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This paper proposes a Dynamic Integrated Resource Strategic Planning (DIRSP) model based on a semi-Markov decision-making process. Considering the policy transfer probability matrix, we discuss the influence of different policy portfolios and input intensity on the timing and scale of low-carbon transition during the power planning process. In addition, we discuss various planning scenarios from a socio-technical system transition perspective. Scenarios are compiled to compare the pathways of power planning in China during 2015–2050 under different policies, including a typical reproduction pathway with unchanged policy that maintains the original coal-dominated technology pathway, a de-alignment/re-alignment pathway where renewable energy power technologies develop from niches to mainstream while the planning time for peak coal power moves ahead in 10–20 years due to subsidies to renewable and carbon tax policy, and the substitution and reconfiguration pathways in which renewable energy technologies compete with coal power in parallel, in which coal power will peak by 2020 while wind power and solar power will realize large-scale development by 2020 and 2030, respectively. Case study on power planning in China indicates that the methodology proposed in our study can enhance our understanding on the low-carbon transition process and the interaction between energy policy and transition pathway

Dynamic Integrated Resource Strategic Planning Model: A Case Study of China’s Power Sector Planning into 2050