本文選題：梯級水庫群 + 支持向量機��； 參考：《華北電力大學(xué)》2014年博士論文

【摘要】：能源是人類生存和發(fā)展的重要物質(zhì)基礎(chǔ),攸關(guān)國計民生和國家安全。水電作為目前開發(fā)規(guī)模龐大、開發(fā)技術(shù)最為成熟的可再生能源,以其良好的調(diào)節(jié)性能、低廉的運行成本和快速的負荷響應(yīng)能力,在世界電力能源格局中發(fā)揮著重要作用。我國水力資源豐富,為經(jīng)濟社會發(fā)展提供了能源保障。加快開發(fā)水能資源是我國增加清潔能源供應(yīng)、優(yōu)化能源結(jié)構(gòu)、應(yīng)對世界氣候變化、實現(xiàn)可持續(xù)發(fā)展的重要措施�！笆濉睍r期是我國全面建設(shè)小康社會的關(guān)鍵時期,從我國的能源特點和自然資源結(jié)構(gòu)來看,加快水電發(fā)展也是實現(xiàn)2020年非化石能源目標(biāo)的必經(jīng)之路,也是有效降低單位GDP二氧化碳排放量的重要措施。 水庫調(diào)度是水庫運行管理的重要環(huán)節(jié),調(diào)度水平直接影響著水庫水電站綜合效益的發(fā)揮。合理優(yōu)化的水庫調(diào)度方式能夠在不增加硬件投入的情況下,獲得可觀的社會效益和經(jīng)濟效益,也是優(yōu)化能源結(jié)構(gòu)、促進節(jié)能減排的有效措施。本論文在對水庫水電站群隱隨機優(yōu)化理論回顧歸納的基礎(chǔ)上,分別從確定性優(yōu)化調(diào)度模型建立與求解、調(diào)度規(guī)則的制定與優(yōu)化、基于調(diào)度規(guī)則的水庫水電站群系統(tǒng)仿真、效益評價及隱隨機優(yōu)化調(diào)度因素影響分析等方面對徑流不確定條件下的水電站群優(yōu)化調(diào)度進行研究。主要研究工作包括： (1)水庫水電站群隱隨機優(yōu)化調(diào)度理論研究及歸納。介紹了水庫確定性優(yōu)化調(diào)度和隨機調(diào)度的概念和特征,從徑流過程角度分析二者之間的區(qū)別和關(guān)系。在分析顯隨機優(yōu)化調(diào)度和隱隨機優(yōu)化調(diào)度原理的基礎(chǔ)上,重點綜述隱隨機優(yōu)化理論方法的國內(nèi)外研究進展及其在水電站水庫調(diào)度規(guī)則制定中的應(yīng)用,并總結(jié)各種調(diào)度規(guī)則制定方法的適用條件和優(yōu)缺點。 (2)基于網(wǎng)格搜索和交叉驗證的改進支持向量機模型研究。基于支持向量機方法的原理分析其在回歸預(yù)測領(lǐng)域的優(yōu)勢,針對支持向量機對參數(shù)敏感和小樣本回歸易受訓(xùn)練樣本隨機性影響的特點,建立基于網(wǎng)格搜索的參數(shù)尋優(yōu)機制和基于交叉驗證的樣本隨機性規(guī)避機制,對支持向量機性能進行改進。通過實例研究,驗證改進機制對支持向量機在小樣本訓(xùn)練擬合能力和預(yù)測能力方面的效果。 (3)基于C++和MATLAB的水庫水電站群混合編程仿真平臺的建立。針對隱隨機優(yōu)化調(diào)度在實際運行中的實現(xiàn)難度,考慮隱隨機優(yōu)化調(diào)度模型復(fù)雜、計算機實現(xiàn)環(huán)境多樣化的特點,以支持向量機理論為例,將基于MATLAB的調(diào)度決策生成算法預(yù)測編譯為動態(tài)庫文件,使其在基于C++的水庫水電站群系統(tǒng)仿真程序中被調(diào)用,實現(xiàn)實時滾動模擬。通過案例應(yīng)用,對仿真平臺的結(jié)構(gòu)及系統(tǒng)穩(wěn)定性和可擴展性進行評價。 (4)金沙江中下游12級梯級水電系統(tǒng)隱隨機優(yōu)化調(diào)度研究及其效益評價。以我國十三大水電梯級中規(guī)模最大的金沙江中下游梯級水電站系統(tǒng)為例,以系統(tǒng)發(fā)電量和保證出力為優(yōu)化目標(biāo),建立并求解梯級中長期確定性優(yōu)化調(diào)度模型,作為隱隨機模型的訓(xùn)練樣本。運用改進支持向量機方法對系統(tǒng)調(diào)度規(guī)則制定,并模擬系統(tǒng)1989-2000年運行過程。另基于多元逐步回歸法制定調(diào)度規(guī)則并仿真,將同期確定性優(yōu)化調(diào)度結(jié)果及兩種仿真結(jié)果進行對比。對仿真結(jié)果的發(fā)電量、發(fā)電過程、保證出力等方面進行對比,分析仿真結(jié)果的效益和可靠性。 (5)隱隨機優(yōu)化調(diào)度模型因素影響研究。定量研究梯級規(guī)模、徑流預(yù)報誤差、模型參數(shù)、輸出決策等因素對梯級水電站群隱隨機優(yōu)化調(diào)度仿真結(jié)果的影響�；诮鹕辰掠巍L江中游大型梯級水電系統(tǒng),以其宗單庫、其宗——向家壩12級和其宗——葛洲壩14級三種電站組合為研究對象,控制各影響因素變化范圍,并分別進行仿真運行和效益評價。評價結(jié)果所揭示的各因素所帶來的影響方式對于支持向量機理論的改進以及隱隨機優(yōu)化調(diào)度的下一步發(fā)展有著重要的參考價值。
[Abstract]:Energy is an important material basis for the survival and development of human beings. It is vital to the national economy and the people's livelihood and national security. As a renewable energy, which has a large scale of development and the most mature development technology, it plays an important role in the world power energy pattern with its good regulation performance, low operating cost and rapid load response ability. China is rich in hydraulic resources and provides energy security for economic and social development. Speeding up the development of water energy resources is an important measure for China to increase the supply of clean energy, optimize the energy structure, cope with the world climate change and achieve sustainable development. "12th Five-Year" period is the key period for China to build a well-off society in an all-round way, from China's energy special. Point and natural resource structure, speeding up the development of hydropower is also the only way to achieve the goal of non fossil energy in 2020, and it is also an important measure to effectively reduce the emissions of GDP carbon dioxide.
