Many studies have demonstrated the importance of clean energy development for China to meet its carbon peaking commitments and to contribute to solving world environmental problems. However, few studies have integrated spatial correlation and carbon peaking process to fully reveal the spatial spillover effects of carbon emissions and the urgency of emission reduction. The unexpected power cuts in 2020 poses a new requirement to deeply grasp China's clean energy development and carbon peaking attainment. To this end, the spatial econometric panel model and GM (1, N) are used to explore the development of clean energy, the spatial characteristics of carbon emissions, the process of carbon peaking, and the association between them. And all these are based on the real-life dilemma of power cuts and the underlying development-emission conflict in China. The results show that: (1) clean energy development in a region will increase local carbon emissions, but will significantly suppress carbon emissions in neighboring regions; (2) there is an inverted "U" curve relationship between clean energy development and carbon emissions, and China is still in the early stage of positive correlation; (3) fossil energy saved in a region tends to flow to neighboring regions with similar scale of economic development; (4) under the current development model, only 17% of the regions with clean energy development will be able to reduce emissions and successfully reach the peak by 2030, which implies a major emissions reduction challenge for China. The situation of carbon emission reduction in China is far from optimistic. Corresponding policy recommendations are given at the end. In short, we believe that greater clean energy support, stricter emission reduction policies, more diverse emission reduction approaches, and more synergistic emission reduction models are needed simultaneously.