Evaluation of Component Cooling System based on Optimization Algorithm in HPR1000
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摘要: 针对电厂设备冷却水等冷链系统的设计余量大、冬季供水温度低等问题，提供了一套创新设计方法，该方法可用于在总体设计阶段确定系统配置和运行方案。首先基于系统热平衡的基本原理，建立热工评估模型；基于满足安全和运行条件下尽可能提高经济性的指导思想，建立经济性评估模型；然后基于优化设计的基本原理，开发多目标优化算法及分析程序；最后应用上述程序处理系统设计中的多目标优化问题，最终实现系统方案评估。给出了华龙一号设备冷却水系统优化评估结果，使电厂经济性明显提高；突破传统过于依赖设计经验、定量分析不充分的单线设计流程；在多专业、多变量设计方案调整及参数优化时，采用软件决策辅助人工决策，缩短设计耗时、提高准确度。
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关键词:
- 设备冷却水系统（RRI） /
- 性能评估 /
- 多目标优化 /
- 新型混合遗传算法 /
- 供水温度
Abstract: Aiming at the problems of large design margin and low winter supply water temperature of cold chain systems such as equipment cooling water in power plants, an innovative design method is provided, which can be used to determine the system configuration and operation scheme in the overall design stage. Firstly, based on the basic principle of system heat balance, a thermal evaluation model is established, and an economic evaluation model is established based on the guiding ideology of improving economy as much as possible under safety and operating conditions. Then, based on the basic principle of optimization design, the multi-objective optimization algorithm and analysis program are developed. Finally, the above program is used to deal with the multi-objective optimization problems in the system design, and finally the system scheme evaluation is realized. The optimization evaluation results of the cooling water system of HPR1000 equipment are given, which significantly improves the economy of the power plant. It breaks through the traditional single-line design process which relies too much on design experience and is subject to insufficient quantitative analysis. In the adjustment of multi-discipline and multi-variable design scheme and parameter optimization, software decision-making is used to assist manual decision-making to shorten the design time and improve the accuracy. -
图 5 供水温度与系统总费用关系
Figure 5. Relationship between Supply Water Temperature and Total System Cost
表 1 NHGA-MO算法性能测试结果
Table 1. Performance Test Results of NHGA-MO Agorithm
变量数 测试函数最优值 NHGA-MO计算值 最大偏差值/10−8 平均偏差值/10−8 最优 最差 平均 10 −4189.82 −4189.82 −4189.82 −4189.82 −3.04 −3.04 20 −8379.65 −8379.65 −8379.65 −8379.65 −3.04 −3.03 30 −12569.50 −12569.487 −12569.098 −12549.291 −1.607×105 −3.096×103 
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表 2 变量母型值及优化范围
Table 2. Master Value and Optimization Range of Variables
优化变量 母型值 下限 上限 RRI供水温度/℃ 35 26 38 乏池热侧出口温度/℃ 37.08 35 39 乏池冷侧流量/（m3·h−1） 450 405 495 冷冻水冷侧流量/（m3·h−1） 332 280 350 三废冷侧流量/（m3·h−1） 12.1 10.89 13.31 海水侧流量/（m3·h−1） 1900 1710 2090
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表 3 系统整体典型优化方案及母型方案优化目标
Table 3. Overall Typical Optimization Scheme of the System and Optimization Objectives of the Master Scheme
方案 重量/
t比值/
%体积/
m3比值/
%费用/
亿元比值/
%耗电/
kw比值/
%母型方案 432 100 636 100 4.54 100 1270 100 优化方案1 397 91.9 543 85.4 3.96 87.2 1052 82.8 优化方案2 428 99.1 593 93.2 4.05 89.2 579 45.6 优化方案3 405 93.8 571 89.8 3.87 85.2 992 78.1
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表 4 变量优化结果
Table 4. Variable Optimization Results
优化变量 母型值 优化后 RRI供水温度/℃ 35 32.82 乏池热侧出口温度/℃ 37.08 35 乏池冷侧流量/（m3·h−1） 450 405 冷冻水冷侧流量/（m3·h−1） 332 280.02 三废冷侧流量/（m3·h−1） 12.1 13.31 海水侧流量/（m3·h−1） 1900 1710.84
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