An integrated energy system (IES) is considered to be an important supporting technology for emission reduction because it can effectively improve the efficiency of energy utilization and promote its sustainable development. Considering the uncertainties and operational conditions

this paper establishes a bilevel multi-objective optimization model for IES for the Smart Park from the standpoint of economy

technology and environment. The upper level with one objective reflects the economic cost composed of investment

operating and maintenance

etc. The lower level constructs three objectives

including pollution emission

operation costs and renewable energy utilization. Simultaneously

various equality and inequality constraints are addressed to satisfy the technical requirements. In addition

an improved MOEA/D-MC-DC algorithm (Multi Objective Evolutionary Algorithm through Decomposition Based on Monte Carlo and Decoupled Coding

MOEA/D-MC-DC) is presented for handling the complex and nonlinear bilevel multi-objective optimization problems with constraints. A genetic algorithm (GA) is used to solve the upper single objective

while MOEA is employed to cope with the multi-objectives of the lower level. Using three typical IESs in the Smart Park as examples

several simulations are carried out to verify the efficiency

applicability and universality of the proposed model and optimization algorithm. The results show that the proposed method can effectively optimize the configuration of an IES in various Smart Parks.