Modeling and Forecasting of Energy Prices using Non-stationary Markov Models versus Stationary Hybrid Models including a Survey of all Methods

In the competitive electricity markets, accurate price forecasting embody crucial information for producers and consumers when planning bidding strategies in order to maximize their benefits and utilities, respectively. This paper presents a succinct survey of energy price forecasting techniques and models. The two major groups of the models are the stationary and non-stationary time series models according to proposed classification. Using of Wavelet Transform and Hidden Markov Models (HMMs) have been recently proposed among these groups respectively. These two time series models have differently upgraded price forecasting. This paper proposes WT- based models and HMMs in detail with a modeling and simulation of the later in the Spanish electricity market.