Nonlinear Adaptive Droop Control Method for the Battery Storage Systems Operating in DC Microgrids

Abstract

Conventional sources of energy like coal, gas, and oil are being depleted and renewable sources of energy are needed to meet ever-increasing energy demands. Renewable Energy Sources (RESs) like solar and wind can be potentially harnessed, however, high penetration of the RESs will introduce new challenges for the safe operation and control of future grids. To solve this problem, microgrids (MG) can be used to coordinate distributed energy resources in a decentralized fashion in order to ensure the reliability and efficiency of the local distribution network. Recently, there has been a great increase in the number of DC sources and loads leading to a need to develop DC MGs, which are more efficient and less costly. Despite the benefits of DC MGs, there are some challenges that need to be addressed in order to take full advantage of DC MGs and ensure the safe operation of the system under all operating conditions. This thesis proposes a decentralized control solution for energy storage systems (ESSs) in islanded DC MGs, namely a nonlinear adaptive droop controller. In the islanded mode of operation, the tight regulation of the DC-bus voltage is very challenging. The proposed decentralized control technique utilizes a nonlinear adaptive droop profile with adaptive parameters, which are able to regulate the DC-bus voltage tightly during various changes in loads/sources within a DC MG. The proposed controller does not need to identify between the charge and discharge operation modes. The adaptive control parameters can be determined by using three different strategies. In the first strategy, only one of two adaptive parameters in each mode of operation (charge and discharge modes) is unknown, which is determined from a look-up table. In the second strategy, a nonlinear Sequential Quadratic Programming (SQP) optimization technique is employed to derive the adaptive parameters. The proposed technique adaptively regulates the controller parameters according to the battery’s SoC and the DC MG voltage. In the third strategy, the fast charge and discharge voltages are assumed to be known. In this approach another droop controller, which is called the speed-droop controller derives the unknown parameters. The stability of the proposed control schemes is proven in this thesis, and the validity of the proposed schemes is proven through simulation and experimental results.