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The dataset originates from microgrid platform (MGP, https://www.microgrid-qehna.com/) located in QehnA lab (https://www.qehna.com/) of the National School of Engineers of Tunis (ENIT) and serves as a testbed for various energy-related studies. The platform includes two microgrids, namely Pla-NeTE and SMARTNESS. Pla-NeTE, which stands for Platform for investigations of New Technologies of the Energy is a microgrid platform, designed for the investigation of new energy technologies in the case of massive residential photovoltaics integration and its impact on the distribution network. On the other hand, SMARTNESS, which stands for Smart Micro-grid plAtfoRm wiTh aN Energy SyStem, is a laboratory-scale microgrid designed for the exploration of emerging energy technologies and associated concepts such as collective self-consumption and energy management systems. Both microgrids are connected to the low-voltage distribution network. The dataset comprises samples of electrical data collected from the microgrid platform. It offers a valuable resource for researchers and analysts to study real-world electrical data and gain insights into the microgrid's performance, encompassing aspects such as energy consumption, renewable energy generation, and energy storage systems while considering residential microgrid in Tunisia. The dataset primarily consists of electrical data samples recorded from both microgrids while considering different operating conditions. It provides a granular view of the microgrids’ real-time electrical performance according to given test procedure. This dataset does not encompass detailed information about the microgrid's physical structure or components, but these later can be found in the related publications. Researchers can use this data to analyse the microgrids’ operational patterns and performance in the context of electrical energy management. The dataset's applicability extends to various research areas, including residential load management, renewable energy integration, and power quality improvement.

Operating measurements from three multi-week test campaigns of the natural circulation FLiBe loop. This system is investigating thermal hydraulic behavior of the molten salt BeF_2 -LiF (33 - 67 mol %). The system behaves in a stable fashion, but shows unusual local transients, such as flow break-down in the riser and thermal jumps at the cooler exit. Heat transfer shows promising trends that FLiBe will behave as a normal heat transfer fluid, as long as salt purity can be maintained. The most recent test shows heat transfer degradation that is likely a result of oxides and impurities. The data archive contains as-built dimensions, Matlab analysis codes, and the raw data files.

Refrigerated road transport (RRT) vehicles are large users of energy, and reportedly have relatively high leakage of hydrofluorocarbon refrigerant gases, both of which contribute to global warming. The experience obtained from widespread research in leak reduction in stationary refrigeration systems can be instructive in combatting leakage in RRT systems, which has received less focus to date. This paper will take an integrated approach to develop and describe a preliminary model for sustainable RRT systems. It will first review lessons learned about refrigerant leakage in stationary systems in an effort to identify problematic/leak prone components common to transport refrigeration systems. This will then be followed by a survey of recent studies conducted in modelling transport refrigeration systems to advance energy efficiency. Initial results from the model illustrate the need to improve the efficiency of the refrigeration system, together with preventative maintenance of the box structure and refrigeration system as a whole.

Fashion products made from repurposed materials (e.g., backpacks made from pineapple leaves) have become more prevalent nowadays, and their environmental sustainability is one of the core advantages. Yet, it is currently unclear how consumers respond to products made from repurposed materials. We conducted three experiments to examine the effects of three material features, namely function, sustainability, and distinguishability, on consumer preferences for fashion products made from repurposed materials. The results indicate that, when the function of repurposed materials is as good as that of conventional materials, consumers prefer a product made from repurposed materials over the same product made from conventional materials. Also, consumers in general prefer repurposed materials to be less visually distinguishable. Finally, when the sustainability of the repurposed products is emphasized, consumers appear more likely to choose products made from repurposed materials, even when these products have an inferior function. In conclusion, to promote fashion products made from repurposed materials, marketers may emphasize the function and sustainability of repurposed materials, and producers may manufacture repurposed materials that visually resemble conventional materials.

