Implementation Of Distributed Autonomous Control Based Battery Energy Storage System For Frequency Regulation

It has been mandated that 5% of the generation capacity of conventional fossil fuel power plants shall be used exclusively for frequency regulation (FR) purposes in South Korea. However, the rotational speed of generators cannot be controlled quickly, and thus the variation in the power generation for FR takes some time. Even during this short period of time, frequency fluctuations may occur, and the frequency may be out of range of its reference value. In order to overcome the limitations of the existing FR method, 374 MW (103 MWh) battery energy storage systems (BESSs) for FR have been installed and are in operation at 13 sites in South Korea. When designing the capacity of BESS for FR, three key factors, i.e., the deployment time, duration of delivery, and end of delivery, are considered. When these times can be reduced, the required capacity for BESS installation can be decreased, achieving the same operational effects with minimal investment in the facilities. However, because a BESS for FR (FR BESS) needs to be installed under a large capacity, providing a single output, a centralized control method is employed. The centralized control method has the advantage of being able to view and check the entire system at once, although in the case of FR BESS, a novel system design that can optimize the above three factors through a faster and more accurate control is required. Therefore, this paper proposes the implementation of a distributed autonomous control-based BESS for frequency regulation. For the proposed FR BESS, the central control system is responsible for the determination of external factors, e.g., power generation/demand forecasting; and the system is designed such that the optimal control method of renewable energy sources and BESS according to real-time frequency variations during practical operation is determined and operated using a distributed autonomous control method. Furthermore, this study was verified through the simulation that the proposed distributed autonomous control method conducts FR faster than an FR BESS with conventional centralized control, leading to an increase in the FR success rate, and a decrease in the deployment time required (e.g., 200 ms).