本文選題：分布式電源 + 不確定性　； 參考：《電力系統(tǒng)自動(dòng)化》2015年14期

【摘要】：針對(duì)計(jì)及分布式電源(DG)出力波動(dòng)性及負(fù)荷需求不確定性的配電網(wǎng)孤島劃分問(wèn)題,提出了一種基于樹(shù)背包理論的最優(yōu)孤島劃分新模型及相應(yīng)求解方法。所述方法的基本思路為:首先,構(gòu)造了DG出力波動(dòng)性和負(fù)荷需求不確定性基于樹(shù)背包理論的隨機(jī)最優(yōu)孤島劃分新模型;進(jìn)而,基于拉丁超立方超樣方法、確定性樹(shù)背包算法、數(shù)理統(tǒng)計(jì)方法,確定各初始孤島的組成,包括DG及相應(yīng)負(fù)荷節(jié)點(diǎn);最后,對(duì)每個(gè)初始孤島在考慮孤島重構(gòu)的基礎(chǔ)上采用基于隨機(jī)最優(yōu)潮流的優(yōu)化調(diào)整,通過(guò)優(yōu)化調(diào)整而保證DG孤島運(yùn)行的最優(yōu)性、安全性和經(jīng)濟(jì)性。所述方法實(shí)現(xiàn)了計(jì)及分布式發(fā)電及負(fù)荷出力不確定性情況下最佳孤島的系統(tǒng)形成方法,能根據(jù)實(shí)時(shí)情況確定最大可能出現(xiàn)的孤島,相對(duì)于在確定性條件下的孤島具有更強(qiáng)的可信度。含有多個(gè)DG的PGE 69節(jié)點(diǎn)系統(tǒng)的算例驗(yàn)證了所述模型及算法的有效性。
[Abstract]:A new optimal islanding model based on tree knapsack theory is proposed to solve the islanding problem of distribution network considering the fluctuation of distributed power generation (DG) and uncertainty of load demand. The basic ideas of the proposed method are as follows: firstly, a new stochastic optimal island partition model based on tree knapsack theory is constructed for DG force fluctuation and load demand uncertainty, and then, based on Latin hypercube hypersample method, deterministic tree knapsack algorithm is proposed. The composition of each initial island, including DG and corresponding load nodes, is determined by mathematical statistical method. Finally, the optimal adjustment based on stochastic optimal power flow is adopted for each initial island based on the consideration of island reconstruction. The optimality, safety and economy of DG island operation are ensured by optimizing adjustment. The method realizes the system forming method that takes into account the uncertainty of distributed generation and load output, and can determine the largest possible isolated island according to the real-time situation. Compared with the island under deterministic conditions, it has stronger reliability. An example of PGE 69 bus system with multiple DG is given to verify the validity of the proposed model and algorithm.
【作者單位】： 智能電網(wǎng)教育部重點(diǎn)實(shí)驗(yàn)室(天津大學(xué));同濟(jì)大學(xué)電子與信息工程學(xué)院;國(guó)網(wǎng)河南省電力公司經(jīng)濟(jì)技術(shù)研究院;
【基金】：國(guó)家自然科學(xué)基金資助項(xiàng)目(51177107)~~
【分類號(hào)】：TM732

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本文編號(hào)：2029832