太阳能与浅层地热能驱动的超低能耗建筑热环境一体化建模与优化

Developing the distributed renewable energy system for ultra-low energy consumption of buildings is a significant measure to deal with worldwide emergent issues of building energy efficiency and the pressure of environmental pollution. During thermal adjustment of bulding indoor environments driven by solar energy and shallow geothermal energy (S-SGE) system, many scientific problems and key technologies related to the integrated control of energy production, supply, and consumption process of the system are tremendous challenging. The proposed research program aims to present cleaning methods for data produced during building operation,mine these cleaned data to obtain occupancy characteristics of indoor thermal zones,realize multi-scale and integrated modeling of heating/cooling energy flow in energy production, transport, storage, and consumption processe of thmer zones, and to forecast energy demand. We also will reveal space-time relationship of heating/cooling energy flows produced by S-SGE system. We are going to comprehensively apply some novel theories and methods of intelligent modeling with fusion of knowledge, data and mechanism to the analysis and modeling in order to reveal the inherent relationship in multi-temporal scales of heating and cooling energy flow driven by multiple kinds of resources. Based on particle swarm optimization theory and method, we will not only study optimization strategies of the distributed reliable energy supply system , but also explore the theories and technologies of hierarchical collaborative optimal operation of the building and distributed S-SGE system systems according to different performance indices of each optimal problem to guarantee some key performances such as environmental friendship, energy efficiency, comfort, and reliability of multi-objective integrated optimal control the system using S-SGE resources. The proposal is among the frontier researches involved in multi-disciplines of control theory and engineering and electrical engineering, energy and power engineering, and building engineering. We believe that the research program will significantly promote not only the development of new energy technologies for buildings in China but also the research and application of the related subjects.

发展可再生分布式能源与建筑集成应用是实现建筑超低能耗、应对建筑节能与环境污染压力的重大举措，太阳能与浅层地热能（S-SGE）驱动建筑热环境调节过程中能量产供用集成控制涉及的科学问题与关键技术极具挑战性。本课题拟研究建筑运行数据清洗与建筑室内人员时空分布特性分析理论与方法；综合利用基于知识/数据/机理融合的智能建模新理论和方法，实现建筑热（冷）量产/输/储/用一体化能量流建模、能耗需求预测，揭示S-SGE驱动的热冷能量流多时空尺度内在关系；基于粒子群优化理论和方法，探索建筑热环境与S-SGE系统基于多指标分解的多层级协同优化调度理论与技术，实现建筑与可再生互补分布式供能系统运行的经济、节能、舒适、高效、可靠等多目标集成群控优化；搭建试验平台，验证所提新理论方法的有效性。本课题属控制、电气、能源、建筑等多学科交叉的前沿方向，对发展我国建筑新能源技术、相关学科的理论研究和应用具有显著促进作用。

发展可再生分布式能源与建筑集成应用是实现建筑超低能耗、应对建筑节能与环境污染压力的重大举措，太阳能与浅层地热能（S-SGE）驱动建筑热环境调节过程中能量产供用集成控制涉及的科学问题与关键技术极具挑战性。本课题研究了建筑运行数据清洗与建筑室内人员时空分布特性分析理论与方法；综合利用基于知识/数据/机理融合的智能建模新理论和方法，实现了建筑热（冷）量产/输/储/用一体化能量流建模、能耗需求预测，揭示了S-SGE驱动的热冷能量流多时空尺度内在关系；基于粒子群优化理论和方法，探索了建筑热环境与S-SGE系统基于多指标分解的多层级协同优化调度理论与技术，实现了建筑与可再生互补分布式供能系统运行的经济、节能、舒适、高效、可靠等多目标集成群控优化；搭建了试验平台，验证了所提新理论方法的有效性。本课题属控制、电气、能源、建筑等多学科交叉的前沿方向，对发展我国建筑新能源技术、相关学科的理论研究和应用具有显著促进作用。共完成论文121篇，其中SCI论文80篇，EI论文32篇，授权发明专利3项，培养博士研究生3名，培养硕士研究生5名，举办国内会议1次，参加国际会议并作分组报告13次，获省部级奖励1项。

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