Effect of the Digital Transformation of Power System on Renewable Energy Utilization in China

Abstract

Power system based on renewable energy is the development direction of power system of China. To further boost the development of China's power industry, the digital transformation of power industry is underway. This study examined the panorama of digital transformation of power industry of China. Through an analysis of digital transformation's effect on renewable energy utilization, three business applications that affect renewable energy utilization were identified: short-term prediction of renewable energy output, renewable energy equipment maintenance, and intelligent power-grid maintenance. The implementation process and effect of the above three business applications are analyzed in detail. The typical representative regions of renewable energy development in China are selected as cases, the effect of the digital transformation of power industry on the efficiency of renewable energy utilization was empirically investigated using the following data covering 2012-2019: the short-term prediction accuracy of renewable energy output, the reduction in the mean time to the fault restoration of renewable energy equipment to the industry average, the reduction ratio of the mean time to power grid fault restoration to the industry average, and the rate of renewable energy utilization. The results indicated that digital transformation boosted the efficiency of renewable energy utilization. Based on the findings, suggestions are proposed for improving the digital transformation of power industry and thereby promoting renewable energy utilization. The first suggestion is to emphasize the scale efficiency of digital application in early stage of digitization and renewable energy development, and emphasize the technical performance of digital application in middle and later stage of development. The second suggestion is to enhance data accuracy, such as meteorological data, historical data for renewable energy power stations, power equipment status data, and strengthen the application of algorithms and computational models. The third suggestion is to improve the overall digitalization rate of the power industry.

Reviewing the impact of AI on renewable energy efficiency and management

“…AI techniques have been employed for modeling, prediction, and forecasting of wind farming data, contributing to the reliable operation of renewable energy systems (Asif, 2020). Moreover, the digital transformation of power systems has been identified as a means to enhance data accuracy and strengthen the application of algorithms and computational models, thereby improving the utilization of renewable energy in various contexts, including China (Zhao et al, 2021). Furthermore, the development of end-state visions to implement digital monitoring in nuclear plants has highlighted the shift from labor-intensive preventative maintenance to cost-effective predictive maintenance, emphasizing the potential advantages of predictive maintenance 4.0, such as increased productivity and reduced downtime (Walker et al, 2022).…”

How Does Enterprise Digital Transformation Affect Total Factor Productivity? Based on the Information Intermediary Role of Analysts’ Attention

“…From a macro perspective, China's urban digital transformation can improve cities' resilience to COVID-19 by promoting social communication, collaborative governance, and resilience [11], and the development of the digital economy has improved the investment efficiency of green finance in China's provinces [12], promoted rapid economic growth, improved people's living standards, improved the effective use of resources, and enhanced environmental protection [13]. Digital transformation in China's power system can improve the utilization efficiency of renewable energy [14] and bring energy-saving effects to various cities in China through technological optimization and industrial upgrading [15].…”

Wind Power Development in China Case in Qinghai-Tibet Plateau

“…Data measurement and equipment maintenance problems will be better solved by the digital transformation of power. Thus, improving the utilization rate of wind power energy in China [6].…”