40220130405012 2

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40220130405012 2

  1. 1. International Journal of Electrical Engineering and Technology (IJEET), INTERNATIONAL JOURNAL September – October (2013), ISSN 0976 – 6545(Print), OF ELECTRICAL ENGINEERING & ISSN 0976 – 6553(Online) Volume 4, Issue 5, © IAEME TECHNOLOGY (IJEET) ISSN 0976 – 6545(Print) ISSN 0976 – 6553(Online) Volume 4, Issue 5, September – October (2013), pp. 126-129 © IAEME: www.iaeme.com/ijeet.asp Journal Impact Factor (2013): 5.5028 (Calculated by GISI) www.jifactor.com IJEET ©IAEME REDUCTION IN CO2 EMISSION FROM THERMAL POWER PLANT BY USING LOAD DISPATCH SCHEDULE S. R. Vyas1, Dr. Rajeev Gupta2 1 2 Research Scholar, Mewar University, Chhitorgrah. India Dean EC Dept., University College of Engg. RTU, Kota. India ABSTRACT Reduction in the emission of the CO2 gases from the thermal power system operation is the very huge task for the pollution control department of power plant. There are so many methods are used for the reduction of the CO2 emission from the power plant. All the methods require so many equipment and additional arrangement for the reduction in CO2 emission from the power plant. On the other hand if we reduce the emission with arraigning load in proper schedule than there are no additional arrangement and equipment require. In this method we can use the optimum output in terms of emission from the different power plant. Overall emissions reduce for the given output of power with same equipment by load dispatch scheduling. Key Word: Load dispatch, Emission, Scheduling. INTRODUCTION Power generation system is the mirror for any developing country. Any development in country is directly related with the development in the power system generation and increase in the power plant. There are different types of power plants are used for the electrical power generation. In India major part of total electrical power generation is form the thermal power plant. Now with the development number of power plant must be increased to fulfill the requirement of load. But due to this increase so many problems arise. Major problem is the pollution from the power plant. In thermal power plant there are so many factors related with the pollution. Green house gases emission from the thermal power plants take main part in air pollution. CO2 gas creates major effect on the environment among the all flue gases generated from the thermal power plant. So reduction in the amount of CO2 emission from the thermal power plant is the major task for the pollution control board and authority with the same electrical power generation. Now there are many filter and 126
  2. 2. International Journal of Electrical Engineering and Technology (IJEET), ISSN 0976 – 6545(Print), ISSN 0976 – 6553(Online) Volume 4, Issue 5, September – October (2013), © IAEME accessories are used from the reduction in the CO2 emission from the thermal power plant. All these arrangements require additional equipment so overall cost is also increased with this additional modification. Now in advance management system emission can be reduce by the proper load arrangement among the all power thermal power plant units which are connected in the same grid. In this paper this load dispatch used for the reduction of CO2 gas emission from the thermal power plant. Problem Formulation A three-generator system has been considered for the load dispatch for the reduction in CO2 emission. General equation for the emission calculation for the individual power plant unit is as per given below. NG F1 = ∑ (a i Pg i 2 + b i Pg i + c i ) kg/h i =1 Where ai, bi and ci are CO2 coefficients and NG is the number of generators and F1 is total CO2 emission from the each thermal power unit. Our requirement is to minimize the value for the F1 for the each plant at given. At different value of load generating output of plant may be differing but the overall value for the F1 must be minimal. So our problem is to minimize the value of F1 with load. For the above there are so many methods has been used. Some of them used here for the optimization and then compare for the selection of best method. METHODOLOGY Different methods for the minimization of emission is as per given below. Classical Method, Weight Method, Genetic Algorithms, Evolutionary Method. Computerized program developed for the above methods with Mat lab language. Data for the generator is as per the given below. Here we consider three units for the calculation and their maximum and minimum capacity is as per table. No. of Generator 1 2 3 Table: 1 Generator rating Maximum in Value in Mw. Mw. 210 240 210 238 120 100 Minimum Value in Mw. 90 85 20 CO2 emission coefficient for the each three plants are as per given in table 2. Sr.No. Table: 2 CO2 emission coefficient for the plant ai bi ci 1 0.265110 -61.01945 5080.148 2 0.140053 -29.95221 3824.770 3 0.105929 -9.552794 1342.851 127
