As a clean energy source, hydrogen not only helps to reduce the use of fossil fuels but also promotes the transformation of energy structure and sustainable development. This paper firstly introduces the development status of green hydrogen at home and abroad and then focuses on several advanced green hydrogen production technologies. Then, the advantages and shortcomings of different green hydrogen production technologies are compared. Among them, the future source of hydrogen tends to be electrolysis water hydrogen production. Finally, the challenges and application prospects of the development process of green hydrogen technology are discussed, and green hydrogen is expected to become an important part of realizing sustainable global energy development.

Transformers in the distribution network must have their carbon emissions analyzed in order to meet the “double carbon” goal. Using an oil-immersed distribution transformer as the research object, this paper develops a “cradle-to-grave” carbon accounting model. A life cycle assessment (LCA)-based methodology is proposed to account for carbon emissions and total energy demand over the full life cycle and further analyze the carbon emissions within each stage. A case study is presented using data from a 200 kVA transformer manufactured by a transformer plant in Xinjiang. According to the data, there are 112.18 t of carbon emissions and 798.21 GJ of total energy consumed. Distribution network transformers have carbon emissions of 282 kg, 782 kg, 122.96 kg, 11,079.64 kg, and −88.6 kg throughout the manufacture and manufacturing stage, transportation stage, construction and installation stage, operation stage, and waste recycling stage, respectively. There are 4.12 GJ, 9.06 GJ, 1.34 GJ, 785.97 GJ, and −0.28 GJ in total energy requirements. According to the study, which covered 99.03% of the entire life cycle, the operation stage had the largest percentage of carbon emissions. In addition to streamlining the production process and using more energy-efficient equipment, the waste recovery stage successfully decreased the environmental impact of carbon emissions. Sensitivity analysis shows that the silicon steel sheet and transformer oil has a significant impact on the carbon emissions of distribution network transformers during the life cycle, and the higher the grade of silicon steel sheet, the lower the carbon emissions, and the synthetic ester transformer oil has the most comprehensive performance and the lowest carbon emissions.

In the optimization scheduling of power systems containing renewable energy, to ensure that the scheduling results have higher security and better economy, this study proposes a multi-objective forecasting, scenario generation, and decision scheduling integrated stochastic optimal scheduling method. Firstly, to improve the accuracy and stability of wind-photovoltaic power forecasting, a novel multi-objective wind-photovoltaic forecasting model is proposed based on the Laguerre polynomial, pseudo-inverse learning, and hybrid multi-objective Runge-Kutta algorithm (HMORUN). Secondly, to deal with wind-photovoltaic uncertainty, scenarios with representative wind-photovoltaic uncertainty characteristics are generated by scenario generation and reduction techniques using wind-photovoltaic power forecast results. Finally, considering wind-photovoltaic output fluctuations, the degree of source-load matching, wind-photovoltaic utilization, and system economic efficiency factors, with the objective of maximizing the tracking of the load curve and minimizing system economic costs, a stochastic optimized scheduling model for power systems is established. This study uses HMORUN as a solution tool for the multi-objective stochastic optimization scheduling problem (MOSSP). This study uses constraint repair techniques to deal with the complex constraints of the MOSSP model to avoid system load shedding and minimize wind and photovoltaic generation curtailment. To verify the effectiveness of the proposed model, a 10-generator power system, including a wind farm and a photovoltaic plant, is used as a test case for simulation experiments and compared with other multi-objective scheduling models. The experimental results show that the proposed stochastic optimal scheduling model has higher safety and better economy.