Robust uncertainty-aware control of energy storage systems using biased renewable energy forecast

Jangkyum Kim, Yoon-Sik Yoo, Hyo Sik Yang and Ho Seon Choi

Applied Energy, 2024, vol. 367, issue C, No S0306261924006925

Abstract: This study presents a novel building energy management system scheme addressing the challenges of biased photovoltaic voltage prediction and optimal energy management methods applicable to existing infrastructure. A biased PV prediction model is proposed to obtain predictions aligned with the intended uncertainty tendencies. In addition, an energy management scheme is introduced to increase energy efficiency by reducing the overall cost without requiring additional controllable power sources. Furthermore, a control scheme for optimizing the operational cost while considering the occupants’ thermal discomfort is proposed by analyzing the occupancy rate in the building and implementing appropriate temperature settings and elevator operations. This approach has the advantage of minimizing overall electricity cost while considering the users’ dissatisfaction, without the installation of additional controllable power resources. Here, the feasibility of the proposed approach is demonstrated through a reduction in the daily electricity cost and peak power by 8.56% and 11.75%, respectively, compared with scenarios without a proper building energy management system. These results demonstrated the effectiveness of the proposed building energy management system for achieving energy efficiency and cost savings in practical building environments. The proposed scheme can be used in buildings with diverse users to reduce energy consumption and overall building cost.

Keywords: Building energy management system; Energy storage system; Photovoltaic voltage prediction; Renewable energy uncertainty; Biased prediction (search for similar items in EconPapers)
Date: 2024
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DOI: 10.1016/j.apenergy.2024.123309

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