Regression Analysis and Indoor Air Temperature Model of Greenhouse in Northern Dry and Cold Regions

Transcription

1 Regression Anlysis nd Indoor Air Temperture Model of Greenouse in Nortern Dry nd Cold Regions Ting Zo, Heru Xue College of computer & informtion Engineering, Inner Mongoli Agriculturl Uniersity, Hoot, Inner Mongoli, P. R. Cin E-mil: Abstrct. Te indoor ir temperture of greenouse is n importnt prmeter in enironmentl monitoring. Existing reserc on it s mny, nd te mtemticl models e been mde. But te obtined models do not pply to te nortern res fetures of dry nd cold. On te bsis of preious studies, te indoor ir temperture model of greenouse will be re-modeling by using te regression nlysis metod in tis pper. Anlysis ec conection et trnsfer coefficient of te model nd re-estblised tem. In te cse of known te outdoor weter conditions, te solution of te indoor temperture will be implemented by using te computer progrmming. And te dt of period is selected rndomly from te obsertionl dt to lidte te model is fesible nd pplied. Key words: Indoor ir temperture model, Regression nlysis metod, Model prmeters, Computer progrmming Introduction Tere re mny dntges in Cin's ligt greenouse, but te enironmentl control leel of greenouse is still lower. Te rtificil experience is still te min force, nd teoreticl nd prcticl guidnce is lcking. Te indoor ir temperture of greenouse is n importnt prmeter in enironmentl monitoring. Predecessors e done lot of reserc on te prediction model of te indoor ir temperture of greenouse. But most studies e been done for te greenouse in Beijing. [, 2]And te obtined models do not pply to te nortern res fetures of dry nd cold. Te prediction model of te indoor ir temperture of greenouse wic cn be used in te nortern res fetures of dry nd cold cn predict te dily cnge of temperture wit time. According to forecsts, te stff cn regulte te temperture ctiely, so tt te crops cn be proided te best growt tempertures. Te model to be build up on te bsis of preious work, nd te indoor ir temperture model of greenouse will be re-modeling by using te regression nlysis metod. Anlysis ec conection et trnsfer coefficient of te model nd re-estblised tem. Te typicl res nd typicl greenouse will be cosen for te study. And using te known conditions to lidte te model is fesible nd pplied.

2 2 Te indoor ir temperture model of greenouse Tble. Sign Description emblem description unit emblem description Q Het excnge W Indoor ir temperture V Volume m3 b Rer wll A Are m2 c Crop cnopy T Temperture K Heting Q Conection et trnsfer W o Outdoor ir energy Temperture cv p Het cpcity Kg/s r Rer slope J/K s Soil Ventiltion Coers 2. Het blnce differentil eqution of indoor ir temperture Te et blnce differentil eqution used in tis pper minly by et conduction differentil eqution. Te model conditions e been simplified some. And ccording to te et trnsfer principles nd te lw of consertion of mss nd energy, te pysicl processes in te greenouse e been considered compreensiely. Te terml cnge s muc effect on terml enironment of greenouse cused by et cnge nd moisture rition wic come from solr rdition, et conection, rdition et trnsfer, et excnge nd nturl entiltion. [3, 4] dt cp b r s c () dt0 On te left of te eqution is te et cnge cused by te ir temperture cnges wit time. And te rigt contins te energy of te indoor ir temperture coming from ot-wter eting--q ; te energy of te indoor ir temperture wsted by nturl entiltion nd infiltrtion et loss-- Q ; nd te energy coming from nturl-conection et trnsfer-- Q i. Tis is te deried formul of te indoor ir temperture cnges wit time.

3 t t 0 t t 0 Q b r s c p c t (2) Known by te Newton's lw of cooling, te conection et trnsfer energy from gs A to solid B cn be sown s tis. QA B A A B A (T B A TB ) (3) In tis eqution, A A is te surfce re of te et trnsfer from A to B; B is A B te coefficient of te et trnsfer between A nd B; T nd A T is te temperture B of A nd B. Te indoor ir is eted minly by te ot-wter eting pipes. And te et trnsfer between eting pipes nd te indoor ir is crried out by conection. Te energy of te indoor ir temperture coming from ot-wter eting is Q. It cn be sown s tis. Q A (T T) (4) p In tis eqution, A is te surfce re of te ot-wter eting pipes; coefficient of te et trnsfer between te eting pipes nd te indoor ir; is te T is te temperture of te ot-wter eting pipes; T is te indoor ir temperture. Te energy of te indoor ir temperture wsted by nturl entiltion nd infiltrtion et loss is Q. It cn be sown s tis. p Q c (T T) (5) o In tis eqution, is te ir quntity of te indoor ir; c p is te specific et olume of te indoor ir; T is te indoor ir temperture; T is te outdoor ir o temperture. Troug te equtions of (2),(3),(4),nd (5), te et blnce differentil eqution of indoor ir temperture cn be simplified s tis.

4 (T T0 ) c p T A (T T ) A (T A (T T ) A (T b b c c T ) A (T b T ) c c r r p (T T ) A (T r T ) o s s T ) s (6) 2.2 Het conection coefficient-- i Het conection is te et trnsfer wic ppened on te liquid flows troug te solid surfce. In te greenouse wic s te smll nturl entiltion, rising or declining te indoor ir temperture is minly troug te et conection wit te coer, te ground soil, plnts nd oter et trnsfer to ciee. Tere re mny essys bout te et conection in oerses. And te studies in tis respect re lso ery mture. Te ritmetic in tese studies cn be used in our country greenouse. Te et conection coefficient cn be sown s tis. [5] ) (Ti T j 4 5 (7) Bsed on suc expression of te et conection, ec et conection coefficient 0.25 of te et blnce differentil equtions cn be explined to T i T. Terefore, te problem of optimizing te eqution is te problem of clculting te lue of. j 3 Known conditions of tis model 3. Structurl prmeters To fcilitte te clcultion, te greenouse structure cn be pproximtely regrded s te following grpic wic does not ffect te results on te premise.

