With extensive application of building information modeling(BIM),vast BIM model resources have accumulated from both new and existing projects.Digital twins,a key application of these models,face two main challenges:e...With extensive application of building information modeling(BIM),vast BIM model resources have accumulated from both new and existing projects.Digital twins,a key application of these models,face two main challenges:exponential growth in geometric and attribute data,risking data explosion,and low data utilization due to insufficient semantic association among multi-source data across projects and domains.This paper addresses the challenge of reducing system complexity via scenario-driven methods while achieving deep semantic integration of cross-domain BIM data.It proposes an ontology-based“Digital Theater”framework that defines data boundaries based on scenario requirements and employs dynamic trimming strategies to reduce complexity.By combining a simplified data standard with a multi-domain fusion ontology model,the framework constructs scenario-based data integration rules for semantic alignment.An adaptive relational database with object storage design further supports efficient engineering data storage and utilization.The proposed method significantly reduces the complexity of data processing,enabling the integrated application of multi-domain data at a lower cost while enhancing the decision-support capabilities of BIM data.This framework demonstrates potential for application in diverse scenarios,supporting engineering digitalization and smart city development.展开更多
微能源网是多能流耦合的微电网系统,为优化其设备容量配置,针对内部分布式可再生能源和负荷的不确定性,提出了综合范数约束下场景概率驱动的微能源网分布鲁棒规划方法。基于风-光出力和电-热-氢负荷的历史数据聚类提取典型场景,并构建基...微能源网是多能流耦合的微电网系统,为优化其设备容量配置,针对内部分布式可再生能源和负荷的不确定性,提出了综合范数约束下场景概率驱动的微能源网分布鲁棒规划方法。基于风-光出力和电-热-氢负荷的历史数据聚类提取典型场景,并构建基于1-范数和∞-范数约束的场景概率分布不确定集以描述源-荷不确定性。以年综合成本最低为目标建立min-max-min三层分布鲁棒规划模型,采用列与约束生成(column and constraint generation, C&CG)算法求解。仿真结果表明,引入所提场景概率不确定集和分布鲁棒模型后,系统年综合成本降低1.33%,且模型在经济性和鲁棒性的平衡方面相比传统随机优化和鲁棒优化更有优势,可在更短的迭代次数内降低年综合成本。展开更多
基金supported by the National Key Research and Development Program of China“Comprehensive Application Demonstration of Self-developed BIM Platform in the Full Life Cycle of Engineering Construction”(Grant No.2024YFC3809700)。
文摘With extensive application of building information modeling(BIM),vast BIM model resources have accumulated from both new and existing projects.Digital twins,a key application of these models,face two main challenges:exponential growth in geometric and attribute data,risking data explosion,and low data utilization due to insufficient semantic association among multi-source data across projects and domains.This paper addresses the challenge of reducing system complexity via scenario-driven methods while achieving deep semantic integration of cross-domain BIM data.It proposes an ontology-based“Digital Theater”framework that defines data boundaries based on scenario requirements and employs dynamic trimming strategies to reduce complexity.By combining a simplified data standard with a multi-domain fusion ontology model,the framework constructs scenario-based data integration rules for semantic alignment.An adaptive relational database with object storage design further supports efficient engineering data storage and utilization.The proposed method significantly reduces the complexity of data processing,enabling the integrated application of multi-domain data at a lower cost while enhancing the decision-support capabilities of BIM data.This framework demonstrates potential for application in diverse scenarios,supporting engineering digitalization and smart city development.
文摘微能源网是多能流耦合的微电网系统,为优化其设备容量配置,针对内部分布式可再生能源和负荷的不确定性,提出了综合范数约束下场景概率驱动的微能源网分布鲁棒规划方法。基于风-光出力和电-热-氢负荷的历史数据聚类提取典型场景,并构建基于1-范数和∞-范数约束的场景概率分布不确定集以描述源-荷不确定性。以年综合成本最低为目标建立min-max-min三层分布鲁棒规划模型,采用列与约束生成(column and constraint generation, C&CG)算法求解。仿真结果表明,引入所提场景概率不确定集和分布鲁棒模型后,系统年综合成本降低1.33%,且模型在经济性和鲁棒性的平衡方面相比传统随机优化和鲁棒优化更有优势,可在更短的迭代次数内降低年综合成本。
