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

机译:一种面向建筑热环境动态模拟和供需协同能源系统集成规划的层次耦合优化方法

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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.
机译:在城市能源系统低碳转型过程中,由于模型和方法的粒度不一致,不同部门协同规划在建模复杂度、优化精度和计算成本方面面临挑战。本研究提出了一种面向城市能源系统供需侧跨部门协同规划的层次耦合优化方法。将基于状态空间法的不同需求侧节能改造的热负荷仿真与整个能源系统的混合整数线性规划相结合。该方法在保留需求侧动态特性的同时,实现了时变多维过程的降阶描述,解决了仿真和优化中的精度和尺度差异问题。案例研究表明,最优需求侧策略可使建筑节能48.20%,而最优供给侧技术全年可减少36.77%的排放。被动节能与主动节能相结合后,整个系统的减排率可进一步提高6.16%~30.42%。同时,与基线情景相比,本方案中的协同优化方案使成本净现值下降了24.22%,总碳排放量下降了50.35%。这意味着,通过整合多种建筑改造策略和可再生技术,可以进一步挖掘集成系统的节能减排潜力。这种分层方法有助于设计有效的跨部门协同解决方案,实现整个系统的经济效益和环境可持续性的合理权衡。总体而言,本研究整合了供需部门的不同模式和方法,为城市能源系统的低碳设计和运营管理提供灵活、集成的解决方案。

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