Impact of data usage for forecasting on performance of model predictive control in buildings with smart energy storage

arXiv:2402.12539v1 Announce Type: cross
Abstract: Data is required to develop forecasting models for use in Model Predictive Control (MPC) schemes in building energy systems. However, data usage incurs costs from both its collection and exploitation. Determining cost optimal data usage requires understanding of the forecast accuracy and resulting MPC operational performance it enables. This study investigates the performance of both simple and state-of-the-art machine learning prediction models for MPC in a multi-building energy system simulation using historic building energy data. …

abstract arxiv building buildings collection control cost costs cs.lg cs.sy data data usage eess.sy energy energy storage exploitation forecasting impact mpc performance predictive smart storage systems type understanding usage