1,720,955 research outputs found
Harnessing Heterogeneity: Understanding Urban Demand to Support the Energy Transition
No full textThis thesis demonstrates that heterogeneous spatio-temporal demand profiles are required for a realistic representation of urban energy systems. This is needed to prepare them for the energy transition. Therefore, existing and future urban energy system models should be expanded with more detailed spatio-temporal local demand data that account for both household and non-household consumers, in particular for the thus far omitted service sector consumers. This thesis describes methods and approaches that allow for such detailed modelling of urban demand profiles based on the few publicly available data sources. Using the developed detailed spatio-temporal demand profiles, this thesis provides new insights in the impact of renewable energy resources in realistic, heterogeneous urban areas. The presented results can support governments, communities, and companies in theirendeavours to bring the energy transition to fruition.System Engineerin
Service Sector and Urban-Scale Energy Demand: Dataset Accompanying the PhD Thesis “Harnessing Heterogeneity - Understanding Urban Demand to Support the Energy Transition”
No full textThis is the dataset accompanying the PhD thesis:
N. Voulis. Harnessing Heterogeneity - Understanding Urban Demand to Support the Energy Transition. PhD Thesis. Delft University of Technology. 2019. https://doi.org/10.4233/uuid:9b121e9b-bfa0-49e6-a600-5db0fbfa904e.
Real urban areas consist of a mix of households, services (such as schools, offices, shops, etc.), and industry.
However, most literature concerned with local energy demand simplifies it to household demand only.
This is, to a large extent, cause by a lack of detailed (e.g., hourly) service sector and urban-scale energy demand data.
This dataset and the accompanying thesis seek to resolve this issue.
The primary focus of this dataset and the accompanying thesis is therefore on service sector and urban-scale demand data.
Households are also taken into account, albeit in less detail. Households and services are often collocated in urban areas,
but extensive research and data already exist for households.
Industry is left out of scope.
The dataset contains:
- Demand profiles of 13 types of service sector consumers (hourly resolution, full year).
- Demand profile of 1 type of average household consumer (hourly resolution, full year).
- Demand profile of an average mix of 100 000 households and associated services, with a total annual demand of 710 GWh (hourly resolution, full year).
- Demand profile of 203 005 households only, also with a total annual demand of 710 GWh (hourly resolution, full year).
- Demand profiles of archetype residential, business, and mixed urban areas. Urban areas include neighbourhoods, districts, and municipalities (hourly resolution, average weekday and average weekend).
- Composition of archetype residential, business, and mixed urban areas. Urban areas include neighbourhoods, districts, and municipalities.
- Spreadsheet tool to estimate the average hourly demand profile of an urban area of interest, based solely on annual demand data of different consumer types. This tool is also published as an addendum to publication.
All profiles pertain to the Netherlands and to the year 2014.
The modelled year can be adapted as described in the input data and assumptions part. The geographic region can be adapted by repeating the research described in the thesis for another region
Going Beyond Counting First Authors in Author Co-citation Analysis
Full text linkThe present study examines one of the fundamental aspects of author co-citation analysis (ACA) - the way co-citation
counts are defined. Co-citation counting provides the data on which all subsequent statistical analyses and mappings
are based, and we compare ACA results based on two different types of co-citation counting - the traditional type that
only counts the first one among a cited work's authors on the one hand and a non-traditional type that takes into
account the first 5 authors of a cited work on the other hand. Results indicate that the picture produced through this non-traditional author co-citation counting contains more coherent author groups and is therefore considerably clearer. However, this picture represents fewer specialties in the research field being studied than that produced through the traditional first-author co-citation counting when the same number of top-ranked authors is selected and analyzed. Reasons for these effects are discussed
Variations on the Author
Full text link“Variations on the Author” discusses two of Eduardo Coutinho’s recent films (Um Dia na Vida, from 2010, and Últimas Conversas, posthumously released in 2015) and their contribution to the general question of documentary authorship. The director’s filmography is characterized by a consistent yet self-effacing form of authorial self-inscription: Coutinho often features as an interviewer that rather than express opinions propels discourses; an interviewer that is good at listening. This mode of self-inscription characterizes him as an author who is not expressive but who is nonetheless markedly present on the screen. In Um Dia na Vida, however, Coutinho is completely absent form the image, while Últimas Conversas, on the contrary, includes a confessional prologue that moves the director from the margins to the center of his films. This article examines the ways in which these works stand out in the filmography of a director who offers new insights into the notion of cinematic authorship
