Carbon emissions and energy consumption of urban buildings represent a notable fraction of global energy utilization. In pursuit of the “carbon peaking and carbon neutrality” goals

urban park building integrated energy system (IES) energy saving technology is regarded as a key technology to achieve sustainable urban development. Therefore

a bi-level optimal capacity allocation method for the park energy supply/storage equipment has been developed in this paper. Flexible load demand response and energy supply reliability are fully considered. First

heterogeneous data analysis of smart park is conducted and models of energy conversion devices and storage devices based on the energy supply/storage characteristics of park IES are established

along with operational constraint models for various equipment. Second

at the upper level

the optimization aims to minimize the park IES cost. The operational cost is minimized in the lower level. The source/storage capacity configurations are optimized by genetic algorithm. In this paper

operational optimization is incorporated into planning

and flexible load control schemes are applied to peak load shifting

contributing to alleviated energy demand pressure during peak periods. Finally

the superiority role of the proposed bi-level optimization method is proved by case studies demonstrated by a real park IES and the effectiveness and feasibility of the data processing methods in improving the quality and accuracy of load data were also verified. The developed methodology enhances economic benefits

fully meeting the multi-energy demand of the system.