A hierarchical coupled optimization approach for dynamic simulation of building thermal environment and integrated planning of energy systems with supply and demand synergy

In the low-carbon transition process of urban energy systems, synergistic planning with different sectors faces challenges in terms of modeling complexity, optimization accuracy and computational cost due to inconsistent granularity of models and methods. This study proposes a hierarchical coupled optimization method for crosssectoral synergistic planning for supply and demand sides of urban energy systems. It integrates thermal load simulation of different demand-side energy-saving retrofits based on state space method with mixed integer linear programming of whole energy systems. This method enables reduced-order description of the time-varying multidimensional process while preserving the dynamic characteristics of demand-side to solve the problems of precision and scale difference in simulation and optimization. The case study shows that the optimal demandside strategy enables 48.20% building energy-saving, while the optimal supply-side technology enables 36.77% emission reduction throughout the year. The emission reduction rate of the whole systems can be further increased by 6.16%~30.42% after the combination of passive and active energy-saving means. Meanwhile, compared with the baseline scenario, the synergistic optimization solutions in this case results in a 24.22% decrease in net present value of cost and a 50.35% decrease in total carbon emission. This means that the energysaving and emission reduction potential of the integrated systems can be further exploited through the integration of multiple building retrofit strategies and renewable technologies. This hierarchical approach helps to design effective cross-sector synergistic solutions that achieve a reasonable trade-off of economic benefits and environmental sustainability of the whole systems. Overall, this study integrates different models and approaches of the supply and demand sectors to provide flexible and integrated solutions for low-carbon design and operation management of urban energy systems with building energy-saving retrofit.

Automated summary

This study proposes a hierarchical coupled optimization method for cross-sectoral synergistic planning in urban energy systems, integrating different models and methods to provide flexible and integrated solutions. The case study demonstrates significant improvements in energy-saving and emission reduction through synergistic optimization.