A hybrid model for day-ahead electricity price forecasting: Combining fundamental and stochastic modelling

The accurate prediction of short-term electricity prices is vital for effective trading strategies, power plant scheduling, profit maximisation and efficient system operation. However, uncertainties in supply and demand make such predictions challenging. We propose a hybrid model that combines a techno-economic energy system model with stochastic models to address this challenge. The techno-economic model in our hybrid approach provides a deep understanding of the market. It captures the underlying factors and their impacts on electricity prices, which is impossible with statistical models alone. The statistical models incorporate non-techno-economic aspects, such as the expectations and speculative behaviour of market participants, through the interpretation of prices. The hybrid model generates both conventional point predictions and probabilistic forecasts, providing a comprehensive understanding of the market landscape. Probabilistic forecasts are particularly valuable because they account for market uncertainty, facilitating informed decision-making and risk management. Our model delivers state-of-the-art results, helping market participants to make informed decisions and operate their systems more efficiently

Analyzing Europe’s Biggest Offshore Wind Farms: A Data Set with 40 Years of Hourly Wind Speeds and Electricity Production

We provide an open, available, and ready-to-use data set covering 40 years of hourly wind speeds and synthetic hourly production signals for the 29 biggest offshore wind farms in Europe. It enables researchers and industry experts to include realistic offshore time series into their analyses. In particular, we provide data from 1980 to 2019 for wind farms already in operation and those that will be in operation by 2024. We document in detail how the data set was generated from publicly available sources and provide manually collected details on the wind farms, such as the turbine power curves. Correspondingly, the users can easily keep the data set up to date and add further wind farm locations as needed. We give a descriptive analysis of the data and its correlation structure and find a relatively high volatility and intermittency for single locations, with balancing effects across wind farms

Data Set for the paper "High-Resolution Working Layouts and Time Series for Renewable Energy Generation in Europe: A Data-Driven Approach for Accurate Fore- and Nowcasting"

The data in this repository consists of 7 files. This includes a readme file [readme.txt], three zip-files including onshore wind, offshore wind and photovoltaic layouts for each year and network nodes per country [offshore_wind_working_layouts.zip], [onshore_wind_working_layouts.zip], [PV_working_layouts.zip], and three zip-files including onshore wind, offshore wind and photovoltaic generation time series for each country and year [offshore_wind_generation.zip], [onshore_wind_generation.zip], [PV_generation.zip]. Each file can be downloaded separately or collectively by clicking the "Download all"-Button. </p