摘要
为了提高对抽水蓄能电站水环境治理效果的准确评价能力,提出基于遗传算法的抽水蓄能电站水环境治理效果评价方法。构建抽水蓄能电站水环境治理的约束指标分布集,以水土理化特性、含水营养盐特征分布、有机垂向特征值为一级约束指标,通过主成分特征分析方法提取水环境沉积物水土微界面理化特征参数,采用营养盐负荷性状分析方法,记录抽水蓄能电站水环境采样点位特征量,采用遗传算法实现对碳、氮等营养盐及生物易降解有机质组成的测定和分析,提高抽水蓄能电站水环境治理效果评价能力。测试结果表明,采用该方法进行抽水蓄能电站水环境治理评价的可靠性较好,对有机质组成测定和分析的精度较高,可为抽水蓄能电站水环境治理提供可靠数据支撑。
In order to improve the accurate evaluation ability of water environment treatment effect of pumped storage power station,the evaluation method of water environment treatment effect of pumped storage power station based on genetic algorithm is put forward.Constructed the constraint index distribution set of water environment treatment of pumped storage power station,taking the physical and chemical characteristics of water and soil,the distribution of water-bearing nutrients and the vertical characteristic value of organic matter as the first-class constraint index,extracted the physical and chemical characteristic parameters of water and soil micro-interface of water environment sediment by principal component analysis,recorded the sampling site characteristic quantity of water environment of pumped storage power station by nutrient load analysis method,and determined and analyzed the composition of nutrients such as carbon and nitrogen and biodegradable organic matter by genetic algorithm,so as to improve the evaluation ability of water environment treatment effect of pumped storage power station.The test results show that this method is reliable in evaluating the water environment treatment of pumped storage power stations,and has high accuracy in measuring and analyzing the organic matter composition,which provides reliable data support for the water environment treatment of pumped storage power stations.
作者
田红霞
TIAN Hong-xia(Shandong Province Linyi City Hedong District Emergency Rescue Command Service Center,Linyi 276000,Shandong,China)
出处
《水利科技与经济》
2022年第8期104-108,共5页
Water Conservancy Science and Technology and Economy
关键词
遗传算法
抽水蓄能电站
水环境治理
效果评价
genetic algorithm
pumped storage power station
water environment treatment
effect evaluation
