A simulation study of the use of electric vehicles as storage on the New Zealand electricity grid

This paper describes a simulation to establish the extent to which reliance on non-dispatchable energy sources, most typically wind generation, could in the future be extended beyond received norms, by utilizing the distributed battery capacity of an electric vehicle fleet. The notion of exploiting the distributed battery capacity of a nation’s electric vehicle fleet as grid storage is not new. However, this simulation study specifically examines the potential impact of this idea in the New Zealand context. The simulation makes use of real and projected data in relation to vehicle usage, full potential non-dispatchable generation capacity and availability, taking into account weather variation, and typical daily and seasonal patterns of usage. It differs from previous studies in that it is based on individual vehicles, rather than a bulk battery model. At this stage the analysis is aggregated, and does not take into account local or regional flows. A more detailed analysis of these localized effects will follow in subsequent stages of the simulation

Power and energy visualization for the micro-management of household electricity consumption

The paper describes a pilot system for the detailed management of domestic electricity consumption aimed at minimizing demand peaks and consumer cost. Management decisions are made both interactively by consumers themselves, and where practical, automatically by computer. These decisions are based on realtime pricing and availability information, as well as current and historic usage data. The benefits of the energy strategies implied by such a system are elaborated, showing the potential for significant peak demand reduction and slowing of the need for growth in generation capacity. An overview is provided of the component technologies and interaction methods we have designed, but the paper focuses on the communication of real-time information to the consumer through a combination of specific and ambient visualizations. There is a need for both overview information (eg how much power is being used right now; how much energy have we used so far today; what does it cost?) and information at the point-of-use (is it OK to turn this dryer on now, or should I wait until later?). To assist the design of these visualizations, a survey is underway aimed at establishing people's understanding of power and energy concepts

Smart energy interfaces for electric vehicles

Electric vehicle charging strategies rely on knowledge of future vehicle usage, or implicitly make assumptions about a vehicle’s usage. For example, a na¨ıve charging strategy may assume that a full charge is required as soon as possible and simply charge at the maximum rate when plugged in, whereas a smart strategy might make use of the knowledge that the vehicle is not needed for a number of hours and optimise its charging behaviour to minimise its impact on the electricity grid. These charging strategies may also offer vehicle-to-grid services. To achieve this functionality, a driver needs to specify the details of the next trip—or sequence of trips—in order for the charging strategy to perform optimally. This paper explores the value of next-trip information, and presents a potential user interface to assist a driver with providing these details

Smart charging strategies for Electric Vehicles utilising non-dispatchable renewable electricity generation

Access to an inexpensive and reliable supply of energy is critical for the success of modern civilisation. Since the beginning of the Industrial Revolution in the mid 18th century, fossil fuels have enabled great advances across many aspects of society, which have increased the standard of living for many. Unfortunately, dwindling supplies and greenhouse gas emissions resulting from their use means that the continued utilisation of these fuels - particularly for electricity generation and transportation - is simply not sustainable. Present-day electricity systems are built around the premise that generation is flexible and controllable, while load - generally speaking - is not. This leads to dispatch models where generation is scheduled to meet load, plus some additional capacity to accommodate forecast errors and potential equipment failure. Many renewable generation technologies, such as wind and solar photovoltaics, are non-dispatchable and cannot be scheduled to produce electricity on-demand. Successfully utilising these energy sources therefore requires flexibility in other parts of the system. Electric Vehicles (EVs) produce no tailpipe emissions, and can be charged at any location with an electricity supply; at home, work, supermarket, or dedicated charging facilities. Because driving times tend to coincide with existing peak electricity demand, EV charging will occur at times of already high electricity demand if not controlled. Fortunately, there is substantial flexibility over the timing of charging, which can be exploited to minimise adverse impacts on electricity grids. Additional benefits are realised when energy is allowed to flow from the vehicle's battery back into the electricity grid; a concept known as vehicle-to-grid (V2G). Through the development of a simulation based on future energy scenarios in New Zealand, the research presented in this thesis evaluates the extent to which the flexibility of EV charging may be exploited to support high levels of non-dispatchable renewable electricity generation. Several EV charging strategies are introduced and evaluated across a range of metrics with wind penetration levels ranging between 10% and 50% on an annual energy basis. With a V2G-enabled fleet consisting of one million vehicles (25% of New Zealand's projected light vehicle fleet size in 2030), it is found that EV charging is sufficiently flexible to the extent that electricity generation does not need to follow daily variations in load. The EV fleet is capable of meeting the power and ramping requirements of the electricity grid, in addition to its own transportation needs, so long as sufficient energy is generated within a few days of its consumption. Such flexibility is expected to greatly assist the future expansion of non-dispatchable renewable electricity generation in New Zealand

Improved grid integration of intermittent electricity generation using electric vehicles for storage: A simulation study

This paper describes a simulation to establish the extent to which reliance on non-dispatchable energy sources, particularly wind generation, could in the future be extended beyond accepted norms, by utilizing the distributed battery capacity of an electric vehicle fleet for storage. The notion of exploiting the distributed battery capacity of an electric vehicle fleet as grid storage is not new. However, this simulation study specifically examines the potential impact of the idea in the New Zealand context. The simulation makes use of real and projected data in relation to vehicle usage, full potential wind generation capacity and availability, taking into account weather variation, and typical daily and seasonal patterns of electricity usage. It differs from previous studies in that it is based on individual vehicles, rather than a bulk battery model. At this stage, the simulation does not take into account local or regional flows. A more detailed analysis of these localized effects will follow in subsequent stages of the simulation work

