CAJ | 학술논문

随着风电大规模的接入电网，风电对电网的影响越来越大。由于风电出力具有随机性、间歇性和不可控性，导致风电对电网调度运行带来巨大的挑战。为了充分利用风电，必须将风电由未知变为基本已知，提高对风电出力的预测精度。提出一种基于帝国主义竞争算法的神经网络（ ICA-NN）方法来提高短期风功率预测的精度。在该方法中，首先，建立一个基于多层感知器（ MLP）人工神经网络的风速预测模型，然后，用帝国主义竞争算法优化神经网络中的权值。将该预测方法应用于新疆某风电场，验证了该方法应用于短期风功率预测的有效性，证明了该方法可以提高短期风功率预测的精度。
수착풍전대규모적접입전망，풍전대전망적영향월래월대。유우풍전출력구유수궤성、간헐성화불가공성，도치풍전대전망조도운행대래거대적도전。위료충분이용풍전，필수장풍전유미지변위기본이지，제고대풍전출력적예측정도。제출일충기우제국주의경쟁산법적신경망락（ ICA-NN）방법래제고단기풍공솔예측적정도。재해방법중，수선，건립일개기우다층감지기（ MLP）인공신경망락적풍속예측모형，연후，용제국주의경쟁산법우화신경망락중적권치。장해예측방법응용우신강모풍전장，험증료해방법응용우단기풍공솔예측적유효성，증명료해방법가이제고단기풍공솔예측적정도。
With the large-scale access of wind power grid , the wind power has more and more influence on power grid .Be-cause the wind power output is random , intermittent and uncontrolled , it brings the huge challenge to power grid dispatching and operation .In order to make full use of wind power , the wind power must be changed from unknown to known , and the prediction accuracy of wind power output should be improved .A neural network method based on imperialist competitive algo-rithm (ICA -NN) is presented to improve the accuracy of short -term wind power prediction.In this method, first of all, a prediction model of wind speed is established based on artificial neural network with multi -layer perceptron ( MLP), and then, the weight values of neural network are optimized with the imperialist competitive algorithm .The prediction method has been applied to a wind farm in Xinjiang , which verifies its effectiveness in short -term wind power prediction , and proves that the proposed method can improve the accuracy of short -term wind power prediction .