Impact of Service Sector Loads on Renewable Resource Integration

Urban areas consist of a mix of households and services, such as offices, shops, schools, etc. Yet most urban energy models only consider household load profiles, omitting the service sector. Realistic assessment of the potential for renewable resource integration in cities requires models that include detailed demand and generation profiles. Detailed generation profiles are available for many resources. Detailed demand profiles, however, are currently only available for households and not for the service sector. This paper addresses this gap. The paper (1) proposes a novel approach to devise synthetic service sector demand profiles based on a combination of a large number of different data sources, and (2) uses these profiles to study the impact of the service sector on the potential for renewable resource integration in urban energy systems, using the Netherlands as a case study. The importance of the service sector is addressed in a broad range of solar and wind generation scenarios, and in specific time and weather conditions (in a single scenario). Results show that including the service sector leads to statistically significantly better estimations of the potential of renewable resource integration in urban areas. In specific time and weather conditions, including the service sector results in estimations that are up to 33% higher than if only households are considered. The results can be used by researchers to improve urban energy systems models, and by decision-makers and practitioners for grid planning, operation and management}.Comment: 32 pages, 7 figures, 4 table

Service Sector and Urban-Scale Energy Demand: Dataset Accompanying the PhD Thesis “Harnessing Heterogeneity - Understanding Urban Demand to Support the Energy Transition”

This 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

Combined fermentation and extraction in a bioelectrochemical system

C

Optimal Intensity and Biomass Density for Biofuel Production in a Thin-Light-Path Photobioreactor

Production of competitive microalgal biofuels requires development of high volumetric productivity photobioreactors (PBRs) capable of supporting high-density cultures. Maximal biomass density supported by the current PBRs is limited by nonuniform distribution of light as a result of self-shading effects. We recently developed a thin-light-path stacked photobioreactor with integrated slab waveguides that distributed light uniformly across the volume of the PBR. Here, we enhance the performance of the stacked waveguide photobioreactor (SW-PBR) by determining the optimal wavelength and intensity regime of the incident light. This enabled the SW-PBR to support high-density cultures, achieving a carrying capacity of OD₇₃₀ 20. Using a genetically modified algal strain capable of secreting ethylene, we improved ethylene production rates to 937 μg L^–1 h^–1. This represents a 4-fold improvement over a conventional flat-plate PBR. These results demonstrate the advantages of the SW-PBR design and provide the optimal operational parameters to maximize volumetric production