[Clean and Low-carbon Transformation Path of the Electric Power Industry in Jiangsu Province Under the Dual Constraints of Pollution Reduction and Carbon Emission Reduction].

Against the backdrop of rapid economic development， Jiangsu Province is confronted with the dual strategic tasks of enhancing ecological environment quality and achieving carbon peaking and carbon neutrality. As a major source of carbon and pollutant emissions， the clean and low-carbon transformation of the power industry is of critical significance. Jiangsu Province is taken as the research object in this study， with the time frame spanning from 2025 to 2060. Under the baseline policy scenario （BAU） and two policy strengthening scenarios （STE1 and STE2）， a goal programming model is constructed， with the minimization of the total cost of the electricity supply as the objective， while the dual constraints of pollution reduction and carbon emission reduction are satisfied. Through the optimization of the power generation structure， the optimal transformation path for the power industry is explored. The results are as follows： ① The evolution of power supply costs under different scenarios was characterized by significant differences. The total cost was the lowest in the BAU scenario， while it was the highest in the STE2 scenario， mainly due to high terminal costs and a slow reduction process. The cost was high in the early stage but dropped in the later stage in the STE1 scenario， with a high proportion of clean energy. ② The characteristics of differences in the energy structure were prominent. In the BAU scenario， the proportion of coal power gradually decreased to 2.4%， forming a pattern of coordinated transition between traditional and clean energy； in the STE1 scenario， the proportion of clean energy exceeded 65%， but the system stability faced challenges； and in the STE2 scenario， coal power was retained at 23.8%， which could maintain power supply resilience， but the proportion of clean energy was relatively low. ③ The speed of coal power exit and the cost of carbon capture showed an inverse correlation. In the BAU scenario， coal power was gradually phased out， and the cost of carbon capture was moderate； in the STE1 scenario， coal power was rapidly phased out， and the cost of carbon capture was basically zero； and in the STE2 scenario， the exit of coal power was delayed， and the cost of carbon capture was the highest. Scientific references for promoting the clean and low-carbon transformation of the power industry in Jiangsu Province can be provided by the research results.