Computer Science ›› 2017, Vol. 44 ›› Issue (6): 226-231.doi: 10.11896/j.issn.1002-137X.2017.06.038

Previous Articles     Next Articles

Short-term Power Forecasting for Photovoltaic Generation Based on HS-ESN

WEN Run and TAN Li   

  • Online:2018-11-13 Published:2018-11-13

Abstract: To improve the accuracy of short-term power prediction for photovoltaic generation,the forecasting model of combination of harmony search(HS) algorithm and echo state network (ESN) algorithm was proposed.The model is based on historical power and weather data provided by a photovoltaic plant.Firstly,it selects the similar day of the forecasting day by the algorithm of similar day,and treats the difference of meteorological feature between the similar day and the forecasting day as the input variable of the model.Secondly,it chooses the training sample to train and forecast with the ESN model based on optimization of HS algorithm.Finally,it takes the photovoltaic plant in Gansu pro-vince as an example to test HS-ESN prediction model.Case analysis shows that the parameters of the reservoir of ESN prediction model optimized by HS algorithm can improve the prediction accuracy effectively,so it has better utility value.

Key words: PV system,Short-term power forecasting,HS algorithm,ESN algorithm,Algorithm of similar day,HS-ESN prediction model

[1] 中华人民共和国气象行业标准—太阳能评估方法[M].北京:气象出版社,2007.
[2] ZHANG X,KANG C Q,ZHANG N,et al.Analysis of Mid/Long Term Random Characteristics of Photovoltaic power Ge-neration[J].Automation of Electric Power Systems,2014,8(6):6-13.(in Chinese) 张曦,康重庆,张宁,等.太阳能光伏发电的中长期随机特性分析[J].电力系统自动化,2014,8(6):6-13.
[3] KONG B L,CUI L Y,DING Z,et al.Short term power prediction based on hybrid wind-PV forecasting model[J].Power System Protection and Control,2015,4(18):62-66.(in Chinese) 孔波利,崔丽艳,丁钊,等.基于风光混合模型的短期功率预测方法研究[J].电力系统保护与控制,2015,4(18):62-66.
[4] CUI Y,SUN Y C,CHANG Z L.A Review of Short-term Solar Photovoltaic Power Generation Prediction Methods[J].Resources Science,2013,5(7):1474-1481.(in Chinese) 崔洋,孙银川,常倬林.短期太阳能光伏发电预测方法研究进展[J].资源科学,2013,5(7):1474-1481.
[5] YENONA A,SENJYU ,FUNABASHI T.Application of recurrent neural network to short-term ahead generation power forecasting for photovoltaic system[C]∥IEEE Power Engineering Society General Meeting.2007:1-6.
[6] WANG S Y,ZHANG N.Short-term Output Power Forecast of Photovoltaic Based on a Grey and Neural Network Hybrid Mo-del[J].Automation of Electric Power Systems,2012,6(19):1-5.(in Chinese) 王守阳,张娜.基于灰色神经网络组合模型的光伏短期出力预测[J].电力系统自动化,2012,6(19):1-5.
[7] YUAN X L,SHI J H,XU J Y.Short-term power forecast for photovoltaic generation based on BP neural network[J].Rene-wable Energy Resources,2013,1(7):11-16.(in Chinese) 袁晓玲,施俊华,徐杰彦.基于BP神经网络的光伏发电短期出力预测[J].可再生能源,2013,1(7):11-16.
[8] YUAN X L,SHI J H,XU J Y.Short-term Power Forecasting for Photovoltaic Generation considering Weather Type Index[J].Proceeding of the CSEE,2013,3(34):57-64.(in Chinese) 袁晓玲,施俊华,徐杰彦.计及天气类型指数的光伏发电短期出力预测[J].中国电机工程学报,2013,3(34):57-64.
[9] PENG G H,MA J C,GONG W J,et al.Research of Prediction Model for Photovoltaic Power Based on ESN[J].Journal of Qingdao University(E&T),2015,0(3):12-15.(in Chinese) 彭光虎,马景超,龚文杰,等.基于ESN的光伏发电功率预测模型研究[J].青岛大学学报(工程技术版),2015,0(3):12-15.
[10] DING M,WANG L,BI R.A short-term prediction model toforecast output power of photovoltaic system based on improved BP neural network[J].Power System Protection and Control,2012,0(11):93-100.(in Chinese) 丁明,王磊,毕锐.基于改进BP神经网络的光伏发电系统输出功率短期预测模型[J].电力系统保护与控制,2012,0(11):93-100.
[11] YE L,CHEN Z,ZHAO Y N,et al.Photovoltaic Power Forecasting Model Based on Genetic Algorithm and Fuzzy Radial Basis Function Neural Network[J].Automation of Electric Power Systems,2015,9(16):16-22.(in Chinese) 叶林,陈政,赵永宁,等.基于遗传算法—模糊径向基神经网络的光伏发电功率预测模型[J].电力系统自化,2015,9(16):16-22.
