本文選題：分布式電源　切入點(diǎn)：潮流計(jì)算　出處：《上海電力學(xué)院》2016年碩士論文

【摘要】：配電網(wǎng)是連接輸電網(wǎng)與電力用戶的中間橋梁,配電網(wǎng)穩(wěn)定、可靠、經(jīng)濟(jì)運(yùn)行對(duì)整個(gè)電力系統(tǒng)的穩(wěn)定性具有重要的影響。配電網(wǎng)重構(gòu)是配電網(wǎng)供電路徑自我優(yōu)化和自我治愈能力的體現(xiàn),是正常運(yùn)行時(shí)降低網(wǎng)絡(luò)損耗、提高電能質(zhì)量以及故障后快速恢復(fù)供電,保持供電連續(xù)性的重要保證。分布式電源的接入改變了傳統(tǒng)配電網(wǎng)潮流模式,將改變配電網(wǎng)的網(wǎng)損和節(jié)點(diǎn)電壓。因此,如何通過(guò)配電網(wǎng)的網(wǎng)絡(luò)重構(gòu)優(yōu)化含有DG的配電網(wǎng)的供電路徑,提高系統(tǒng)運(yùn)行經(jīng)濟(jì)性、穩(wěn)定性以及解決故障后的供電恢復(fù)問(wèn)題具有重要的現(xiàn)實(shí)意義。本文針對(duì)含有DG的配電網(wǎng)重構(gòu)優(yōu)化和故障恢復(fù)策略兩個(gè)方面進(jìn)行研究,主要研究工作有:建立各類型DG的發(fā)電功率模型和節(jié)點(diǎn)類型,根據(jù)潮流計(jì)算中處理一些節(jié)點(diǎn)的困難之處,用無(wú)功補(bǔ)償方法和無(wú)功轉(zhuǎn)換的方式將其他類型節(jié)點(diǎn)進(jìn)行轉(zhuǎn)換,針對(duì)潮流計(jì)算過(guò)程中不確定性因素的影響,提出了基于兩點(diǎn)估計(jì)的概率計(jì)算,提高潮流計(jì)算的效率和準(zhǔn)確度。在供電路徑優(yōu)化重構(gòu)時(shí),根據(jù)分布式電源出力變化分為靜態(tài)重構(gòu)和動(dòng)態(tài)重構(gòu)策略,通過(guò)對(duì)初始復(fù)雜的配電網(wǎng)進(jìn)行拓?fù)浜?jiǎn)化處理,簡(jiǎn)化計(jì)算過(guò)程,引入無(wú)重復(fù)生成樹策略,從簡(jiǎn)化網(wǎng)絡(luò)的基本樹出發(fā),通過(guò)樹支與連支的交換生成不重復(fù)的輻射型網(wǎng)絡(luò)結(jié)構(gòu),無(wú)需在尋優(yōu)中進(jìn)行重復(fù)性的輻射型約束校驗(yàn),減少解的冗余度,提高供電路徑尋優(yōu)的效率;并與新型群智能動(dòng)態(tài)優(yōu)化算法-改進(jìn)“教與學(xué)”優(yōu)化算法相結(jié)合,提高動(dòng)態(tài)優(yōu)化的全局尋優(yōu)能力。在動(dòng)態(tài)尋優(yōu)時(shí),由于分布式電源出力隨時(shí)間發(fā)生不確定性變化,在構(gòu)造的重構(gòu)概率場(chǎng)景模型基礎(chǔ)上,提出了基于時(shí)序曲線劃分多場(chǎng)景的分析法來(lái)分割分布式電源出力,該方法能夠很好的適應(yīng)出力具有間歇性的風(fēng)機(jī)、光伏對(duì)配電系統(tǒng)影響,符合工程實(shí)際的運(yùn)用,為當(dāng)今智能配電網(wǎng)的供電路徑實(shí)時(shí)尋優(yōu)提供一定理論指導(dǎo)。在配電網(wǎng)故障恢復(fù)的過(guò)程中,考慮多目標(biāo)、多約束的情況,與配電網(wǎng)整體運(yùn)行特性相適應(yīng),具有全面性,針對(duì)孤島劃分問(wèn)題,采用兩階段方法進(jìn)行處理,CSP模型可以靈活的運(yùn)用于較為復(fù)雜的多點(diǎn)電源接入的情況,并應(yīng)用到孤島劃分第一階段尋找可行解,第二階段根據(jù)電壓指標(biāo)評(píng)價(jià)模型對(duì)初始方案進(jìn)行評(píng)優(yōu)修正來(lái)求最優(yōu)解;最后對(duì)孤島外的剩余網(wǎng)絡(luò)模型進(jìn)行開關(guān)組合尋優(yōu),求得最終的含多類型DG接入的配電網(wǎng)故障恢復(fù)方案。采用IEEE33節(jié)點(diǎn)系統(tǒng)和69節(jié)點(diǎn)系統(tǒng)對(duì)上述所提方法進(jìn)行算例驗(yàn)證,結(jié)果表明所提方法的有效性、可行性。
[Abstract]:Distribution network is a bridge between transmission network and power users. Distribution network is stable and reliable. Economic operation has an important effect on the stability of the whole power system. The reconfiguration of distribution network is the embodiment of self-optimization and self-healing ability of power supply path of distribution network and the reduction of network loss during normal operation. It is important to improve the power quality and restore the power supply quickly after the fault and maintain the continuity of the power supply. The access of the distributed power supply changes the traditional power flow mode of the distribution network and will change the network loss and node voltage of the distribution network. How to optimize the power supply path of the distribution network with DG through the network reconfiguration of the distribution network, so as to improve the operation economy of the system, It is of great practical significance to solve the problem of power supply recovery after failure. In this paper, the reconfiguration optimization of distribution