5 Te lengt of te greenouse L5=50(m) Lef re index of te indoor crops L=0.3 Te re of te coers L*L5 Te re of te ground L4*L5 Te re of te rer slope L2*L5 Te re of te rer wll L3*L5 Te re of te crop cnopy L4*L5*L Te olume of te indoor ir V=506 Te specific et olume of te indoor ir c =85; kj/(kg ) p Te temperture of te eting pipes during te dy T=60+273;(K) Te re of te eting pipes is 9 m^2 Te coefficient of te et trnsfer between te eting pipes nd te indoor ir *(T T 空气管内水 ) Te ir quntity of te indoor ir Φ=0.00*V/ Known conditions (Temperture indictors) ) Te 24-our predicted lues come from te weter forecst. Tey include te outdoor ir temperture, te outdoor umidity, te wind elocity, te wind direction nd te uitriolet intensity. 2) Ec erge of te dt clculted by our is obtined. And te dt of te coer temperture, te soil temperture, te rer wll temperture, te rer slope temperture, te crop cnopy temperture nd indoor ir temperture is detected by te greenouse monitoring system.

6 4 Model lidtion Experimentl dt is te obsered dt wic cn stnd for te nortern res fetures of dry nd cold. Use nonliner regression nlysis to optimize te prmeters wic comes from tis et blnce differentil eqution of indoor ir temperture. Nonliner regression nlysis is using lest squre metod to estimte te prmeters of non-liner model. Formul six is used to te regression eqution of non-liner model. Te strting lue of te prmeter cose te empiricl lue.25.te smple dt cose te dt from Noember nd December of 2009 nd Jnury nd Februry of 200. Oter required temperture used te obsered dt. Ec et trnsfer coefficient of te model ws re-estblised by using SAS softwre. Noember 23 to 30, 2009 nd Jnury to 6, 200 is te tested dte. And te forecsting module of te indoor ir temperture s been erified by using tese dt. Te two pictures below re te comprison digrm of predicted lues nd mesured lues using MATLAB subroutine to output. Fig.. Te test nd prediction dt inside ir temperture of te solr greenouse

7 Fig. 2. Te test nd prediction dt inside ir temperture of te solr greenouse Tble 2. Te test nd prediction dt indoor ir temperture of te greenouse Jn.2, Predictie lue Mesurements Predictie lue Mesurements Predictie lue Mesurements Interprettion of result Vlidtion dt used te dt of te weter including sunny, cloudy nd cloudy. Digrm one nd digrm two sows tt te rition trend wit time of predicted lues nd mesured lues is consistent. And te temperture contrst between predicted lues nd mesured lues is smll. Te erge reltie error is less tn 0%. Terefore, te simultion results wic clculted by te mtemticl model of re relible. Te two digrms lso sow tt te mximum between predicted lues nd mesured lues present to 9 o'clock nd 0 o'clock fter lifting up te quilt used to

8 keep wrm. Becuse te solr rdition ligt into te indoor, te indoor ir temperture soot up. But tis prediction model cnnot predict it. So tis is te model sould be improed. 5 Conclusion Te rebuilding et trnsfer coefficients pply to te nortern res fetures of dry nd cold. So te prediction model of indoor ir temperture is fesible nd pplied. But te lues predicted re not good fter lifting up te quilt. And te problem will be studied next. References. Sun Fugui, Simultion nd Anlysis of Direct Ligt Enironment in Typicl Greenouse in Beijing-- Ligt Simultion nd Anlysis Fcility Agriculture Reserc 4 [J], Agriculturl Engineering,993,9(2): Liu Hong,Gou Wenli,Li Huijun, Ligt Enironment Simultion nd Anlysis of Greenouse in Beijing [J], Journl of Applied Meteorology,2008,9(3): Li Wei, Dong Renjie, Tng Cuzou, Zng Sumin, Teoreticl Model of Terml Enironment in SolrPlstic Greenouses wit One-Slope [J], Trnsctions of te CSAE, 997, 5(3): Cen Qingyun,Wng Zengfu, Dynmic Simultion of Terml Enironment in Solr Greenouse [J],996,(): Li Xiofng, Mtemticl Simultion nd Structurl Optimiztion of Greenouse Terml Enironment [C], Cin Agriculturl Uniersity, Meng Lili, Terml Enironment Model in Cinese Solr Greenouse Bsed on VB nd MATLAB nd Structure Optimiztion [c], Cinese Acdemy of Agriculturl Sciences, Wu Cunyn,Zo Xinping,Guo Liwen, Simultion nd Anlysis of Greenouse Crop Terml Enironment [J],Agriculturl Engineering,2007,23(4): Xin Benseng,Qio Xiojun,Teng Gungui, Construction of Greenouse Enironmentl Prediction Model [J], Agriculturl Reserc,2006,4(2): Wng Guiying,Kng Guobin, egression nd Anlysis of Greenouse Enironment [J], Beijing Agriculturl College,994,9(2): Rcel Jonn Ctrin n Ootegem.Optiml Control Design for Solr Greenouse[M].CIP gegeens Koninklijke Biblioteek,Den Hg, O. Korner,H. Cll nd R.J.C.n Ootegem. Crop bsed climte regimes for energy sing in greenouse cultition[d]. Wgeningen, Te Neterlnds: Wgeningen Uniersity,2003.