• Energy Research
• NO close
• SE close
• SINTEF AS close

This dataset, in the context of the MultiPACK Project, describes the development of a CO2 air/water reversible heat pump, specifically investigating the domestic hot water (DHW) production operating mode. A dynamic model of the heat pump is developed with the software Simcenter Amesim. After validation against experimental data, the numerical model is utilized to predict the performance of the heat pump to varying hot water demand, evaporator air inlet conditions and high-pressure value, leading to the discussion of the optimal control strategy. A paper, based on this dataset, "Experimental and numerical investigation of a transcritical CO2 air/water reversible heat pump: analysis of domestic hot water production (14th Gustav Lorentzen Conference, Kyoto, Japan, 6th- 9th December 2020, DOI:10.18462/iir.gl.2020.1160).

In this dataset, the field data from an integrated CO2 refrigeration system installed in a supermarket located north of the capital of Lisbon was shared. The scheme of the refrigerating system is provided in Figure 1-2, while the installed capacities and main components characteristics are listed in Table 1 and Table 2, respectively.The system can meet AC demand by direct evaporation in the air handling units (AHUs) units. Due to the summer season and warm ambient temperatures, AC is applied to meet the temperature set-point inside the shop (Figure 2). Moreover, compressor racks and AHU units are shown only with a single symbol. The system consists of the LT compressor rack (three semi-hermetic compressors), the MT compressor rack (four semi-hermetic compressors), and the parallel compressor (PC) rack (four semi-hermetic compressors) for AC; a gas cooler (GC); MEs; liquid receiver, MT suction line accumulator; LT and MT evaporators, expansion valves (EVs), oil recovery system, and two rooftop AHUs. For each compressor rack, one compressor is equipped with an inverter to allow smoother capacity modulation. The PCs are organized in such a way that they can manage different suction pressures according to heat pump functionality and/or PC. The ME blocks were sized for vapor pre-compression (HPE) according to the climate profile of the region and liquid return (LE) in the case of liquid leaving the MT evaporators. The AHU comprises two identical rooftop units. These units deliver the entire heating and cooling capacity of the supermarket. CO2 is directly applied inside the heating and cooling coils of the AHUs. SH demand can be covered seamlessly by means of a 3-way valve allowing high pressure CO2 gas supply to the heating coils in the AHU. An increasing high pressure and separate heat pump functionality can be utilized to cover high heating demands. In summertime, the AHU’s cooling coils can be operated in two different ways: the first alternative is the DX downstream of the GC, i.e., the refrigerant expands from the high-pressure side directly into the coils where it is evaporated and enters the liquid receiver. The second alternative is using a low-pressure lift high entrainment ratio ejector (AC ejector). The AC ejector sucks the whole vapor of the AC evaporators to compress it to the receiver pressure level. The first alternative was in operation during the time period analyzed in this study; thus, the effect of AC ejectors will not be mentioned in the following sections. High-pressure lift and liquid ejectors are applied to return both vapor and liquid from the suction line accumulator to the liquid receiver.

Abstract This paper provides new empirical insights on the capital structure of project-financed LNG infrastructures and gas pipeline projects, by using data relating to projects whose financial close occurred between June 2004 and March 2011. Most results are consistent with the basic view of risk-averse funds suppliers. Especially, the projects located in risky countries and larger projects tend to exhibit lower debt ratios and less-concentrated equity ownerships. In addition, regasification projects appear to have a more diluted equity ownership. Methodological issues raised by the financing of these projects are also examined from a capital-budgeting perspective. In particular, the equity residual method, usually used by industrial practitioners to value these projects, should be adjusted.

The dataset presents, the estimation of the Multi-ejector performance in a supermarket, based on the compressor mass flow rates from a trained data-driven method, (refer to https://doi.org/10.18710/HS8QAH) and the comparison with the existing performance function based on operational conditions. The pilot installation used the dataset is in the frame of MultiPack, an EU funded project. The Multipack is an integrated R744 parallel compression system with expansion work recovery through Multi Ejector SolutionTM, providing: refrigeration, space heating and cooling, and hot water production as shown in Figure 1. The space cooling and heating are by two direct CO2 rooftop air handling units. Three compression groups were installed in the pilot. Three compressors for medium temperature level (MT comp), three compressors at Low-Temperature level (LT comp), and four units are dedicated for Air-Conditioning (AC comp) total installed electrical power for compressors and fans is 177 kW (Excluding air handling fans). A paper, based on this dataset, "Performance of integrated R744-packs Part 2 - Ejectors performance, a comparison of onsite measurements and model predictions" was published at a conference (Compressors Conferences).

