Optimization strategy of secondary frequency modulation based on dynamic loss model of the energy storage unit. (July 2022)

• Record Type: Journal Article
• Authors: Li, Cuiping; Li, Jing; Li, Junhui; Zhang, Xiaochi; Hou, Tao
• Is Part Of: Journal of energy storage. Volume 51(2022)
• Publication Date: 2022-07
• Subjects: Lithium battery -- Variable-parameter model -- Capacity loss -- Secondary frequency regulation -- Fuzzy control; Energy storage -- Periodicals; Energy storage -- Research -- Periodicals; 621.3126
• DOI: 10.1016/j.est.2022.104425
• Languages: English
• ISSNs: 2352-152X

Abstract

Abstract: When the Energy Storage System (ESS) participates in the secondary frequency regulation, the traditional control strategy generally adopts the simplified first-order inertia model, and the power allocated to each energy storage unit follows the principle of equal distribution. Therefore, it is impossible to consider the inconsistency of each internal unit for a long time, increasing capacity loss of the energy storage system, and the difficulty in improving the frequency regulation effect. This paper proposes an optimal control strategy based on the ESS unit loss and dynamic model. Firstly, we established the dynamic variable-parameter model of lithium batteries and gave the capacity loss of the Li-cell model. And then on this basis, we deduced the capacity loss of each unit to apply in the power system. Secondly, the requirements of Automatic Generation Control (AGC) signals to the differences between generator unit and ESS units are analyzed, and the output constraints of generator units and ESS are given, and the weight coefficients are determined by using the fuzzy control theory. Finally, a double-level control strategy considering frequency deviation rate and the capacity loss rate is formed, and the implementation process is given. The capacity loss of each ESS unit is 16.19% lower than that of the traditional method, and the frequency deviation of the regional power grid is effectively improved by more than 23.07%. The control strategy of this paper is of great significance for the design of a large-scale ESS control system. Highlights: The dynamic loss model of lithium battery was established. An improved Kalman algorithm considering capacity loss An adaptive control strategy of energy storage unit output based on fuzzy control theory is proposed. A generator output control strategy based on fuzzy control theory