In recent years, global energy shortages and environmental pollution have intensified. With the large-scale development of new energy wind energy, there is also a major problem-insufficient absorption capacity. In order to promote large-scale wind power consumption, a model predictive control method based on wind hydrogen coupled power generation system is proposed. Firstly, the mathematical models of equivalent state of charge in wind power, hydrogen energy storage systems (HESS), and gas storage tanks are analyzed. Secondly, the optimization objective function is to maximize the local wind energy consumption and minimize the energy interaction between the main grid. Establish an SSM prediction model based on the MPC strategy. Genetic optimization algorithm is used for rolling solution. Aiming at the interference and prediction error generated during the operation of the system, a feedback mechanism is introduced to embed it into the MPC framework. Then, the rolling time domain method is used to compensate for system interference. Finally, a case study was conducted based on actual measurement data from a certain area in the Netherlands. By comparing the wind power dissipation effects of the system during operation, it is verified that the proposed method can effectively reduce interactive power consumption. Maximize the local consumption of wind power.

Driven by the strategic goal of “dual carbon,” the electric power industry is entering a critical period of transformation and upgrading, and there is a growing demand for composite and applied talents who are both proficient in professional technology and good at management. Taking the electrical engineering and automation major of Liupanshui Normal University as an example, this study addresses existing challenges in current talent cultivation practices. By emphasizing the deep integration of theory and practice and aligning closely with industry needs, the study aims to ensure that the talent cultivation system is both forward-looking and practical. Focusing on key aspects such as the practical teaching system, practice platforms, teaching content, instructional methods, assessment and evaluation strategies, and resource optimization, a series of targeted measures are proposed. These measures aim to construct a comprehensive, multi-dimensional practice education system that enhances students’ practical innovation abilities and overall competencies. This approach not only improves the quality of talent cultivation but also serves as a valuable reference for the development of electrical engineering education in similar local colleges and universities.