Evaluation of stochastic reservoir operation optimization models

This paper investigates the performance of seven stochastic models used to define optimal reservoir operating policies. The models are based on implicit (ISO) and explicit stochastic optimization (ESO) as well as on the parameterization–simulation–optimization (PSO) approach. The ISO models include multiple regression, two-dimensional surface modeling and a neuro-fuzzy strategy. The ESO model is the well-known and widely used stochastic dynamic programming (SDP) technique. The PSO models comprise a variant of the standard operating policy (SOP), reservoir zoning, and a two-dimensional hedging rule. The models are applied to the operation of a single reservoir damming an intermittent river in northeastern Brazil. The standard operating policy is also included in the comparison and operational results provided by deterministic optimization based on perfect forecasts are used as a benchmark. In general, the ISO and PSO models performed better than SDP and the SOP. In addition, the proposed ISO-based surface modeling procedure and the PSO-based two-dimensional hedging rule showed superior overall performance as compared with the neuro-fuzzy approach.     

Probabilistic reservoir operation using Bayesian stochastic model and support vector machine

Available water resources are often not sufficient or too polluted to satisfy the needs of all water users. Therefore, allocating water to meet water demands with better quality is a major challenge in reservoir operation. In this paper, a methodology to develop operating strategies for water release from a reservoir with acceptable quality and quantity is presented. The proposed model includes a genetic algorithm (GA)-based optimization model linked with a reservoir water quality simulation model. The objective function of the optimization model is based on the Nash bargaining theory to maximize the reliability of supplying the downstream demands with acceptable quality, maintaining a high reservoir storage level, and preventing quality degradation of the reservoir. In order to reduce the run time of the GA-based optimization model, the main optimization model is divided into a stochastic and a deterministic optimization model for reservoir operation considering water quality issues.The operating policies resulted from the reservoir operation model with the water quantity objective are used to determine the released water ranges (permissible lower and upper bounds of release policies) during the planning horizon. Then, certain values of release and the optimal releases from each reservoir outlet are determined utilizing the optimization model with water quality objectives. The support vector machine (SVM) model is used to generate the operating rules for the selective withdrawal from the reservoir for real-time operation. The results show that the SVM model can be effectively used in determining water release from the reservoir. Finally, the copula function was used to estimate the joint probability of supplying the water demand with desirable quality as an evaluation index of the system reliability. The proposed method was applied to the Satarkhan reservoir in the north-western part of Iran. The results of the proposed models are compared with the alternative models. The results show that the proposed models could be used as effective tools in reservoir operation.     

Optimization of the Sefid-Roud Dam desiltation process using a sophisticated one-dimensional numerical model

Although water and soil conservation activities reduce reservoir sedimentation, it is inevitable that reservoirs fed by rivers transporting high amounts of sediment will experience sedimentation. The Ghezel-Ozan and Shah-Roud rivers, which flow to the Sefld-Roud reservoir dam, are both highly sediment-laden and transport significant amounts of sediment in both bed load and suspended load forms to the reservoir. Hence, it seems that the only practical way to remove the sediment from the reservoir is to flush it out using the Chasse method. In the present paper, field measurements of Chasse operation characteristics taken in previous years are presented, and a numerical model that simulates this process is introduced. After calibrating the model using field measured data, the calculated results （for reservoir pressure flushing and released sediment volume） of the numerical model were compared with other measured data for the same Chasse operation and the results agree well. Finally, using the numerical simulation results, the best approaches to ensure highly effective flushing while conserving reservoir water are presented （at least for the Sefid-Roud dam）. The operation of the bottom outlet gates, the shape of the output hydrograph, and the reservoir water level variation during flushing were optimized. In addition, the numerical model and related parameters, which need to be calibrated, are discussed.     