Reservoir operation is an important link in the operation and management of the reservoir. The level of dispatching directly affects the comprehensive benefit of the reservoir. The rational and optimized reservoir scheduling method can obtain considerable social and economic benefits without increasing the input of hardware. It is also an effective measure to optimize the energy source structure and promote energy conservation and emission reduction. On the basis of the review of the theory of hidden stochastic optimization for reservoir hydroelectric stations, this paper is based on the establishment and solution of the deterministic optimal scheduling model, the formulation and optimization of the scheduling rules, the simulation of the reservoir hydroelectric station group system based on the scheduling rules, the benefit evaluation and the factor influence analysis of the implicit stochastic optimization scheduling, and so on. The optimal operation of hydropower stations is studied. The main research work includes:
(1) the study and induction of the implicit stochastic optimization scheduling theory of reservoir hydropower stations. The concept and characteristics of reservoir deterministic optimal scheduling and stochastic scheduling are introduced. The difference and relationship between the two are analyzed from the point of view of the runoff process. On the basis of the analysis of the explicit stochastic optimization scheduling and the implicit stochastic optimization scheduling, the implicit stochastic optimization theory is mainly summarized. The research progress of the method at home and abroad and its application in the formulation of hydropower station reservoir scheduling rules, and the application conditions and advantages and disadvantages of various scheduling rules formulation methods are summarized.
(2) an improved support vector machine model based on grid search and cross validation. Based on the principle of support vector machine (SVM), the advantages of the support vector machine in the domain of regression prediction are analyzed. In view of the characteristics of the parameter sensitivity of support vector machines and the randomness of the small sample regression which are easily subject to the randomness of the training samples, the parameter optimization mechanism and the base based on the grid search are established. The performance of SVM is improved by the random evasion mechanism of cross validation. The effect of the improved mechanism on the fitting ability and prediction ability of the support vector machine in small sample training is verified by an example.
(3) the establishment of a hybrid programming simulation platform for the reservoir hydropower station group based on C++ and MATLAB. In view of the difficulty of realizing the hidden random optimization scheduling in the actual operation, the characteristics of the complexity of the hidden stochastic optimization scheduling model and the diversification of the computer environment are considered, and the support vector machine theory is taken as an example, and the scheduling decision generation algorithm based on MATLAB is predicted. As a dynamic library file, it is called in the simulation program of the C++ based reservoir hydroelectric station group system. The real time rolling simulation is realized. The structure of the simulation platform, the stability and extensibility of the system are evaluated by the case application.
(4) the research and benefit evaluation of the cascade hydropower system in the middle and lower reaches of the middle and lower reaches of the Jinsha River, taking the cascade hydropower stations in the middle and lower reaches of the middle and lower Jinsha River, the largest in the thirteenth big hydropower cascade in China as an example, to establish and solve the middle and long term deterministic optimal scheduling model of the cascade. Training samples of implicit stochastic model. The system scheduling rules are formulated with improved support vector machine (improved SVM), and the 1989-2000 year operation process of the system is simulated. In addition, the scheduling rules are formulated and simulated based on the multiple stepwise regression method. The results of the deterministic optimal scheduling and the two simulation results are compared. Compare the process, guarantee output and other aspects, and analyze the effectiveness and reliability of the simulation results.
(5) study on the factor influence of the implicit stochastic optimization scheduling model. Quantitative study of the influence of cascade scale, runoff forecasting error, model parameters, output decision and other factors on the simulation results of cascade hydropower stations' implicit stochastic optimization scheduling. Based on the lower reaches of the Jinsha River, the large cascade hydropower system in the middle reaches of the Yangtze River, with its single library and its sect to Jiaba 12 level The combination of the three kinds of power stations in Gezhouba Dam 14 is the research object, which controls the range of the influence factors, and carries out the simulation operation and the benefit evaluation respectively. The influence mode of the factors revealed by the evaluation results has an important reference for the improvement of the support vector machine theory and the next step of the hidden stochastic optimization scheduling. Value.
【學(xué)位授予單位】：華北電力大學(xué)
【學(xué)位級別】：博士
【學(xué)位授予年份】：2014
【分類號】：TV737;TV697.12

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