| Title |
A Study on Optimal Scheduling Model of Digital Twin-based Energy Storage System using Artificial Intelligence |
| Authors |
박향아(Hyang-A Park) ; 변길성(Gil-Sung Byeon) ; 김종율(Jong-Yul Kim) ; 김성신(Sung-Shin Kim) |
| DOI |
https://doi.org/10.5370/KIEE.2022.71.6.819 |
| Keywords |
Digital Twin; Machine Learning; Optimization; Power System; Energy Storage System |
| Abstract |
Recently, due to the digitalization of power systems, the convergence technology of power systems and ICT has become important, and with the development of operational technologies, the importance of intelligent energy management is increasing. The importance of energy management through intelligent operating technology is emerging. In this paper, a digital twin model simulated by empirical simulation was constructed using the empirical ESS measurement data information collected from the power system. An optimal operation plan model for ESS was established by simulating the state and environment of the system in the virtual space of the digital twin similar to the actual system. It aims to improve the stable operation and efficiency of ESS through rapid situational awareness and correct decision-making by applying a data-based machine learning model rather than an existing optimization-based operation model. |