With the global energy structure transformation and the strengthening of environmental policies, the traditional power industry faces problems such as low resource allocation efficiency and environmental pollution, which has spurred the demand for green transformation of the power supply chain. This paper proposes a method of building a green supply chain information platform for electric power materials based on cloud computing, which utilizes advanced cloud computing technology and big data analysis to achieve efficient material management and optimized resource allocation. First, this paper develops a cloud platform for centralized data processing to support large-scale data storage and processing; second, this paper uses machine learning algorithms to analyze supply chain data, which is used to forecast material demand and optimize inventory management; in addition, this paper uses a real-time data visualization tool to improve the transparency and responsiveness of decision makers to the state of the supply chain. The value of this research lies in the fact that through the application of informationization and automation technology, it not only improves the operational efficiency of the power material supply chain, but also helps to reduce energy consumption and carbon emissions, and promotes the sustainable development of the power industry. From the perspective of energy consumption, from 500,000 kWh/year before implementation to 340,000 kWh/year in the 6th year after implementation, the enterprise is reducing energy consumption every year. Through the application of this platform, power enterprises can achieve accurate material procurement, optimize costs and minimize environmental impact, providing strong technical support and management optimization solutions for the green transformation of the power industry.