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| On-Line Power Regulation of Wind-Photovoltaic-Storage-Hydrogen Coupling System Based on Weight Adjustment Model Predictive Control |
| Kong Lingguo1, Wang Jiaqi1, Han Zijiao2, Yan Huaguang3, Wang Shibo1, Liu Chuang1, Cai Guowei1 |
1. Key Laboratory of Modern Power System Simulation and Control & Renewable Energy Technology Northeast Electric Power University Jilin 132012 China;
2. State Grid Liaoning Electric Power Co. Ltd Shenyang 110006 China;
3. China Electric Power Research Institute Beijing 100192 China |
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Abstract With the proposal of carbon peaking and carbon neutrality, the development of renewable energy has become a top priority in the construction of a new green power system. The development and utilization of wind-photovoltaic-storage-hydrogen coupling system will become one of the best options to make full use of solar energy resources. Due to the intermittency and uncertainty of wind power generation, coupled with the randomness of load, the importance of source-storage-load research in dynamic power balance is gradually manifested. In addition, the working state of each unit in the coupling system is not the same, so enhancing the safety of the hydrogen storage system and the reliability of the electric storage system is an urgent problem to be solved in the wind-photovoltaic-storage-hydrogen coupling system. In this paper, an online power regulation method of wind-photovoltaic-storage-hydrogen coupling system based on weight regulation model predictive control is proposed to optimize and match storage-hydrogen power and wind- photovoltaic power in real time, aiming at the wind wave fluctuation and the dynamic response characteristics of hydrogen storage.
Firstly, the topological structure of the wind-photovoltaic-storage-hydrogen coupling energy system was constructed in Matlab/Simulink, and the state-space model of the coupling system was established. The power balance of the coupling system was taken as the goal, and hydrogen production power, fuel cell power and battery power were taken as the control variables. According to the characteristics of hydrogen energy storage and battery energy storage and the objective function of each constraint condition, it is transformed into the quadratic programming problem for solving. In the MPC controller, the weight factors are adjusted according to the state information of the energy storage system, and the parameter adaptive of the controller is realized. Finally, the closed-loop simulation of the power control layer and the energy management layer is completed, and the three different control methods are compared and analyzed.
The results show that: (1) the online power control method based on MPC can realize the online quantitative proportional regulation of the electric-hydrogen energy storage in the coupled system. (2) Based on the custom s-function, the MPC online controller with self-adaptive parameters is developed, and the closed-loop simulation verification of the system is completed, which provides a flexible and open online MPC optimization control module under Simulink environment for multi-input and multi-output systems such as wind-photovoltaic-storage-hydrogen. (3) By comparing three different control strategies, the simulation shows that although state control and fixed weight MPC control can maintain SOC and SOH in the maximum upper and lower limits, some energy storage device will be fully utilized while another energy storage device does not reach the ideal working condition, so the battery is more likely to overcharge or overdischarge. Hydrogen storage levels reached the warning range more often and the time for both to return to normal level was slower. Compared with MPC control which adopts state control and fixed weight factor, this paper changes MPC weight factor according to different working conditions. In the MPC control with adjustable weight, the battery is in the deep charge and discharge area for a shorter time, and the number of start-stop of electrolytic cell is less, thus increasing the flexibility of electric-hydrogen energy storage participation and system operation reliability.
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Received: 27 February 2023
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2023, Vol. 38 
