电力系统负荷预报的matlab实现.docVIP

摘 要 电力系统负荷预测是电力生产部门的重要工作之一。通过准确的负荷预测，可以合理安排机组启停，减少备用容量，合理安排检修计划及降低发电成本等。准确的预测，特别是短期预测对提高电力经营主体的运行效益有直接的作用，对电力系统控制、运行和计划都有重要意义。神经网络具有以下优点：（1)可以任意逼近复杂的非线性函数；（2）所有定量或定性的信息都等势分布贮存于网络内的各神经元，故有很强的鲁棒性和容错性(3)采用并行分布处理方法，使得快速进行大量运算成为可能；(4)可学习和自适应不知道或不确定的系统；(5)能够同时处理定量、定性知识。 本文介绍了电力负荷预测的主要方法和神经网络的原理、结构，分析了反向传播算法和广义神经网络算法，采用改进的三层人工神经网络来建立负荷预测模型，以前七天的负荷数据和当天影响负荷的天气因素作为数据样本，进行神经网络的自我训练和学习。用Matlab软件中分别实现了基于BP和GRNN的两种神经网络的短期电力负荷预测，取得了良好的预测效果，并对两种神经网络的仿真结果进行对比，结果表明GRNN的相对误差率比BP的相对误差率要小，这说明GRNN的仿真效果胜于BP。 关键字: 短期负荷预测, 人工神经网络, BP算法, 广义回归神经网络 Power System Load Forecast Matlab Abstract Power system load forecasting power production department is one of the most important work. Through the precise load forecast, can arrange unit start-stop, reduce the spare capacity, reasonable arrangement of the maintenance plan and reduce power cost, etc. Accurate projections, especially the short-term forecast to improve the running efficiency power operators have direct effect, on power system control, operation and plans to have the important meaning. Neural network advantages (1) can be arbitrary approximation complex nonlinear functions; (2) all quantitative or qualitative information stored in the potential distribution as the neurons in the network, it has strong robustness and fault tolerance; (3) using the parallel distributed processing methods, making quick lots of computing become possible; (4) can learn and adaptive dont know or uncertain system; (5) can simultaneously processing quantitative and qualitative knowledge. This paper based on matlab software to short-term neural function power load forecasting, in the prediction process of neural network achieved good prediction effect, mainly using BP and GRNN of two kinds of neural network to predict major electricity load. Then the forecast results are analyzed, in Matlab simulation model to establish two neural network, the simulation results are analyzed, get good results.With the two neural network compar