Optimal design of distributed energy systems in cold regions across renewable energy penetration rates

The low-carbon transition of integrated power systems drives a continuous rise in renewable energy penetration rate (REPR), which profoundly influences the optimal design and operation of grid-connected distributed energy systems (DES). Aiming at the issue that existing studies rarely consider the dynamic variation of REPR in optimal design, this paper establishes a multi-objective bi-level stochastic optimization model incorporating REPR on the power supply side. Typical scenarios are constructed using the Copula function, Latin Hypercube Sampling, and Wasserstein distance-based scenario reduction. Optimization solutions are carried out under multiple scenarios with REPR ranging from 0% to 100%. The impacts of REPR variations on the optimal configuration of DES are analyzed, and the differences in operational performance among various configuration schemes under the same REPR condition are further evaluated. Results reveal that with increasing REPR, Combined heat and power unit capacity declines and exits the system above 60% REPR, while ground source heat pump capacity rises sharply. Photovoltaic/Thermal system capacity increases initially and falls to zero at 100% REPR. When REPR is within the range of 0%–80%, considering REPR in the optimal design model can reduce the total system cost by 1.0%–10.0% and primary energy consumption by 4.4%–61.1%. CO 2 emissions increase slightly by 9.52% at 20% REPR but achieve a 49.8% reduction at 80% REPR. Thus, the dynamic evolution of REPR on the power supply side should be taken into account in DES optimal design, so as to avoid the mismatch between system configuration and actual operation.