基于SVM預(yù)測(cè)電動(dòng)汽車并網(wǎng)局部電壓穩(wěn)定的研究
吳恒，余秋鵬
（國(guó)網(wǎng)江蘇省電力有限公司宿遷供電分公司, 江蘇 宿遷 223800）
摘 要：以IEEE14節(jié)點(diǎn)系統(tǒng)作為電動(dòng)汽車隨機(jī)并網(wǎng)充電的模型，通過(guò)基于MATLAB仿真環(huán)境的PSAT軟件分別計(jì)算出電動(dòng)汽車隨機(jī)并網(wǎng)充電時(shí)充電母線和相鄰母線的電壓和相角參數(shù)，從而得出相應(yīng)的局部電壓穩(wěn)定性指標(biāo)(L 指標(biāo))。運(yùn)用支持向量機(jī)(SVM) 算法對(duì)電壓L 指標(biāo)進(jìn)行訓(xùn)練和預(yù)測(cè)，結(jié)果表明，支持向量機(jī)算法簡(jiǎn)單高效，有助于預(yù)測(cè)電動(dòng)汽車隨機(jī)接入并網(wǎng)充電對(duì)電網(wǎng)電壓穩(wěn)定L 指標(biāo)的影響。通過(guò)仿真算例得出電動(dòng)汽車隨機(jī)接入電網(wǎng)不僅對(duì)自身母線產(chǎn)生電壓穩(wěn)定的影響，而且對(duì)相鄰的母線電壓穩(wěn)定也產(chǎn)生較大的影響，其中對(duì)于電動(dòng)汽車并網(wǎng)充電的中部母線產(chǎn)生的電壓穩(wěn)定影響最大，最容易導(dǎo)致電壓穩(wěn)定事故。
關(guān)鍵詞：電動(dòng)汽車；并網(wǎng)充電；電壓穩(wěn)定L 指標(biāo)；支持向量機(jī)(SVM)
中圖分類號(hào)：TM712；U469.72 文獻(xiàn)標(biāo)識(shí)碼：A 文章編號(hào)：1007-3175(2019)10-0009-05
Research on Prediction of Local Voltage Stability of Electric Vehicles Based on SVM
WU Heng,YU Qiu-peng
（State Grid Jiangsu Electric Power Co., Ltd, Suqian Power Supply Company, Suqian 223800, China）
Abstract: Taking the IEEE 14-bus system as the model of random grid charging of electric vehicles, this paper used the software PSAT in MATLAB simulation environment to respectively calculate the random grid charging electric vehicle charging bus and adjacent bus voltage and phase parameters, to obtain the corresponding index L of local voltage stability. The support vector machine (SVM) algorithm was used to train and predict the index L. The results show that the SVM algorithm is simple and efficient, helpful to predict the impact of random grid charging of electric vehicles on the grid voltage index L. Through simulation examples, it is concluded that the random access of the electric vehicle to the grid not only affects the voltage stability of its own bus, but also has a greater impact on the stability of the adjacent bus voltage, of which the voltage stability impact generated by the central bus of the electric vehicle connected to the grid is the maximum, easy to cause a voltage stability accident.
Key words: electric vehicle; grid charging; voltage stability index L; support vector machine
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