20320130406013

458 views

Published on

Published in: Technology, Business
0 Comments
0 Likes
Statistics
Notes
  • Be the first to comment

  • Be the first to like this

No Downloads
Views
Total views
458
On SlideShare
0
From Embeds
0
Number of Embeds
2
Actions
Shares
0
Downloads
2
Comments
0
Likes
0
Embeds 0
No embeds

No notes for slide

20320130406013

  1. 1. International Journal of Advanced Research in Engineering and Technology IN ENGINEERING INTERNATIONAL JOURNAL OF ADVANCED RESEARCH (IJARET), ISSN 0976 – 6480(Print), ISSN 0976 – 6499(Online) Volume 4, Issue 7, November – December (2013), © IAEME AND TECHNOLOGY (IJARET) ISSN 0976 - 6480 (Print) ISSN 0976 - 6499 (Online) Volume 4, Issue 7, November - December 2013, pp. 109-119 © IAEME: www.iaeme.com/ijaret.asp Journal Impact Factor (2013): 5.8376 (Calculated by GISI) www.jifactor.com IJARET ©IAEME DEMAND BASED OPTIMAL PERFORMANCE OF A HYDROELECTRIC POWER PLANT Shambhu Ratan Awasthi1, Vishnu Prasad2, Saroj Rangnekar3 1 Department of Energy, Maulana Azad National Institute of Technology, Bhopal, India 2 Department of Civil Engineering, Maulana Azad National Institute of Technology, Bhopal, India 3 Department of Energy, Maulana Azad National Institute of Technology, Bhopal, India ABSTRACT Climate change is emerging as one of the greatest challenges of 21st century for which fossil fuels are mainly responsible which emit green house gases. In order to meet this challenge, it is necessary to adopt alternative sources of energy and make optimum use of natural resources, predominantly water. The paper presents a concept for regulating the release of water so as to achieve optimal performance of the units in a of hydro power plant while meeting the load demand. Present work considers all the hydraulic and electrical losses in a hydro power plant and meets the load demand with minimum quantity of water. The concept is applied to an operational 8x125 MW Indira Sagar hydroelectric power plant in India and conservation of water is computed in three cases viz. near rated head, below rated head and above rated head. Keywords: Optimal Performance, Head Loss in Starts/Stops, Hydro Power Plant, Tail Race Level, Turbine Efficiency, Water Conservation. 1. INTRODUCTION In order to mitigate the challenges imposed by the climate change, it is necessary to minimize dependency of power on fossil fuels and make optimum use of natural resources in a sustainable manner. The reduction in per capita availability of water necessitates meticulous attention on water management. In view of this, efficient operation of hydro power plants is drawing more attention of the researchers in the 21st century. Variation in turbine efficiency play an important role in the optimum generation scheduling. Polynomial functions of 2nd and 4th degree are used to model the efficiency of turbine-generator. 109
  2. 2. International Journal of Advanced Research in Engineering and Technology (IJARET), ISSN 0976 – 6480(Print), ISSN 0976 – 6499(Online) Volume 4, Issue 7, November – December (2013), © IAEME Difference in efficiency obtained from these two models is found to be negligible[1]. In generation scheduling of hydro power plants, it is observed that all the hydraulic and electrical losses are not considered [2, 3]. The concept of start-up and shut-down for hydro power plants is presented from cost considerations due to wear and tear caused by start-ups and shut-downs [4, 5]. The start-up and shut-down processes are phased out and loss of water is modeled mathematically [6]. Strategic planning for enhanced generation with same quantity of water is presented [7] which is achieved by optimal operation of large hydroelectric power plants [7]. This paper presents a concept of running the optimum number of units at maximum turbine efficiency to meet the load demand in a short term scheduling of 24-hours so that water required is minimised. The concept is demonstrated by applying to an operational 8x125 MW hydroelectric power plant under three conditions, namely, near rated head, below rated head and above rated head. 2. PROBLEM FORMULATION In this work, the load demand is met by optimizing the quantity of water used. This is achieved by optimum selection of turbine units and their operation at maximum efficiency. 2.1 Objective function (1) subject to constraints : (2) m ≤ n 2.2 Bounds (3) Reservoir level Turbine discharge Unit output Head : MDDL ≥ Hlh ≤ FRL : Qmin < Q < Qmax : Pgmin < Pgeach < Pgmax : Hmin < Hnet < Hmax 3. COMPUTATION OF PARAMETERS 3.1 Turbine output It is computed in kW as: Pt = 9.8*Q*Hnet*Et (3) 3.2 Turbine efficiency In a Francis turbine, variation in efficiency with output is large as shown in Fig. 1 and plays an important role in optimum generation scheduling. Turbine efficiency is read from hill curves of a prototype. 110
