智能建筑环境及分布式能源系统整体动态优化与调度

Dynamic optimization and scheduling of energy production, supply, and consumption are key scientific problems during the operation of an intelligent building environment and its distributed energy resources for building a comfortable, healthy, economical, energy efficient, low emission smart space. We plan to find modeling methods of uncertain characteristics such as weather parameters outside buildings, occupants' space-time distribution, data mining algorithms of PMV zones in comfort and energy efficiency modes for thermal environment operation. Base on priori knowledge and pricing policies of different energy resources, we will present a soft measurement model of the energy production and environmental pollution costs as well as the on-time capacity estimation models for these resources. We will also build thermal (cool) or electrical energy consumption predictive fuzzy models using modeled uncertain characteristics. An artificial system model of the building environment and distributed energy resource system comprises models mentioned above. We aim to explore multiple objective article swarm optimization and mixed integer linear programming methods based on the artificial system under conditions of limited energy resource capacity or unlimited energy consumption in order to search for optimal operating schadules of buiding engergy consumption units and thermal comfort setpoints for local comfort control systems, along with a performance evaluation method for optimation and schaduling methods of thermal (cool)/electrical engergy comsuption in intelligent building environments. The research program would contribute not only to data based theory and method of integration of management and control for complex systems, but also to intellgient environments and green energy resource application technology as a multidisciplinary leading research field including building environment, energy resource application, and intelligent control.

智能建筑环境及分布式能源系统的能量"产-供-耗"一体化动态优化与调度是构建舒适、健康、经济、节能、减排等多目标的智能空间的关键科学问题。本项目拟研究基于数据和神经计算的建筑周围短期气象参数、环境人员时空分布等不确定性建模方法，提出舒适/节能模式PMV区间值的挖掘算法；构建基于先验知识和定价机制的能源生产和环境污染成本的软测量模型，以及实时能源容量估计模型；研究基于不确定性估计的设备冷热电能耗模糊建模方法，构建实际系统的人工系统模型。研究能耗无限制和供能受限条件下，基于该人工系统的多目标粒子群优化和混合整数线性规划方法，以寻求设备运行最优规划和热舒适度控制给定值；探索系统冷热电能量应用的优化与调度性能评价方法。该项目属于建筑环境、能源应用与智能控制等多学科交叉前沿方向，不仅对完善基于数据的复杂系统管控一体化理论和方法有促进作用，而且对我国智能环境和绿色能源应用技术具有重要价值。

智能建筑环境及分布式能源系统的能量"产-供-耗"一体化动态优化与调度是构建舒适、健康、经济、节能、减排等多目标的智能空间的关键科学问题。本项目拟研究基于数据和神经计算的建筑周围短期气象参数、环境人员时空分布等不确定性建模方法，提出舒适/节能模式PMV区间值的挖掘算法；构建基于先验知识和定价机制的能源生产和环境污染成本的软测量模型，以及实时能源容量估计模型；研究基于不确定性估计的设备冷热电能耗模糊建模方法，构建实际系统的人工系统模型。研究能耗无限制和供能受限条件下，基于该人工系统的多目标粒子群优化和混合整数线性规划方法，以寻求设备运行最优规划和热舒适度控制给定值；探索系统冷热电能量应用的优化与调度性能评价方法。四年来，共完成论文54篇，其中SCI论文13篇，EI论文18篇，发明专利2项，培养硕士研究生5名，参加国际会议并作分组报告13次。