郭浩然1，李 映1，黃鶴程2

　　(1.中國電建集團貴陽勘測設計研究院有限公司，貴州 貴陽 550081;

　　2.南方電網調峰調頻發電有限公司，廣東 廣州 510630)

　　摘 要：抽水蓄能電站上、下水庫落差大，水頭高，針對輸水系統沿線山體地下水位變化的監測和預測對電站安全運行過程中的監測分析具有重要意義。為實現施工期山體水位預測，通過環境監測站獲取多項環境監測數據，結合PCA(主成分分析)和GA(遺傳算法)優化BP神經網絡方法，建立PCA-GA-BP優化模型對地下水位進行預測。選取廣東某抽水蓄能電站環境量及輸水系統沿線山體水位孔數據，在分析測點、測站布置及地下水位影響因素基礎上，對優化算法模型進行驗證、比較。實驗結果表明：優化模型具有較高預測精度，在高、中、低水位預測中綜合相對誤差較低，決定系數更高，均優于單BP預測模型，并通過PCA法使得網絡拓撲結構更簡單，提高綜合預測精度，具有較好的預測效果，在實際運用中可以為安全分析、工程預警等領域提供一定參考。

　　關鍵詞：地下水位預測;主成分分析;遺傳算法;優化神經網絡;抽水蓄能電站;輸水系統

　　Optimized neural network model for groundwater level prediction in pumped-storage power stations

　　GUO Haoran1，LI Ying1，HUANG Hecheng2

　　(1.Powerchina Guiyang Engineering Corporation Limiter，Guiyang 550081，China;

　　2.CSG Power Generation Co.,Ltd.，Guangzhou 510630，China)

　　Abstract：The drop between upper and lower reservoirs of a pumped-storage power station is large, and the water head is high. The monitoring and prediction of mountain groundwater level change along the water conveyance system is of great significance to safe operation monitoring of the power station. In order to predict mountain groundwater level during construction period, environmental monitoring data were obtained through the environmental monitoring station. By combining PCA (Principal Component Analysis) and GA (Genetic Algorithm) to optimize the BP neural network method, a PCA-GA-BP optimization model was established for groundwater level prediction. One pumped-storage power station in Guangdong is selected, and its environmental factors and mountain groundwater well data along the water delivery system are used. The optimized algorithm model is verified on the basis of analyzing measuring points, layout of the measuring station and impact factors of the groundwater level. The results show that the optimized model has high prediction accuracy, low comprehensive relative error and high determination coefficient in high, medium and low water level prediction, which is better than the single BP prediction model. And the network topology is simpler than the PCA method, which improves comprehensive prediction accuracy and thus has a better prediction performance. In practice, the optimized model can provide reference for safety analysis, engineering early warning and other fields.

　　Key words：groundwater level prediction;principal component analysis;genetic algorithm;optimized BP neural network;pumped-storage power station;water conveyance system;