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Energies 2018, 11(8), 2093; https://doi.org/10.3390/en11082093

The Financial Effect of the Electricity Price Forecasts’ Inaccuracy on a Hydro-Based Generation Company

1
Management Engineering Department, Istanbul Technical University, Besiktas, Istanbul 34367, Turkey
2
Industrial Engineering Department, Istanbul Technical University, Besiktas, Istanbul 34367, Turkey
3
Biomedical Engineering Department, King’s College London, London SE1 7EU, UK
*
Author to whom correspondence should be addressed.
Received: 13 July 2018 / Revised: 7 August 2018 / Accepted: 8 August 2018 / Published: 11 August 2018
(This article belongs to the Special Issue Forecasting Models of Electricity Prices 2018)
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Abstract

Electricity price forecasting has a paramount effect on generation companies (GenCos) due to the scheduling of the electricity generation scheme according to electricity price forecasts. Inaccurate electricity price forecasts could cause important loss of profits to the suppliers. In this paper, the financial effect of inaccurate electricity price forecasts on a hydro-based GenCo is examined. Electricity price forecasts of five individual and four hybrid forecast models and the ex-post actual prices are used to schedule the hydro-based GenCo using Mixed Integer Linear Programming (MILP). The financial effect measures of profit loss, Economic Loss Index (ELI) and Price Forecast Disadvantage Index (PFDI), as well as Mean Absolute Error (MAE) of the models are used for comparison of the data from 24 weeks of the year. According to the results, a hybrid model, 50% Artificial Neural Network (ANN)–50% Long Short Term Memory (LSTM), has the best performance in terms of financial effect. Furthermore, the forecast performance evaluation methods, such as Mean Absolute Error (MAE), are not necessarily coherent with inaccurate electricity price forecasts’ financial effect measures. View Full-Text
Keywords: profit loss; electricity price forecasting; mixed integer linear programming; self-scheduling; hydro-based generation company profit loss; electricity price forecasting; mixed integer linear programming; self-scheduling; hydro-based generation company
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Ugurlu, U.; Tas, O.; Kaya, A.; Oksuz, I. The Financial Effect of the Electricity Price Forecasts’ Inaccuracy on a Hydro-Based Generation Company. Energies 2018, 11, 2093.

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