電動(dòng)汽車(chē)充電站短期負(fù)荷的神經(jīng)網(wǎng)絡(luò)預(yù)測(cè)模型
喬維德1，喬淳2
(1 無(wú)錫開(kāi)放大學(xué) 科研與發(fā)展規(guī)劃處，江蘇 無(wú)錫 214011；
2 錫山水務(wù)集團(tuán)有限公司，江蘇 無(wú)錫 214101)
摘 要：為提高電動(dòng)汽車(chē)充電站短期負(fù)荷預(yù)測(cè)精確度，以某電動(dòng)汽車(chē)充電站的相關(guān)數(shù)據(jù)為依據(jù)，分析了電動(dòng)汽車(chē)充電站的負(fù)荷特性以及影響負(fù)荷變化的主要因素，并構(gòu)建了基于人工魚(yú)群-蛙跳算法優(yōu)化反向傳播 (BP) 神經(jīng)網(wǎng)絡(luò)的電動(dòng)汽車(chē)充電站短期負(fù)荷預(yù)測(cè)模型。仿真算例結(jié)果表明，該模型預(yù)測(cè)優(yōu)勢(shì)明顯，預(yù)測(cè)速度快，預(yù)測(cè)精度高，適用于電動(dòng)汽車(chē)充電站的短期負(fù)荷預(yù)測(cè)，為下一步工程實(shí)踐應(yīng)用提供了理論依據(jù)。
關(guān)鍵詞： 電動(dòng)汽車(chē)充電站；短期負(fù)荷預(yù)測(cè)；神經(jīng)網(wǎng)絡(luò)
中圖分類(lèi)號(hào)：U469.72 ；TM714 文獻(xiàn)標(biāo)識(shí)碼：A 文章編號(hào)：1007-3175(2023)05-0007-05
Neural Network Forecasting Model for Short-Term Load of
Electric Vehicle Charging Stations
QIAO Wei-de1, QIAO Chun2
（1 Scientific Research and Development Planning Office of Wuxi Open University, Wuxi 214011, China;
2 Xishan Water Group Co., Ltd, Wuxi 214101, China）
Abstract: In order to increase the short-term load forecasting accuracy of electric vehicle charging stations, the paper, according to the relevant data of a electric vehicle charging station, makes analysis of its load characteristics and main factors affecting load variation, and builds a short-term load forecasting model of electric vehicle charging stations based on the back propagation (BP) neural network optimized by artificial fish-frog leap algorithm. The simulation results show that this model has great advantages of fast forecasting speed and high forecasting accuracy. It not only suits for short-term load forecasting of electric vehicle charging stations, but also provides a theoretical basis for the next engineering practice.
Key words: electric vehicle charging station; short-term load forecasting; neural network
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