本文選題：供水網(wǎng)絡(luò)優(yōu)化 + 節(jié)能低碳�。� 參考：《青島理工大學(xué)》2013年碩士論文

【摘要】：供水網(wǎng)絡(luò)優(yōu)化的研究可以有效地節(jié)省投資、保證供水安全，具有十分重要的理論和實(shí)際價(jià)值。近些年隨著節(jié)能低碳理念逐漸深入人心，節(jié)能思想已廣泛應(yīng)用于各領(lǐng)域，如何將節(jié)能低碳理論應(yīng)用到供水網(wǎng)絡(luò)優(yōu)化中是本文研究的重點(diǎn)。國內(nèi)外很多學(xué)者根據(jù)不同的優(yōu)化目的建立了相應(yīng)的供水網(wǎng)絡(luò)優(yōu)化目標(biāo)函數(shù)模型，針對(duì)不同的函數(shù)模型又提出了各種各樣的模型求解算法。針對(duì)以上問題，本文進(jìn)行了如下研究： 本文通過對(duì)供水網(wǎng)絡(luò)的能耗進(jìn)行研究實(shí)現(xiàn)節(jié)能低碳理念的應(yīng)用，基于全生命周期理論，分別對(duì)不同管材在生產(chǎn)、施工、運(yùn)行3個(gè)階段的能耗進(jìn)行了研究。根據(jù)不同管材的原材料、生產(chǎn)工藝、加工成型工序的不同，建立供水網(wǎng)絡(luò)全生命周期的能耗函數(shù)模型。 考慮到供水安全性，當(dāng)供水網(wǎng)絡(luò)流量已初分時(shí)，通過添加流量、流速懲罰項(xiàng)的方式對(duì)一般經(jīng)濟(jì)性目標(biāo)函數(shù)進(jìn)行改進(jìn)。通過耦合能耗數(shù)學(xué)模型和改進(jìn)經(jīng)濟(jì)模型，得到多目標(biāo)優(yōu)化數(shù)學(xué)模型，從而能夠在保證經(jīng)濟(jì)性和供水安全性的基礎(chǔ)上，達(dá)到節(jié)能低碳理念應(yīng)用目的，實(shí)現(xiàn)多目標(biāo)優(yōu)化。 針對(duì)多目標(biāo)優(yōu)化數(shù)學(xué)模型，本文運(yùn)用混合進(jìn)化算法進(jìn)行求解，并對(duì)混合進(jìn)化算法的實(shí)現(xiàn)過程展開重點(diǎn)研究。本文中混合進(jìn)化算法是基于C++平臺(tái)實(shí)現(xiàn)的，并且算法在實(shí)現(xiàn)過程中利用EPANET調(diào)用管段信息進(jìn)行計(jì)算。最終經(jīng)混合進(jìn)化算法得到Pareto最優(yōu)解集，再從最優(yōu)解集中挑選最符合設(shè)計(jì)者要求的解，實(shí)現(xiàn)多目標(biāo)優(yōu)化問題的解決。與此同時(shí)，為檢驗(yàn)混合進(jìn)化算法性能的優(yōu)劣，，本文應(yīng)用遺傳算法對(duì)目標(biāo)函數(shù)求解作了類比實(shí)驗(yàn)。 本文應(yīng)用膠州市產(chǎn)業(yè)新區(qū)部分管網(wǎng)作為實(shí)例，對(duì)提出的多目標(biāo)優(yōu)化數(shù)學(xué)模型和混合優(yōu)化算法進(jìn)行了多工況實(shí)例檢驗(yàn)。通過對(duì)最高日最高時(shí)、消防時(shí)、事故時(shí)3種不同工況檢驗(yàn)得知，本文建立的供水網(wǎng)絡(luò)多目標(biāo)優(yōu)化函數(shù)和多目標(biāo)混合進(jìn)化算法得到的最優(yōu)解是合理的，能夠滿足實(shí)際應(yīng)用的要求。
[Abstract]:The research of water supply network optimization can effectively save investment and ensure water supply safety, which has very important theoretical and practical value. In recent years, with the idea of saving energy and low carbon, the idea of energy saving has been widely used in various fields. How to apply the theory of energy saving and low carbon to the optimization of water supply network is the focus of this paper. Many scholars at home and abroad have established the corresponding water supply network optimization objective function model according to different optimization purposes, and put forward a variety of model solving algorithms for different function models. In view of the above problems, this paper has carried out the following research: In this paper, the energy consumption of water supply network is studied to realize the application of the idea of energy saving and low carbon. Based on the whole life cycle theory, the energy consumption of different pipes in the three stages of production, construction and operation is studied respectively. According to the different raw materials, production technology and processing process of different pipes, the energy consumption function model of the whole life cycle of water supply network is established. Considering the safety of water supply, the general economic objective function is improved by adding flow rate and velocity penalty term when the flow of water supply network has been initially divided. By coupling the energy consumption mathematical model and improving the economic model, the multi-objective optimization mathematical model is obtained, which can achieve the purpose of energy saving and low carbon application on the basis of ensuring the economy and the safety of water supply, and realize the multi-objective optimization. In this paper, the hybrid evolutionary algorithm is used to solve the mathematical model of multi-objective optimization, and the implementation process of the hybrid evolutionary algorithm is studied emphatically. In this paper, the hybrid evolutionary algorithm is implemented on C platform, and the algorithm uses EPANET to call the information of pipe segment in the process of implementation. Finally, the optimal solution set of Pareto is obtained by hybrid evolutionary algorithm, and the optimal solution is selected from the optimal solution set to realize the solution of multi-objective optimization problem. At the same time, in order to test the performance of hybrid evolutionary algorithm, the genetic algorithm is used to solve the objective function. In this paper, the multi-objective optimization mathematical model and hybrid optimization algorithm are tested by using some pipe networks in Jiaozhou Industrial New area as an example. Through the test of three different working conditions of maximum day, fire time and accident time, it is found that the optimal solution obtained by the multi-objective optimization function and multi-objective hybrid evolutionary algorithm of water supply network established in this paper is reasonable and can meet the requirements of practical application.
【學(xué)位授予單位】：青島理工大學(xué)
【學(xué)位級(jí)別】：碩士
【學(xué)位授予年份】：2013
【分類號(hào)】：TU991.3

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