Estimation of Power Generation and Consumption based on eXplainable Artificial Intelligence

Recently, various policy and technical efforts have been underway around the world to solve global warming. Major companies are also converting 100% of their electricity used inside the workplace to renewable energy. The most widely used PV energy in renewable energy has uncertainty and instability due to the nature of climate change, so accurate power generation prediction is essential, and power load prediction is required to increase energy efficiency. Although artificial intelligence technology is used in various ways to accurately predict it, it does not provide the basis for the result and the validity of the derivation process due to the black box problem of artificial intelligence technology. In this paper, we develop a PV power generation and power load prediction model using an explainable artificial intelligence model that increases the energy efficiency inside the workplace and derive a basis for the prediction results using an explainable artificial intelligence.