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基于遗传算法的绿色建筑节能的增量效益实证研究

Case Study on Incremental Benefits of Energy-saving in Green Building Based on Genetic Algorithms

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【作者】 任继勤; 杨思佳; 祁士伟; 殷悦;

【Author】 REN Ji-qin;YANG Si-jia;QI Shi-wei;YIN Yue;School of Economics and Management,Beijing University of Chemical Technology;

【通讯作者】 祁士伟;

【机构】 北京化工大学经济管理学院;

【摘要】 基于绿色建筑节能项目全寿命周期,分析综合效益的构成和测算方法:在给出假设条件和约束条件下,构建绿色建筑节能方案增量成本最小化和增量效益最大化的目标函数模型,并通过比较分析常用的优化算法,选择遗传算法进行模型求解。通过实证研究,设计节能方案,基于De ST能耗模拟各项技术使用的能耗值,采用遗传算法得到投入单位增量成本所取得增量效益最大化的最优解的方案。结果表明:理想的增量效益来自于合理有效的技术组合,主要来源于空调系统和照明系统;基准收益率的设定会直接影响节能方案的优化结果,为决策者呈现出最优的节能技术组合。

【Abstract】 This paper studied the incremental benefits of energy-saving in green building project of whole life cycle and analyzed the comprehensive benefits and the calculation methods,established the objective function model that included the incremental cost minimization and the incremental benefit maximization of green building energy-saving scheme. And the genetic algorithms was selected by comparing and analyzing the commonly used optimization algorithms,designed energy-saving schemes and obtained the optimal solution of maximizing incremental benefits of unit incremental cost based on De ST energy consumption value about various technologies by case study. The results showed that the ideal incremental benefits came from reasonable and effective technology combination and air-conditioning system and lighting system,the optimization results of energy-saving schemes depended on the benchmark return rate directly. This study could present the optimal energy-saving technology combination for decision makers.

【基金】 科技部“国家质量基础的共性技术研究与应用”重点专项项目(编号:2016YFF0204405);北京市社会科学基金项目(编号:18GLB029);国家社会科学基金项目(编号:16BGL007)
  • 【文献出处】 资源开发与市场 ,Resource Development & Market , 编辑部邮箱 ,2019年04期
  • 【分类号】TU201.5
  • 【被引频次】9
  • 【下载频次】332
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