Appropriate Similarity Measures for Author Cocitation Analysis
Full text linkWe provide a number of new insights into the methodological discussion about author cocitation analysis. We first argue that the use of the Pearson correlation for measuring the similarity between authors’ cocitation profiles is not very satisfactory. We then discuss what kind of similarity measures may be used as an alternative to the Pearson correlation. We consider three similarity measures in particular. One is the well-known cosine. The other two similarity measures have not been used before in the bibliometric literature. Finally, we show by means of an example that our findings have a high practical relevance.information science;Pearson correlation;cosine;similarity measure;author cocitation analysis
Understanding spatio-temporal electricity demand at different urban scales: A data-driven approach
No full textCities and communities worldwide are seeking to become more sustainable by transitioning to renewable energy resources, and by introducing electric transportation and heating. The impact and suitability of such technologies for a given area heavily depend on local conditions, such as characteristics of local demand. In particular, the shape of a local demand profile is an important determinant for how much renewable energy can be used directly, and how charging of electric vehicles and use of electric heating affect a local grid. Unfortunately, a systematic understanding of local demand characteristics on different urban scales (neighbourhoods, districts and municipalities) is currently lacking in literature. Most energy transition studies simplify local demand to household demand only. This paper addresses this knowledge gap by providing a novel data-driven classification and analysis of demand profiles and energy user compositions in nearly 15000 neighbourhoods, districts and municipalities, based on data from the Netherlands. The results show that on all urban scales, three types of areas can be distinguished. In this paper, these area types are termed “residential”, “business” and “mixed”, based on the most prevalent energy users in each. Statistic analysis of the results shows that area types are pairwise significantly different, both in terms of their profiles and in terms of their energy user composition. Moreover, residential-type demand profiles are found only in a small number of areas. These results emphasise the importance of using local detailed spatio-temporal demand profiles to support the transition of urban areas to sustainable energy generation, transportation and heating. To facilitate the implementation of the obtained insights in other models, a spreadsheet modelling tool is provided in an addendum to this paper.System Engineerin
Dispelling the Myths Behind First-author Citation Counts
Full text linkWe conducted a full-scale evaluative citation analysis study of scholars in the XML research field to explore just how different from each other author rankings resulting from different citation counting methods actually are, and to demonstrate the capability of emerging data and tools on the Web in supporting more realistic citation counting methods. Our results contest some common arguments for the continued
use of first-author citation counts in the evaluation of scholars, such as high correlations between author rankings by first-author citation counts and other citation
counting methods, and high costs of using more realistic citation counting methods that are not well-supported by the ISI databases. It is argued that increasingly available digital full text research papers make it possible for citation analysis studies to go beyond what the ISI databases have directly supported and to employ more
sophisticated methods
Aggregator-mediated demand response: Minimizing imbalances caused by uncertainty of solar generation
No full textThe high level of uncertainty of renewable energy sources generation creates differences between electricity supply and demand, endangering the reliable operation of the power system. Demand response has gained significant attention as a means to cope with uncertainty of renewable energy sources. Demand response of residential and service sector consumers, when accumulated and managed by aggregators, can play a role in existing electricity markets. This paper addresses the question to what extent aggregator-mediated demand response can be used to deal with the impacts of the uncertainty of solar generation. Uncertain solar generation leads to imbalances of an aggregator. These imbalances can be reduced by shifting flexible loads, which is called demand response for internal balancing. The aim of this paper is to assess the impact of demand response from loads in residential and service sectors for internal balancing to reduce the imbalances of an aggregator, caused by uncertain solar generation. For this purpose, a Model Predictive Control model which minimizes the imbalances of the aggregator through load shifting is presented. The model is applied to a realistic case study in the Netherlands. The results show that demand response for internal balancing succeeds in reducing imbalances. Even though this is favorable from the power system's perspective, economic analysis shows that the aggregator is not financially incentivized to implement demand response for internal balancing.Energie and IndustrieSystem Engineerin
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