【摘要】：隨著國(guó)際社會(huì)對(duì)能源、生態(tài)、氣候等問(wèn)題的重視,大力發(fā)展可再生能源成為應(yīng)對(duì)這些問(wèn)題的重要舉措。太陽(yáng)能作為可再生能源中的一員,近年來(lái)發(fā)展迅速,分布式光伏作為光伏產(chǎn)業(yè)下一步大力發(fā)展的對(duì)象,具有運(yùn)用方式靈活,節(jié)約電能損耗,能源利用率高等特點(diǎn),是智能電網(wǎng)配電環(huán)節(jié)的重要組成部分。由于光伏輸出呈現(xiàn)間歇性、不穩(wěn)定的特點(diǎn),隨著分布式光伏在配網(wǎng)中滲透率的增加,配電網(wǎng)的結(jié)構(gòu)與運(yùn)行方式將會(huì)發(fā)生變化,為了減少對(duì)配網(wǎng)的影響,需要對(duì)分布式光伏進(jìn)行短期功率預(yù)測(cè),而且還要對(duì)分布式光伏在配網(wǎng)中的位置以及容量進(jìn)行優(yōu)化。因此,本文搭建了分布式光伏短期功率預(yù)測(cè)模型,對(duì)收集到的樣本進(jìn)行預(yù)測(cè)并對(duì)結(jié)果作誤差分析;在分布式光伏優(yōu)化配置方面,建立了多目標(biāo)優(yōu)化模型,運(yùn)用改進(jìn)多目標(biāo)微分進(jìn)化算法,對(duì)標(biāo)準(zhǔn)配網(wǎng)中的分布式光伏進(jìn)行優(yōu)化配置,主要研究?jī)?nèi)容如下:(1)研究了光伏發(fā)電系統(tǒng)的組成與分類,通過(guò)對(duì)理論模型與實(shí)際數(shù)據(jù)的仿真,從影響光伏功率輸出的角度,研究了光伏發(fā)電功率特性,并確定出光伏預(yù)測(cè)模型的輸入。從配電網(wǎng)系統(tǒng)潮流、供電可靠性、電能質(zhì)量等方面分析了分布式光伏并網(wǎng)對(duì)配電網(wǎng)所造成的影響,并從中選取多目標(biāo)優(yōu)化模型的優(yōu)化目標(biāo)與約束條件。(2)研究了小波變換的基本原理,對(duì)采集到的光伏功率序列作小波變換預(yù)處理,得到功率的各層序分量,分別建立預(yù)測(cè)模型進(jìn)行預(yù)測(cè)。分析了ESN神經(jīng)網(wǎng)絡(luò)的原理與結(jié)構(gòu),明確了ESN網(wǎng)絡(luò)訓(xùn)練的方法。針對(duì)收集到的光伏數(shù)據(jù)確定出預(yù)測(cè)模型的結(jié)構(gòu),輸入以及輸出參數(shù),搭建了WT+ESN光伏功率預(yù)測(cè)模型。(3)在matlab平臺(tái)上,選取晴天樣本與陰天樣本,分別運(yùn)用ESN,BP,WT+ESN以及WT+BP四種預(yù)測(cè)模型對(duì)分布式光伏的出力進(jìn)行預(yù)測(cè),并運(yùn)用三種誤差指標(biāo)對(duì)預(yù)測(cè)結(jié)果進(jìn)行評(píng)估。仿真結(jié)果表明,WT+ESN相較于其它三種模型,預(yù)測(cè)曲線更平穩(wěn),變化趨勢(shì)更貼近實(shí)際曲線,三種誤差評(píng)價(jià)指標(biāo)均是最優(yōu)的,驗(yàn)證了WT+ESN預(yù)測(cè)模型的有效性與優(yōu)越性。(4)建立了包含分布式光伏成本與運(yùn)維費(fèi)用,配電網(wǎng)有功網(wǎng)損,電壓穩(wěn)定指標(biāo)VSI以及各種約束條件的多目標(biāo)優(yōu)化模型。介紹了多目標(biāo)優(yōu)化問(wèn)題的數(shù)學(xué)描述。研究了微分進(jìn)化算法的原理與算法流程,鑒于傳統(tǒng)微分進(jìn)化算法過(guò)度依賴經(jīng)驗(yàn)控制參數(shù),將自適應(yīng)策略融入到算法中,并結(jié)合Pareto占優(yōu)概念提出了改進(jìn)多目標(biāo)微分進(jìn)化算法—MOSADE。(5)針對(duì)IEEE-33節(jié)點(diǎn)的標(biāo)準(zhǔn)配網(wǎng),在matlab平臺(tái)上進(jìn)行分布式光伏優(yōu)化配置研究。仿真結(jié)果表明,在網(wǎng)損最優(yōu)方面,SADE與DE及LDWPSO算法相比,在算法前期保持了種群多樣性,在算法后期提升了收斂速度;在全局最優(yōu)方面,運(yùn)用MOSADE對(duì)1-10組的DPV進(jìn)行有效配置,結(jié)果表明DPV的合理配置可以有效提升配網(wǎng)電壓水平、減小有功網(wǎng)損、增加發(fā)電收益,驗(yàn)證了多目標(biāo)優(yōu)化模型以及MOSADE算法的合理性與有效性。
[Abstract]:With the attention of the international community on energy, ecology, climate and other issues, vigorously developing renewable energy has become an important measure to deal with these problems. Solar energy, as a member of renewable energy, has developed rapidly in recent years. Distributed photovoltaic, as the next step of the photovoltaic industry, has the characteristics of flexible application, energy saving, high energy utilization and so on. It is an important part of the distribution link of smart grid. Because of the intermittent and unstable characteristics of photovoltaic output, with the increase of permeability of distributed photovoltaic in distribution network, the structure and operation mode of distribution network will change, in order to reduce the influence on distribution network. It is necessary to predict the short term power of distributed photovoltaic, and to optimize the position and capacity of distributed photovoltaic in distribution network. Therefore, this paper builds a distributed PV short-term power prediction model, forecasts the collected samples and makes error analysis of the results, and establishes a multi-objective optimization model for the distributed photovoltaic optimal configuration. Using the improved multi-objective differential evolution