Abstract

With the advancement of global energy transformation, the rapid rise of the new energy industry has become a strategic highland that countries are eager to seize. The inherent instability and unpredictability of renewable energy production pose significant obstacles to the seamless operation of the power system. To address these challenges, this article employs text analysis, data-driven methods, and artificial intelligence technology in neologisms to conduct an in-depth international evaluation and comparative research on the power quality of the new energy industry. Using text mining techniques to conduct an in-depth analysis of new energy policy texts in various countries, revealing their policy characteristics and trends. At the same time, the combination of data-driven and artificial intelligence technology enables more accurate prediction and decision analysis. Based on the findings of this study, the United States has achieved a significant 35% enhancement in the quality of new energy electricity over the past decade, attributed to its consistent monitoring and improvement initiatives. Meanwhile, Germany, owing to its robust monitoring system, has witnessed a 25% improvement in electricity quality in the last five years. However, in developing nations like India and Brazil, approximately 60% of new energy projects encounter challenges related to grid connectivity and scheduling, resulting in a deterioration of electricity quality. In contrast, only 20% of developed countries have issues with grid access and scheduling. This phenomenon reflects that developing countries still need to increase investment and improve the layout of new energy industries and the construction of power grid infrastructure. Developing countries should actively learn from the successful experiences of developed countries in the new energy industry and power grid construction, formulate appropriate policy measures based on their national conditions, improve the quality of new energy electricity, and promote energy transformation and sustainable development.

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