A hierarchical coupled optimization approach for dynamic simulation of building thermal environment and integrated planning of energy systems with supply and demand synergy. (15th April 2022)

• Record Type: Journal Article
• Authors: Huang, Yuan; Kang, Jiguang; Liu, Liu; Zhong, Xiaoyi; Lin, Jian; Xie, Shan; Meng, Chao; Zeng, Yizhang; Shah, Nilay; Brandon, Nigel; Zhao, Yingru
• Is Part Of: Energy conversion and management. Volume 258(2022)
• Publication Date: 2022-04-15
• Subjects: Dynamic simulation -- Hierarchical coupled optimization -- Energy saving retrofit -- Supply and demand synergy -- System planning; Direct energy conversion -- Periodicals; Energy storage -- Periodicals; Energy transfer -- Periodicals; Énergie -- Conversion directe -- Périodiques; Direct energy conversion; Periodicals; 621.3105
• DOI: 10.1016/j.enconman.2022.115497
• Languages: English
• ISSNs: 0196-8904

Abstract

Graphical abstract: Highlights: A hierarchical coupled method reduces the computational cost of co-optimization. Synergistic planning of supply and demand further enhances economic and environmental benefits. Consider dynamic features of the thermal load to further exploit energy-saving potential. Excessive insulation of building envelope may lead to opposite effect for energy saving. Abstract: 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 cross-sectoral 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 demand-side 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 energy-saving 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.