algorithm, the distributed photovoltaic system in standard distribution network is optimized. The main contents are as follows: (1) the composition and classification of photovoltaic power generation system are studied, and the simulation of theoretical model and practical data is carried out. From the point of view of affecting the output of photovoltaic power, the characteristics of photovoltaic power generation are studied, and the input of photovoltaic prediction model is determined. The influence of distributed photovoltaic grid connection on distribution network is analyzed from power flow, power supply reliability, power quality and so on. And the optimization objectives and constraints of the multi-objective optimization model are selected. (2) the basic principle of wavelet transform is studied. The collected photovoltaic power sequence is preprocessed by wavelet transform to obtain the sequence components of the power. The prediction models are established respectively. The principle and structure of ESN neural network are analyzed, and the training method of ESN neural network is clarified. According to the collected photovoltaic data, the structure, input and output parameters of the prediction model are determined, and the WT ESN photovoltaic power prediction model is built. (3) on the matlab platform, the sunny and overcast samples are selected. Four prediction models, ESN,BP,WT ESN and WT BP, are used to predict the output of distributed photovoltaic, and three kinds of error indexes are used to evaluate the prediction results. The simulation results show that compared with the other three models, the prediction curve of, WT ESN is more stable, the trend of change is closer to the actual curve, and the three kinds of error evaluation indexes are all the best. The validity and superiority of WT ESN prediction model are verified. (4) A multi-objective optimization model including distributed photovoltaic cost and operation cost, distribution network active power loss, voltage stability index (VSI) and various constraints is established. The mathematical description of multi-objective optimization problem is introduced. In this paper, the principle and flow of differential evolution algorithm are studied. In view of the traditional differential evolution algorithm relying too much on empirical control parameters, adaptive strategy is integrated into the algorithm. Combined with the concept of Pareto dominance, an improved multi-objective differential evolutionary algorithm (MOSADE. (5) is proposed for the standard distribution of IEEE-33 nodes. The distributed photovoltaic optimal configuration is studied on the matlab platform. The simulation results show that, compared with DE and LDWPSO algorithms, SADE maintains population diversity in the early stage of the algorithm, and improves the convergence speed in the later stage of the algorithm. In the aspect of global optimization, MOSADE is used to effectively configure 1-10 groups of DPV. The results show that the reasonable allocation of DPV can effectively enhance the voltage level of distribution network, reduce the loss of active power network, increase the income of generation, and verify the rationality and validity of the multi-objective optimization model and MOSADE algorithm.
【學(xué)位授予單位】：太原理工大學(xué)
【學(xué)位級(jí)別】：碩士
【學(xué)位授予年份】：2017
【分類號(hào)】：TM615

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