Blar i SINTEF Open på forfatter "Löschenbrand, Markus"

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    • A data set of a Norwegian energy community 

      Berg, Kjersti; Löschenbrand, Markus (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 ...

    • Generating scenarios from probabilistic short-term load forecasts via non-linear Bayesian regression 

      Löschenbrand, Markus; Gros, Sebastien; Lakshmanan, Venkatachalam (Chapter; Peer reviewed, 2021)
      In this paper we present a simple and intuitive method for fitting a non-linear Bayesian regression model on short-term load forecasts. Such models have been implemented via Bayesian neural networks, which are known for ...

    • Market Power in Hydro-Thermal Systems with Marginal Cost Bidding 

      Löschenbrand, Markus; Korpås, Magnus; Fodstad, Marte (International Conference on the European Energy Market;, Peer reviewed; Chapter, 2018)
      Traditionally, electricity markets have been designed with the intention of disabling producer side market power or prohibiting exercising it. Nonetheless it can be assumed that players participating in pool markets and ...

    • Modeling competition of virtual power plants via deep learning 

      Löschenbrand, Markus (Peer reviewed; Journal article, 2020)
      Traditionally, models pooling flexible demand and generation units into Virtual Power Plants have been solved via separated approaches, decomposing the problem into parts dedicated to market clearing and separate parts ...

    • Modelling and Simulation Approaches for Local Energy Community Integrated Distribution Networks 

      Rana, Rubi; Berg, Kjersti; Degefa, Merkebu Zenebe; Löschenbrand, Markus (Peer reviewed; Journal article, 2022)
      Due to the absence of studies of local energy communities (LECs) where the grid is represented, it is very difficult to infer implications of increased LEC integration for the distribution grid as well as for the wider ...

    • Modelling Approaches for Local Energy Community 

      Rana, Rubi; Degefa, Merkebu Zenebe; Berg, Kjersti; Löschenbrand, Markus (SINTEF Rapport;, Research report, 2021)
      Due to the absence of well documented experiences from implementations of Local Energy Communities (LECs), it is very difficult to infer implications of increased LEC integrations for the distribution network as well as ...

    • Stochastic variational inference for probabilistic optimal power flows 

      Löschenbrand, Markus (Peer reviewed; Journal article, 2021)
      This paper applies a generative deep learning model, namely a Variational Autoencoder, on probabilistic optimal power flows. The model utilizes Gaussian approximations in order to adequately represent the distributions of ...

    • A systematic review of machine learning techniques related to local energy communities 

      Hernandez-Matheus, Alejandro; Löschenbrand, Markus; Berg, Kjersti; Fuchs, Ida; Aragüés-Peñalba, Mònica; Bullich-Massagué, Eduard; Sumper, Andreas (Peer reviewed; Journal article, 2022)
      In recent years, digitalisation has rendered machine learning a key tool for improving processes in several sectors, as in the case of electrical power systems. Machine learning algorithms are data-driven models based on ...

    • A transmission expansion model for dynamic operation of flexible demand 

      Löschenbrand, Markus (Peer reviewed; Journal article, 2020)
      This paper proposes a model to include investments in demand flexibility into traditional transmission expansion problems under uncertainty. To do so, a dynamic power flow model is proposed. The model is solved via applying ...

    • Trends in local electricity market design: Regulatory barriers and the role of grid tariffs 

      Maldet, Matthias; Revheim, Frida Huglen; Schwabeneder, Daniel; Lettner, Georg; Crespo Del Granado, Pedro; Saif, Aziz; Löschenbrand, Markus; Khadem, Shafi (Peer reviewed; Journal article, 2022)
      New concepts of local electricity markets (LEMs) have led increased focus on the decentralization of energy systems and a raise in local energy communities (LECs). Under the right market-regulatory incentives, peer-to peer ...