The mass flow rates through a compressor can be calculated from the polynomial function the manufacturer is providing, or via methods based on energy balance in the system, Sawalha et al, (2017), and Piscopiello et at al. (2018), or the volumetric displacement of the compressor. Nowadays, with the wide utilization of data-driven models it is possible to train models that can predict with relatively high accuracy the requested parameters based on controlled/normal operation of the installation. In this dataset, the data, collected from the installation in a supermarket in Porto de MOS, for a part of the research activity of the MultiPACK Project is shared. It is aimed to compare between the methods of indirect calculation of compressors mass flow rates, with observed measurements from mass flow meters installed in the system. Additionally, the emphasis is given to the development and benefits of the data-driven model. A paper, based on this dataset, "Performance of integrated R744-packs Part 1 - Compressor mass flow estimation based on data-driven models using analytical methods and actual field measurement" was published at a conference (Compressors Conferences).

In Norway there has during the last 20 years been verified a trend of more damage to electrical appliances in general and electronic equipment in particular. This has been believed to be caused by cheaper and poorer electrical appliances but also increased voltage levels and levels of voltage swells to some of the customers in the low voltage network. The latter has partly been caused by stronger economic regulation of the Norwegian electric power network that has amongst others led to stronger utilization of the distribution network. Instead of strengthening the low voltage network with increasing load, many Utilities tend to step up the transformer and introduce larger voltage variations from the transformer LV busbar to the far end of the LV feeders. The paper describes the laboratory tests recently performed by SINTEF Energy Research of common electrical appliances immunity to voltage swells. Test procedure and test results are presented in the paper. A total of 62 electric appliances were tested for immunity against voltages swells until damages occurred or the maximum output voltage from the test generator of 230 V + 40 % was reached. Many of the tested 230V electrical appliances (television sets, computers, computer screens, music systems etc) are able to handle relatively severe voltage swells, 40 % overvoltage for up to 100 seconds.

Abstract Variable electricity generation from wind and solar influences the design of a cost-efficient and reliable energy system. This paper presents a method that uses stochastic programming to represent variable renewable electricity generation in long-term energy system models, and demonstrates this on a Norwegian TIMES model. First, we derive hourly PV- and wind-generation data by modifying satellite-based data, based on a comparison with historical generation data. Second, the satellite-based dataset is transformed into a manageable set of scenarios that is used as an input to the stochastic energy-system model. This is done using six different scenario generation methods. Third, we solve the energy-system model with three of the scenario-generation methods and evaluate the quality of the corresponding model value by stability tests. We demonstrate that scenarios generated from the six methods have significantly different moment-based and Wasserstein distance error relative to the dataset. Further, the energy system model results show that the number of scenarios needed to achieve stability differs between the three used scenario generation methods.

This paper presents a new approach to wideband modeling of tower footing grounding impedances. Appropriate representation of transmission tower footing impedances is essential in electromagnetic (EM) transient simulations for proper evaluation of overvoltages and flashovers in the system during fast-front transient conditions such as lightning strikes. In this paper, a field solver is used to precisely model the most popular types of tower footing grounding systems, i.e., rods, counterpoises, and ring electrodes, for a variety of dimensions and soil parameters. Results are stored in a lookup table and used for generating frequency-dependent models that are exported to EM transient simulators. The table and model generation tool can be used by utility companies to model tower footings while taking into account local variations along the right-of-way, such as local variations in soil resistivity. The presented examples show close agreement of results of lightning studies using developed electrode models included in EM tools, e.g., PSCAD, EMTP-RV, and ATP-EMTP. A sensitivity study shows that the maximum voltage at the tower top during a direct lightning strike can be up to 19% higher when using the adopted modeling procedure, as compared to a standard approach of using a fixed resistor equal to the power frequency resistance.

This data article refers to the paper "Analysis of residential EV energy flexibility potential based on real-world charging reports and smart meter data" [1]. The reported datasets deal with residential electric vehicle (EV) charging in apartment buildings. Several datasets are provided, with different levels of detail, aiming to serve various needs. The paper provides real-world EV charging reports describing 6,878 charging sessions registered by 97 user IDs, from December 2018 to January 2020. The charging reports include identifiers, plug-in time, plug-out time and charged energy for the sessions. Synthetic charging loads are provided with hourly resolution, assuming charging power 3.6 kW or 7.2 kW and immediate charging after plug-in. The non-charging idle time reflects the flexibility potential for the charging session, with synthetic idle capacity as the energy which could potentially have been charged during the idle times. Synthetic hourly charging loads and idle capacity are provided both for individual users, and aggregated for users with private or shared charge points. For a main garage with 33% of the charging sessions, smart meter data and synthetic charging loads are available, with aggregated values each hour. Finally, local hourly traffic density in 5 nearby traffic locations is provided, for further work related to the correlation with plug-in/plug-out times. Researchers, energy analysts, charge point operators, building owners and policy makers can benefit from the datasets and analyses, serving to increase the knowledge of residential EV charging. The data provides valuable insight into residential charging, useful for e.g. forecasting energy loads and flexibility, planning and modelling activities.