Abstract: Under the "dual carbon" goal，the electric energy systems need to gradually develop towards the

way of energy saving and low carbon. The integrated energy system（IES）is an important measure to solve energy

and environmental protection problems. At present，the research on IES mainly focuses on distributed energy，

energy storage grid connection and multi-objective optimization. Intelligent algorithm is an essential way to deal

with optimization problems. However，with the complexity of the model，the traditional intelligent algorithms have

the problem of poor convergence and easy to fall into the local optimum. Centering on the objectives of economy，

environmental protection and stable operation，a multi-objective optimization model of IES based on improved

particle swarm optimization considering three indicators of economy，environmental protection and output

imbalance was built. Firstly，the IES model was established with the goal of optimizing the three indicators.

Secondly，the membership function and the analytic hierarchy process（AHP）were used to normalize and

determine the weight coefficient. Finally，the particle concentration evaluation operator was introduced to improve

the particle swarm algorithm to solve the proposed model，and the operating results of the system under singleobjective and multi-objective conditions were analyzed，which verifies the effectiveness of the model and

algorithm. The improved algorithm significantly improve the convergence speed and effectively avoide the particles

falling into the local optimum.

      Key words: integrated energy system（IES）；economic dispatch；energy conservation and environmental

protection；particle concentration；improved particle swarm optimization algorithm