Abstract

The optimized operation of integrated energy systems (IES) is of great significance to reduce carbon emissions and improve the overall efficiency of the system, at present, IES planning lacks comprehensive planning. As a response, in this paper, a grid-connected IES is proposed, which considers the complementarity of geothermal energy and solar energy and takes heat storage into account. The multi-objective optimization problem of IES is studied for the coupling mode of electric energy, heat energy and cold energy.Taking a multi-functional park as the research object, a multi-objective optimization model was established aiming at integrating operation cost, exergic efficiency and pollution gas emission penalty cost. MO-NSGA-II algorithm was proposed to solve the optimization model, and it was compared with MOI-PSO algorithm and MO-WA algorithm.The results show that MO-NSGA-II algorithm has stronger convergence, pareto solution set is obviously better than the other two optimization algorithms, and the solution set has better continuity and uniformity.Secondly, the comparison between IES and the traditional energy supply system proved the superiority of IES in multi-objective. The cost saving rate of IES was up to 57.3%, exergic efficiency was improved 39.5% and pollution emissions were reduced 54.8%. It also proved again that MO-NSGA-II algorithm had a good effect on solving the IES model in this paper.Then, we analyzed the cold, hot and electric energy hub scheduling diagram of the three algorithms and found that MO-NSGA-II algorithm had better self-regulation ability, and the coordinated output ratio of gas turbine and power grid was a key factor affecting the overall economic and environmental benefits of IES, which was strongly correlated with the operation strategy of the system.These results can provide reference for the optimization of integrated energy system and further tap the development potential of multi-energy system.

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