Optimization of integrated energy systems considering adaptive incentive-penalty tiered carbon trading and joint operation of carbon capture power plants-power to gas

A framework for adaptive tiered carbon trading and a multi-energy collaborative operation architecture are proposed to address the needs of enhancing low-carbon performance and ensuring operational reliability for the park-level integrated energy system. The framework optimizes the traditional tiered carbon quota trading mechanism via reward-penalty coefficients, calibrates key parameters through an adaptive algorithm, and establishes a dynamic reward-penalty tiered trading mechanism. The multi-energy architecture integrates carbon capture power plants, two-stage Power to Gas processes, combined heat and power units, hydrogen utilization, and diverse energy storage technologies. Flexible regulation is achieved through carbon capture power plants buffer tank retrofitting and joint power to gas-carbon capture power plants optimization. The Kalina cycle and electric boilers are employed to decouple the combined heat and power heat-to-power ratio, while demand-side response measures are embedded to construct a source-load collaborative model. To tackle the optimization challenges of large-scale multi-energy systems, researchers develop a multi-strategy fusion improved secretary bird optimization algorithm incorporating lens-imaging strategy and dynamic focusing technology. The algorithm’s superiority in optimization performance, convergence speed, and computational efficiency is validated using CEC2005 benchmark functions. An optimal scheduling model targeting minimum park-level integrated energy system operational costs is established. Case studies under five scenarios confirm the effectiveness and robustness of the proposed scheduling strategy in practical applications.