In the context of intensified global climate change

the establishment of a new-type power system dominated by renewable energy sources is a core pathway to achieving the ‘dual carbon’ goals; however

its reliance on meteorological services has significantly increased. This paper systematically reviews the meteorological demands of the new-type power system in areas while identifying three major technical challenges in current electric meteorological services. Firstly

there are blind spots in the meteorological monitoring network covering renewable energy power plants and transmission lines

leading to insufficient acquisition of micro-meteorological data such as icing and snow cover under extreme conditions. Secondly

traditional numerical weather prediction has limited accuracy in forecasting power-related meteorological factors at high spatial and temporal resolutions and poor interpretability of extreme weather events. Thirdly

the depth of data fusion between meteorology and power systems is insufficient

making it difficult to support customised services tailored to the actual operational needs of power grids. To address these challenges

this paper proposes future technical development directions

including constructing a ‘satellite-radiosonde-ground’ integrated monitoring system to enhance full-element perception capabilities in special regions such as deserts

Gobi areas and high-altitude zones; the development of a multimodal forecasting approach that combines physical mechanisms with AI large language models and improves the spatial and temporal resolution of renewable energy power forecasting and grid fault warnings under extreme weather conditions; and creating specialised meteorological service products for power systems

deeply integrating meteorological data with grid dispatch and energy storage optimisation algorithms to achieve flexible load response and dynamic market risk management

thereby providing critical support for the large-scale integration of renewable energy and the ‘dual carbon’ goals.