Medium-Term Probabilistic Forecasting of Extremely Low Prices in Electricity Markets: Application to the Spanish Case

Abstract

Abstract:One of the most relevant challenges that have arisen in electricity markets during the last few years is the emergence of extremely low prices. Trying to predict these events is crucial for market agents in a competitive environment. This paper proposes a novel methodology to simultaneously accomplish punctual and probabilistic hourly predictions about the appearance of extremely low electricity prices in a medium-term scope. The proposed approach for making real ex ante forecasts consists of a nested compounding of different forecasting techniques, which incorporate Monte Carlo simulation, combined with spatial interpolation techniques. The procedure is based on the statistical identification of the process key drivers. Logistic regression for rare events, decision trees, multilayer perceptrons and a hybrid approach, which combines a market equilibrium model with logistic regression, are used. Moreover, this paper assesses whether periodic models in which parameters switch according to the day of the week can be even more accurate. The proposed techniques are compared to a Markov regime switching model and several naive methods. The proposed methodology empirically demonstrates its effectiveness by achieving promising results on a real case study based on the Spanish electricity market. This approach can provide valuable information for market agents when they face decision making and risk-management processes. Our findings support the additional benefit of using a hybrid approach for deriving more accurate predictions.

Short-Term Price Forecasting Models Based on Artificial Neural Networks for Intraday Sessions in the Iberian Electricity Market

“…The MIBEL allows any consumer in the Iberian region (mainland of Portugal and Spain) to purchase electrical energy under a free competition regime from any producer or retailer acting in that region. It represents a regional electricity market with a remarkable growth of renewable energy production that frequently pushes the most expensive thermal power stations outside the generation scheduling of the wholesale market [1]. The MIBEL consists of the forward markets, managed by the company Iberian Energy Market Operator-Portuguese Division (OMIP) [2], and the daily and intraday markets, both managed by the company Iberian Energy Market Operator-Spanish Division (OMIE) [3].…”

Long Term Expected Revenue of Wind Farms Considering the Bidding Admission Uncertainty

“…Participation of wind farms in the electricity markets causes the prices to be decreased [32]. In a UP auction, wind farms show zero bidding behavior [33] and the mentioned uncertainty is nullified unless the market price takes a negative value.…”

Electricity Price Forecasting by Averaging Dynamic Factor Models

“…Some of them are the relative forecast error, and the mean (and median) average percentage error (MAPE). However, these measures are not valid when the data have negative and/or positive, but close to zero, values [40], a frequent occurrence for many electricity prices ( [21,41] deal with the issue of forecasting extreme prices in the Spanish electricity market).…”

“…Some examples of these variables are demand, weather conditions, fuel prices, production by technology and excess capacity. Interesting references are [21,41]. However, for this, it would be necessary to assess if the uncertainty in the prediction of the explanatory variables does not outweigh the improvement in the forecast of the price.…”