frequencies that non-coding RNA SS shapes appear in nature. Our main findings are firstly that only the most frequent structures appear in nature; the vast majority of possible structures in the morphospace have not yet been explored. Secondly, and perhaps more surprisingly, these frequencies are accurately predicted by the likelihood that structures appear upon uniform random sampling of sequences. The ultimate cause of these patterns is not natural selection, but rather strong phenotype bias in the RNA genotype-phenotype (GP) map, a type of developmental bias which tightly constrains evolutionary dynamics to only act within a reduced subset of structures that are easy to âfindâ.
Preprint on:
https://www.biorxiv.org/content/10.1101/2020.12.03.410605v
Why Are Outcomes Different for Registry Patients Enrolled Prospectively and Retrospectively? Insights from the Global Anticoagulant Registry in the FIELD-Atrial Fibrillation (GARFIELD-AF).
Background: Retrospective and prospective observational studies are designed to reflect real-world evidence on clinical practice, but can yield conflicting results. The GARFIELD-AF Registry includes both methods of enrolment and allows analysis of differences in patient characteristics and outcomes that may result. Methods and Results: Patients with atrial fibrillation (AF) and â„1 risk factor for stroke at diagnosis of AF were recruited either retrospectively (nâ=â5069) or prospectively (nâ=â5501) from 19 countries and then followed prospectively. The retrospectively enrolled cohort comprised patients with established AF (for a least 6, and up to 24 months before enrolment), who were identified retrospectively (and baseline and partial follow-up data were collected from the emedical records) and then followed prospectively between 0-18 months (such that the total time of follow-up was 24 months; data collection Dec-2009 and Oct-2010). In the prospectively enrolled cohort, patients with newly diagnosed AF (â€6 weeks after diagnosis) were recruited between Mar-2010 and Oct-2011 and were followed for 24 months after enrolment. Differences between the cohorts were observed in clinical characteristics, including type of AF, stroke prevention strategies, and event rates. More patients in the retrospectively identified cohort received vitamin K antagonists (62.1% vs. 53.2%) and fewer received non-vitamin K oral anticoagulants (1.8% vs . 4.2%). All-cause mortality rates per 100 person-years during the prospective follow-up (starting the first study visit up to 1 year) were significantly lower in the retrospective than prospectively identified cohort (3.04 [95% CI 2.51 to 3.67] vs . 4.05 [95% CI 3.53 to 4.63]; pâ=â0.016). Conclusions: Interpretations of data from registries that aim to evaluate the characteristics and outcomes of patients with AF must take account of differences in registry design and the impact of recall bias and survivorship bias that is incurred with retrospective enrolment. Clinical Trial Registration: - URL: http://www.clinicaltrials.gov . Unique identifier for GARFIELD-AF (NCT01090362)
Risk profiles and one-year outcomes of patients with newly diagnosed atrial fibrillation in India: Insights from the GARFIELD-AF Registry.
BACKGROUND: The Global Anticoagulant Registry in the FIELD-Atrial Fibrillation (GARFIELD-AF) is an ongoing prospective noninterventional registry, which is providing important information on the baseline characteristics, treatment patterns, and 1-year outcomes in patients with newly diagnosed non-valvular atrial fibrillation (NVAF). This report describes data from Indian patients recruited in this registry. METHODS AND RESULTS: A total of 52,014 patients with newly diagnosed AF were enrolled globally; of these, 1388 patients were recruited from 26 sites within India (2012-2016). In India, the mean age was 65.8 years at diagnosis of NVAF. Hypertension was the most prevalent risk factor for AF, present in 68.5% of patients from India and in 76.3% of patients globally (P < 0.001). Diabetes and coronary artery disease (CAD) were prevalent in 36.2% and 28.1% of patients as compared with global prevalence of 22.2% and 21.6%, respectively (P < 0.001 for both). Antiplatelet therapy was the most common antithrombotic treatment in India. With increasing stroke risk, however, patients were more likely to receive oral anticoagulant therapy [mainly vitamin K antagonist (VKA)], but average international normalized ratio (INR) was lower among Indian patients [median INR value 1.6 (interquartile range {IQR}: 1.3-2.3) versus 2.3 (IQR 1.8-2.8) (P < 0.001)]. Compared with other countries, patients from India had markedly higher rates of all-cause mortality [7.68 per 100 person-years (95% confidence interval 6.32-9.35) vs 4.34 (4.16-4.53), P < 0.0001], while rates of stroke/systemic embolism and major bleeding were lower after 1 year of follow-up. CONCLUSION: Compared to previously published registries from India, the GARFIELD-AF registry describes clinical profiles and outcomes in Indian patients with AF of a different etiology. The registry data show that compared to the rest of the world, Indian AF patients are younger in age and have more diabetes and CAD. Patients with a higher stroke risk are more likely to receive anticoagulation therapy with VKA but are underdosed compared with the global average in the GARFIELD-AF. CLINICAL TRIAL REGISTRATION-URL: http://www.clinicaltrials.gov. Unique identifier: NCT01090362
Coarse-grained modelling of nucleic acids
This thesis considers coarse-grained models of DNA and RNA, developed in particular to study nanotechnological applications as well as some important biophysical processes. We first introduce sequence-dependent thermodynamics into a previously developed coarse-grained rigid base-pair model of DNA. This model is then used to study sequence-dependent effects in multiple DNA systems including: the heterogeneous stacking transition of single strands, the fraying of a duplex, the effects of stacking strength in the loop on the melting temperature of hairpins, the force-extension curve of single strands, and the structure of a kissing-loop complex. We further apply the DNA model to study in detail the properties of an autonomous unidirectionally propagating DNA nanotechnological device, called the ``burnt bridges motor''. We then apply the coarse-graining methods developed for the DNA model to construct a new sequence-dependent coarse-grained model of RNA, which aims to capture basic thermodynamic, structural and mechanical properties of RNA molecules. We test the model by studying its thermodynamics for a variety of secondary structure motifs and also consider the force-extension properties of an RNA duplex. This RNA model allows for efficient simulations of a variety of RNA systems up to hundreds or even thousands of base-pairs. Its versatility is further demonstrated by studying the thermodynamics of a pseudoknot folding, the formation of a kissing loop complex, the structure of a hexagonal RNA nanoring, and the unzipping of a hairpin.</p
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