To address the issues that carbon trading fails to cover the full life cycle and that traditional demand response achieves poor emission reduction due to a lack of accurate carbon-intensity feedback in park integrated energy systems (PIESs) during low-carbon transition, this study proposes a two-layer optimal scheduling method synergizing life-cycle stepwise carbon trading and low-carbon demand response (LCDR) to balance low-carbon performance and economic efficiency. Firstly, based on life cycle theory, embodied carbon from new energy equipment manufacturing and transportation is incorporated into accounting, with a stepwise carbon trading mechanism designed. Secondly, corrected dynamic carbon emission factors for power and heating networks are constructed to quantify real-time carbon intensity. A dual-driven LCDR model (electricity price and carbon factor) is established to coordinate shiftable and sheddable electric-thermal loads and is combined with a two-layer scheduling model (pre-scheduling and re-scheduling) targeting the minimal total operation cost. Simulation results of a South China park show that life-cycle stepwise carbon trading reduces emissions by 16.7%, and LCDR further cuts 4.05%. Their synergy achieves significant carbon reduction with a slight cost increase, while supplementary sensitivity analyses further confirm the scalability and robustness of the proposed framework under varying load levels and demand response capabilities.
Zhang et al. (Thu,) studied this question.