| 引用本文: | 缑新科,崔乐乐,巨圆圆,等.火电厂机组煤耗特性曲线拟合算法研究[J].电力系统保护与控制,2014,42(10):84-89.[点击复制] |
| GOU Xin-ke,CUI Le-le,JU Yuan-yuan,et al.Study on curve fitting algorithm for thermal power plant units coal consumption[J].Power System Protection and Control,2014,42(10):84-89[点击复制] |
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| 摘要: |
| 火电厂机组的煤耗特性曲线一般是由生产厂家提供的性能参数或通过热力试验数据获得的，这些曲线长期保持不变，导致与机组实际运行情况不符。以解决这一问题为目的，提出了基于遗传算法对火电厂机组的煤耗特性曲线进行拟合的方法。该方法采用二次函数作为目标函数；设置适当的初始种群数、交叉率和变异率等参数；对机组的实际煤耗特性曲线进行了拟合。对遗传算法拟合曲线与最小二乘法拟合曲线进行了比较，结果表明拟合效果前者优于后者，进一步说明采用该方法进行曲线拟合在一定意义下能最佳逼近已知数据，实时反映出火电厂机组发电量与煤耗量之间的依 |
| 关键词: 火电厂 遗传算法 煤耗特性曲线 曲线拟合 最小二乘法 |
| DOI：10.7667/j.issn.1674-3415.2014.10.013 |
| 投稿时间：2013-06-18修订日期：2013-08-30 |
| 基金项目:国家自然科学基金（61064003）资助 |
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| Study on curve fitting algorithm for thermal power plant units coal consumption |
| GOU Xin-ke,CUI Le-le,JU Yuan-yuan,GUO Tao,,ZHANG Shun |
| (College of Electrical and Information Engineering, Lanzhou University of Technology, Lanzhou 730050, China) |
| Abstract: |
| Coal consumption curve of the thermal power plant is usually obtained from the performance parameters which are provided by the manufacturer or from the thermal test data. These curves remain unchanged for a long time and are incompatible with the actual operation situation of the unit. Therefore, a method of coal consumption curve fitting of the thermal power plant units based on genetic algorithm is proposed. The quadratic function is used as the objective function; appropriate parameters such as initial population size, crossover rate and mutation rate are set; the unit’s actual coal consumption curves are fitted. The fitting curve of the proposed method is compared with that of the least squares method. The results indicate that fitting effect of the former is better than that of the latter. It is indicated that the proposed method can best approximate the known data in the curve fitting, and they can real-timely reflect the interdependence between unit generation and coal consumption. |
| Key words: thermal power plant genetic algorithm coal consumption curve curve fitting least squares method |
