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D 3.3 Oxygen-carrier validation in CLC pilot units
(Research report, 2021) -
D1.4 Mapping, characterization and critical evaluation of the state-of-the-art
(ArbaHeat Deliverable;D1.4, Research report, 2019) -
D3.4 Fuel conversion phenomena
(Research report, 2022) -
D4.1 Status: legal/regulatory barriers for transboundary CO2 ship transport
(Working paper, 2020) -
D4.2 Legal and regulatory framework for Swedish/Norwegian CCS cooperation
(SINTEF Rapport;2022:00023, Research report, 2022)A description is provided of the legal/regulatory situation, as of early December 2021, for CO2 transport from Sweden/Preem AB to Norway/Northern Lights. CO2 transport from Sweden to Norway for the purpose of geological ... -
D5.3 Studies on CLC-CCS deployment and infrastructure development
(Research report, 2022-11-29) -
D6.4 - 3MWth CLC demonstration unit testing
(Research report, 2024) -
Data set for power system reliability analysis using a four-area test network
(Peer reviewed; Journal article, 2020)This article presents a test data set combining data relevant for power system reliability analysis, including network data, reliability data, basic interruption cost data, and exemplary operating state data. The data set ... -
A data set of a Norwegian energy community
(Peer reviewed; Journal article, 2021)This paper presents a data set designed to represent Norwegian energy communities. As such it includes household consumption data collected from smart meter measurements and divided into consumer groups, appliance consumption ... -
Data-driven Household Load Flexibility Modelling: Shiftable Atomic Load
(Chapter; Peer reviewed, 2018)To keep a stable power system, there should always be balance between the generation and consumption of electricity. In this study, a flexibility modelling method for atomic loads which is based on high resolution appliance ... -
Dataset for a Norwegian medium and low voltage power distribution system with industrial loads
(Peer reviewed; Journal article, 2023)This article presents a dataset for a Norwegian industrial medium voltage (MV) and low voltage (LV) electric power distribution grid with load time series. The raw dataset was collected in collaboration with the Norwegian ... -
Decarbonizing integrated chlor-alkali and vinyl chloride monomer production: Reducing the cost with industrial flexibility
(Peer reviewed; Journal article, 2023)Industrial demand response will become increasingly important in power grids with high shares of variable renewables, yet the existing knowledge on how the industrial electricity demand and flexibility will change with the ... -
Decarbonizing the European energy system in the absence of Russian gas: Hydrogen uptake and carbon capture developments in the power, heat and industry sectors
(Peer reviewed; Journal article, 2023) -
Decentralized Energy Management Concept for Urban Charging Hubs with Multiple V2G Aggregators
(Peer reviewed; Journal article, 2022)This work introduces a decentralized management concept for the urban charging hubs (UCHs) where electric vehicles (EVs) can access multiple charger clusters, each controlled by an aggregator. The given day ahead schedules ... -
Decentralized Production of Fischer-Tropsch Biocrude via Coprocessing of Woody Biomass and Wet Organic Waste in Entrained Flow Gasification: Techno-Economic Analysis
(Journal article; Peer reviewed, 2017)The present work addresses the techno-economics of the decentralized coproduction of Fischer-Tropsch biocrude and liquefied natural gas via thermochemical conversion of woody biomass and wet organic waste to syngas in an ... -
Decoupled Active and Reactive Power Controllers for Damping Low-Frequency Oscillations using Virtual Synchronous Machines
(Chapter; Peer reviewed, 2023)In this paper, a power oscillation damping (POD) controller embedded in virtual synchronous machines (VSMs) is proposed. This controller suggests the decoupled use of both active and reactive powers to damp low-frequency ... -
Deep Reinforcement Learning for Long Term Hydropower Production Scheduling
(Chapter; Peer reviewed, 2020)We explore the use of deep reinforcement learning to provide strategies for long term scheduling of hydropower production. We consider a use-case where the aim is to optimise the yearly revenue given week-by-week inflows ... -
Deep Sea Offshore Wind R&D Conference 24-25 January 2013
(SINTEF Energi. Rapport;, Research report, 2013) -
DeepWind-from Idea to 5 MW Concept
(Journal article; Peer reviewed, 2014)The DeepWind concept has been described previously on challenges and potentials, this new offshore floating technology can offer to the wind industry [1]. The paper describes state of the art design improvements, new ...