Abstract
Peak shaving is one of the most important applications of battery energy storage system. In order to prolong battery life or to study the relationship between the battery lifetimes, the charge-discharge cycles and the depth of discharge, constraints concerning charge-discharge cycles and depth of discharge should be added to the optimization model. Therefore, algorithms based on continuous models fail to solve this kind of problem. This paper presents a dynamic programming algorithm containing multi-modules of states. The remaining capacity is discretized and modularized. Tests are carried out using a set of predicted load data. The results show the effectiveness of the method.
This work was supported by National Natural Science Foundation of China (51037002) and the Major State Basic Research Development Program of China (2012CB215206).
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Dong, X., Bao, G., Lu, Z., Yuan, Z., Lu, C. (2011). Optimal Battery Energy Storage System Charge Scheduling for Peak Shaving Application Considering Battery Lifetime. In: Yang, D. (eds) Informatics in Control, Automation and Robotics. Lecture Notes in Electrical Engineering, vol 133. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-25992-0_30
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DOI: https://doi.org/10.1007/978-3-642-25992-0_30
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