111 citations · 392 across the 9 of their papers we have counts for
9 papers
Distributional neural networks for electricity price forecasting
Grzegorz Marcjasz, Michał Narajewski, Rafał Weron +1
We present a novel approach to probabilistic electricity price forecasting which utilizes distributional neural networks. The model structure is based on a deep neural network that…
Probabilistic forecasting of German electricity imbalance prices
Michał Narajewski
The exponential growth of renewable energy capacity has brought much uncertainty to electricity prices and to electricity generation. To address this challenge, the energy exchange…
High-Resolution Peak Demand Estimation Using Generalized Additive Models and Deep Neural Networks
Jonathan Berrisch, Michał Narajewski, Florian Ziel
This paper covers predicting high-resolution electricity peak demand features given lower-resolution data. This is a relevant setup as it answers whether limited higher-resolution…
Optimal bidding in hourly and quarter-hourly electricity price auctions: trading large volumes of power with market impact and transaction costs
Michał Narajewski, Florian Ziel
This paper addresses the question of how much to bid to maximize the profit when trading in two electricity markets: the hourly Day-Ahead Auction and the quarter-hourly Intraday Au…
tsrobprep - an R package for robust preprocessing of time series data
Michał Narajewski, Jens Kley-Holsteg, Florian Ziel
Data cleaning is a crucial part of every data analysis exercise. Yet, the currently available R packages do not provide fast and robust methods for cleaning and preparation of time…
Changes in electricity demand pattern in Europe due to COVID-19 shutdowns
Michał Narajewski, Florian Ziel
The article covers electricity demand shift effects due to COVID-19 shutdowns in various European countries. We utilize high-dimensional regression techniques to exploit the struct…