Dynamic Modeling, Monitoring and Control of Energy Storage System

Today there is a great interest on the small scale renewable electricity generation due to the changing economics and the demand for highly sustainable electricity generation. However, renewable energy sources are unreliable and fluctuating which causes variation of power flow. In this situation, there can be server problems such as frequency oscillations, violation of the power line capability jeopardizing the security of the power system. Batteries can be an emerging technology which acts as the fast acting spinning reserve that can balance between the load and generation. Conversely, it very difficult to accurately predict battery performance and the total cost of the investment of storage system by integrating batteries to the renewable system as batteries in this situation have to bear a wide range of the operational conditions . Henceforth, modeling of the battery is extremely important. This master thesis gives the dynamic modeling of the batteries which can replicate the relevant behavior of the battery. The proposed methodology is the model based approach where the parameters are determined to develop a suitable model. In this thesis, the battery is modeled as an R-C circuit comprising of elements each of which represents certain battery characteristics. An appropriate model is selected based on the comparative study of the characteristics of experimental output of the battery using model identification. Parameters of the battery are computed in the MATLAB Simulink parameter estimation toolbox using least square estimation .The initial parameter values for the simulink are found with the help of the lab test. Validation results from the two experimental data shows that the model can accurately estimate the battery characteristics with an error of 0.3%.The aforementioned battery model is later used to make an appropriate charge controller. The methods used in the thesis performed quite well within the limited tests performed during the experimental works. To use the model online in the future, further investigation is recommended in order to refine the model