Recent advances in electricity price forecasting: A review of probabilistic forecasting

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Demand Response for Home Energy Management Using Reinforcement Learning and Artificial Neural Network (2019, background): “More information about price forecasting by different techniques, the readers can refer to [29], [32].”
Forecasting day-ahead electricity prices: A review of state-of-the-art algorithms, best practices and an open-access benchmark (2020, background): “…series: where 𝜀 Z 𝑑 is the 24-dimensional vector of prediction errors of model Z for day 𝑑 , ‖ Z 𝑑 ‖ 𝑝 = ( The univariate version of the test has the advantage of providing a deeper analysis as it indicates which forecast is significantly better for which hour of the day [6,55,57,65,133,134].”
Energy Forecasting: A Review and Outlook (2020, background): “Recent advances in probabilistic electricity price forecasting can be found in [9].”
Forecasting: theory and practice (2020, background): “In recent years the focus on probabilistic forecasting grew rapidly, as they are highly relevant for many applications in energy trading and risk management, storage optimization and predictive maintenance, (Ziel and Steinert, 2018; Nowotarski and Weron, 2018).”