The HEU MODERATE Building Stock Data provides information regarding the building stock for all EU27 member states at the national level (i.e., NUTS 0) considering 2020 as the reference year. Regarding the Service Sector, the data distinguishes the following subsectors: single-family houses, multifamily houses, and apartment blocks. Regarding the Service Sector, the data distinguishes the following subsectors: offices, trade, education, health, hotels and restaurants, and other non-residential buildings. Moreover, for each subsector, the data distinguishes the following construction periods: before 1945, 1945-1969, 1970-1979, 1980-1989, 1990-1999, 2000-2010, and 2011-2020. For each building stock subsector and construction period, the data provide information regarding total values at the national level for: - Number of buildings - Number of dwellings - Number of dwellings according to ownership (i.e., owner occupied, rented, social housing) - Number of dwellings according to occupation (i.e., occupied, vacant, secondary houses) - Total constructed area - Total heated area - Total cooled area - Total final energy consumption for space heating and domestic hot water - Total final energy consumption for space cooling Moreover, the following average values for single building characteristics are provided: - Number of floors - Volume-to-surface ratio - Vertical area - Ground area - Window surface - U-values for the different building elements (roof, walls, windows, and floors) - Useful energy demand (ued) differentiating between space heating, domestic hot water, and space cooling - Final energy consumption (fed) differentiating between space heating, domestic hot water, and space cooling Finally, the data provide information about the prevalence of: - Building materials and methodology for the different building elements (roof, walls, windows, and floors) - Different systems used for space heating, domestic hot water, and space cooling The data is provided as a `csv` file (long format with all details and data source) and as an excel file (wide format with separate sheets for each country). Data and a complete description of the available fields can be found at https://github.com/MODERATE-Project/building-stock-analysis/tree/main/T3.2-static-analysis The dataset was obtained by combining information from European and national resources and the review of scientific literature. Data gaps were subsequently filled via statistical modeling.

This publication highlights important aspects for commercial refrigeration systems, which comprise parallel compression like for example part load conditions and the reverse operation between flash gas bypass and parallel compression. A case study offers and explains possible solutions on basis of a new system design. The system, which comprises novelties with respect to the design, is installed by BITZER at its St. Marys site in Australia. The potential for an improved energy efficiency with parallel compression is shown for a state-of-the-art transcritical CO2 booster system with flash gas bypass, which is installed by BITZER at its Rottenburg site for practical training seminars since autumn 2010.

The renewable energy such as wind or solar power plays an important role in a modern power system. Due to low reliability of renewable energy source, uncertainty in a system is increasing. There are many models proposed for managing systems with renewable energy. However, these models are complicated and not computationally efficient when applied to large scale problems. In this work, we propose a stochastic model which incorporates uncertainty in renewable energy. A two-stage recourse model is used for our stochastic model with finite scenarios. Additionally, we increase a spinning reserve power of the system by adding a reserve from renewable energy. The additional reserve is computed from the expected value of renewable energy serving the system. Moreover we propose an analysis process to determine a suitable spinning reserve level once the renewable energy introduced to a conventional power system.

The atmosphere concentration of CO2 is steadily increasing and causing climate change. To achieve the Paris 1.5 or 2 oC target, negative emissions technologies must be deployed in addition to reducing carbon emissions. The ocean is a large carbon sink but the potential of marine primary producers to contribute to carbon neutrality remains unclear. Here we review the alterations to carbon capture and sequestration of marine primary producers (including traditional ‘blue carbon’ plants, microalgae, and macroalgae) in the Anthropocene, and, for the first time, assess and compare the potential of various marine primary producers to carbon neutrality and climate change mitigation via biogeoengineering approaches. The contributions of marine primary producers to carbon sequestration have been decreasing in the Anthropocene due to the decrease in biomass driven by direct anthropogenic activities and climate change. The potential of blue carbon plants (mangroves, saltmarshes, and seagrasses) is limited by the available areas for their revegetation. Microalgae appear to have a large potential due to their ubiquity but how to enhance their carbon sequestration efficiency is very complex and uncertain. On the other hand, macroalgae can play an essential role in mitigating climate change through extensive offshore cultivation due to higher carbon sequestration capacity and substantial available areas. This approach seems both technically and economically feasible due to the development of offshore aquaculture and a well-established market for macroalgal products. Synthesis and applications: This paper provides new insights and suggests promising directions for utilizing marine primary producers to achieve the Paris temperature target. We propose that macroalgae cultivation can play an essential role in attaining carbon neutrality and climate change mitigation, although its ecological impacts need to be assessed further. To calculate the parameters presented in Table 1, the relevant keywords "mangroves, salt marshes, macroalgae, microalgae, global area, net primary productivity, CO2 sequestration" were searched through the ISI Web of Science and Google Scholar in July 2021. Recent data published after 2010 were collected and used since area and productivity of plants change with decade. For data with limited availability, such as net primary productivity (NPP) of seagrasses and global area and NPP of wild macroalgae, data collection was extended back to 1980. Total NPP and CO2 sequestration for mangroves, salt marshes, seagrasses and wild macroalgae were obtained by the multiplication of area and NPP/CO2 sequestration density and subjected to error propagation analysis. Data were expressed as means ± standard error.

