Emission Reduction Technique from Thermal Power Plant By Load Dispatch

Transcription

1 Emsson Reducton Technque from Thermal Power Plant By Load Dspatch S. R. Vyas 1, Dr. Rajeev Gupta 2 1 Research Scholar, Mewar Unversty, Chhtorgrah. Inda 2 Dean EC Dept., Unversty College of Engg. RTU, Kota. Inda Abstract - Reducton n the emsson of the SO2 gases from power system operaton s the very gant task of polluton control system. There are so many methods are used for the reducton of the SO2 emsson from the power plant. All the methods requre so many equpment and addtonal arrangement for the reducton n SO2 emsson from the power plant. On the other hand f we reduce the emsson wth arragnng load n proper schedule than there are no addtonal arrangement and equpment requre. In ths method we can use the optmum output n terms of emsson from the dfferent power plant. Overall emssons reduce for the gven output of power wth same equpment by load dspatch schedulng. Keywords - Emsson constrant, Schedulng, Load dspatch. I. INTRODUCTION Power generaton system s the mrror for any developng country. Any development n country s drectly related wth the development n the power system generaton and ncrease n the power plant. There are dfferent types of power plants are used for the electrcal power generaton. In Inda major part of total electrcal power generaton s form the thermal power plant. Now wth the development number of power plant must be ncreased to fulfl the requrement of load. But due to ths ncrease so many problems arse. Major problem s the polluton from the power plant. In thermal power plant there are so many factors related wth the polluton. Greenhouse gases emsson from the thermal power plants takes man part n ar polluton. SO2 gas creates major effect on the envronment among the all flue gases generated from the thermal power plant. So reducton n the amount of SO2 emsson from the thermal power plant s the major task for the polluton control board and authorty wth the same electrcal power generaton. Now there are many flter and accessores are used from the reducton n the SO2 emsson from the thermal power plant. All these arrangements requre addtonal equpment so overall cost s also ncreased wth ths addtonal modfcaton. Now n advance management system emsson can be reduce by the proper load arrangement among the all power thermal power plant unts whch are connected n the same grd. In ths paper ths load dspatch used for the reducton of SO2 gas emsson from the thermal power plant. II. PROBLEM FORMULATION A three-generator system has been consdered for the load dspatch for the reducton n SO2 emsson. General equaton for the emsson calculaton for the ndvdual power plant unt s as per gven below. NG 2 F1 = Pg b Pg c 1 a Kg. /h Where a, b and c are SO2 coeffcents and NG s the number of generators and F1 s total SO2 emsson from the each thermal power unt. Our requrement s to mnmze the value for the F1 for the each plant at gven. At dfferent value of load generatng output of plant may be dfferng but All rghts Reserved 152

