基于改进CS算法优化Elman-IOC神经网络的短期负荷预测
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摘要
为提高负荷预测精度,提出一种基于混沌定向布谷鸟算法优化Elman-IOC神经网络的短期负荷预测模型,首先对Elman神经网络拓扑结构进行改进设计,通过增添输入-输出层连接单元,加强网络并行运算能力,提高预测精度,然后在布谷鸟算法中,利用最优位置信息指导随机游动过程,同时引入混沌扰动算子,增强全局搜索能力,最后将算法应用于Elman-IOC神经网络参数优化,建立了短期负荷预测模型。实验结果表明,较之其他模型,此模型具有更高的预测精度。
In order to improve the accuracy of load forecasting,a short-term load forecasting model based on Elman-IOC neural network with chaotic oriented cuckoo optimization algorithm was proposed in this paper. Firstly,the Elman neural network topology is improved by adding the input-output layer connection unit,the network parallel computing capability is enhanced and the prediction accuracy is improved. Then,in the cuckoo algorithm,the optimal location information is used to guide the random walk process. Meanwhile,the chaos disturbance operator is introduced to enhance the global search ability. Finally,the algorithm is applied to Elman-IOC neural network parameter optimization,and a short-term load forecasting model is established. The experimental results show that compared with other models,this model has higher prediction accuracy.
In order to improve the accuracy of load forecasting,a short-term load forecasting model based on Elman-IOC neural network with chaotic oriented cuckoo optimization algorithm was proposed in this paper. Firstly,the Elman neural network topology is improved by adding the input-output layer connection unit,the network parallel computing capability is enhanced and the prediction accuracy is improved. Then,in the cuckoo algorithm,the optimal location information is used to guide the random walk process. Meanwhile,the chaos disturbance operator is introduced to enhance the global search ability. Finally,the algorithm is applied to Elman-IOC neural network parameter optimization,and a short-term load forecasting model is established. The experimental results show that compared with other models,this model has higher prediction accuracy.
引文
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[2]汤庆峰,刘念,张建华,等.基于EMD-KELM-EKF与参数优选的用户侧微电网短期负荷预测方法[J].电网技术,2014,38(10):2691-2699.Tang Qingfeng,Liu Nian,Zhang Jianhua,et al.A Short-Term Load Forecasting Method for Micro-Grid based on EMD-KELM-EKF and Parameter Optimizaton[J].Power System Technology,2014,38(10):2691-2699.
[3]Zhang X,Wang J,Zhang K.Short-term electric load forecasting based on singular spectrum analysis and support vector machine optimized by Cuckoo search algorithm[J].Electric Power Systems Research,2017,146:270-285.
[4]Sun H,Pan X,Meng C.A Short-Term Power Load Prediction Algorithm of Based on Power Load Factor Deep Cluster Neural Network[J].Wireless Personal Communications,2017:1-12.
[5]Rana M,Koprinska I.Forecasting electricity load with advanced wavelet neural networks[J].Neurocomputing,2016,182:118-132.
[6]王惠中,刘轲,等.电力系统短期负荷预测建模仿真研究[J].计算机仿真,2016,33(2):175-179.Wang Huizhong,Liu Ke,et al.Computer simulation Pretreatment of Short-Term Load Forecasting Based on K-Means Clustering Algorithm[J].Computer Simulation,2016,33(2):175-179.
[7]陆宁,武本令,刘颖.基于自适应粒子群优化的SVM模型在负荷预测中的应用[J].电力系统保护与控制,2011,39(15):43-46.Lu Ning,Wu Benling,Liu Ying.Application of support vector machine model in load forecasting based on adaptive particle swarm optimization[J].Power System Protection and Control,2011,39(15):43-46.
[8]Mordjaoui M,Haddad S,Medoued A,et al.Electric load forecasting by using dynamic neural network[J].International Journal of Hydrogen Energy,2017,42(28):17655-17663.
[9]Li P,Li Y,Xiong Q,et al.Application of a hybrid quantized Elman neural network in short-term load forecasting[J].International Journal of Electrical Power&Energy Systems,2014,55:749-759.
[10]张健美,周步祥,林楠,等.灰色Elman神经网络的电网中长期负荷预测[J].电力系统及其自动化学报,2013,25(4):145-149.Zhang Jianmei,Zhou Buxiang,Lin Nan,et al.Prediction of Mid-long Term Load Based Based on Gray Elman Neural Networks[J].Proceedings of the CSU-EPSA,2013,25(4):145-149.
[11]韩佳,王宏华,杜炜.基于FOA-Elman神经网络的光伏电站短期出力预测模型[J].电测与仪表,2014,51(12):120-124.Han Jia,Wang Honghua,Du Wei.Short-Term photovoltaic Power Forecasting Based on Elman Neural Network with Fruit Fly Optimization Algorithm[J].Electrical Measurement&Instrumentation,2014,51(12):120-124.
[12]T.M.Peng.Advancement in the application of neural networks for short-term load forecasting[J].IEEE/PES 1991 Summer Meeting,Paper#451-5 PWRS.
[13]Ren Y,Suganthan P N,Srikanth N,et al.Random vector functional link network for short-term electricity load demand forecasting[J].Information Sciences,2016,367:1078-1093.
[14]Yang X S,Deb S.Cuckoo search via Levy flights[C].Proceedings of World Congress on Nature&Biologically Inspired Computing,India:IEEE Publication,2009,210-214.
[15]Cui Z,Sun B,Wang G,et al.A novel oriented cuckoo search algorithm to improve DV-Hop performance for cyber-physicalsystems[J].Journal of Parallel and Distributed Computing,2017,103:42-52.