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The RICO dataset: A multivariate HVAC indoors and outdoors time-series dataset
Full text linkIndoor temperature forecasting is an area of interest and importance as it contributes to improving HVAC systems control, thus reducing wasted energy and improving health and comfort. Acquiring high-quality transitory regime data for training Machine Learning models is challenging due to the scarcity of publicly available dataset. Additionally, such a dataset acquisition incurs high costs from repeated heating and cooling buildings in ranges of temperatures that go beyond normal operation thresholds. In response, we propose an open-source dataset called ‘RICO Dataset’. It is acquired in a dedicated and controlled physical test-building, alleviating potential issues encountered by digital simulation and modelling. It contains 305, four hours long 80-features rich multivariate transitory time series data from sensors in both internal and external environments sampled at a rate of one per minute.publishedVersio
Accuracy Analysis of a Commercial Photovoltaic Production Forecasting Solution in Norway
Full text linkThis technical report provides detailed analyses of the accuracy performance of a commercial photovoltaic production forecasting solution implemented for a building in Oslo, Norway. These analyses are based on forecasting and monitoring data collected from January 2025 to June 2025. The evaluation shows that the normalized mean absolute error (NMAE) is 3.5% on average for PV power forecasts and 2% for energy forecasts. Power forecasting errors range from 1.5% in winter to 5% in summer, increasing slightly with the forecasting horizon. Energy forecasting errors benefit from temporal aggregation, which smooths short-term inaccuracies, thus decreasing the summed energy forecasting error with increasing prediction horizon. The forecasting service tends to slightly underestimate production during high-output periods and overestimate during low-output periods. While absolute errors remain moderate, normalized metrics can appear inflated during low-production periods. Four service outages occurred during the evaluation period, resulting in 4% missing data and no automated fault alerts. Future studies are recommended to compare this commercial solution with simple data-driven models using the same inputs to better understand the sources of forecasting error.publishedVersio
Developing a framework to assess water smartness and sustainability of circular economy solutions in the water sector
Full text linkThe transition to a circular economy in the water sector is challenged by the lack of comprehensive tools to assess and compare the performance of innovative solutions across multiple sustainability dimensions. This study aims to develop a structured framework of indicators to support such assessments and guide the sector toward achieving the United Nations Sustainable Development Goals (SDGs). The framework was co-developed with stakeholders and encompasses technical, social, environmental, economic, and governance dimensions. It is organized into four hierarchical layers: dimensions, objectives, criteria, and indicators. Objectives were designed to be broadly applicable, while criteria and indicators were formulated to assess alignment with these objectives and capture the multifaceted nature of “water smartness.” The framework was tested and validated through workshops and structured engagement activities across six demonstration cases. Results from exploratory data analysis confirmed the framework's relevance for decision-making, highlighting its capacity to compare alternatives under diverse scenarios and its alignment with the SDGs. Additionally, the testing process pointed out the differentiated responsibilities of involved stakeholders, offering practical insights for advancing full-scale implementation of circular economy models in the water sector.publishedVersio
Impact of activating energy demand flexibility in the building stock: A case study of Norway as a highly electrified country in the European power market
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Experimental evaluation of density meters using liquid CO2 and their effect on volumetric to mass flow conversion for CCS
Full text linkCO2 capture and storage (CCS) is an important technology for reducing atmospheric CO2 emissions. Urgent climate targets require widespread implementation of CCS. CCS commands the deployment of measurement technology that enables accountability, process control, and reporting of the stored mass of CO2 to regulatory bodies. The metering needs through the CCS value chain encompass as a bare minimum mass flow rates and stream composition. Most CCS-suitable flow metering technologies measure volumetric flow rates; thus, density knowledge is needed for volumetric-to-gravimetric flow rate conversion. Mass flow measurement, or mass derived from combined volume and density measurements, is fundamental in all nodes where custody transfer occurs. In this