Dataset Information

Resource and technology data for spatio-temporal value chain modelling of the Great Britain energy system.

ABSTRACT: A comprehensive dataset for the resources and technologies in a present-day energy system is presented. These data were used as the model input data for spatio-temporal value chain optimisation studies for the Great Britain energy system. Although focussed on Great Britain, these data may be applicable to other energy systems worldwide. Data are presented for energy resources and energy technologies. Spatio-temporal energy resource data include availabilities of primary resources such as wind and solar, and demands for heat and electricity in the domestic, commercial and industrial sectors. Economic and operating parameters for a wide range of energy technologies are presented, including resource utilisation and conversion technologies such as wind turbines and electrolysers, resource transportation such as gas transmission systems, and energy storage technologies. The data were gathered from a wide range of academic literature, technical reports, and government databases; all references are provided with the data. This dataset will be valuable for greater understanding of the energy value chain optimisation studies performed using the Value Web Model, carrying out further energy system modelling, and as a general reference for the resources and technologies in present-day energy systems.

SUBMITTER: Quarton CJ

PROVIDER: S-EPMC7329933 | biostudies-literature | 2020 Aug

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Resource and technology data for spatio-temporal value chain modelling of the Great Britain energy system.

Quarton Christopher J CJ Samsatli Sheila S

Data in brief 20200620

A comprehensive dataset for the resources and technologies in a present-day energy system is presented. These data were used as the model input data for spatio-temporal value chain optimisation studies for the Great Britain energy system. Although focussed on Great Britain, these data may be applicable to other energy systems worldwide. Data are presented for energy resources and energy technologies. Spatio-temporal energy resource data include availabilities of primary resources such as wind an ...[more]

PMID: 32637493

Similar Datasets

Project description:BackgroundGliomas are the most common types of brain cancer, well known for their aggressive proliferation and the invasive behavior leading to a high mortality rate. Several mathematical models have been developed for identifying the interactions between glioma cells and tissue microenvironment, which play an important role in the mechanism of the tumor formation and progression.MethodsBuilding and expanding on existing approaches, this paper develops a continuous three-dimensional model of avascular glioma spatio-temporal evolution. The proposed spherical model incorporates the interactions between the populations of four different glioma cell phenotypes (proliferative, hypoxic, hypoglychemic and necrotic) and their tissue microenvironment, in order to investigate how they affect tumor growth and invasion in an isotropic and homogeneous medium. The model includes two key variables involved in the proliferation and invasion processes of cancer cells; i.e. the extracellular matrix and the matrix-degradative enzymes concentrations inside the tumor and its surroundings. Additionally, the proposed model focuses on innovative features, such as the separate and independent impact of two vital nutrients, namely oxygen and glucose, in tumor growth, leading to the formation of cell populations with different metabolic profiles. The model implementation takes under consideration the variations of particular factors, such as the local cell proliferation rate, the variable conversion rates of cells from one category to another and the nutrient-dependent thresholds of conversion. All model variables (cell densities, ingredients concentrations) are continuous and described by reaction-diffusion equations.ResultsSeveral simulations were performed using combinations of growth and invasion rates, for different evolution times. The model results were evaluated by medical experts and validated on experimental glioma models available in the literature, revealing high agreement between simulated and experimental results.ConclusionsBased on the experimental validation, as well as the evaluation by clinical experts, the proposed model may provide an essential tool for the patient-specific simulation of different tumor evolution scenarios and reliable prognosis of glioma spatio-temporal progression.

Project description:The nature of contacts between hosts can be important in facilitating or impeding the spread of pathogens within a population. Networks constructed from contacts between hosts allow examination of how individual variation might influence the spread of infections. Studying the contact networks of livestock species managed under different conditions can additionally provide insight into their influence on these contact structures. We collected high-resolution proximity and GPS location data from nine groups of domestic cattle (mean group size = 85) in seven dairy herds employing a range of grazing and housing regimes. Networks were constructed from cattle contacts (defined by proximity) aggregated by different temporal windows (2 h, 24 h, and approximately 1 week) and by location within the farm. Networks of contacts aggregated over the whole study were highly saturated but dividing contacts by space and time revealed substantial variation in cattle interactions. Cows showed statistically significant variation in the frequency of their contacts and in the number of cows with which they were in contact. When cows were in buildings, compared to being on pasture, contact durations were longer and cows contacted more other cows. A small number of cows showed evidence of consistent relationships but the majority of cattle did not. In one group where management allowed free access to all farm areas, cows showed asynchronous space use and, while at pasture, contacted fewer other cows and showed substantially greater between-individual variation in contacts than other groups. We highlight the degree to which variations in management (e.g. grazing access, milking routine) substantially alter cattle contact patterns, with potentially major implications for infection transmission and social interactions. In particular, where individual cows have free choice of their environment, the resulting contact networks may have a less-risky structure that could reduce the likelihood of direct transmission of infections.

Dataset Information

Resource and technology data for spatio-temporal value chain modelling of the Great Britain energy system.

Publications

Resource and technology data for spatio-temporal value chain modelling of the Great Britain energy system.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets