UC Research RepositoryThe UC Research Repistory captures, stores, indexes, preserves, and distributes digital research material.http://ir.canterbury.ac.nz:802018-08-18T19:01:56Z2018-08-18T19:01:56Zevmix: An R package for Extreme Value Mixture Modeling, Threshold Estimation and Boundary Corrected Kernel Density EstimationHu YScarrott Chttp://hdl.handle.net/10092/157952018-08-17T15:01:03Z2018-01-01T00:00:00Zevmix: An R package for Extreme Value Mixture Modeling, Threshold Estimation and Boundary Corrected Kernel Density Estimation
Hu Y; Scarrott C
evmix is an R package (R Core Team 2017) with two interlinked toolsets: i) for extreme
value modeling and ii) kernel density estimation. A key issue in univariate extreme value
modeling is the choice of threshold beyond which the asymptotically motivated extreme
value models provide a suitable tail approximation. The package implements almost
all existing extreme value mixture models, which permit objective threshold estimation
and uncertainty quantification. Some traditional diagnostic plots for threshold choice are
provided.
Kernel density estimation with a range of kernels is provided, including cross-validation
maximum likelihood inference for the bandwidth. A key contribution over existing kernel
smoothing packages in R is that a wide range of boundary corrected kernel density estimators
are implemented, which are designed for populations with bounded support. These
non-parametric density estimators are also incorporated into the extreme value mixture
model framework to describe the density below the threshold.
The quartet of density, distribution, quantile and random number generation functions
is provided along with parameter estimation by likelihood inference and standard model fit
diagnostics, for both the mixture models and kernel density estimators. The key features
of the mixture models and (boundary corrected) kernel density estimators are described
and their implementation using the package demonstrated.
2018-01-01T00:00:00ZDegree and the Brauer-Manin obstructionCreutz BViray Bhttp://hdl.handle.net/10092/157942018-08-17T15:01:19Z2017-01-01T00:00:00ZDegree and the Brauer-Manin obstruction
Creutz B; Viray B
Let X be a smooth variety over a number field k embedded as a degree d
subvariety of {P}^nk and suppose that X is a counterexample to the
Hasse principle explained by the Brauer-Manin obstruction. We consider the
question of whether the obstruction is given by the d-primary subgroup of the
Brauer group, which would have both theoretic and algorithmic implications. We
prove that this question has a positive answer in the case of torsors under
abelian varieties, Kummer varieties and (conditional on finiteness of
Tate-Shafarevich groups) bielliptic surfaces. In the case of Kummer varieties
we show, more specifically, that the obstruction is already given by the
2-primary torsion. We construct a conic bundle over an elliptic curve that
shows that, in general, the answer is no.
2017-01-01T00:00:00ZManagement of Distributed Generation Using DGHost in NZMcNab, S.Lemon, S.Crownshaw, T.Strahan, R.Miller, A.http://hdl.handle.net/10092/157932018-08-16T15:01:06Z2018-01-01T00:00:00ZManagement of Distributed Generation Using DGHost in NZ
McNab, S.; Lemon, S.; Crownshaw, T.; Strahan, R.; Miller, A.
2018-01-01T00:00:00ZGuideline for the connection of small-scale inverter based distributed generation: an introduction and summaryMiller AJVStrahan RMcnab SCrownshaw TPandey SWatson NRLemon SMWood ARhttp://hdl.handle.net/10092/157922018-08-16T15:01:07Z2016-01-01T00:00:00ZGuideline for the connection of small-scale inverter based distributed generation: an introduction and summary
Miller AJV; Strahan R; Mcnab S; Crownshaw T; Pandey S; Watson NR; Lemon SM; Wood AR
Small-scale distributed generation (DG) in New Zealand, particularly photovoltaic (PV)
generation, has been growing steadily over the past few years. In the last year alone to 31 March
2016, installed PV generation of all capacities has grown by a factor of about 1.6 to reach 37
MW. Approximately 90% (33 MW) of this installed PV capacity is made up of small-scale,
single phase residential grid-tied systems with ratings below 10 kW. This corresponds, on
average, to approximately 300-400 new PV systems being installed each month within low
voltage (LV) distribution networks.
Traditionally, the flow of power in electricity distribution networks has been largely
unidirectional. However, distributed generation introduces reverse power flows into the LV
network when the power produced by DG systems is greater than what can be consumed
locally. This introduction of reverse power flows and the dynamic behavior of DG system
inverters can negatively impact the electricity network, causing issues such as over-voltage,
phase imbalance, overloading of conductors and transformers, and create unique safety
challenges. As such, each DG connection application received by electricity distribution
businesses (EDBs) presently needs to be carefully considered for its impact on the electricity
network. The resourcing demand imposed by larger numbers of connection applications, and
the difficulty of technical assessment including congestion evaluation, are likely to increase
substantially as DG uptake intensifies. This has prompted the Electric Power Engineering
Centre (EPECentre) via its GREEN Grid programme, with the assistance of the electricity
industry based Network Analysis Group (NAG), to develop a small-scale inverter based DG
connection guideline for New Zealand EDBs. This has been developed on behalf of the
Electricity Engineersâ€™ Association (EEA) specifically for the connection of inverter energy
systems (IES) of 10 kW or less.
This paper summarizes key aspects of this guideline. This includes a streamlined connection
application evaluation process that enables EDBs to efficiently categorize DG applications into
three groups. These groups vary from those with minimal or moderate network impact that can
be auto-assessed, to those most likely to cause network congestion that require manual
assessment. These categories are determined by looking at the DG hosting capacity specific to
the LV network that the DG is connecting to. For two of these categories, mitigation measures
for connection, are prescribed. It is also shown how DG hosting capacity can be used to simply
evaluate LV network congestion in order to satisfy Electricity Industry Participation Code
(EIPC) Part 6 requirements. Key technical requirements for all IES, appropriate for New
Zealand conditions, are also summarized.
2016-01-01T00:00:00Z