本文選題：智能電網(wǎng)　切入點：多目標優(yōu)化　出處：《蘭州理工大學》2014年碩士論文

【摘要】：智能電網(wǎng)是應對全球能源、氣候、環(huán)境以及經(jīng)濟和可持續(xù)發(fā)展的綜合解決方案,也是未來電網(wǎng)研究與發(fā)展的方向。輸配電網(wǎng)的智能化是堅強智能電網(wǎng)的重要內(nèi)容。智能電網(wǎng)規(guī)劃是電力系統(tǒng)規(guī)劃的重要組成部分,對其進行科學合理的規(guī)劃,能夠給社會帶來巨大的經(jīng)濟效益和社會效益,同時也是發(fā)展智能電網(wǎng)的重要基礎。電網(wǎng)規(guī)劃是一個非線性、多目標、多約束的問題,其涉及潮流計算、無功補償、網(wǎng)絡損耗、供電可靠性及經(jīng)濟性等約束。 用傳統(tǒng)的電網(wǎng)優(yōu)化方法求解電網(wǎng)規(guī)劃時,算法往往容易陷入局部最優(yōu)解,使得最終不能尋到全局最優(yōu)解。近年來,現(xiàn)代啟發(fā)式算法被廣泛應用于各個領域并且取得很好的效果,這些算法具有全局尋優(yōu)能力強及通用性強等特點,但是容易產(chǎn)生“維數(shù)災”問題。本文根據(jù)粒子群算法的基本思想,結合量子理論,提出一種改進的量子粒子群優(yōu)化算法,并將其應用在輸電網(wǎng)網(wǎng)架規(guī)劃和含分布式電源的智能電網(wǎng)多目標優(yōu)化規(guī)劃中。研究表明,該算法對智能電網(wǎng)多目標優(yōu)化規(guī)劃是有效的。 本文根據(jù)電網(wǎng)規(guī)劃的多目標性,選擇合適的目標建立電網(wǎng)規(guī)劃的數(shù)學模型。對量子粒子群算法進行改進,使其能應用在離散問題的求解中。改進后的量子粒子群算法提高了算法的運行速度和收斂速度。以18節(jié)點輸電網(wǎng)系統(tǒng)擴展規(guī)劃和8節(jié)點含分布式電源的配電網(wǎng)擴展規(guī)劃為例,驗證該算法求解多目標規(guī)劃的有效性及高效性。對于多目標Pareto最優(yōu)解集,采用擁擠距離排序方法進行構造。 最后應用MATLAB軟件對算例進行仿真研究并得出相應規(guī)劃結果。結果表明本文應用的量子粒子群算法在智能電網(wǎng)多目標規(guī)劃時能夠在保證計算速度的前提下,很好的完成電網(wǎng)規(guī)劃的任務。
[Abstract]:Smart grid is a comprehensive solution to global energy, climate, environment, economic and sustainable development. It is also the direction of grid research and development in the future.Intelligent transmission and distribution network is an important content of strong smart grid.Smart grid planning is an important part of power system planning. Scientific and reasonable planning can bring great economic and social benefits to the society, and it is also an important basis for the development of smart grid.Power network planning is a nonlinear, multi-objective, multi-constraint problem, which involves power flow calculation, reactive power compensation, network loss, power supply reliability and economic constraints.When the traditional power network optimization method is used to solve the power network planning, the algorithm is easily trapped in the local optimal solution, so that the global optimal solution can not be found in the end.In recent years, modern heuristic algorithms have been widely used in various fields and achieved good results. These algorithms have the characteristics of strong global optimization ability and strong versatility, but they are easy to produce the problem of "dimension disaster".Based on the basic idea of particle swarm optimization and quantum theory, an improved quantum particle swarm optimization algorithm is proposed in this paper. It is applied to transmission network planning and smart grid multi-objective optimization planning with distributed generation.The research shows that the algorithm is effective for multi-objective optimization planning of smart grid.In this paper, according to the multi-objective of power network planning, the mathematical model of power network planning is established by selecting suitable targets.The quantum particle swarm optimization (QPSO) algorithm is improved so that it can be used to solve discrete problems.The improved Quantum Particle Swarm Optimization (QPSO) algorithm improves the speed of operation and convergence of the algorithm.Taking the expansion planning of 18-node transmission network system and the distribution network expansion planning with 8-node distributed generation as examples, the effectiveness and efficiency of the algorithm for solving multi-objective programming are verified.For the multi-objective Pareto optimal solution set, the congestion distance sorting method is used to construct the optimal solution set.Finally, the MATLAB software is used to simulate the example and the corresponding programming results are obtained.The results show that the quantum particle swarm optimization (QPSO) algorithm applied in this paper can accomplish the task of power network planning well under the premise of ensuring the computing speed when the smart grid multi-objective programming is carried out.
【學位授予單位】：蘭州理工大學
【學位級別】：碩士
【學位授予年份】：2014
【分類號】：TM715

【參考文獻】

相關期刊論文 前10條

1 劉波;張焰;楊娜;;改進的粒子群優(yōu)化算法在分布式電源選址和定容中的應用[J];電工技術學報;2008年02期

2 伍力,吳捷,鐘丹虹;多目標優(yōu)化改進遺傳算法在電網(wǎng)規(guī)劃中的應用[J];電力系統(tǒng)自動化;2000年12期

3 王成山;陳愷;謝瑩華;鄭海峰;;配電網(wǎng)擴展規(guī)劃中分布式電源的選址和定容[J];電力系統(tǒng)自動化;2006年03期

4 麻常輝;薛禹勝;魯庭瑞;王小英;;輸電規(guī)劃方法的評述[J];電力系統(tǒng)自動化;2006年12期

5 陳琳;鐘金;倪以信;甘德強;;聯(lián)網(wǎng)分布式發(fā)電系統(tǒng)規(guī)劃運行研究[J];電力系統(tǒng)自動化;2007年09期

6 王志剛,楊麗徙,陳根永;基于蟻群算法的配電網(wǎng)網(wǎng)架優(yōu)化規(guī)劃方法[J];電力系統(tǒng)及其自動化學報;2002年06期

7 謝敬東,唐國慶,吳新余;進化規(guī)劃在電網(wǎng)規(guī)劃中的應用[J];電力系統(tǒng)及其自動化學報;1998年02期

8 劉曉飛,彭建春,高效,陳景懷,卜永紅;基于單親遺傳算法的配電網(wǎng)絡規(guī)劃[J];電網(wǎng)技術;2002年03期

9 張文亮;劉壯志;王明俊;楊旭升;;智能電網(wǎng)的研究進展及發(fā)展趨勢[J];電網(wǎng)技術;2009年13期

10 徐玉琴;李雪冬;;基于改進免疫克隆選擇算法的含分布式電源配電網(wǎng)規(guī)劃方法[J];電網(wǎng)技術;2010年08期

相關博士學位論文 前1條

1 孫俊;量子行為粒子群優(yōu)化算法研究[D];江南大學;2009年

，

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