本文選題：分布式電源 + 無(wú)功優(yōu)化��； 參考：《蘭州交通大學(xué)》2017年碩士論文

【摘要】：配電網(wǎng)的無(wú)功優(yōu)化是增強(qiáng)網(wǎng)絡(luò)電壓水平、降低網(wǎng)絡(luò)損耗、保障電力網(wǎng)安全穩(wěn)定運(yùn)行的一項(xiàng)重要手段。采用在配電網(wǎng)中安裝DG(Distributed Generation,分布式能源)可在一定程度上緩解目前所面臨的能源危機(jī),達(dá)到節(jié)能減排,環(huán)保低碳的目標(biāo)。但是DG加入配電網(wǎng)使網(wǎng)絡(luò)中的潮流分布發(fā)生變化,從而使配電網(wǎng)的規(guī)劃、運(yùn)行以及控制方式發(fā)生改變。本文研究含DG的配電網(wǎng)的無(wú)功優(yōu)化問題,所做的主要工作如下:(1)本文構(gòu)建含DG配電網(wǎng)的無(wú)功優(yōu)化模型,其以減少系統(tǒng)的網(wǎng)損為目標(biāo),且考慮系統(tǒng)電壓的穩(wěn)定性指標(biāo)以及DG的無(wú)功調(diào)節(jié)的能力。同時(shí)基于無(wú)功裕度值的計(jì)算,確定無(wú)功補(bǔ)償點(diǎn)。模型以DG的無(wú)功出力以及電容器組投切組數(shù)作為無(wú)功優(yōu)化模型的控制變量,以網(wǎng)絡(luò)中負(fù)荷節(jié)點(diǎn)電壓作為其狀態(tài)變量,經(jīng)過優(yōu)化并網(wǎng)DG的無(wú)功出力大小以及所配置的電容器組的無(wú)功補(bǔ)償量達(dá)到對(duì)含DG配電網(wǎng)無(wú)功優(yōu)化的目的。(2)對(duì)含不同DG的潮流算法進(jìn)行改進(jìn)。首先將DG分別等效為不同的節(jié)點(diǎn)類型,通過前推回代法求解含不同DG的潮流計(jì)算。在處理PV節(jié)點(diǎn)時(shí),通過無(wú)功分?jǐn)傇碓O(shè)定無(wú)功初值,采用無(wú)功補(bǔ)償?shù)姆椒ㄟM(jìn)行功率修正。在IEEE33節(jié)點(diǎn)配電系統(tǒng)上,對(duì)含不同DG的配電網(wǎng)進(jìn)行潮流計(jì)算。仿真結(jié)果表明,DG的接入能提升系統(tǒng)節(jié)點(diǎn)電壓。(3)提出一種MABC(Modified Artificial Bee Colony,改進(jìn)的人工蜂群)算法。通過借鑒DE(Differential Evolution,差分進(jìn)化)算法的突變算子,使跟隨蜂的搜索策略受個(gè)體目前所獲得的最優(yōu)值的引導(dǎo),并加入擾動(dòng)項(xiàng),使算法的全局探索與局部開采能力得以平衡。此外,根據(jù)標(biāo)準(zhǔn)ABC算法中偵察蜂搜尋機(jī)制的不足,本文融合一般反向?qū)W習(xí)策略的思想,生成之前遺棄蜜源的反向解,加強(qiáng)了偵察蜂的搜尋經(jīng)驗(yàn),進(jìn)一步提高算法的搜索效率。在仿真實(shí)驗(yàn)中可以發(fā)現(xiàn),改進(jìn)的算法保持了ABC算法簡(jiǎn)單容易實(shí)現(xiàn)的特點(diǎn),增強(qiáng)了全局收斂性,有效提高了算法的收斂速度和收斂精度。(4)本文采用IEEE33以及美國(guó)PGE69節(jié)點(diǎn)系統(tǒng)進(jìn)行MATLAB仿真測(cè)試,分別使用本文提出的MABC算法、標(biāo)準(zhǔn)ABC算法和文獻(xiàn)中的IABC算法進(jìn)行優(yōu)化計(jì)算并比較,測(cè)試結(jié)果驗(yàn)證了本文所搭建的含DG配電網(wǎng)無(wú)功優(yōu)化數(shù)學(xué)模型和提出的MABC算法的有效性,其能夠使配電系統(tǒng)中的無(wú)功功率分布得以合理的優(yōu)化。此優(yōu)化方案可有效提高配電網(wǎng)的電壓水平和電力系統(tǒng)運(yùn)行的穩(wěn)定性。
[Abstract]:Reactive power optimization is an important means to enhance network voltage level, reduce network loss and ensure the safe and stable operation of power network. Installing DG(Distributed Generation (distributed Energy) in the distribution network can partly alleviate the current energy crisis and achieve the goal of saving energy and reducing emissions and protecting environment and low carbon. However, the distribution of power flow in the distribution network is changed by adding DG to the distribution network, and the planning, operation and control mode of the distribution network are changed. In this paper, the reactive power optimization problem of distribution network with DG is studied. The main work is as follows: 1) in this paper, the reactive power optimization model of distribution network with DG is constructed, which aims at reducing the network loss of the system. The stability index of system voltage and the ability of reactive power regulation of DG are also considered. At the same time, the reactive power compensation point is determined based on the calculation of reactive power margin. In the model, the reactive power of DG and the number of capacitor switching groups