四川前兆钻孔应变仪台站观测系统运行管理现状分析

四川数字地震观测网络项目前兆分项目建设已通过中国地震局监测司的验收,四川前兆钻孔应变仪台站观测系统已运行一年多,从观测工作的各个环节都有值得总结和分析的必要,从而更好地服务于地震预报和科学研究。     

机房动力环境监控系统

通过解决新疆维吾尔自治区地震局应急指挥中心和信息网络机房动力环境设备的控制与管理中遇到的实际问题,介绍了机房动力环境监控系统在网络机房中的应用.     

三维地质建模技术方法研究——以东昆仑造山带为例

三维地质建模的关键技术, 是如何利用专业地理信息系统(GIS)的立体空间平台将三维空间地质实体真实地再现, 实现地质体的三维可视化和相关空间分析, 为地质研究和矿产资源勘查提供技术支撑。本文以东昆仑造山带为研究对象, 利用Micromine软件系统对地质体三维实体建模中的关键技术和建模方法进行了探索性研究, 初步总结出三维地质建模的主要技术和方法流程。      

基于简单要素模型的多边形分割算法

多边形是GIS研究和应用中使用最频繁的几何对象,该文描述了基于简单要素模型的任意多边形分割算法。从计算几何出发,结合GIS空间数据的特点,将基于简单要素模型的多边形分割算法设计为:1)对多边形及分割线的边界排序,基于扫描线及外包矩形检测查找可能相交的线段,提高相交线段的搜索效率;2)计算交点生成结点信息(包括交点坐标、线号及交点的出入),并存储在独立的单向链表中;3)根据结点链表和原多边形坐标搜索结果多边形。该算法能够分割任意简单多边形(凹凸、曲线边界和带洞的多边形)以及有共享边的多边形。最后在MapGIS7.0平台上,实现了基于简单要素类的多边形分割功能。     

马氏珠母贝育珠细胞小片和珠核处理技术研究Ⅲ:插核手术贝伤口区弧菌类型的初步研究

从马氏珠母贝(Pinctada martensii)插核部位蘸取组织液分离弧菌,研究插核手术前后室内休养3 d时伤口部位弧菌类型的变化,比较使用不同小片和珠核处理液对手术伤口部位弧菌类型的影响。形态和生理生化特征分型和鉴定结果显示,插核前和休养期贝样上分离的优势弧菌类型无明显差异,只是休养期弧菌的分离频率有所下降;从术后不同处理组的马氏珠母贝伤口上均分离得到7个类型弧菌,弧菌所属的种类也一致,而从未插核的对照组相应部位上只分离到4个类型弧菌,除未分离到副溶血弧菌(Vibrio parahaemolyticus)外,对照组与两个处理组贝样上分离到的弧菌种类基本上一致。     

海上拖航过程的风险评估方法研究

以南海某平台组块海上拖航作业为例,阐述风险评估的基本流程;针对海上拖航过程提出一套具体、实用的风险辨识、事故树建立以及建立风险控制措施的方案;同时给出一种将风险因素定性计算予以量化的方法,即风险值计算方法,并且针对海油工程确定风险值标准.     

Intelligent control for modelling of real‐time reservoir operation

This paper presents a new approach to improving real‐time reservoir operation. The approach combines two major procedures: the genetic algorithm (GA) and the adaptive network‐based fuzzy inference system (ANFIS). The GA is used to search the optimal reservoir operating histogram based on a given inflow series, which can be recognized as the base of input–output training patterns in the next step. The ANFIS is then built to create the fuzzy inference system, to construct the suitable structure and parameters, and to estimate the optimal water release according to the reservoir depth and inflow situation. The practicability and effectiveness of the approach proposed is tested on the operation of the Shihmen reservoir in Taiwan. The current M‐5 operating rule curves of the Shihmen reservoir are also evaluated. The simulation results demonstrate that this new approach, in comparison with the M‐5 rule curves, has superior performance with regard to the prediction of total water deficit and generalized shortage index (GSI). Copyright © 2001 John Wiley & Sons, Ltd.