基于神经网络的新能源电站发电功率预测方法

Power Generation Power Prediction Method of New Energy Power Station Based on Neural Network

针对忽视了天气因素,功率预测结果与实际功率相差较大的问题,提出了基于神经网络的新能源电站发电功率预测方法。使用卷积神经网络,构建新能源电站发电功率预测模型,确定神经网络激活函数,确定不同新能源电站发电功率数据之间的关联性,分析预测结果与实际发电功率间的误差,完成新能源电站发电功率预测。实验结果表明,此方法在晴天与非晴天条件下,均可得到精度较好的预测结果,缩短预测结果与实际发电功率的差距。

Aiming at the problem that the weather factors are ignored and the power prediction results are quite different from the actual power,a power generation power prediction method of new energy power station based on neural network is proposed.The convolutional neural network is used to construct the power generation power prediction model of new energy power stations,determine the neural network activation function,determine the correlation between the power generation power data of different new energy power stations,analyze the error between the prediction results and the actual power generation power,and complete the power generation power prediction of new energy power stations.The experimental results show that this method can get better prediction results in sunny or non sunny days,and shorten the gap between the prediction results and the actual power generation power.