  3. 3. International Journal of Advanced Research in Engineering and Technology (IJARET), ISSN 0976 – 6480(Print), ISSN 0976 – 6499(Online) Volume 4, Issue 7, November – December (2013), © IAEME Fig. 1. Variation in turbine efficiency with output at rated head 3.3 Electrical losses in transfer of power from generator to switchyard are computed as the difference between generated power and dispatched power 3.4 Turbine output is obtained from generator efficiency curve 3.5 Head water level is read from the level measuring instrument 3.6 Hydraulic losses in water conductor system are directly proportional to the square of discharge. It is calculated as equivalent head loss to obtain net head 3.7 Start–up/Shut down : Water required till loading of the units during start-up and then during shut-down do not contribute in generation of power. This loss of water is taken into account using empirical formulae given below : 3.7.1 Loss of Water in each Start-up (4) In case of Indira Sagar Project, it works out to be 5700 m3 3.7.2 Loss of water in each shut-down (5) In case of a Indira Sagar Project, it works out to be 7000 m 3 4. COMPUTATION OF OPTIMUM PERFORMANCE The computation is carried out in three stages: Stage-I : computation of initial net head For a given load demand, compute gross head, plant discharge, maximum turbine efficiency. Obtain net head by subtracting head loss from gross head. 111
  4. 4. International Journal of Advanced Research in Engineering and Technology (IJARET), ISSN 0976 – 6480(Print), ISSN 0976 – 6499(Online) Volume 4, Issue 7, November – December (2013), © IAEME Stage-II : Computation of final net head Compute plant discharge, tail water level, head loss and net head iteratively to obtain final value of net head. Compute number of units to operate. Stage-III : Optimization and optimality check The development of computer program is shown in the form of a flow chart in Fig. 2. Fig. 2. Flow – chart for computation of optimal performance 112
  5. 5. International Journal of Advanced Research in Engineering and Technology (IJARET), ISSN 0976 – 6480(Print), ISSN 0976 – 6499(Online) Volume 4, Issue 7, November – December (2013), © IAEME 5. APPLICATION TO A HYDROELECTRIC POWER PLANT The concept is applied to a 8x125 MW Indira Sagar hydroelectric power plant situated in the state of Madhya Pradesh in India. Relevant project data are given in Table 1. Table 1: Relevant Data of Indira Sagar Project Description Data Reservoir gross storage 12.22 Billion m3 capacity Reservoir area at FRL 913 km2 Rated head 60 m Turbine output 125 MW + 10% overload Rated discharge 229.5 cumecs The optimisation is carried out for 24-h in different seasons of a year for different head conditions. The optimisation is applicable when number of units in operation are two or more. Water requirement on a typical day under following two situations are computed : (i) on the basis of ‘Daily Report’ of Indira Sagar Project (ii) as per the proposed methodology for same generation by operating turbines at maximum efficiency Above two water requirements are compared to obtain water conservation. Case-I : Operation at above rated head Following data on a typical day in November is taken from ‘Daily Report’. Energy generated = 6.7183 MU Energy dispatched = 6.6982 MU Energy transfer efficiency = 0.997% Average reservoir elevation Average plant discharge Cumulative volume of water released in 24 h = 259.855 m = 498.25 cumecs = 43.0488 million m3 No. of start-ups No. of shut-downs Water loss in start-ups Water loss in shut-downs Water utilized in generation =10 =9 = 