are taken as the control variables of the model, and the load node voltage in the network is taken as the state variable. The power flow algorithm with different DG is improved by optimizing the reactive power output of DG and the reactive power compensation of the capacitor bank to optimize the reactive power of distribution network with DG. First, the DG is equivalent to different node types, and the power flow calculation with different DG is solved by the forward pushback method. In dealing with PV nodes, the reactive power initial value is set by the reactive power allocation principle, and the reactive power compensation method is used to correct the power. The power flow of distribution network with different DG is calculated on IEEE33 node distribution system. The simulation results show that the access of DG can increase the node voltage of the system. (3) A MABC(Modified Artificial Bee colony algorithm is proposed. By using the mutation operator of the DE(Differential evolution (differential evolution) algorithm, the search strategy of the following bee is guided by the optimal value obtained by the individual at present, and the disturbance term is added to balance the global exploration and the local mining ability of the algorithm. In addition, according to the deficiency of search mechanism of reconnaissance bee in standard ABC algorithm, this paper combines the idea of general reverse learning strategy to generate the reverse solution of abandoned honey source, which strengthens the search experience of reconnaissance bee, and further improves the search efficiency of the algorithm. In the simulation experiment, it can be found that the improved algorithm keeps the characteristic of ABC algorithm simple and easy to realize, and enhances the global convergence. The convergence speed and precision of the algorithm are improved effectively. (4) in this paper, IEEE33 and PGE69 node system are used to carry out MATLAB simulation test, and the MABC algorithm, standard ABC algorithm and IABC algorithm in literature are used to optimize and compare, respectively, the proposed MABC algorithm, the standard ABC algorithm and the IABC algorithm in the literature. The test results verify the validity of the mathematical model of reactive power optimization with DG and the proposed MABC algorithm, which can optimize the distribution of reactive power in distribution system. This optimization scheme can effectively improve the voltage level of distribution network and the stability of power system operation.
【學(xué)位授予單位】：蘭州交通大學(xué)
【學(xué)位級(jí)別】：碩士
【學(xué)位授予年份】：2017
【分類號(hào)】：TM714.3

【參考文獻(xiàn)】

相關(guān)期刊論文 前10條

1 李敏霞;楊警衛(wèi);李云霞;;提高堅(jiān)強(qiáng)智能電網(wǎng)社會(huì)經(jīng)濟(jì)效益的對(duì)策建議[J];科技展望;2017年07期

2 彭躍進(jìn);張國(guó)瑞;王勇;劉志祥;黃明;鄭義斌;;陰、陽(yáng)極加濕對(duì)質(zhì)子交換膜燃料電池性能影響的差異性[J];電工技術(shù)學(xué)報(bào);2017年04期

3 趙挺;孟子航;沈海斌;;基于反向?qū)W習(xí)與Levy飛行的改進(jìn)蜂群算法[J];傳感器與微系統(tǒng);2017年01期

4 辛乳江;魏勇;;淺議儲(chǔ)能技術(shù)在風(fēng)力發(fā)電系統(tǒng)中的運(yùn)用[J];低碳世界;2017年01期

5 楊s铞，

本文編號(hào)：1826375