Method Of Long-term Hydrological Forecasting And Optimal Operation Of Reservoirs And Its Integration

With the development of the technology of computer and the theory of optimization andforecasting, researchers of hydraulic engineering have utilized many different algorithms tosolve the problems of hydrological forecasting and optimal operation of reservoirs system. Alarge amount of results have been made and come into effect. However, there are still a lot ofproblems by using these new methods duo to lack of reorganization of the mechanics ofhydrological forecasting. Therefore, large numbers of subjects inbasic work, theory study andimprovement of models should be studied and solved further. This dissertation focuses onimproving the models and the methods for hydrological forecasting and optimal operation.Long-term hydrological forecasting and optimal operation modeling methods and itsintegration are studied in-depth using the Fuzzy Optimization Neural Network (FONN),Support Vector Machines (SVM), wavelet transform subband forecast method and particleswarm optimization algorithm (PSOA). The main task of this dissertation includes thefollowing sections:(1) A new fuzzy optimization neural network model is proposed based on theLevenberg-Marquardt (LM) algorithm on account of the disadvantages of slow convergenceof traditional fuzzy optimization neural network model. In this new model, the gradientdescent algorithm is replaced by the LM algorithm to obtain the minimum of output errorsduring network training, which changes the weights adjusting equations of the network andincreases the training speed. Two cases study is utilized to validate this new model, and theresults reveal that the new model fast training Speed and better forecasting capability.(2) Using the global searching performance of PSOA to identify the parameters of SVM.In the process of modeling SVM, radial basis function (RBF) is used as kernel function, basedon which PSOA is employed to identify the parameters of SVM. Before particle swarmsearches the parameters, the parameters are transformed into exponent, which makes interval[0, 1] and interval [1,∞] have the same searching probability. Adaptive value function ofPSOA takes the generalization capability of SVM model as the criterion; thus two kind ofestimation of the generalization capability of SVM, the minimum error of test samples andleave-one-out method, have been discussed. Sequential minimal optimization trainingalgorithm is taken as the training algorithm of SVM. In order to improve the training speed,the second derivative of objective function are employed to choose the working set for training, which makes the two multipliers in working set have the maximum variation incurrent iteration. Taken the monthly discharge of Yichang station, Cuntan station in YangtzeRiver and Manwan reservoir as examples, ARMA model, and seasonal ARMA model, BPneural network model and proposed SVM model are used to forecast the monthly discharge,respectively. The simulation and forecasting results show the effectivity of the proposedmodel.(3) Based on wavelet analysis theory, a wavelet prediction model is presented for thesimulation and prediction of monthly discharge time series. In this model, the non-stationarytime series of monthly discharge is decomposed into an approximated time series and severalstationary detail time series according to the principle of wavelet decomposition. Each one ofthe decomposed time series is predicted respectively through the ARMA model for stationarytime series. Taking the monthly discharge at Yichang station and Cuntan station of YangtzeRiver as examples, the monthly discharge is simulated by using ARMA model, seasonalARIMA model, BP artificial neural network model and the wavelet prediction modelproposed in this article, respectively. And the effect of decomposition scale for the waveletprediction model is also discussed. Meanwhile, the practicability and the shortcoming ofwavelet prediction model are analyzed. Moreover, the influence of the wavelet extensionmode on the forecasting accuracy is discussed.(4) To improve the optimization capability of traditional PSOA, a revised PSOA isproposed and used to solve the problems of optimal operation for cascade reservoirs. Forincreasing the searching efficiency, the revised PSOA introduces crossover operator andmutation operator, which are similar to the operators in genetic algorithm. The positions ofthe particles in solution space are doing the arithmetical crossover at a certain of probabilitycalls crossover, and mutation means the particles at a certain of probability randomly makingsome one dimension component change into zero. In order to increase the convergence speed,a stochastic generated method under certain conditions is utilize to generate the initial particleswarm, and penalty function is used to deal with the boundary conditions and other inequalityconstraints. Taking example for Fengman-Baishan cascade reservoirs to compare the revisedPSOA with the traditional dynamic programming algorithm and the traditional PSOA, theresults show that the revised PSOA has faster calculation speed and optimal operation resultsare satisfied. Furthermore, the spans of the parameters (crossover probability, mutationprobability, the number of the particles and the maximum speed of the particles) in the revisedPSOA are also studied.(5) Using the proposed SVM method and the revised PSOA into the optimal operation ofthe cascade reservoirs. Firstly, the proposed SVM is used to estimate the incoming monthlyrunoff according to the monthly discharge in history. Secondly, the weighted Markov-Chain is used to estimate the total runoff of current year according to the annual runoff in history.Finally, the total runoff is used to revise the current monthly runoff in main flood period. Inthis way, after obtaining the forecasting monthly runoff, the revised PSOA is used to get theoptimal operation of the cascade reservoirs. Taking Feng-man-Baishan cascade reservoirs asan example, a rolling prediction operation method, which combines the runoff forecasting andthe optimal operation, is put forward to determine the optimal operation manner ofhydroelectric station. Meanwhile, the benefit of electric power generation under differentrunoff situations, such as real, forecasting, upper limit, lower limit and interpolation, arediscussed. The results show that it is feasible to using the proposed rolling predictionoperation method in Fengman-Baishan cascade reservoirs.(6) Based on the graph theory, multi-reservoir is conceptualized as a digraph. Theadjacent list, adjacent matrix and incidence matrix are used to analyze topology relations andto solve the integration of multi-reservoir. And relation tables of alternatives are used toanalyze topology relations, so the complexity of alternative management is reduced for theconvenient use and management of client. Then several design patterns in softwareengineering were studied for the purpose of applying them to the forecast and operationSystem for reservoirs (FOSR). The bridge pattern is employed to design the architecture ofFOSR and the data access; the strategy pattern is used to manage the models of FOSR; theiterator pattern and the decorator pattern are employed in the alternatives management; theproxy pattern is for managing the users' authorities; and the singleton pattern for the databaseconnection pool. The patterns used in the software achieve the loose coupling relationshipbetween different modular and increase the maintainability and reusability of the FOSR. Twotypes of display interfaces, Web Browser and Java window, are developed in this system.When FOSR is running, it can choose the communication manner automatically and interactwith the system business logic functional modular according to the operating environment.Finally, a summary is given and some problems to be further studied are discussed.