Optimization of Micro Multi-Carrier Energy Hub Operation Under Uncertain Predictions

Finding an optimal schedule(s) for the buildings' energy equipment cluster is vital to realize sustainable development and energy-saving goals. However, high-impact uncertainties pose critical challenges in this regard. To relax these challenges, this paper develops an optimization model for operating the buildings' energy equipment cluster under uncertain predictions whose principal elements are the energy hub (EH) concept and the two-point estimate (TPE) method. The EH concept is used to find levels of the degree of freedom for optimization by modeling efficiently how multi-carrier energy resources and demands can be connected through this cluster of converters, conditioners, storage, and others. The TPE method is, however, used to improve the reliability and robustness of the model's predictions, leading to better decision-making under uncertainty. The TPE method integrates high-impact uncertainties related to multi-carrier energy prices and demands and the production capacity of renewable energy resources in optimization. The proposed optimization model has been applied to an industrial building, and its sufficiency and profitableness are examined in different scenarios.