Wind Power Smoothing With Energy Storage System: A Stochastic Model Predictive Control Approach

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.

Comparative assessment of four low voltage fault ride through techniques (LVFRT) for wind energy conversion systems (WECSs)

“…ESS solutions are usually proposed for power smoothing or other long-term applications [41]. To utilize ESSs for LVFRT applications, it is imperative that the ESS employed has sufficient power and energy capacity, whereas the system specifications are usually given by the relevant SO and apply to all generating units.…”

Model Based Predictive Control Strategy for Grid-Connected Wind Energy System

“…The suggested system includes a boost converter, which can bring the voltage from the input up to a higher level. This converter is included into the system so that a greater amount of electricity may be generated by the system and sent to the grid [15]. The boost converter is a kind of DC-DC converter that maintains a steady output voltage while simultaneously increasing the input voltage.…”

A novel output power determination and power distribution of hybrid energy storage system for wind turbine power smoothing

“…In Ref. [13,14], the turbine output power is allocated by employing the model predictive control and Kalman filter, respectively. The main challenges in these references are as follows: satisfying the grid restrictions, ensuring the microgrid stability, minimising the exchanged energy of ESS, and regulating the ESS SOC.…”

“…These power fluctuations affect the performance of loads connected in the vicinity of these RESs. In the worst case, if the RES capacity is considerable compared to the grid power, the microgrids, these power fluctuations may lead the system to instability [1,2].…”

“…The fluctuations are transferred to the HESS, and the smoothed input power is injected into the microgrid or utility grid. The wind turbine power is calculated by Equation (1).…”