Dynamic operational optimization of air source heat pump heating system with consideration of energy saving

DING Qiang; XING Changxin; JIANG Aipeng; CHENG Wen; ZHOU Dahan

doi:10.11949/j.issn.0438-1157.20141763

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Dynamic operational optimization of air source heat pump heating system with consideration of energy saving

更新时间：2025-12-10

- Dynamic operational optimization of air source heat pump heating system with consideration of energy saving
- CIESC Journal Issue 6, Pages: 2166-2173(2015)
- 作者机构：
  
  杭州电子科技大学能量利用系统与控制研究所,浙江,杭州,310018
- 作者简介：
- 基金信息：
- DOI：10.11949/j.issn.0438-1157.20141763
  CLC： P202.7
- Online First：25 March 2015，
  
  Published：25 March 2015
- 稿件说明：
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DING Qiang, XING Changxin, JIANG Aipeng, et al. Dynamic operational optimization of air source heat pump heating system with consideration of energy saving[J]. CIESC Journal, 2015, (6): 2166-2173.
DOI：

DING Qiang, XING Changxin, JIANG Aipeng, et al. Dynamic operational optimization of air source heat pump heating system with consideration of energy saving[J]. CIESC Journal, 2015, (6): 2166-2173. DOI： 10.11949/j.issn.0438-1157.20141763.

摘要

采用系统工程的方法优化热泵供暖系统操作

实现节能运行具有重要意义。在建立热泵供暖系统基本动态方程的基础上

给出了考虑室温控制精度和能耗节省的优化操控目标

通过联立求解方法将原微分代数方程优化问题(DAOPs)转化为非线性规划问题

然后对不同目标侧重下的动态操作优化问题进行了分析

并提出了动态调整目标函数权重的优化策略。优化计算结果表明:在室温跟踪误差最大为0.85℃的情况下系统可实现16%以上的节能效果;环境温度和电价对系统操作优化具有重要影响

根据两者的变化特征而动态调整目标函数权重可以进一步降低系统能耗4.7%左右。本研究对热泵供暖系统优化节能控制具有一定的现实意义。

Abstract

It is quite important to improve the energy saving of air source heat pump heating system through optimal operation and system engineering method. In this work

the nonlinear dynamic model of heat pump heating process is established and the integral optimal objective function is then formulated to balance the control accuracy and energy saving. To solve the differential and algebraic optimization problems (DAOPs) efficiently

a simultaneous method is used to discretize the problem by collocation of finite elements. Then

the problem is analyzed with different weights and an optimal strategy to dynamically adjust the weight of objective function is proposed for further energy cost reduction. Computing results show that the potential energy saving of more than 16% can be achieved under permitted indoor temperature tracking error of 0.85 ℃; the ambient temperature and electricity price have significant effect on the optimal operation and performance of the heat pump heating system; and considering the characters of these factors

the proposed strategy of dynamically adjust the weight of objective function can further reduce energy cost for about 4.7%. Our research is of significant meaning for the optimal operation of heat pump heating system under dynamical conditions.

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