An Explainable AI-Based Framework for Supporting Decisions in Energy Management

Climate change and energy production and consumption are two inextricably linked concrete concepts of great concern. In an attempt to guarantee our future, the European Union (EU) has prioritized the addressing of both concepts, creating a new social contract between its citizens and the environment. The dazzling progress in its methodologies and applications during the recent years and the familiarization of the public with its abilities indicate Artificial Intelligence (AI) as a potential and powerful tool towards addressing important threats that climate change imposes. However, when using AI as a tool, it is vital to do so responsibly and transparently. Explainable Artificial Intelligence (xAI) has been coined as the term that describes the route of responsibility when implementing AI-driven systems. In this paper, we expand applications that have been previously built to address the problem of energy production and consumption. Specifically, (i) we conduct a survey to key stakeholders of the energy sector in the EU, (ii) we analyse the survey to define the required depth of AI explainability and (iii) we implement the outcomes of our analysis by developing a useful xAI framework that can guarantee higher adoption rates for our AI system and a more responsible and safe space for that system to be deployed.