基于NSGA-Ⅱ算法的太阳能蓄供热系统配置优化研究

范满; 时正平; 刘莹珊; 孔祥飞; 李晗; 袁建娟

doi:doi:10.19912/j.0254-0096.tynxb.2024-1724

English Version Journal Login

您当前的位置：

首页 >

文章列表页 >

基于NSGA-Ⅱ算法的太阳能蓄供热系统配置优化研究

更新时间：2026-03-06

- 基于NSGA-Ⅱ算法的太阳能蓄供热系统配置优化研究
- Vol. 47, Issue 2, Pages: 188-194(2026)
- 作者机构：
- 作者简介：
- 基金信息：
- DOI：doi:10.19912/j.0254-0096.tynxb.2024-1724
  CLC： TK513
- Online First：05 March 2026，
  
  Published：05 March 2026
- 稿件说明：
移动端阅览
范满, 时正平, 刘莹珊, et al. 基于NSGA-Ⅱ算法的太阳能蓄供热系统配置优化研究[J]. 2026, 47(2): 188-194.
DOI：

范满, 时正平, 刘莹珊, et al. 基于NSGA-Ⅱ算法的太阳能蓄供热系统配置优化研究[J]. 2026, 47(2): 188-194. DOI： doi:10.19912/j.0254-0096.tynxb.2024-1724.

摘要

为协同优化太阳能蓄供热系统的舒适性和经济性

以高速公路某服务区建筑为研究对象

利用TRNSYS软件建立系统能耗模型。以经济性和舒适性为目标函数

热舒适分区为约束条件

得到系统设计参数的Pareto最优解集

再利用TOPSIS熵权法得到最优设计参数组。与初始设计参数组对比

在热舒适性均满足要求的前提下

系统年生命周期成本降低18.58%、COP提高27.64%

具有节省投资和运行费用的双重优势。

Abstract

To synergistically optimize the solar heat storage and supply system

a system energy consumption model was established using TRNSYS software for an expressway serving area building. Taking economy and comfort as objective functions and thermal comfort zones as constraints

a Pareto optimal solution set for the system configurations was obtained. Subsequently

the optimal configuration was determined using the TOPSIS entropy weight method. Compared to the initial design parameters group

under the premise of meeting the requirements of thermal comfort

the system’s annual life cycle cost is decreased by 18.58% and the COP is increased by 27.64%

offering dual advantages of saving investment and operating costs.

关键词

Keywords

references

徐伟,何涛,张昕宇,等.太阳能热利用技术研究进展与展望[J]. 太阳能, 2024(7): 200-30.

ZHANG T H, WANG F X, GAO Y, et al.Optimization of a solar-air source heat pump system in the high-cold and high-altitude area of China[J]. Energy, 2023, 268: 126653.

李霏, 杨翠丽, 李文静, 等. 基于均匀分布NSGAⅡ算法的污水处理多目标优化控制[J]. 化工学报, 2019, 70(5): 1868-1878.

杨舒婷, 叶天震, 马欣桐, 等. 波纹丝网型太阳能空气集热器热性能特性研究[J]. 太阳能学报, 2021, 42(1):130-135.

JIAO Y, YU Y F, YU H, et al.The impact of thermal environment of transition spaces in elderly-care buildings on thermal adaptation and thermal behavior of the elderly[J]. Building and environment, 2023, 228: 109871.

BO L, JUAN Y, ARCHITECTURE S O, et al.Assessment standard for green building-“Health and Comfort” chapter[J]. Construction science and technology, 2019, 93:104502.

BS EN ISO7730-2005, Ergonomics of the thermal environment-analytical determination and interpretation of thermal comfort using calculation of the PMV and PPD indices and local thermal comfort criteria[S].

丁胜, 周博滔, 胡宝华. 基于NSGA-Ⅱ算法的小型分布式能源系统设计优化[J]. 太阳能学报, 2021, 42(1):438-445.

DEB K, PRATAP A, AGARWAL S, et al.A fast and elitist multiobjective genetic algorithm: NSGA-Ⅱ[J]. IEEE transactions on evolutionary computation, 2002, 6(2): 182-197.

ASCIONE F, BIANCO N, DE STASIO C, et al.Multi-stage and multi-objective optimization for energy retrofitting a developed hospital reference building: a new approach to assess cost-optimality[J]. Applied energy, 2016, 174: 37-68.

SIMO-TAGNE M, ZOULALIAN A, RÉMOND R, et al. Mathematical modelling and numerical simulation of a simple solar dryer for tropical wood using a collector[J]. Applied thermal engineering, 2018, 131: 356-369.

YUE Z L.A method for group decision-making based on determining weights of decision makers using TOPSIS[J]. Applied mathematical modelling, 2011, 35(4): 1926-1936.

杨雨莹, 任晓芬, 张景, 等. 基于改进AHP-TOPSIS的村镇太阳能+生物质能联合供暖综合评价[J]. 太阳能学报, 2024, 45(2): 342-350.

Views

下载量

CSCD

Alert me when the article has been cited

提交

Tools

Publicity Resources

OPTIMIZATION OF SOLAR-GAS ENERGY SYSTEM CONSIDERING GRID RENEWABLE ENERGY POWER PENETRATION RATES

计及需求响应与多目标优化的风光氢储综合能源系统容量配置研究

基于相变换热形式的金属氢化物储氢性能实验分析

改性海泡石基复合蓄热材料的制备与性能

不同压缩比螺旋翅片对相变储能罐放热的影响机制

Related Author

Han Jing

Cheng Tanghua

Xu Jinzhao

Wang Faze

Wang Jun

安源

施宗链

冯昊彤

Related Institution

PowerChina Huadong Engineering Corporation Limited

Jiangsu Provincial Key Laboratory of Solar Energy Science and Technology, School of Energy and Environment, Southeast University

Nanjing Paruote Solar Energy Co., Ltd.

Department of Power Engineering, North China Electric Power University

Hebei Key Laboratory of Low-Carbon and High-Efficiency Power Generation Technology, North China Electric Power University

AI问答

⁰