In the background of “dual carbon”

the structure of power supply needs to be adjusted for the development of the new power system

and this system proposes higher demand of flexible adjustment of capacity such as energy storage. Therefore

the energy-technology-environment model(ETEM) is proposed for energy strategic transformation

and this model is a long-term power structure planning method considering energy utilization

energy storage technology development and environmental impact. Random events and variables keep coming out in long-term planning. To solve the uncertainty problem in unknown distribution characteristics

this study selects cumulative installed capacity and market maturity in the development of energy storage as two uncertainties

and introduces a Bayesian stochastic optimization method. The calculation results show that compared with traditional planning methods

the total cost of ETEM method achieves lower cost and carbon emissions. By using Bayesian stochastic optimization method to deal with the uncertainty of energy storage technology

energy storage cost data can result in a lower fitting error

and the economy and emission effects are better. The new ETEM planning model optimizes phased capacity planning and its low-carbon pathways to achieve the “dual carbon” goals earlier and more economically.