  3. 3. International Journal of Electrical Engineering and Technology (IJEET), ISSN 0976 – 6545(Print), ISSN 0976 – 6553(Online) Volume 4, Issue 5, September – October (2013), © IAEME Table: 3 Loss coefficient for the given plant di fi Sr.No. gi 1 0.000134 0.0000176 0.000183 2 0.0000176 0.000153 0.000282 3 0.000183 0.000282 0.00162 RESULT Comparison of result for above methods are given below CO2 Emission 8426 9391 9168 8925 Method Evolutionary Genetic Wait age Classical 9500 9000 CO2 EMISSION 8500 8000 Classical 7500 Weightage 7000 Genetic 6500 Evolutionary 6000 5500 300 350 400 450 GENERATION MW CONCLUSION Result shows that Emission is low with the help of Evolutionary technique. In all methods total output is never change but the emission of CO2 gas is reduced with the proper selection of their generating station. Best result shows the lesser emission of CO2 gas form the generating unit at same load. This will reduce the overall generation of CO2 gas for the Power system. 128
  4. 4. International Journal of Electrical Engineering and Technology (IJEET), ISSN 0976 – 6545(Print), ISSN 0976 – 6553(Online) Volume 4, Issue 5, September – October (2013), © IAEME REFERENCES [1] [2] [3] [4] [5] [6] [7] [8] [9] [10] [11] [12] [13] Abido M A. and A Niched Pareto, “Genetic algorithm for multi-objective environmental/economic dispatch”, International Journal Electrical Power, Vol. 25, No.2, pp. 79–105, 2003. Abido M A., “Environmental/economic power dispatch using multi objective evolutionary algorithm”, IEEE Transactions on Power System, Vol.18, No.4, pp. 1529–37,2003. C. Palnichamy and K shrkrishna, “Economic thermal power dispatch with emission constraint”, Journal of Institute of Engineering (India), vol. 72, pp. 11-18, 1991. Deb K, Pratap A, Agarwal S, and Meyarivan T., “A fast and elitist multi objective genetic algorithm: NSGA-II”, IEEE Transactions on Evolutionary Computation, Vol. 6, No. 2, pp.182–97, 2002. Franscisco D. Galiana, “Allocation of transmission losses to bilateral contracts in a competitive environment”, IEEE Transactions on Power System, Vol. 15, No.1, pp. 143-147, 2000. Jong-Hwan Kim, and Hyun Myung, “Evolutionary programming techniques for constrained optimization problems”, IEEE Transactions on Evolutionary Computation, Vol. 1, No.2, pp.129-130, 1997. K. Chandram, N. Subrahmanyam and M. Sydulu Thammasat , “On-Line Optimal Power Flow Using Evolutionary Programming Techniques, International Journal Science and Technology Vol. 15, No.1, pp. 20-27, 2010. Simona Dinu, Ioan Odagescu and Maria Moise, “Environmental economic dispatch optimization using a modified GA”, International Journal of Computer Applications, Vol. 20, No.2, pp.187-195, 2011. Srinivasan D. and Tettamanzi A., “An evolutionary algorithm for evaluation of emission compliance options in view of the clean air act amendments”. IEEE Transactions on power System, Vol.12, pp.152–8, 1997. Sanjay Mathur, Shyam K. Joshi and G.K. Joshi, “Development of Controller for Economic Load Dispatch by Generating Units Under Varying Load Demands”, International Journal of Electrical Engineering & Technology (IJEET), Volume 4, Issue 4, 2013, pp. 159 - 171, ISSN Print : 0976-6545, ISSN Online: 0976-6553. Bharathkumar S, Arul Vineeth A D, Ashokkumar K and Vijay Anand K, “Multi Objective Economic Load Dispatch using Hybrid Fuzzy, Bacterial Foraging-Nelder–Mead Algorithm”, International Journal of Electrical Engineering & Technology (IJEET), Volume 4, Issue 3, 2013, pp. 43 - 52, ISSN Print : 0976-6545, ISSN Online: 0976-6553. Preeti Manke and Sharad Tembhurne, “Artificial Neural Network Based Nitrogen Oxides Emission Prediction and Optimization in Thermal Power Plant”, International Journal of Computer Engineering & Technology (IJCET), Volume 4, Issue 3, 2013, pp. 491 - 502, ISSN Print: 0976 – 6367, ISSN Online: 0976 – 6375. Mr.Vijay Kumar, Dr.Jagdev Singh, Dr.Yaduvir Singh and Dr.Sanjay Sood, “Design & Development of Genetic Algorithms for Economic Load Dispatch of Thermal Generating Units”, International Journal of Computer Engineering & Technology (IJCET), Volume 3, Issue 1, 2012, pp. 59 - 75, ISSN Print: 0976 – 6367, ISSN Online: 0976 – 6375. 129

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