On the Evaluation of Binary Event Probability Predictions in Electricity Price Forecasting

In this paper we present an evaluation framework for predictions of binary events in probabilistic electricity price forecasting. It employs the MSE-equivalent QPS together with the DM test and allows for further insights about deficiencies of the considered models. Additionally, techniques from the field of classification are considered, which extend our framework and are particularly suited for the evaluation of predictions of rare events. We consider binary events with direct applicability to a generators daily decision making such as profitability of a pumped-hydro storage plant and evaluate the respective forecasts statistically. We show that the task of forecast evaluation can be simplified from assessing a multivariate distribution over prices to assessing a univariate distribution over a binary outcome, fully characterized by a single probability.

• Publication year

  2019

• Venue

  Social Science Research Network

• Publication date

  2019-12-07

• Fields of study

  Engineering, Computer Science, Economics

• Identifiers
  DOI 10.2139/ssrn.3499541
• External record

  Open on Semantic Scholar

• Source metadata

  Semantic Scholar

• No claims are published for this paper.

• No concepts are published for this paper.

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