Explainable Artificial Intelligent as a solution approach to the Duck Curve problem

Abstract

This paper presents a new approach for solving the electrical load sharing problem generally known in energy circles as the Duck Curve problem. The Duck Curve problem is a curve showing the difference between the total electrical load a utility serves to its consumers (energy from thermal power plants), and what that load looks like after wind and solar generation (or local generation) has served a portion of that load (renewable resources or green energy). This approach based on unsupervised learning Long Short Term Memory (LSTM), with the attention mechanism, aims to give a clear interpretation of the Duck Curve prediction, and to understand the clear reasons for this discrepancy which can help decision makers to better interpret the curve and solve the problem efficiently. Information and Communication Technology (ICT) and Internet of Things (IoT) are necessary for the deployment of green energies. Therefore, the data from the different sensors can be used as a support to validate the information at the local production level and contribute in an effective and targeted way to solve the problem of the ”Duck Curve”.