Modeling and Forecasting Electricity Loads and Prices: A Statistical Approach

By Rafal Weron. 2006

913 citations recorded by the source corpus.

Subfields: Computer Vision and Pattern Recognition, Electrical and Electronic Engineering

View Paper: https://www.semanticscholar.org/paper/234811c79ba579eaf72697a35f767f9d37c81e8d

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Computer Vision and Pattern Recognition

In Electrical and Electronic Engineering

Citations in the corpus

Causal modeling and inference for electricity markets (2011, background): “The EEX market is generally assumed to be less mature than the Nordic market (Weron, 2006; Weigt and von Hirschhausen, 2008; Müsgens, 2006; Fridolfsson and Tanger̊as, 2009).”
Forecasting spot electricity prices: A comparison of parametric and semiparametric time series models (2008, methodology): “This approach was also inspired by the extensive research on demand forecasting, which has generally favored the multi-model specification for short-term predictions (Bunn, 2000, Shahidehpour et al., 2002, Weron, 2006).”
Prosumer bidding and scheduling in electricity markets (2016, methodology): “Our starting point is the ARX-model proposed by Weron [35] which is further elaborated and used at Nord Pool Spot-prices by Kristiansen [36].”
Robust Estimation in Signal Processing: A Tutorial-Style Treatment of Fundamental Concepts (2012, background): “IEEE SIGNAL PROCESSING MAGAZINE [74] JULY 2012 same time minimizes the costs and maximizes the security and reliability of an electrical power transmission system [59].”
Electricity price forecasting: A review of the state-of-the-art with a look into the future (2014, methodology): “As Weron (2006) observes, this may lead to confusion, since the names are not used consistently.”
An empirical comparison of alternate schemes for combining electricity spot price forecasts (2013, positive): “The air temperature was chosen as the exogenous (fundamental) variable; typically it is the most influential on electricity prices weather variable (Weron, 2006).”
Recent advances in electricity price forecasting: A review of probabilistic forecasting (2016, background): “The second on the list is Rafał Weron (Wrocław University of Technology, Poland) with 11 Scopus-indexed articles, including the most comprehensive EPF review to date – Electricity price forecasting: A review of the state-of-the-art with a look into the future [1] (103 citations since 2014); Weron ha”
Electricity price forecasting using sale and purchase curves: The X-Model (2015, background): “These are summarized as the stylized facts of electricity prices, see e.g. Weron (2006).”
Functional clustering and linear regression for peak load forecasting (2010, methodology): “A review of statistical methods for electrical load forecasting has been given by Weron (2006), for instance.”
Short-Term Load Forecasting Based on a Semi-Parametric Additive Model (2012, methodology): “models are widely adopted for the load forecasting problem, which include linear regression models, stochastic process models, exponential smoothing, and ARIMA models [2]–[7].”
Electricity markets around the world (2018, background): “These results are in line with many previous studies on the behavior of electricity spot prices, see, e.g. Clewlow and Strickland (2000); Weron (2006) who also point out that spot electricity prices are typically skewed to the right and exhibit extreme levels of kurtosis.”