work, three off-the-shelf density measurement technologies were tested. The technologies encompass a Coriolis meter, a Gamma-ray densitometer and a torsional resonator. Densities calculated using the Span-Wager equation of state were used as reference. To assess the capabilities of each technology, the experimental campaign encompasses a broad operation envelope relevant to CCS applications. The gamma-ray meter, calibrated in situ, presented the least deviation from the reference density. The Coriolis measurements were highly repetitive, suggesting that calibration with CO2 would improve the performance. Density measurements exhibited a high sensitivity to temperature; thus accurate reference temperature is required in the vicinity of the fiscal meters when deployed in the field.Experimental evaluation of density meters using liquid CO2 and their effect on volumetric to mass flow conversion for CCSpublishedVersio
Circularity Index and Benchmarks for Buildings: A Novel and Transferable Approach to Evaluating the Circularity Performance Tested in a Norwegian Context
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The Renaissance of Reuse in Norway: The Future Is Back
Full text linkSociety has historically valued labor and resources, including the intermediate and end products produced through them. Discarding these artifacts was seen as squandering valuable effort and resources, and waste was historically an activity to be avoided. This tradition was rapidly lost in many western countries, replaced by a more rapid linear approach whereby materials quickly went from cradle to grave in a linear system or economy. There has been a recent revival of the idea of moving back from this modern linear model, however, with increasing pressures from environmental degradation, climate change, material scarcity, and population growth. The recent resurgence in interest in circularity in Norway is assessed with an eye toward potential pitfalls, based on the past 75 years of modern building methods. How can society expect to move away from the linear approach if the buildings themselves were created within that paradigm?publishedVersio
Monitoring Optimisation of a Retrofitted Hydrogen Pipeline Using Markov State Model
Full text linkThe lower volumetric energy density of hydrogen compared to natural gas requires cost-effective transport solutions. Compressed hydrogen transport via pipelines has been considered the most economical for distances under 3000 km. Retrofitting existing natural gas pipelines is crucial for efficiently delivering hydrogen since it is expected to penetrate and decarbonize several sectors. However, its interaction with most metallic materials makes this approach challenging. Pipelines are often subject to cyclic loads due to pressure fluctuations, which can result in accelerated fatigue crack growth in hydrogen environments. This enhanced degradation reduces the expected lifetime of the infrastructure. Ensuring rigorous maintenance and inspection protocols is essential to detect potential structural defects and prevent failures. This study investigates further the issue of retrofitting pipelines for hydrogen transportation. Combining a physical model and the Markov state model, which helps consider the variable and stochastic nature of the pressure fluctuations, provides an inspection and maintenance plan for an existing pipeline connecting Norway and the United Kingdom. Copyright © 2025, AIDIC Servizi S.r.l.Monitoring Optimisation of a Retrofitted Hydrogen Pipeline Using Markov State ModelpublishedVersio
Alkali-silica reactions (ASR) in concrete dams – field survey, ND-testing and laboratory analyses
Full text linkThe main scope of the Norwegian R&D project "Excon" (2023-2025) is to contribute to extending the surface life of important concrete infrastructure and developing a decision-making tool that considers both economic and environmental factors. A sub-aim is developing innovative methods for non-destructive field survey, monitoring, and laboratory analysis of cored samples. Moreover, a review of methods for the repair of concrete structures with Alkali-Silica Reactions (ASR) is also part of the project, with a focus on concrete dams. The project is mainly financed by the Norwegian Research Council, with supplementary funding and in-kind work from many industrial partners.
In the first part of the project, a review report on methods for non-destructive testing and monitoring was prepared. During 2024, some of these methods have been applied to selected case structures, among them three concrete dams. The focus was placed on monitoring of cracking caused by ASR. In addition to the “Cracking Index” (CI) method, crack detection by use of photogrammetry and advanced NDT measurements (ultrasound scanning) was also performed. One aim was to assess the accuracy of using those tools for the measurement of the extent of cracking. From all dams, samples were cored for laboratory analysis; Stiffness Damage Testing (SDT) for all dams, and microstructural analysis for Dam I.publishedVersio