Different from the widely used volatility models with least square or maximum likelihood techniques in probabilistic forecast of prices, this paper proposes a reliable continuous ranked probability score-oriented predictive density construction strategy for day-ahead electricity prices. The proposed method ...
This paper aims to forecast the electricity prices in the day-ahead market (DAM) with complex recurrent neural networks (RNNs), which are powerful in predicting the sequential prices with lags of unknown duration between significant peaks in the price curve. Recently, the electricity markets have...
However, the prices of July 9–July 15 are relatively stable, and their results are good. Therefore, the proposed method may be more suitable for forecasting electricity prices during periods of the year which have historically shown stable electricity prices. 6. Conclusion Aiming at the time-...
In a competitive electricity market, forecast of energy prices is a key information for the market participants. However, price signal usually has a complex behavior due to its nonlinearity, nonstationarity, and time variancy. In spite of all performed researches on this area in the recent years...
Vogstadetc, A dynamic simulation model for long-term analysis of the power market, 14th... J. Valenzuela, M. Mazumdar, On the computation of the probability distribution of the spot market price in a... J. Contreras et al. ARIMA models to predict next-day electricity prices IEEE Trans....
[1] used an ARMA model to forecast next-day electricity prices for mainland Spain and Californian markets. A novel technique was proposed to forecast day-ahead electricity prices based on wavelet transform and ARIMA models in [2]. A more robust time series modeling, GARCH model, was developed...
Forecasting day-ahead electricity prices: A comparison of time series and neural network models taking external regressors into account Electricity price forecastTime series forecasting(S)ARIMA(X)Vector autoregressive modelLong-short term memory neural networkConvolutional neural network... M Lehna,F Schell...
However, the number remains above the 4.5 percent tolerance ceiling of the bank's 3 percent inflation target, as consumer prices picked up due to higher electricity and food costs amid a major drought. Meanwhile, the bank raised its inflation forecast for 2025 from 4.12 percent to 4.34 percent...
In the following article the crucial impact parameters of forward electricity prices and the relationship between forward and future spot prices will be assessed by an empirical analysis of electricity prices at the European Energy Exchange and the Nord Pool Power Exchange. In fact, price formation ...
Natural gas-fired generation is expected to inch up by 1.4pc from a year earlier to 1,719.4bn kWh in 2024 but then slide below 2023 levels to 1,695.3bn next year, as the higher prices suppress demand for gas. EIA said overall US electricity generation was 5pc higher...