2 Internatonal Journal of Modern Trends n Engneerng and Research (IJMTER) Volume 02, Issue 07, [July 2015] ISSN (Onlne): ; ISSN (Prnt): overall value for the F1 must be mnmal. So our problem s to mnmze the value of F1 wth load. For the above there are so many methods has been used. III. METHODOLOGY Dfferent method for the mnmzaton of emsson s as used wth dfferent computersed model. Here we use Evolutonary. Evolutonary Programmng has been used n the feld of desgn search and optmzaton more thoroughly after the exposure. There are a qute number of data that has shown the mplementaton of economc dspatch usng classcal Evolutonary Programmng. Manly, the nterest of usng classcal Evolutonary Programmng as the method for the economc dspatch problem s because of ts smplcty to GA where Evolutonary Programmng does not nvolve any specal codng. Real number valued s used n the process. Secondly, Evolutonary Programmng does not mpose any alteraton of the objectve functon or constrants restrcton. Hence, the transfer of the problem nto algorthm s farly smplfed. For the purposes of ths study, types of Evolutonary Programmng to be used are as per gven. 3.1 General Evolutonary Programmng Ths program used for standard calculaton and mutaton. Normal Dstrbuton s used n General Evolutonary Programmng method. Selecton of Mutaton s on the base of random populaton. In GEP for the generaton of offsprng Gaussan or normalzed random varables are undertaken (Rambabu, et al. 2011). For local optmal soluton GEP performs better as t takes mall steps to fnd the global optmum soluton f t les wthn the local neghborhood regon. Due to ts lmtaton of searchng global soluton n the local neghborhood regon, t has a slow convergence rate to the optmal soluton f t les far from the local search area. It can also be mplemented nto some unmodal functons and multmodal functons wth some local mnma as t provdes fne tunng to fnd the global optmum soluton. 3.2 Fast Evolutonary Programmng Evolutonary programmng technque usng Cauchy mutaton operator for the mutaton or the generaton of offsprng s termed as FEP. Fast evolutonary programmng performs more effcently and relatve have more strength to fnd the optmal soluton. As the step sze of FEP s larger, smple and straghtforward to fnd a global optmal soluton (Rajsomshekhar, et al. 2009). So t performs more effcently and faster to fnd the globally optmal soluton to multmodal optmzaton problems. Snce ts step sze s large to fnd the globally optmal soluton, but t s only effectve at the start of evoluton to fnd a soluton as the global optmal soluton les far away from startng search pont. As the evoluton proceeds for the soluton, t becomes slow or there may also be chance of selectng a less optmal soluton as the global soluton les very near n the searchng area (Lng, et al. 2011). Fgure 3 depcts that Cauchy mutaton operator generates offsprng further away from man populaton or parents as compared to Gaussan mutaton operator due to ts long flat tals. So Cauchy mutaton has more probablty of escapng from local optmum and moreover a smaller hll around the center ndcates that Cauchy mutaton spends less tme n explotng the local neghborhood and thus has, the weaker fne tunng ablty as compared to Gaussan mutaton operator n small to md range regons. 3.3 Selectve Evolutonary Programmng As poston of the global optmum soluton s unknown, makng a choce between a selecton of Cauchy and Gaussan mutaton operator. So nstead of swtchng from Gaussan to Cauchy All rghts Reserved 153

3 Internatonal Journal of Modern Trends n Engneerng and Research (IJMTER) Volume 02, Issue 07, [July 2015] ISSN (Onlne): ; ISSN (Prnt): operator, the dea s to mx dfferent search bass Cauchy and Gaussan mutatons. In SEP generate two offsprng one from Gaussan mutaton operator and one from Cauchy mutaton operator. Therefore populaton sze of SEP s half than that requred n GEP and FEP. The Selectve Evolutonary Programmng uses both types of dstrbuton n ts mutaton. Moreover SEP s robust and does not requre no pror knowledge of the problem to be solved. Table:-1 Generator Data No. of Generator Generator ratng n Mw. Maxmum Value n Mw. Mnmum Value n Mw Computerzed program developed for the above methods wth Mat lab language. Data for the generator s as per the gven below. Here we consder three unts for the calculaton and ther maxmum and mnmum capacty s as per table. SO2 emsson coeffcent for the each three plants are as per gven n table Table:-2 SO2 emsson coeffcent Sr.No. a b c Loss coeffcent of plant s as per gven n table Table:-3 Loss coeffcent Sr.No. d f g IV. RESULT From runnng program wth above data total emsson for SO2 can be produce. Collect total output of emsson for all method whch s to be studed. From the above procedure we get SO2 emsson for dfferent value of generaton wth dfferent methodology for the comparson. Comparson of all method at dfferent loadng condton of plant s as per gven n table 4. Colum no.2 ndcate total load on the power generatng unt. Colum no. 3 ndcates Emsson of SO2 wth evolutonary technque. Colum no. 4 ndcates Emsson of SO2 wth Genetc technque. Colum no. 5 ndcates Emsson of SO2 wth Weghted method. Colum no. 6 ndcates Emsson of SO2 wth Classcal technque. Table:-4 Result wth all method Sr.No. Load MW Emsson by Evolutonary Emsson by Genetc Emsson by Weghted Emsson by All rghts Reserved 154

