| 保障舒适度的城市建筑电力节能优化 |
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| 引用本文： | 王晓晶,陈星莺,余昆,彭堃. 保障舒适度的城市建筑电力节能优化[J]. 现代电力, 2019, 36(4): 38-47 |
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| 作者姓名： | 王晓晶 陈星莺 余昆 彭堃 |
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| 作者单位： | 1.新疆大学电气工程学院,新疆乌鲁木齐 830046; |
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| 基金项目： | 新疆维吾尔自治区高校科研计划青年教师科研启动基金 (XJEDU2016S033);国家自然科学基金 (51577051);自治区引进高层次人才天池百人计划;新疆大学博士科研启动基金(BS150253) |
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| 摘 要： | 提高城市建筑用电系统集控的智能化水平是低碳建筑、节能减排的重要途径,而舒适是城市建筑的重要功能之一,将舒适与节能相结合研究城市建筑的电力节能优化具有重要意义。分析城市建筑空调、照明和电梯三类用电系统的能耗组成,建立相应的能耗指标。研究城市建筑舒适度的内涵,并分析舒适度随季节、天气、温度、人流量等因素变化所带来的不确定性,在此基础上,建立热舒适度、光舒适度和乘梯舒适度指标。分析城市建筑节能优化是具有不确定性因素的优化问题,提出节能不以降低用户舒适满意度为代价,建立以用电系统总能耗最小为目标函数,以舒适度为满足给定置信度水平的机会约束条件的优化模型。采用改进PSO算法对优化模型进行求解。通过算例分析,验证本文建立的保障舒适度的城市建筑节能优化模型及优化算法的有效性。
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| 关 键 词： | 能耗指标 舒适度指标 城市建筑 节能优化 改进PSO 机会约束 |
| 收稿时间： | 2018-03-25 |
Energy Saving Optimization of Urban Buildings Considering Comfort Degree |
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| WANG Xiaojing,CHEN Xingying,YU Kun,PENG. Energy Saving Optimization of Urban Buildings Considering Comfort Degree[J]. Modern Electric Power, 2019, 36(4): 38-47 |
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| Authors: | WANG Xiaojing CHEN Xingying YU Kun PENG |
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| Affiliation: | 1.School of Electrical Engineering,Xinjiang University,Urumqi 830046,China;2.College of Energy & Electrical Engineering,Hohai University,Nanjing 211100,China;3.Jiangsu Engineering Research Center for Distribution & Utilization and Energy Efficiency, Nanjing 211100,China |
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| Abstract: | Improving the intelligent level of centralized control of urban building power system is an important way to realize low carbon building and energy saving. The combination of comfort and energy saving is of great significance for energy saving optimization of urban building because comfort is an important function of urban building. The energy consumption composition of three kinds of power consumption system of urban building including air conditioning, lighting and elevator is analyzed, and the corresponding power consumption index is proposed. The connotation of urban building comfort is studied in this paper. The comfort degree uncertainty brought by the change of season, weather, temperature and traffic flow is studied. On this basis, thermal comfort, light comfort and elevator comfort index are established. Energy saving optimization model with uncertain factors is put forward not to reduce the consumers' comfort. The optimization model is proposed to minimize the total energy consumption and satisfy the chance constraints of the given confidence level with the comfort degree. The improved PSO algorithm is applied to solve the optimization model. The validity of the urban building energy saving optimization model based on comfort and the optimization algorithm is verified through the case study. |
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| Keywords: | energy consumption index comfort index urban buildings energy-saving optimization improved PSO chance constraint |
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