On the trails of Josias Braun-Blanquet II : first results from the 12th EDGG Field Workshop studying the dry grasslands of the inneralpine dry valleys of Switzerland

The 12th EDGG Field Workshop took place from 11 to 19 May 2019, organised by the Vegetation Ecology Group of the Institute of Natural Resource Sciences (IUNR) of the Zurich University of Applied Sciences (ZHAW). Like in the 11th Field Workshop in Austria, the main target was the "Inneralpine Trockenvegetation" (Festuco-Brometea and Sedo-Scleranthetea), which was first extensively sampled by Josias Braun-Blanquet and collaborators during the 1950s. We visited the Rhône valley in the cantons of Vaud and Valais, one of the most ex-treme xerothermic islands of the Alps and the Rhine and Inn valleys in the canton of Grison. In total, 30 nested-plot series (EDGG biodi-versity plots) of 0.0001 to 100 m² and 82 plots of 10 m² were sampled in meso-xeric, xeric and rocky grasslands of 25 different sites, rang-ing from 500 to 1,656 m a.s.l., under different topographic, bedrock and landuse conditions. All vascular plants, bryophytes and lichens were recorded in each plot, along with their cover values. We found on average 28.9 vascular plants on 10 m²; which was the lowest mean species richness of any previous EDGG Field Workshop. These values are comparable to the average species richness values of dry grasslands of the Aosta valley in Italy. The data sampled will be used to understand the biodiversity patterns regionally and in the Palae-arctic context as well as to place the Swiss dry grasslands in the modern European syntaxonomic system

Visualising present and past: a meter with a flexible pointer

Meters and gauges based on analogue pointers provide a convenient way to visualise single dimensional data streams, such as speed, voltage, altitude, or fuel level. However, often a small amount of historical information helps to understand the data at a glance, and reduces the need for constant vigilance; is the parameter relatively stable; is it increasing or decreasing? Have there been any transients in the past minute? What trends are present? This paper describes a virtual analogue meter with a flexible pointer that shows both the instantaneous value at the tip and bends to a brief interval of history along its length. The meter has been developed in the context of monitoring the electricity grid, but has many other potential applications

Taking down the FLAG! How Insect Cell Expression Challenges an Established Tag-System

In 1988 the preceding journal of Nature Biotechnology, Bio/Technology, reported a work by Hopp and co-workers about a new tag system for the identification and purification of recombinant proteins: the FLAG-tag. Beside the extensively used hexa-his tag system the FLAG-tag has gained broad popularity due to its small size, its high solubility, the presence of an internal Enterokinase cleavage site, and the commercial availability of high-affinity anti-FLAG antibodies. Surprisingly, considering the heavy use of FLAG in numerous laboratories world-wide, we identified in insect cells a post-translational modification (PTM) that abolishes the FLAG-anti-FLAG interaction rendering this tag system ineffectual for secreted proteins. The present publication shows that the tyrosine that is part of the crucial FLAG epitope DYK is highly susceptible to sulfation, a PTM catalysed by the enzyme family of Tyrosylprotein-Sulfo-transferases (TPSTs). We showed that this modification can result in less than 20% of secreted FLAG-tagged protein being accessible for purification questioning the universal applicability of this established tag system

SPOT: a web-based tool for using biological databases to prioritize SNPs after a genome-wide association study

SPOT (http://spot.cgsmd.isi.edu), the SNP prioritization online tool, is a web site for integrating biological databases into the prioritization of single nucleotide polymorphisms (SNPs) for further study after a genome-wide association study (GWAS). Typically, the next step after a GWAS is to genotype the top signals in an independent replication sample. Investigators will often incorporate information from biological databases so that biologically relevant SNPs, such as those in genes related to the phenotype or with potentially non-neutral effects on gene expression such as a splice sites, are given higher priority. We recently introduced the genomic information network (GIN) method for systematically implementing this kind of strategy. The SPOT web site allows users to upload a list of SNPs and GWAS P-values and returns a prioritized list of SNPs using the GIN method. Users can specify candidate genes or genomic regions with custom levels of prioritization. The results can be downloaded or viewed in the browser where users can interactively explore the details of each SNP, including graphical representations of the GIN method. For investigators interested in incorporating biological databases into a post-GWAS SNP selection strategy, the SPOT web tool is an easily implemented and flexible solution

AMS 3.0: prediction of post-translational modifications

<p>Abstract</p> <p>Background</p> <p>We present here the recent update of AMS algorithm for identification of post-translational modification (PTM) sites in proteins based only on sequence information, using artificial neural network (ANN) method. The query protein sequence is dissected into overlapping short sequence segments. Ten different physicochemical features describe each amino acid; therefore nine residues long segment is represented as a point in a 90 dimensional space. The database of sequence segments with confirmed by experiments post-translational modification sites are used for training a set of ANNs.</p> <p>Results</p> <p>The efficiency of the classification for each type of modification and the prediction power of the method is estimated here using recall (sensitivity), precision values, the area under receiver operating characteristic (ROC) curves and leave-one-out tests (LOOCV). The significant differences in the performance for differently optimized neural networks are observed, yet the AMS 3.0 tool integrates those heterogeneous classification schemes into the single consensus scheme, and it is able to boost the precision and recall values independent of a PTM type in comparison with the currently available state-of-the art methods.</p> <p>Conclusions</p> <p>The standalone version of AMS 3.0 presents an efficient way to indentify post-translational modifications for whole proteomes. The training datasets, precompiled binaries for AMS 3.0 tool and the source code are available at <url>http://code.google.com/p/automotifserver</url> under the Apache 2.0 license scheme.</p