本文選題：梯級(jí)水電站　切入點(diǎn)：多目標(biāo)優(yōu)化調(diào)度　出處：《華北電力大學(xué)》2014年碩士論文　論文類型：學(xué)位論文

【摘要】：大型梯級(jí)水電站具有復(fù)雜的流域拓?fù)浣Y(jié)構(gòu)、緊密的電力和水力聯(lián)系等特點(diǎn)。由于上述特點(diǎn)導(dǎo)致了其聯(lián)合優(yōu)化調(diào)度較為復(fù)雜；同時(shí),大型梯級(jí)水電站具有大庫(kù)容、高水頭的特征,優(yōu)化時(shí)還存在大范圍尋優(yōu)而導(dǎo)致計(jì)算效率低下的問(wèn)題。除此之外,電網(wǎng)負(fù)荷與梯級(jí)水電站入庫(kù)徑流的不確定性,對(duì)水電站安全、穩(wěn)定、經(jīng)濟(jì)運(yùn)行帶來(lái)較大的負(fù)面影響。因此,亟需開(kāi)展大型梯級(jí)水電站聯(lián)合優(yōu)化調(diào)度研究,尤其是短期優(yōu)化調(diào)度研究,以快速響應(yīng)電網(wǎng)負(fù)荷與梯級(jí)水電站入庫(kù)徑流的突變,提高水頭效益,增加水能利用率。在確保梯級(jí)水電站群安全性的前提下,實(shí)現(xiàn)經(jīng)濟(jì)效益、通航率最大化。 本文在深入分析了傳統(tǒng)優(yōu)化方法在解決梯級(jí)水電站聯(lián)合優(yōu)化調(diào)度問(wèn)題時(shí),存在“維數(shù)災(zāi)”、尋優(yōu)效果不理想等不足的基礎(chǔ)上,利用系統(tǒng)工程理論和現(xiàn)代智能優(yōu)化算法,對(duì)多目標(biāo)優(yōu)化算法、多屬性決策方法及其在梯級(jí)調(diào)度決策中的應(yīng)用進(jìn)行了研究。論文具體內(nèi)容概括如下： 本文首先根據(jù)三峽-葛洲壩實(shí)際運(yùn)行數(shù)據(jù)和工況,基于最小二乘法,建立了三峽-葛洲壩梯級(jí)水電站的水力計(jì)算流程。通過(guò)對(duì)基本數(shù)和水力計(jì)算流程的研究分析,建立了三峽-葛洲壩梯級(jí)水電站短期優(yōu)化調(diào)度數(shù)學(xué)模型。為智能優(yōu)化算法的使用創(chuàng)造了條件；其次基于建立的短期優(yōu)化調(diào)度數(shù)學(xué)模型,運(yùn)用權(quán)重法將多目標(biāo)的優(yōu)化調(diào)度問(wèn)題轉(zhuǎn)化為單目標(biāo)問(wèn)題,并且采用基于Sigmoid曲線改進(jìn)后的自適應(yīng)遺傳算法進(jìn)行模型求解。根據(jù)三峽-葛洲壩梯級(jí)水電站運(yùn)行規(guī)程和算法優(yōu)化后的水力數(shù)據(jù),制定三峽-葛洲壩短期發(fā)電計(jì)劃；最后,在分析了上述單目標(biāo)遺傳算法在處理具有高維度、非線性、尋優(yōu)范圍大等特點(diǎn)的梯級(jí)水電站優(yōu)化調(diào)度問(wèn)題時(shí),存在權(quán)重系數(shù)受主觀因素影響大、優(yōu)化結(jié)果單一、計(jì)算效率較低等缺陷的前提下,采用了對(duì)連續(xù)決策變量尋優(yōu)效果較好的多目標(biāo)優(yōu)化算法—非支配排序遺傳算法-Ⅱ型(NSGA-Ⅱ)進(jìn)行優(yōu)化調(diào)度模型求解,得到優(yōu)化調(diào)度問(wèn)題的非劣解集。再使用基于多輸入多規(guī)則模糊推理法的TOSIS決策方法對(duì)優(yōu)化問(wèn)題的非劣解集進(jìn)行方案篩選,從而得出最符合調(diào)度需求的梯級(jí)水電站調(diào)度方案。為解決三峽-葛洲壩梯級(jí)聯(lián)合優(yōu)化調(diào)度問(wèn)題提供了一種新思路。
[Abstract]:Large-scale cascade hydropower stations have the characteristics of complex basin topology, close connection between power and water, etc. Because of the above characteristics, the joint optimal operation of large-scale cascade hydropower stations is more complicated, and the large-scale cascade hydropower stations have the characteristics of large reservoir capacity and high water head. In addition, the uncertainty of grid load and inflow runoff of cascade hydropower stations has a great negative impact on the safety, stability and economic operation of hydropower stations. It is urgent to study the joint optimal dispatching of large-scale cascade hydropower stations, especially the short-term optimal dispatching, in order to quickly respond to the sudden change of grid load and inflow runoff of cascade hydropower stations, and to improve the efficiency of water head. Under the premise of ensuring the safety of cascade hydropower stations, the economic benefit and navigation rate are maximized. Based on the deep analysis of the shortcomings of the traditional optimization method in solving the joint optimal dispatching problem of cascade hydropower stations, such as "dimension disaster" and unsatisfactory optimization effect, the system engineering theory and modern intelligent optimization algorithm are used in this paper. The multi-objective optimization algorithm, multi-attribute decision making method and its application in cascade scheduling decision are studied. The specific contents of this paper are summarized as follows:. Based on the actual operation data and working conditions of the three Gorges Gezhou Dam, the hydraulic calculation process of the cascade hydropower station of the three Gorges Gezhou Dam is established based on the least square method, and the basic number and the hydraulic calculation flow are studied and analyzed in this paper. The mathematical model of short-term optimal dispatching of the three Gorges Gezhouba Cascade Hydropower Station is established, which creates the conditions for the use of intelligent optimization algorithm. Secondly, based on the established mathematical model of short-term optimal dispatching, The weight method is used to transform the multi-objective optimal scheduling problem into a single-objective problem. Based on the improved adaptive genetic algorithm based on Sigmoid curve, the model is solved. According to the operation rules of the three Gorges Gezhouba Cascade Hydropower Station and the optimized hydraulic data of the algorithm, the short term power generation plan of the three Gorges Gezhouba Dam is formulated. In this paper, the single objective genetic algorithm is used to deal with the cascade hydropower stations with high dimension, nonlinearity and large range of optimization. The weight coefficient is greatly affected by subjective factors, and the optimization result is single. On the premise of low computational efficiency, the optimal scheduling model is solved by using a multi-objective optimization algorithm, the non-dominated sorting genetic algorithm (NSGA- 鈪，

本文編號(hào)：1608847