Data analytics in the electricity market: a systematic literature review

In the last decade, data analytics studies have covered a wide range of fields across the entire value chain in the electricity sector, from production and transmission to the electricity market, distribution, and load consumption. It is essential to integrate and organize the wide range of current scientific publications to effectively allow researchers and specialists to implement and progress cutting-edge methodologies in the future. Because of the electricity market’s significance in the value chain of the electricity sector, in this study, we structure a systematic literature review of the data analytics-related works following the PRISMA (Preferred Reporting Items for Systematic Review and Meta-Analysis) framework to categorize the more common applications and approaches in the electricity market field. After refining the identified studies from the Web of Science database using the inclusion and exclusion criteria, 925 articles were chosen as the final pool of literature. Investigation of the extracted studies reveals that the application of data analytics in the electricity market can be clustered into four distinct groups: Prediction, Demand Side Management (DSM), Analysis of the market power, and Market simulation. Within the categorized applications, Prediction with 67% is the most frequent application of data analytics in the electricity market, followed by market simulation (14%), analysis of the market power (9%), DSM (7%), and other applications (3%).