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杨新乐, 李娇荣, 卢胜东, 等. 地热驱动的R-DPORC系统动态仿真及控制策略研究[J]. 太阳能学报, 2026,47(6):523-532.
杨新乐, 李娇荣, 卢胜东, et al. 地热驱动的R-DPORC系统动态仿真及控制策略研究[J]. 2026, 47(6): 523-532.
杨新乐, 李娇荣, 卢胜东, 等. 地热驱动的R-DPORC系统动态仿真及控制策略研究[J]. 太阳能学报, 2026,47(6):523-532. DOI: 10.19912/j.0254-0096.tynxb.2025-0091.
杨新乐, 李娇荣, 卢胜东, et al. 地热驱动的R-DPORC系统动态仿真及控制策略研究[J]. 2026, 47(6): 523-532. DOI: 10.19912/j.0254-0096.tynxb.2025-0091.
对于地热源再热双压有机朗肯循环(R-DPORC)系统因冷/热源瞬态波动变化所造成的运行不稳定问题
有针对性地提出恒定负荷和变负荷控制两种策略。利用Matlab/Simscape建立R-DPORC系统动态仿真模型
对冷/热源及负荷变化条件下系统的动态响应特性进行分析
研究系统效率、过热度、压力和质量流量的变化规律。结果表明
调节工质泵的流量是实现R-DPORC系统动态控制的关键手段
根据具体的工作场景可灵活组合不同的运行模式
通过控制调节能使系统逐步实现新的稳定状态并达到输出要求。优化后的控制策略可显著提高系统在复杂工况下的动态适应性
可保障系统长期稳定运行和更高的能效输出。
To address the operational instability of the geothermal reheated dual-pressure organic Rankine cycle (R-DPORC) system caused by transient fluctuations in cold/heat sources
this study proposes two targeted control strategies: constant-load control and variable-load control. A dynamic simulation model of the R-DPORC system has been developed using Matlab/Simscape to analyze its dynamic response characteristics under varying cold/heat source conditions and load changes. The variations in system efficiency
degree of superheat
pressure
and mass flow rate are investigated. Results indicate that regulating the flow rate of working fluid pump is a critical method for achieving dynamic control of the R-DPORC system. Depending on specific operational scenarios
different operating modes can be flexibly combined. Through adjustments
the system can gradually achieve a new stable state and meet output requirements. Moreover
the optimized control strategy significantly improves the dynamic adaptability of the system under complex operating conditions
ensuring long-term stable operation and higher energy efficiency.
黄璜, 刘然, 李茜, 等. 地热能多级利用技术综述[J]. 热力发电, 2021, 50(9): 1-10.
胡冰, 郭嘉俊, 黄斯珉. 低温地热双循环式发电系统横管喷淋降膜蒸发器传热性能实验研究[J]. 太阳能学报, 2022, 43(7): 493-498.
ZHOU J Z, CHU Y T, REN J Z, et al.Integrating machine learning and mathematical programming for efficient optimization of operating conditions in organic Rankine cycle(ORC) based combined systems[J]. Energy, 2023, 281: 128218.
LI X Y, XU B, TIAN H, et al.Towards a novel holistic design of organic Rankine cycle (ORC) systems operating under heat source fluctuations and intermittency[J]. Renewable and sustainable energy reviews, 2021, 147: 111207.
PING X, YANG F B, ZHANG H G, et al.Energy, economic and environmental dynamic response characteristics of organic Rankine cycle(ORC) system under different driving cycles[J]. Energy, 2022, 246: 123438.
WANG H X, LEI B, WU Y T, et al.Operational characteristics and performance optimizations of the organic Rankine cycle under different heat source/condensing environment conditions[J]. Energy, 2024, 310: 133198.
SHI Y, LIN R Z, WU X L, et al.Dual-mode fast DMC algorithm for the control of ORC based waste heat recovery system[J]. Energy, 2022, 244: 122664.
HERNANDEZ A, RUIZ F, GUSEV S, et al.Experimental validation of a multiple model predictive control for waste heat recovery organic Rankine cycle systems[J]. Applied thermal engineering, 2021, 193: 116993.
刘雪玲, 牛锦涛, 汪健生, 等. 利用地热能的双压有机朗肯循环性能分析[J]. 太阳能学报, 2022, 43(9): 437-443.
饶建业, 李骥飞, 郭智琳, 等. 地热能有机朗肯循环系统设计与动态仿真[J]. 热力发电, 2024, 53(4): 19-27.
SAHA B K, CHAKRABORTY B, MONDAL J, et al.Design and implementation of a control strategy for a dynamic organic Rankine cycle-based power system in the context of industrial waste heat recovery[J]. Energy technology, 2023, 11(11): 2300425.
WANG X, WANG R, JIN M, et al.Control of superheat of organic Rankine cycle under transient heat source based on deep reinforcement learning[J]. Applied energy, 2020, 278: 115637.
刘芳, 杨志鹏, 袁卫星, 等. 微小通道换热器内流动沸腾换热与压降特性[J]. 工程热物理学报, 2023, 44(8): 2240-2249.
SINAN TURGUT M.Neural Koopman operator-assisted model predictive control of an organic Rankine cycle[J]. Applied thermal engineering, 2023, 230: 120696.
杨新乐, 杨森, 卜淑娟, 等. 有机朗肯循环工质热源转折温度的新求解法及应用[J]. 热能动力工程, 2023, 38(4): 46-54.
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