Mid-and-Long Term Hydrological Forecasting And Operation Techniques Research And Application

The development and utilization of water resources,especially the usage of hydropower resources,is a complicated system engineering which refers to the knowledge of several subjects such as Water Resources & Hydroelectric Engineering,Hydrology & Water Resources,Automation of Electric Power System,etc.,and contains many issues like flood forecasting,hydrological forecasting,reservoir operation,multireservoir compensation optimal operation and so on.Among these issues,hydrological forecasting and hydropower station(group) optimal operation are the most significant ones.Reliable and timely hydrological forecasting is the basis of operation,while hydropower station(group) optimal operation is more important which has a direct effect on resources collocation and operation of power grid.Due to the complicated processes from rainfall to streamflow,special form of power generation by hydropower stations,dynamic relationship among water head,discharge. power,and electricity energy etc.,as well as inherent connecting of upstream hydropower reservoirs and downstream reservoirs,both hydrological forecasting and hydropower station (group) optimal operation are characterized by stochastic,multidimensional,multistage, non-linear,non-convex and discrete characteristics,and both of them are still the most difficult issues in hydropower system up to now.On the basis of the National Natural Science Foundation of China(Grant No.50679011) and the Ph.D.Programs Foundation of Ministry of Education of China(Grant No.20060183043),as well as based on the project background of Fujian Power Grid Multireservoir System Advanced Application Software in the charge of Fujian Power Grid Dispatching and Communication Center,this dissertation researched deeply on aforementioned two issues in terms of model and method research.Regarding to the ftrst issue,main focuses are on the combination of algorithms and import of numerical weather prediction information for improving forecasting quality.With respect to the second issue,emphases are on the improvement of intelligent optimization methods for solution of practical engineering requirement.In this dissertation,main focus is on the application of intelligent algorithms including neural networks,support vector machine,ant colony optimization,genetic algorithm,particle swarm optimization,etc.,and their hybrid algorithms in above-mentioned two issues.The main contents and outlines are as follows:(1) An ant colony optimization(ACO) based support vector machine model (ACO-SVM) is proposed for long term hydrological forecasting.SVM algorithm is of reliable global optimality and good generalization,and it is suitable for mid-and-long term hydrological forecasting which contains the study of finite samples.However,the results considerably depend on relevant parameters in SVM and conventional choosing method by experience can not obtain satisfactory outcomes.Radial basis function is selected as kernel function and parameters of SVM are optimized by ACO.An'sha reservoir in Fujian province is selected as a case study to demonstrate the modeling of ACO-SVM and forecasting results are compared with that of conventional ARMA model and BP-ANN model.The experimental results show that ACO-SVM model is much more efficient in global optimization,the forecasting accuracy is better than that of the other two models,and the ability of generalization is superior to BP-ANN.(2) A back-propagation neural network model taking account of quantitative precipitation forecasting(QPF) is proposed for mid term hydrological forecasting.The model is based on multi-layer perceptron network and forecasting factors include basin QPFs transformed from region QPFs.A statistic method which makes use of auto-correlation function(ACF) and cross-correlation function(CCF) is employed to specify the most efficient predictors' lags which were generally selected by empiricism.The standard back-propagation algorithm is improved by using self-adaptive learning rate and self-adaptive momentum coefficient which import the error function variation into the adjustment of weights matrix and biases matrix.Shuikou reservoir in Fujian province is selected as a case study to demonstrate the modeling and forecasting results are compared with that of conventional ARMA model and standard BP-ANN model.The experimental results show that the proposed model outperforms ARMA and standard BP-ANN model,and the utilization of QPF information can prolong lead-times as well as improve forecasting accuracy.(3) A virus evolution genetic algorithm(VEGA) based hydropower station operation model is proposed and this is the first time that VEGA is used for the optimal problems in the field of water resources.Virus infection mechanism is employed by VEGA for enhancing population diversity of GA,so as to improve the global searching ability of GA.Mianhuatan reservoir in Fujian province is selected as a case study to demonstrate the modeling of VEGA and operation results are compared with that of standard GA model as well as dynamic programming(DP) model.The experimental results show that the proposed VEGA model outperforms standard GA,in cases of different typical year,and the annual electricity energy are all close to that of classical DP model.Therefore,VEGA based hydropower station operation model is feasible,effective and advanced.(4) A hybrid improved PSO algorithm(HIPSO) is proposed for hydropower station group optimal operation.The improvement of PSO contains three aspects:(a) A new updating strategy of inertia weight coefficient-Self-adaptive Exponential Inertia Weight Coefficient (SEIWC) is proposed to replace the linearly decreasing inertia weight coefficient (LDIWC).(b):The crossover and mutation techniques of chromosome from genetic algorithm are imported into updating adjustment of particles to improve the global searching ability of PSO.(c):Particle elite set is established to reserve particles with better fitness value which are used to replace the bad ones during evolution process.The proposed HIPSO is applied to the optimal operation of hydropower station group of Minjiang basin in Fujian province,using energy maximization as optimized objective function,and results indicate that the HIPSO performs much better than standard PSO and optimal operation results of HIPSO is comparable with that of progressive optimization algorithm(POA) with much shorter time consumption.So,the proposed HIPSO is an effective method in engineering practice for hydropower station group optimal operation.(5) Based on Oracle clustered databases and J2EE framework,a mid- and- long term hydrological forecasting and operation system,the core part of Fujian Power Grid Multireservoir System Advanced Application Software,is deigned and developed utilizing several techniques such as Java,EJB,Servlet,Web,object-oriented and so on for the purpose of providing decision support for Fujian Power Grid.This section focuses on the key techniques of system structure design,function design,programming design,etc.,and the characteristics and major function modules are also introduced.Finally,a summary is given and some problems to be further studied are discussed.