Critical success factors for the implementation and management of energy cloud environments

Summary Energy management systems, both at the level of end‐users and companies and organizations, are migrating from a centralized way to cloud‐based environments, thus generating virtual environments for the users to manage their energy generation, storage, and consumption. This energy management system, also called Energy Cloud (EC), is driven by the distributed generation of renewable energies, electric vehicles, and new energy storage technologies, thus providing ample flexibility and autonomy to users. In this sense, the objective of this article is to identify, evaluate, and discuss the Critical Success Factors (CSFs) that impact the implementation and management of EC environments. For this, an approach based on a survey with experts and the Multi‐attribute Utility Theory multicriteria method was used, evaluating the impact levels of CSFs for EC by grouping them according to business areas and structuring them hierarchically in a decision tree. Thus, this research shows that the implementation of EC environments depends more heavily on the energy infrastructure, data management, and the computational systems that process this data. This shows the need for investments in infrastructure renewal and also in the development of new and innovative technological solutions for energy management. Another important result was the evidence of the centralizing role that the users who make up the EC environments have, demanding easier access to the technologies that make up this energy management trend, as well as greater freedoms and decision autonomy, establishing themselves in the role of free users in a dynamic and flexible energy market. This article identifies, evaluates, and discusses the Critical Success Factors that impact the implementation and management of cloud‐based energy management environments – Energy Cloud. Energy Cloud is driven by the distributed generation of renewable energies, electric vehicles, and energy storage technologies, thus providing flexibility and autonomy to users. The factors are hierarchically structured following the corresponding business area and, with the MAUT method, they are evaluated, generating relevant management insights regarding the development and implementation of these energy management environments.