[12] LI Y Z,NIU J C.Forecast of power generation for grid-connec-ted photovoltaic system based on Markov chain[C]∥Proceedings of Asia-Pacific Power and Energy Engineering Conference.2009:1-4.
[13] WU Z Y,TANG Y,FANG J X,et al.Collaborative FilteringRecommendation Algorithm Based on Ontology Semantic Similarity [J].Computer Science,2015,2(9):204-207.(in Chinese) 吴正洋,汤庸,方家轩,等.一种基于本体语义相似度的协同过滤推荐方法[J].计算机科学,2015,2(9):204-207.
[14] GU H,ZHANG W X,JIN P,et al.Method of Software Design Patterns Identification Based on Correlation and Feature Constraints[J].Computer Science,2015,2(2):133-176.(in Chinese) 古辉,张炜星,金鹏,等.基于关联度和特征约束的软件设计模式识别方法[J].计算机科学,2015,2(2):133-176.
[15] WANG X L,GE P J.PV array output power forecasting based on similar day and RBFNN[J].Electric Power Automation Equipment,2013,3(1):100-103.(in Chinese) 王晓兰,葛鹏江.基于相似日和径向基函数神经网络的光伏阵列输出功率预测[J].电力自动化设备,2013,3(1):100-103.
[16] LI C B,LI X H,ZHAO R,et al.A Novel Algorithm of Selecting Similar Days for Short-term Power Load Forecasting[J].Automation of Electric Power Systems,2008,2(9):69-73.(in Chinese) 黎灿兵,李晓辉,赵瑞,等.电力短期负荷预测相似日选取算法[J].电力系统自动化,2008,2(9):69-73.
[17] CAI J H,LIU J Y.Selecting method for similar day in super short-term load forecasting[J].Journal of North China Electric Power University,2006,3(1):38-41.(in Chinese) 蔡佳宏,刘俊勇.超短期负荷预测中相似日的选择方法[J].华北电力大学学报,2006,3(1):38-41.
[18] YANG J S,ZENG B Q,HU P P.Spectrum Allocation and Po-wer Control Based on Harmony Search Algorithm in Cognitive Radio Network[J].Computer Science,2015,2(11A):258-262.(in Chinese) 杨劲松,曾碧卿,胡翩翩.认知无线电网络中基于和声搜索的频谱分配与功率控制[J].计算机科学,2015,2(11A):258-262.
[19] GEEM Z W,TSENG C L.New Methodology,Harmony Search-and Its Robustness[C]∥Late-Breaking Papers of Genetic and Evolutionary Computation Conference(GECCO-2002).New York,USA,2002:174-178.
[20] KANG S L,GEEM Z W.A new structural optimization Method based on harmony search algorithm[J].Computes and Structures,2004,2(9/10):781-798.
[21] LEE K S,GEEM Z W.A new meta-heuristic algorithm For continuous engineering optimization:harmony Search theory and practice[J].Computer Methods in Applied Mechanics and Engineering,2005,4 (36-38):3902-3933.
[22] GEEM Z W,LEE K S,PARK Y.Application of harmony search to vehicle routing[J].American Journal of Applied Sciences,2005,2(12):1552-1557.
[23] KOUNTOURIOTIS P A,OBRADOVIC D,MANDIC D P,et al.Multi-step forecasting using echo state networks[C]∥ International Conference on Computer As a Tool.2005:1574-1577.
[24] BUEHNER M,YOUNG P.A Tighter Bound for the Echo State Property[J].IEEE Transactions on Neural Networks,2006,7(3):820-824.
[25] SKOWRONSKI M D,HARRI J G.Automatic speech recognition using a predictive echo state network classifier[J].Neural Networks,2007,20(3):414-423.
[26] LIN X,YANG Z,SONG Y.Short-term stock price prediction based on echo state networks[J].Expert Systems with Applications,2009,36(3):7313-7317.
[27] HOLZMANN G,HAUSER H.Echo State networks with filter neurons and a delay & sun readout[J].Neural Networks,2010,3(2):244-256.
[28] OZTURK M C,XU D M,Principle J C.Analysis and design of echo state networks[J].Neural Computation,2007,9(1):111-138.
[29] TIAN Z D,GAO X W,LI S J,et al.Prediction Method for Network Traffic Based on Genetic Algorithm Optimized Echo State Network[J].Journal of Computer Research and Development,2015,2(5):1137-1145.(in Chinese) 田中大,高宪文,李树江,等.遗传算法优化回声状态网络的网络流量预测[J].计算机研究与发展,2015,2(5):1137-1145.

No related articles found!
Viewed
Full text


Abstract

Cited

  Shared   
  Discussed   
No Suggested Reading articles found!