Heavy trucks contribute significantly to climate change, and in 2020 were responsible for 7% of total Swedish GHG emissions and 5% of total global CO2 emissions. Here we study the full lifecycle of cargo trucks powered by different energy pathways, comparing their biomass feedstock use, primary energy use, net biogenic and fossil CO2 emission, and cumulative radiative forcing. We analyse battery electric trucks with bioelectricity from standalone or combined heat and power (CHP) plants, and pathways where bioelectricity is integrated with wind and solar electricity. We analyse trucks operated on fossil diesel fuel and on dimethyl ether (DME). All energy pathways are analysed with and without carbon capture and storage (CCS). Bioelectricity and DME are produced from forest harvest residues. Forest biomass is a limited resource, so in a scenario analysis we allocate a fixed amount of biomass to power Swedish truck transport. Battery lifespan and chemistry, the technology level of energy supply, and the biomass source and transport distance are all varied to understand how sensitive the results are to these parameters. The scenario spans 100 years into the future. We find that pathways using electricity to power battery electric trucks have much lower climate impacts and primary energy use, compared to diesel and DME based pathways. The pathways using bioelectricity with CCS result in negative emissions leading to global cooling of the earth. The pathways using diesel and DME have significant and very similar climate impact, even with CCS. The robust results show that truck electrification and increased renewable electricity production is a much better strategy to reduce the climate impact of cargo transport and much more primary energy efficient than the adoption of DME trucks. This climate impact analysis includes all fossil and net biogenic CO2 emissions as well as the timing of these emissions. Considering only fossil emissions is incomplete and could be misleading. This dataset contains data on 4 metrics (primary energy use, biomass feedstock use, cumulative CO2 emissions, and cumulative radiative forcing) resulting from scenario modeling of cargo truck use in Sweden powered by different energy pathways. The energy pathways include battery electric trucks powered by bioelectricity, solar photovoltaic electricity and wind electricity, and internal combustion trucks powered by fossil diesel and dimethyl ether. The scenario spans 100 years into the future. The Excel sheet "tables" contains input data for the scenario modeling, with sources listed where applicable. The remaining sheets contains the modeled results and generated figures that are also a published in the associated article Sathre & Gustavsson (2023). Refer to the method description and reference list in the included documentation files for details. Tunga lastbilar bidrar kraftigt till klimatförändringarna och stod 2020 för 7% av de totala svenska växthusgasutsläppen och 5% av de totala globala CO2-utsläppen. Här studerar vi hela livscykeln för lastbilar som drivs av olika energivägar, jämför deras användning av biomassaråvaror, primär energianvändning, biogena och fossila CO2-utsläpp netto och kumulativ strålningstvingning. Vi analyserar batterielektriska lastbilar med bioel från fristående eller kraftvärmeverk och vägar där bioel integreras med vind- och solkraft. Vi analyserar lastbilar som drivs med fossilt dieselbränsle och med dimetyleter (DME). Alla energivägar analyseras med och utan avskiljning och lagring av koldioxid (CCS). Bioelektricitet och DME produceras av skogsavverkningsrester. Skogsbiomassa är en begränsad resurs, så i en scenarioanalys avsätter vi en fast mängd biomassa för att driva svenska lastbilstransporter. Batteriets livslängd och kemi, tekniknivån för energiförsörjning och biomassakällan och transportavståndet varierar alla för att förstå hur känsliga resultaten är för dessa parametrar. Scenariot sträcker sig 100 år in i framtiden. Vi finner att vägar som använder el för att driva batterielektriska lastbilar har mycket lägre klimatpåverkan och primär energianvändning, jämfört med diesel- och DME-baserade vägar. De vägar som använder bioelektricitet med CCS resulterar i negativa utsläpp som leder till global kylning av jorden. Vägarna med diesel och DME har betydande och mycket liknande klimatpåverkan, även med CCS. De robusta resultaten visar att elektrifiering av lastbilar och ökad förnybar elproduktion är en mycket bättre strategi för att minska godstransporternas klimatpåverkan än införandet av DME-lastbilar, och mycket mer primärenergieffektiv. Denna klimatkonsekvensanalys omfattar alla fossila och biogena CO2-utsläpp samt tidpunkten för dessa utsläpp. Att bara ta hänsyn till fossila utsläpp är ofullständigt och kan vara missvisande. Detta dataset innehåller data om 4 mätvärden (primär energianvändning, biomassaråvara, kumulativa CO2-utsläpp och kumulativ strålkraftspåverkan) som härrör från scenariomodellering av lastbilsanvändning i Sverige som drivs av olika energivägar. Energivägarna inkluderar batterielektriska lastbilar som drivs av bioelektricitet, solcellselektricitet och vindkraft samt förbränningsbilar som drivs av fossil diesel och dimetyleter. Scenariot sträcker sig 100 år in i framtiden. På arket "tables" i Excelfilen återfinns den indata som använts i modelleringen med angivna källor där detta är tillämpligt. Övriga ark innehåller resultat samt figurer som också publiceras i den samhörande artikeln Sathre & Gustavsson (2023). Se metodbeskrivning samt referenslista i tillhörande dokumentationsfiler för detaljer.