UC Merced

The accelerating deployment of lithium-ion batteries within stationary energy storage facilities across the United States, notably driven by California, has sparked a notable surge in their usage, giving an opportunity for the first time to analyze their performance. In this thesis, the real-world data reported in Energy Information Administration datasets are used to quantify the efficiency of the plants, investigate parameters that effectively change the efficiencies, and analytically model the efficiencies. By quantifying the efficiencies, it is observed that plants experiencing more than five cycles per month show around 85% efficiencies, while for a lower number of cycles, the efficiency drops severely. Also, by analyzing the change of efficiencies with time, it was observed that the degradation of efficiencies is less than 0.1% per year. Moreover, a model is proposed which expresses efficiency in terms of number of monthly cycles. According to the model, newer plants show slightly higher efficiencies, which could be attributed to technological advancements in making batteries. Additionally, using the model, the drop in the efficiency of some plants with an infrequent number of monthly cycles could be justified by the recorded idle loss values in the literature; however, the drop is more significant for other plants. Therefore, the loss could be related to parasitic losses for the latter plants. Lastly, some plants show slight seasonal variations in the observed efficiencies, which could be related to the cooling and heating of the parasitic loads. However, it also might be associated with seasonal variations in the number of monthly cycles of the plants. More research could be done to analyze the efficiency's seasonal variations by separating the two mentioned factors.