Optimization and economic analysis of active-passive cooperative cooling system based on time-sharing tariffs

CHEN Yifeng; CAI Yang; LIN Zhentao; ZHENG Shanle; LU Yancong

doi:10.19799/j.cnki.2095-4239.2025.1033

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Optimization and economic analysis of active-passive cooperative cooling system based on time-sharing tariffs

Special Issue on Multi\-Scenario Applications of Thermal and Cold Energy Storage | 更新时间：2026-07-01

- Optimization and economic analysis of active-passive cooperative cooling system based on time-sharing tariffs
- Energy Storage Science and Technology Vol. 15, Issue 3, Pages: 886-894(2026)
- 作者机构：
  
  暨南大学国际能源学院，广东珠海 519070
- 作者简介：
- 基金信息：
- DOI：10.19799/j.cnki.2095-4239.2025.1033
  CLC： TM 73;TU 83
- Received：18 November 2025，
  
  Revised：2026-01-27，
  
  Published：28 March 2026
- 稿件说明：
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陈亿锋, 蔡阳, 林振涛, 等. 分时电价下主被动协同降温系统性能及经济性分析[J]. 储能科学与技术, 2026, 15(3): 886-894.

CHEN Yifeng, CAI Yang, LIN Zhentao, et al. Optimization and economic analysis of active-passive cooperative cooling system based on time-sharing tariffs[J]. Energy Storage Science and Technology, 2026, 15(3): 886-894.
陈亿锋, 蔡阳, 林振涛, 等. 分时电价下主被动协同降温系统性能及经济性分析[J]. 储能科学与技术, 2026, 15(3): 886-894. DOI： 10.19799/j.cnki.2095-4239.2025.1033.

CHEN Yifeng, CAI Yang, LIN Zhentao, et al. Optimization and economic analysis of active-passive cooperative cooling system based on time-sharing tariffs[J]. Energy Storage Science and Technology, 2026, 15(3): 886-894. DOI： 10.19799/j.cnki.2095-4239.2025.1033.

摘要

在全球气候治理紧迫性加剧的当下，建筑领域作为能源转型的战略支柱，零碳转型已成当务之急，传统降温模式面临能效与经济性双重瓶颈。本研究针对这一问题，提出一种融合光伏相变墙体与冰蓄冷热泵的主被动协同降温系统，从系统建模与运行调控双维度突破传统技术局限，通过光伏发电、相变蓄热与冰蓄冷技术的多能互补，实现“光伏降温-相变调峰-热泵补冷”的协同运行；基于广州夏季典型气候数据与当地分时电价政策，运用TRNSYS软件构建建筑降温系统模型，并通过实验验证确保模型可靠性，进而探究相变温度/厚度、蓄冰罐容积及需求响应策略对系统热工性能与经济性的影响。结果表明：28℃相变温度、0.2 m相变厚度与0.4 m

蓄冰罐的组合最优，可最小化室内温度波动并降低能耗，使谷电利用率提升75.31%，分时电价下日净购电成本较传统空调系统降低61.33%；添加全局温度重设策略可进一步实现6.37% 的电费节省，且单位冷量成本低至0.182元/kWh；该系统静态投资回收期为5~7年，兼具技术可行性与商业推广价值，为亚热带地区建筑零碳设计与能源优化管理提供重要参考。

Abstract

As global climate governance grows increasingly urgent

the building sector—a strategic pillar of energy transition—faces an imperative need for zero-carbon transformation

while traditional cooling models struggle with dual bottlenecks in energy efficiency and economic viability. To address this

a hybrid active-passive cooperative cooling system integrating photovoltaic phase-change (PV-PCM) walls with ice-storage heat pumps is proposed

overcoming the limitations of conventional technologies

through dual innovations in system modeling and operational control. By harnessing the multi-energy complementarity of photovoltaic power generation

phase-change thermal storage

and ice-storage technology

the system achieves coordinated operation characterized by "photovoltaic cooling

phase-change peak shaving

and heat pump supplementary cooling." Using typical summer climate data from Guangzhou and the local time-of-use electricity pricing policy

a building energy consumption prediction model was developed in TRNSYS

validated experimentally

and applied to investigate the effects of phase-change parameters (temperature/thickness)

ice-storage tank volume

and demand response strategies on the system's thermal performance and economic efficiency. Results indicate that the optimal configuration

a phase-change temperature of 28℃

a phase-change material thickness of 0.2 m

and an ice-storage tank volume of 0.4 m

minimizes indoor temperature fluctuations and reduces energy consumption

increasing the off-peak electricity utilization rate by 75.31%. Under time-of-use pricing

the daily net electricity purchase cost is 61.33% lower than that of conventional air-conditioning systems. Furthermore

incorporating the Global Temperature Adjustment strategy reduces electricity costs by an additional 6.37%

achieving a cooling cost coefficient as low as 0.182 CNY/kWh. With a static payback period of 5—7 years

the system demonstrates both technical feasibility and commercial potential

offering valuable insights for zero-carbon building design and energy optimization management in subtropical regions.

关键词

Keywords

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