A Review on Edge Computing in Smart Energy by means of a Systematic Mapping Study

Context: Smart Energy is a disruptive concept that has led to the emergence of new energy policies, technology projects, and business models. The development of those models is driven by world capitals, companies, and universities. Their purpose is to make the electric power system more efficient through distributed energy generation/storage, smart meter installation, or reduction of consumption/implementation costs. This work approaches Smart Energy as a paradigm that is concerned with systemic strategies involving the implementation of innovative technological developments in energy systems. However, many of the challenges encountered under this paradigm are yet to be overcome, such as the effective integration of solutions within Smart Energy systems. Edge Computing is included in this new technology group. Objective: To investigate developments that involve the use of Edge Computing and that provide solutions to Smart Energy problems. The research work will be developed using the methodology of systematic mapping of literature, following the guidelines established by Kitchenham and Petersen that facilitate the identification of studies published on the subject. Results: Inclusion and exclusion criteria have been applied to identify the relevant articles. We selected 80 papers that were classified according to the type of publication (journal, conferences, or book chapter), type of research (conceptual, experience, or validation), type of activity (implement, validate, analyze) and asset (architecture, framework, method, or models). Conclusion: A complete review has been conducted of the 80 articles that were closely related to the questions posed in this research. To reach the goal of building Edge Computing architectures for Smart Energy environments, several lines of research have been defined. In the future, such architectures will overcome current problems, becoming highly energy-efficient, cost-effective, and capacitated to process and respond in real-time.