间接空冷背压预测及变频循环泵控制优化OA北大核心CSTPCD
PREDICTION OF INDIRECT AIR COOLING BACK PRESSURE AND CONTROL OPTIMIZATION OF VARIABLE FREQUENCY CIRCULATING PUMP
根据山西省河坡电厂2 ×350 MW循环流化床一号机组2019年7月15日到8月15日电厂与背压有关的实际运行数据,通过分析其影响因素(环境温度,机组负荷,凝汽器温度、压力等),使用相关系数法和主成分分析法对数据降维,在Python平台上使用Keras、TensorFlow等库编写预测算法,建立背压预测模型,使用RNN神经网络对背压建模预测,分析预测结果.结合现场实际运行实验数据,辨识变频循环泵的模型,并使用模糊PID对其控制进行优化.
According to the actual operation data related to back pressure of 2 × 350 MW circulating fluidized bed unit 1 of Hepo power plant in Shanxi Province from July 15 to August 15,2019,by analyzing the influencing factors(ambient temperature,unit load,condenser temperature,pressure,etc.),the correlation coefficient method and principal component analysis method were used to reduce the dimension of data.On the Python platform,Keras,TensorFlow and other libraries were used to compile the prediction algorithm,and the back pressure prediction model was established.The RNN neural network was used to predict the back pressure,and we analyzed the prediction results.The model of variable frequency circulating pump was identified combining with the actual operation data,and the fuzzy PID was used to optimize its control.
孟宏君;张凯奇;王尚尚;李丽锋
山西大学自动化与软件学院 山西太原 030013
计算机与自动化
间接空冷背压预测变频循环泵LSTMPython
Indirect air coolingBack pressure predictionVariable frequency circulating pumpLSTMPython
《计算机应用与软件》 2024 (004)
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国家自然科学基金青年科学基金项目(51605321);山西省自然科学基金面上项目(201701D221144).
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