Multi-Objective Optimal Component Capacity and MPC-based Optimal Scheduling in Smart Apartment Building

• Published in: 2022 IEEE 1st Industrial Electronics Society Annual On-Line Conference (ONCON) pp. 1 - 6
• Main Authors: Tamashiro, Kanato, Krishnan, Narayanan, Hemeida, Ashraf Mohamed, Omine, Eitaro, Takahashi, Hiroshi, Senjyu, Tomonobu
• Format: Conference Proceeding
• Language: English
• Published: IEEE 09-12-2022
• Subjects: Buildings; Carbon dioxide; Costs; Industrial electronics; Model Predictive Control; Multi-Objective Op-timization; Optimal scheduling; Predictive models; Smart Apartment Building; Uncertainty
• DOI: 10.1109/ONCON56984.2022.10126681

In this study, we propose an optimization algorithm that achieves both optimal component capacity and high effi-ciency operation of a Smart Apartment Building (SAB). Multi-objective optimization is used to optimize component capacity, with the goal of minimizing the total cost and carbon footprint of the SAB. A Pareto front is then gener-ated to present flexibility to the SAB operator. For high efficiency operations, a Model Predictive Control (MPC)-based optimal scheduling method is used. This method can achieve higher operational efficiency than conventional methods by taking future data into account. Furthermore, it avoids over-integration of components by evaluating component capacities determined by a multi-objective optimization problem. As a result, compared to the base case, the MPC algorithm reduces operation costs by 73.0% and carbon emissions by 49.0%.