An adaptive virtual inertia control strategy for distributed battery energy storage system in microgrids. (15th October 2021) - Xing, Wei; Wang, Hewu; Lu, Languang; Han, Xuebing; Sun, Kai; Ouyang, Minggao
Abstract: Recently with the large-scale access of renewable energy into power system through power electronics, distributed energy systems attract more attention. However, low inertia decreases the voltage or frequency stability and anti-disturbance capability of systems, causing power quality is vulnerable to the intermittency and uncertainty in photovoltaics or wind plants. Therefore, the virtual inertia control (VIC) is proposed to maintain system stability. This paper proposes a virtual adaptive inertia control (VAIC) strategy. The states of energy storage battery packs (ESBPs) are estimated online by the dual extended Kalman filter. Then the virtual inertia and droop parameters are designed through the fuzzy logic and virtual battery algorithms based on battery states and bus voltage fluctuations, aiming at distributing inertia and power in the dynamic and steady periods respectively. The stability is analyzed using the small signal model, and its feasibility is verified on the Matlab/Simulink platform. In microgrids with multiple ESBPs, the VAIC distributes power and inertia among ESBPs considering their different capabilities of power supplying and the system requirement for inertia. It can suppress the voltage fluctuations, improve the system stability, and achieve the decentralized and coordinated control during the whole running process of microgrid. Highlights: A novel distributed inertia control method for DC microgrid is proposed. The virtual battery algorithm is used for steady power allocation. Dual extended Kalman filter algorithm provides batteries' real-time states. The small-signal model is established to analyze the stability. The adaptive virtual inertia is designed and allocated by fuzzy logic algorithm.