ELECTRICITY PRICE FORECASTING: A SYSTEMATIC LITERATURE REVIEW INFORMED BY TEXT MINING

Abstract

Developing forecasting models is a difficult task. Particularly concerning electricity prices, accurately predicting their forthcoming values makes it possible to minimize planning risks. This fact becomes even more relevant in the current geopolitical scenario, represented by the war between Russia and Ukraine. Given the above, this paper presents a systematic review of the literature on electricity price forecasting (EPF) models. It presents a methodology that does a robust search of the literature, obtaining the most relevant papers (n = 554) that addressed this theme. Following that search, we: (i) constructed an attribute matrix of the publications, and (ii) presented a descriptive analysis based on bibliographic data, and network relationships. The sample period comprises the years 1991 to 2019, with an annual growth rate equal to 23.13% and an annual publication rate of 19 papers. Despite the increase in the number of studies on electricity price forecasting, the predominance of papers is produced in only a few countries. This fact reinforces the need to encourage research and development projects related to the energy market. It was also found that research collaboration networks are still weak, highlighting the need for new partnerships between countries, and research institutions. Thus, stimulating global energy security, as well as encouraging cooperation and technology transfer between countries, becomes relevant.