4 Internatonal Journal of Modern Trends n Engneerng and Research (IJMTER) Volume 02, Issue 07, [July 2015] ISSN (Onlne): ; ISSN (Prnt): Comparson graph of above all method s as per shown n fg.1 Fg. 1 SO2 Emsson for all method V. CONCLUSION Result shows that Emsson s low wth the help of Evolutonary technque. In all method total output s never change but the emsson of SO2 gas s reduced wth the proper selecton of ther generatng staton. Best result shows the lesser emsson of SO2 gas form the generatng unt at same load. Ths wll reduce the overall generaton of SO2 gas for the Power system. REFERENCE 1. Abou El Ela, A.A., M.A. Abdo, and S.R. Spea, Dfferental evoluton algorthm for emsson constraned economc power dspatch problem, Electrc Power Systems Research, Vol. 80, No. 10, pp , Balakrshnan, S., et al., On-lne emsson and economc load dspatch usng adaptve hopfeld neural network, Internatonal Journal of Appled Soft Computng, Vol.2, No. 4, pp , Basu M., Fuel constraned economc emsson load dspatch usng Hopfeld neural networks, Electrc Power Systems Research, Vol. 63, No.1, pp , Bhattacharya A. and P.K. Chattopadhyay, Solvng economc emsson load dspatch problems usng hybrd dfferental evoluton, Internatonal Journal of Appled Soft Computng, Vol. 11, No.2, pp , Bnod Shaw, V. Mukherjee and S.P. Ghoshal, A novel opposton-based gravtatonal search algorthm for combned economc and emsson dspatch problems of power systems,electrcal Power and Energy Systems, Vol. 35, pp , Dhanalakshm, S., et al., Applcaton of modfed NSGA-II algorthm to Combned Economc and Emsson Dspatch problem, Internatonal Journal of Electrcal Power & amp; Energy Systems, Vol. 3, No. 4, pp , E. Deny, and M. O Malley, Wnd generaton, power system operaton, and emsson reducton, IEEE Transactons on Power System, Vol. 21, No.1, pp , Gnagadass R., N. P. Padhy and K. Manvannan, Assessment of avalable transfer capablty for practcal power systems wth combned economc emsson dspatch, Electrc Power Systems Research, Vol. 69, No. 2-3, pp , Guo C. X., J. P. Zhan and Q. H. Wu, Dynamc economc emsson dspatch based on group search optmzer wth multple producers, Electrc Power Systems Research, Vol. 86, pp. 8-16, Hota P.K., R. Chakrabart and P.K. Chattopadhyay, Economc emsson load dspatch through an nteractve fuzzy satsfyng method, Electrc Power Systems Research, Vol.54, No.3, pp , J. S. Dhllon, S. C. Part and D. P. Kothar Stochastc economc emsson load dspatch, Electrcal Power Systems Research, Vol. 26, pp , All rghts Reserved 155

5 Internatonal Journal of Modern Trends n Engneerng and Research (IJMTER) Volume 02, Issue 07, [July 2015] ISSN (Onlne): ; ISSN (Prnt): Jacob Raglend, Sowjanya Veeravall, Kasanur Salaja, B. Sudheera, and D.P. Kothar, Comparson of AI technques to solve combned economc emsson dspatch problem wth lne flow constrants, Electrcal Power and Energy Systems Vol. 32, pp , K Satsh Kumar,V Tamlselvan, N Mural, R Rajaram, N Shanmuga Sundaram, and T Jayabharath, Economc load dspatch wth emsson constrants usng varous PSO algorthms, WSEAS Transactons on Power System, Issue 9, Vol. 3, No. 9, pp , K. Senthl and K. Mankandan, Economc thermal power dspatch wth emsson constrant and valve pont effect loadng usng mproved tabu search algorthm, Internatonal Journal of Computer Applcatons, Vol. 3, No.9, pp. 6-11, K.K.Swarnkar, Dr.S.Wadhwan and Dr.A.K.Wadhwan, Optmal power flow of large dstrbuton system soluton for combned economc emsson dspatch problem usng partcal swarm optmzaton, Electrcal Power and Energy Systems Vol. 32, pp , M. R. Alrashd, and M. E. El-Hawary, Impact of Loadng Condtons on the Emsson-Economc Dspatch, World Academy of Scence, Engneerng and Technology Vol. 39, pp , Osman, M. S., M. A. Abo-Snna and A.A. Mousa, A ɛ-domnance-based mult objectve genetc algorthm for economc emsson load dspatch optmzaton problem, Electrc Power Systems Research, Vol. 79, No. 11, pp , P. Venkatesh, R. Gangadas and N. Prasad Padhy, Comparson and applcaton of evolutonary programmng technques to combned economc emsson dspatch wth lne flow constrants, IEEE Transactons on Power System, Vol. 18, No.2, pp , All rghts Reserved 156

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