10 x 5700 = 57,000 m3 = 9 x 7000 = 63,000 m3 = 43.0488 – 0.12 = 42.9288 million m3 The units are operated in different time periods as per ‘Load Dispatch Schedule’. As a general practice, units are equally loaded without any consideration of turbine efficiency. For each head there is a maximum turbine efficiency. Tail water elevation, net head and plant discharge are computed while operating the turbines at maximum efficiencies as given in Table 2. Duration of operation is computed for total quantity of water i.e. 42.9288 million m3. For example, duration of operation of 2 units is calculated as 25.17 hr (42928800 x 3600/473.72). 113
  6. 6. International Journal of Advanced Research in Engineering and Technology (IJARET), ISSN 0976 – 6480(Print), ISSN 0976 – 6499(Online) Volume 4, Issue 7, November – December (2013), © IAEME Table 2 : Plant Discharge and Duration of Operation Units in Tail water Net head Maximum Plant Duration of operation level (m) (m) turbine discharge operation (No.) efficiency (cumecs) (hr) 2 194.163 64.621 0.94991 473.72 25.17 3 194.499 64.287 0.95004 710.11 16.79 4 194.838 63.949 0.95015 946.19 12.60 5 195.181 63.608 0.95026 1181.96 10.09 6 195.520 63.271 0.95036 1417.45 8.41 7 195.854 62.937 0.95044 1652.66 7.22 8 196.190 62.603 0.95052 1887.59 6.32 As per the optimization methodology i.e. by operating the units at maximum turbine efficiency, duration of operation for same generation is obtained. For example, to generate 6.7183 MU of energy, 2 units will operate for 24.43 hr (6.7183 MWh/275 MW) as given in Table 3. Table 3 : Water Conservation in Power Generation of 6.7183 MU Units in Output of Total output Duration of Total water Total water of units operation required conserved, operation each unit (No.) (MW) (MW) (hr) (million m3) (million m3) 2 137.50 275.00 24.43 41.6630 1.2658 3 137.50 412.50 16.29 41.6355 1.2933 4 137.50 550.00 12.22 41.6081 1.3207 5 137.50 687.50 9.77 41.5807 1.3481 6 137.01 822.06 8.17 41.7029 1.2259 7 136.21 953.49 7.05 41.9208 1.0080 8 135.41 1083.32 6.20 42.1418 0.7870 Upto 5 units, power output of each unit at maximum turbine efficiency is more than permissible maximum output limit of 137.5 MW. Hence, it is desirable to maximize generation by operating the units at their maximum output limits irrespective of turbine efficiency. In the present case, as per Table 3, the load demand will be met by operating 3 units at maximum output limit of 137.5 MW which will result in water conservation of 3.01%. For different number of units in operation, water conservation from 1.83% to 3.14% will be achieved for same generation as shown in Fig. 3. Fig. 3. Variation in water conservation above rated head 114
  7. 7. International Journal of Advanced Research in Engineering and Technology (IJARET), ISSN 0976 – 6480(Print), ISSN 0976 – 6499(Online) Volume 4, Issue 7, November – December (2013), © IAEME It is observed from Fig. 3 that there is a rising trend in water conservation upto 5 units when each of them operate at their maximum output limit of 137.5 MW though at sub-optimal turbine efficiencies. When 6th unit onwards are added, they operate below maximum output limit but at maximum turbine efficiency. Effect of reduction in net head caused by rise in tail race level is visible with the addition 6th unit onwards, resulting in reduced water conservation. Case-II : Operation near to rated head Following data on a typical day in the month of February is taken from ‘Daily Report’. Energy generated = 2.15 MU Energy dispatched = 2.1251 MU Energy transfer efficiency = 0.98842% Average reservoir elevation = 255.375 m Average plant discharge = 168.98 cumecs Cumulative volume of water released in 24-hr = 14.599872, say 14.6 million m3 No. of start-ups No. of shut-downs Water loss in start-ups Water loss in shut downs Water utilized in generation = 6 = 6 = 6 x 5700 = 34200 m3 = 6 x 7000 = 42000 m3 = 14.6 – 0.0762 = 14.5238 million m3 Tail water elevation, net head and plant discharge are computed while operating the turbines at maximum efficiencies. Duration of operation for total quantity of water i.e. 14.5238 million m3 is computed on the basis of plant discharges given in Table 4. Table 4 : Plant Discharge and