CAJ | 학술논문

在分析影响光伏阵列发电功率的天气因素基础上,提出了一种基于天气预报信息和相似日分类选取的反馈型神经网络预测模型. 运用天气预报和相似日评价函数,从天气的历史数据中选择出天气相似日,结合相似日的发电功率和相似日与预测日的天气数据建立Elman神经网络预测模型. 实验结果表明,模型预测精度较好,具备一定有效性.
재분석영향광복진렬발전공솔적천기인소기출상,제출료일충기우천기예보신식화상사일분류선취적반궤형신경망락예측모형. 운용천기예보화상사일평개함수,종천기적역사수거중선택출천기상사일,결합상사일적발전공솔화상사일여예측일적천기수거건립Elman신경망락예측모형. 실험결과표명,모형예측정도교호,구비일정유효성.
With the analysis of factors effecting the generated power of PV arrays,a feedback neural network prediction model was proposed based on the weather forecasting information and similar-day selection method in this paper.In the presented methodology,the similar-day was picked from the historical data using the evaluation function and the weather forecasting information.In addition,the applied Elman neural network prediction model was built based on the power generation data in the similar-day and the weather data of similar-day and the predicted date.The experiments show that the forecasting model has high prediction accuracy.