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-This paper presents a study of a DFIG wind power generation system for real-time simulations. For real-time simulations, the Real-Time Digital Simulator (RTDS) and its user friendly interface simulation software RSCAD are used. A 2.2MW grid-connected variable speed DFIG wind power generation system is modeled and analyzed in this study. The stator-flux oriented vector control scheme is applied to the stator/rotor side converter control, and the back-to-back PWM converters are implemented for the decoupled control. The real-wind speed signal extracted by an anemometer is used for a realistic, reliable and accurate simulation analysis. Block diagrams, a mathematical presentation of the DFIG and a control scheme of the stator/rotor-side are introduced. Real-time simulation cases are carried out and analyzed for the validity of this work.

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Due to the recent development of information and communication technology (ICT), various studies using real-time data are now being conducted. The microgrid research field is also evolving to enable intelligent operation of energy management through digitalization. Problems occur when operating the actual microgrid, causing issues such as difficulty in decision making and system abnormalities. Using digital twin technology, which is one of the technologies representing the fourth industrial revolution, it is possible to overcome these problems by changing the microgrid configuration and operating algorithms of virtual space in various ways and testing them in real time. In this study, we proposed an energy storage system (ESS) operation scheduling model to be applied to virtual space when constructing a microgrid using digital twin technology. An ESS optimal charging/discharging scheduling was established to minimize electricity bills and was implemented using supervised learning techniques such as the decision tree, NARX, and MARS models instead of existing optimization techniques. NARX and decision trees are machine learning techniques. MARS is a nonparametric regression model, and its application has been increasing. Its performance was analyzed by deriving performance evaluation indicators for each model. Using the proposed model, it was found in a case study that the amount of electricity bill savings when operating the ESS is greater than that incurred in the actual ESS operation. The suitability of the model was evaluated by a comparative analysis with the optimization-based ESS charging/discharging scheduling pattern.