摘要
针对传统供热机组调峰能力评估方法过程过于复杂、资料难以收集齐全等弊端及供热机组调峰能力预测的电网调度急迫需求性,运用聚类分析算法,对供热机组海量运行大数据进行归类划分,运用高斯分布概率密度函数工具按照设定的约束条件进行寻优遍历计算,评估特定工况下机组的调峰能力区间。该计算方法较工况图法等传统方法,计算方式更加简洁,且其计算结果来源于机组海量历史运行数据,因此其结果的可复现性及准确性较理论方法更加可靠。
Aiming at the complex process and the difficulty of data collection in traditional assessment methods for predicting the regulation capacity of heating units and the urgent requirements for the heating unit dispatch, by adopting the cluster analysis algorithm, the large collections of operating data are divided into several clusters. The Gaussian distribution probability density function tool is used to optimize the regulation capacity according to the preset constraints. Compared with the traditional methods, the cluster analysis algorithm is more concise and since the calculation results come from the large collections of historical operating data, the reproducibility and accuracy of the results are more reliable.
出处
《中国电力》
CSCD
北大核心
2016年第7期82-85,共4页
Electric Power
关键词
热电联产机组
供热机组
调峰能力
大数据
高斯分布
cogeneration power unit
heating units
peak load capacity
big data
Gauss distribution
