發(fā)布時間：2018-06-11 19:48

  本文選題：線性化 + 潮流�。� 參考：《電網(wǎng)技術(shù)》2017年09期

【摘要】：電力系統(tǒng)潮流和最優(yōu)潮流是典型的非線性計算,需要處理復雜的非線性方程,因此計算量大,求解效率低,且在大電網(wǎng)運行分析領(lǐng)域易出現(xiàn)不收斂情況。線性化模型可以解決上述問題,直流模型是目前應(yīng)用最廣泛的線性化模型,計算速度快,但是計算精度相對較低�；诖�,以熱啟動和冷啟動環(huán)境為基準,首先對目前比較典型的5種線性化模型進行綜述,然后提出一種可以求解更完備潮流信息的線路解耦等值線性化模型。文章首先對5種線性化模型分別進行潮流計算和最優(yōu)潮流計算,并分別與交流模型計算結(jié)果進行對比,從理論和仿真2個角度探討了各線性化模型的優(yōu)缺點以及適用場景,驗證了所提模型在潮流計算以及最優(yōu)潮流計算中均具有較高的計算精度,求解效率高,且能夠計算更完備的潮流信息,綜合表現(xiàn)強于其他線性化模型。
[Abstract]:Power flow and optimal power flow in power system are typical nonlinear calculations, which need to deal with complex nonlinear equations. Therefore, power flow and optimal power flow have the advantages of large computational complexity, low efficiency and non-convergence in the field of large power network operation analysis. The linearization model can solve the above problems. The DC model is the most widely used linearization model at present. The calculation speed is fast, but the calculation accuracy is relatively low. Based on this, based on hot start and cold start environment, five typical linearization models are reviewed firstly, and then a line decoupling equivalent linearization model which can solve more complete power flow information is proposed. In this paper, five linearized models are calculated by power flow calculation and optimal power flow calculation respectively, and the results are compared with those of AC model, and the advantages and disadvantages of each linearization model and its applicable scenarios are discussed from two aspects of theory and simulation. It is verified that the proposed model has higher accuracy in power flow calculation as well as optimal power flow calculation. The proposed model is more efficient and can calculate more complete power flow information, which is better than other linearized models.
【作者單位】： 河海大學能源與電氣學院;國網(wǎng)江蘇省電力公司電力科學研究院;國網(wǎng)江蘇省電力公司檢修分公司;
【基金】：國家自然科學基金項目(51277052) 國家電網(wǎng)公司科技項目(J2017047)~~
【分類號】：TM744

【相似文獻】

相關(guān)期刊論文 前1條

1 廖翔,敖偉智,郝正航;復雜靈活交流輸電系統(tǒng)的通用線性化模型[J];貴州工業(yè)大學學報(自然科學版);2005年05期

，

本文編號：2006480