CAJ | 학술논문

随着光伏发电系统容量的不断扩大,光伏阵列发电预测技术对于减轻光伏阵列输出电能的随机性对电力系统的影响具有重要意义.本文提出了一种加入天气预报信息的神经网络发电预测模型的设计方案.结合历史发电量数据和气象数据分析了影响光伏阵列发电量的各项因素,采用光伏阵列的发电量序列、日类型指数和气温建立了神经网络预测模型,并对训练好的模型进行了测试和评估.预测结果表明,预测模型有较高的精度,能够解决光伏发电的随机化问题,提高系统的稳定运行能力.
수착광복발전계통용량적불단확대,광복진렬발전예측기술대우감경광복진렬수출전능적수궤성대전력계통적영향구유중요의의.본문제출료일충가입천기예보신식적신경망락발전예측모형적설계방안.결합역사발전량수거화기상수거분석료영향광복진렬발전량적각항인소,채용광복진렬적발전량서렬、일류형지수화기온건립료신경망락예측모형,병대훈련호적모형진행료측시화평고.예측결과표명,예측모형유교고적정도,능구해결광복발전적수궤화문제,제고계통적은정운행능력.
With the increase of the capacity of photovoltaic generated systems, how to eliminate the problem caused by the randomness of power output for photovoltaic system becomes more significant. A novel neutral network power forecasting model based on weather forecast is proposed to solve the randomness of power output for photovoltaic system. According to historical power and weather data provided by experiment, all factors which influence photovoltaic generated energy are discussed and neutral network forecasting module is trained and evaluated by adopting generated power series of photovoltaic arrays, day-type and temperature. Forecasting results show the high precision and high efficiency of this forecasting model which is applied in stable operation of photovoltaic generation system.