network with DG and the strategy of fault recovery are studied. The main research work is as follows: the generation power model and node type of DG are established. According to the difficulties of dealing with some nodes in power flow calculation, the reactive power compensation method and reactive power conversion are used to convert other types of nodes. In order to improve the efficiency and accuracy of power flow calculation, a probability calculation based on two-point estimation is proposed for the influence of uncertain factors in the process of power flow calculation. According to the dynamic and static reconfiguration strategies of distributed power generation, the topology simplification of the initial complex distribution network is carried out to simplify the calculation process, and the no-repetition spanning tree strategy is introduced to simplify the basic tree of the network. Through the exchange of tree branches and connected branches, the non-repeated radiation type network structure is generated, which does not need to carry out the repetitive radiation type constraint check in the optimization, reduces the redundancy of the solution, and improves the efficiency of power supply path optimization. Combined with the new swarm intelligence dynamic optimization algorithm, the improved "teaching and learning" optimization algorithm is used to improve the global optimization ability of dynamic optimization. In dynamic optimization, the output force of distributed power supply changes with the uncertainty of time. On the basis of the reconstruction probability scenario model, an analysis method based on time series curve partitioning multi-scene is proposed to divide the distributed power generation. This method can adapt to the intermittent fan and the influence of photovoltaic on the distribution system. In accordance with the practical application of engineering, this paper provides some theoretical guidance for real-time optimization of power supply path of smart distribution network. In the process of fault recovery of distribution network, the situation of multi-objective and multi-constraint is considered, which adapts to the overall operating characteristics of distribution network. Because of its comprehensiveness, the two-stage method can be used to deal with the problem of island partition, which can be flexibly applied to the complicated multi-point power access, and to the first stage of islanding to find a feasible solution. In the second stage, according to the voltage index evaluation model, the initial scheme is evaluated and modified to find the optimal solution. Finally, the residual network model outside the island is optimized by switching combination. Finally, the final fault recovery scheme of distribution network with multi-type DG access is obtained. The IEEE33 node system and 69 bus system are used to verify the proposed method. The results show that the proposed method is effective and feasible.
【學(xué)位授予單位】：上海電力學(xué)院
【學(xué)位級(jí)別】：碩士
【學(xué)位授予年份】：2016
【分類號(hào)】：TM711

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