Study of electro-hydrogen cooperative optimization operation based on big data analysis

Abstract With the deepening of the energy transition, the electro-hydrogen synergistic system, as an important energy solution, is facing challenges such as prominent light abandonment and low utilization of photovoltaic (PV), which requires the adoption of a more intelligent and refined management of the electro-hydrogen synergistic system. Traditional control and management methods make it difficult to cope with the uncertainty and complexity of the system. This study aims to promote the intelligence and efficiency of electro-hydrogen synergistic systems by using big data analytics to explore the potential of big data application in the field of electro-hydrogen synergistic systems by collecting, modeling, and analyzing the operating parameters of electro-hydrogen synergistic systems. The research steps include the collection, modeling, and analysis of contact line and PV output parameters. Combined with the local outlier factor (LOF) algorithm and real-time control of the number of electrolyzers based on the PV output, the theoretical basis and technical support for the efficient operation of the electro-hydrogen synergistic system are provided. It is of great significance for solving the key problems of current energy systems.