Abstract
The utilization of energy storage system (ESS) is an effective method for dealing with the randomness and variability of wind power. Therefore, improving the coordination between ESS and wind power is a direction worthy of research. This study develops a two-layer stochastic model predictive control (SMPC) method for wind power smoothing on different time-scales. The proposed optimization framework smooths wind energy by adjusting the charge and discharge power of hybrid ESSs; moreover, it combines the SMPC approach and the chance constraints to address the uncertainties of wind energy. Furthermore, the previous states are taken into account, in addition to states within the rolling time horizon, to obtain optimal control of the hybrid ESSs, and capacity planning for hybrid ESSs is conducted simultaneously. The numerical results obtained through amplitude-frequency simulation comparison prove that the proposed method is superior to the conventional method in terms of minimizing the frequency fluctuation of wind power and the size of the ESS.
Highlights
Microgrids are expected to play a significant role in the future because they meet network demands locally, which reduces the purchased power from the main grid, in addition to reducing power losses, and increases the reliability indices [1]
This study focuses on the problem of chance-constrained predictive control under the stochastic uncertainty of wind power
According to the characteristics of energy storage system (ESS), the lead acid battery unit is selected as the ESSup to store and dispatch wind energy, and the Ultra battery unit is selected as the ESSdown for rapid short-term smoothing [7]
Summary
Microgrids are expected to play a significant role in the future because they meet network demands locally, which reduces the purchased power from the main grid, in addition to reducing power losses, and increases the reliability indices [1]. The utilization of wind energy is an effective way to promote energy transformation in microgrids [2]. A. RELATED WORK In the literature, several studies have focused on the effective utilization of wind energy in microgrids. As a high-density and easy-to-control unit, an energy storage system (ESS) is an interesting option to reduce the risk of instability in a microgrid with wind power [3]. Sattar et al [5] examined the dynamic and transient performance of an ESS connected to the output of a wind energy conversion system to smooth the short-term fluctuations in the output power. Caralis et al [6] investigated the role that energy storage can play in the further development of wind energy in microgrids and examined the solution of ESSs in curtailment exploitation. The aforementioned studies have ignored the fact that the peak-valley characteristic and the fluctuation characteristic of wind power need to be dealt with on different time-scales
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