储能科学与技术 ›› 2025, Vol. 14 ›› Issue (3): 1234-1246.doi: 10.19799/j.cnki.2095-4239.2024.1160

• 储能新锐科学家专刊 • 上一篇    下一篇

太阳能热发电储热系统动态建模与仿真研究

黎涵1(), 于刚1, 徐二树1, 廖志荣1(), 王强2, 陈晨2, 星月鹏2   

  1. 1.华北电力大学新型储能技术北京实验室,北京 102206
    2.中国广核新能源控股有限公司,北京 100048
  • 收稿日期:2024-12-06 修回日期:2025-01-01 出版日期:2025-03-28 发布日期:2025-04-28
  • 通讯作者: 廖志荣 E-mail:120222202465@ncepu.edu.cn;zhirong.liao@ncepu.edu.cn
  • 作者简介:黎涵(2000—),男,硕士研究生,研究方向为储热,E-mail:120222202465@ncepu.edu.cn
  • 基金资助:
    国家自然科学基金资助项目(52376181)

Dynamic modeling and simulation of solar thermal power storage systems

Han LI1(), Gang YU1, Ershu XU1, Zhirong LIAO1(), Qiang WANG2, Chen CHEN2, Yuepeng XING2   

  1. 1.Key Laboratory of Power Station Energy Transfer Conversion and System of MOE, North China Electric Power University, Beijing 102206, China
    2.China General Nuclear Power New Energy Holdings Co. , Ltd, Beijing 100048, China
  • Received:2024-12-06 Revised:2025-01-01 Online:2025-03-28 Published:2025-04-28
  • Contact: Zhirong LIAO E-mail:120222202465@ncepu.edu.cn;zhirong.liao@ncepu.edu.cn

摘要:

近年来,众多示范性的光热电站在全国范围内相继建成,配备适宜的储热系统对于提升这些光热电站的发电效率和降低运营成本具有重要意义。为了研究储热系统的运行,本工作建立了双罐间接储热系统的动态模型,分别搭建储盐罐、油/盐换热器、熔盐泵的数学模型,并通过引入PI调节模块实现熔盐泵转速的自动控制,利用STAR-90仿真平台模拟了中广核德令哈50 MW槽式太阳能热发电站在春分日和秋分日典型日工况下的储、放热动态运行过程。结果表明,本工作熔盐泵数学模型得到的性能曲线与厂家实测数据匹配度高,同时相比于原有储热系统模型,本模型能更好地反映储热系统的输入导热油温度和流量波动引起的熔盐流量波动的动态过程。在储热过程中,油/盐换热器热股导热油入口温度的变化趋势显著影响了冷股熔盐流量的波动趋势,熔盐泵的转速与流量呈现较强的非线性关系,熔盐泵的功耗与转速呈线性关系。春分日工况下熔盐的平均质量流量约为800 t/h,熔盐泵的平均转速和平均功率分别为154 r/min和87 kW;秋分日工况下熔盐的平均质量流量约为1400 t/h,熔盐泵的平均转速和平均功率分别为265 r/min和115 kW。汽轮机运行在28 MW的放热过程中,由于油/盐换热器中冷股导热油的流量和温度均较为稳定,因此热股熔盐的流量维持在2411 t/h,熔盐泵的转速和总功耗分别为855 r/min和205 kW。本研究为太阳能热发电站储热系统的设计和运行提供了重要的理论指导和实践参考。

关键词: 光热发电, 储热系统, 动态建模, 系统仿真

Abstract:

In recent years, numerous exemplary solar thermal power stations have been established nationwide. Integrating these stations with efficient thermal energy storage systems is crucial for improving their power generation efficiency and reducing operational costs. This study investigates the operation of thermal energy storage systems by developing a dynamic model of a two-tank indirect thermal energy storage system. Mathematical models for the salt storage tank, oil/salt heat exchanger, and molten salt pump have been constructed, along with a PI control module to automatically control the speed of the molten salt pump. The STAR-90 simulation platform simulates the dynamic charging and discharging processes under typical daily conditions at the CGN Delingha 50 MW trough solar thermal power stations during the vernal and autumnal equinoxes. The results indicate that the performance curve of the molten salt pump model closely matches the actual manufacturer data. Compared to the original thermal energy storage system model, this new model more accurately captures molten salt flow fluctuations resulting from variations in input heat transfer oil temperature and flow rate. During heat storage, fluctuations in the hot oil inlet temperature at the oil/salt heat exchanger considerably influence the cold molten salt flow. The speed of the molten salt pump exhibits a strong nonlinear correlation with the flow rate, while the power consumption of the pump is linearly related to its speed. Under vernal equinox conditions, the average mass flow rate of molten salt is about 800 t/h, with an average pump speed of 154 r/min and a power consumption of 87 kW. During the autumnal equinox, the average mass flow rate increases to 1400 t/h about, with an average pump speed of 265 r/min and power consumption of 115 kW. When the turbine operates at a power output of 28 MW during heat discharge, the flow of hot molten salt is maintained at 2411 t/h owing to the stable flow and temperature of the cold heat transfer oil in the oil/salt heat exchanger. In this situation, the speed and total power consumption of the molten salt pump reach 855 r/min and 205 kW, respectively. The research provides valuable theoretical insights and practical references for optimizing the design and operation of thermal energy storage systems in solar thermal power stations.

Key words: solar thermal power generation, thermal storage system, dynamic modeling, system simulation

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