An adaptive virtual inertia control strategy for distributed battery energy storage system in microgrids

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 fre-quency 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 capa-bilities of power supplying and the system requirement for inertia. It can suppress the voltage fluctua-tions, improve the system stability, and achieve the decentralized and coordinated control during the whole running process of microgrid. (c) 2021 Elsevier Ltd. All rights reserved.

Automated summary

A virtual adaptive inertia control (VAIC) strategy is proposed in this paper to maintain system stability by estimating the states of energy storage battery packs (ESBPs) online and designing virtual inertia and droop parameters. In microgrids, VAIC can distribute power and inertia among ESBPs, improving system stability and achieving decentralized and coordinated control throughout the entire running process.