Duration of Operation Net head Maximum Plant Duration of Units in Tail water turbine discharge operation operation level (m) (m) efficiency (cumecs) (hr) (No.) 1 193.835 60.487 0.95079 235.06 17.16 2 194.171 60.326 0.95080 470.01 8.58 3 194.513 59.985 0.95080 704.60 5.73 4 194.838 59.661 0.95079 938.96 4.30 5 195.172 59.328 0.95078 1173.04 6 195.507 58.995 0.95075 1406.87 3.44 2.87 7 195.837 58.666 0.95072 1640.46 2.46 8 196.170 58.334 0.95068 1873.80 2.15 It is observed from Table 4 that net head available is near rated head of 60 m. Power output, duration of operation and water conservation are computed at maximum turbine efficiency as given in Table 5. 115
  8. 8. International Journal of Advanced Research in Engineering and Technology (IJARET), ISSN 0976 – 6480(Print), ISSN 0976 – 6499(Online) Volume 4, Issue 7, November – December (2013), © IAEME Table 5 : Water Conservation in Power Generation of 2.15 MU Units in Output of Total output Duration of Total water Total water operation each unit of units operation required conserved (No.) (MW) (MW) (hr) (million m3) (million m3) 1 130.17 130.17 16.517 13.9768 0.5470 2 129.99 259.98 8.270 13.9929 0.5309 3 129.18 387.54 5.548 14.0724 0.4514 4 128.41 513.63 4.186 14.1494 0.3744 5 127.62 638.08 3.369 14.2291 0.2947 6 126.82 760.94 2.825 14.3102 0.2136 7 126.04 882.29 2.437 14.3911 0.1327 8 125.25 1002.01 2.146 14.4741 0.0497 It is observed from Table 5 that generation required is so small that it is met by operating only 1 unit at maximum turbine efficiency which results in water conservation of 3.77% as shown in Fig. 4. As the number of units are increased, there is decrease in conservation of water. Fig. 4. Variation in water conservation near rated head Case-III : Operation below rated head conditions Following data on a typical day in the month of May is taken from ‘Daily Report’. Energy generated = 4.976 MU Energy dispatched = 4.8709 MU Energy transfer efficiency = 0.97888% Average reservoir elevation Average plant discharge Cumulative volume of water released in 24 h = 248.72 m = 446 cumecs = 38.5344 million m3 No. of start-ups No. of shut-downs Water loss in start-ups Water loss in shut-downs Total water loss in start-ups and shut-downs Water utilized in generation =6 =5 = 6 x 5700 = 34200 m3 = 5 x 7000 = 35000 m3 = 69200 m3 = 0.0692 million m3 = 38.5344 – 0.0692 = 38.4652 million m3 116
  9. 9. International Journal of Advanced Research in Engineering and Technology (IJARET), ISSN 0976 – 6480(Print), ISSN 0976 – 6499(Online) Volume 4, Issue 7, November – December (2013), © IAEME Tail water elevation, net head and plant discharge are computed while operating the turbines at maximum efficiencies. Duration of operation for the total quantity of water i.e. 38.4652 million m3 is computed on the basis of plant discharges given in Table 6. Table 6 : Plant Discharge and Duration of Operation Units in Tail water Net head Maximum Plant Duration of (m) operation operation level (m) discharge turbine (cumecs) (hr) (No.) efficiency 2 194.162 53.528 0.94902 464.94 22.98 3 194.495 53.197 0.94884 697.06 15.33 4 194.823 52.871 0.94866 928.96 11.50 5 195.152 52.544 0.94847 1160.63 9.21 6 195.483 52.216 0.94827 1392.07 7.68 7 195.812 51.890 0.94808 1623.29 6.57 8 196.140 51.567 0.94787 1854.29 5.76 Power output and duration of operation are computed at maximum turbine efficiency. Water conservation achieved is given in Table 7. Table 7 : Water Conservation in Actual Power Generation of 4.976 MU Duration of Total water Total water Units in Output of Total operation each unit output of operation required, conserved, (MW) units (MW) (million m3) (million m3) (No.) (hr) 2 113.84 227.68 21.86 36.5907 1.8745 3 113.05 339.15 14.67 36.8203 1.6449 4 112.28 449.10 11.08 37.0475 1.4177 5 111.50 557.50 8.93 37.2924 1.1728 6 110.71 664.28 7.49 37.5425 0.9227 7 109.94 769.55 6.47 37.8577 0.6075 8 109.16 873.30 5.70 38.0254 0.4398 It is seen from Table 7 that unit output decreases with the increase in number of units. It is due to reduction in net head with increase in plant discharge. Hence, it is most advantageous to operate minimum number of units. In this case, operation of 2 units as above will meet the load demand efficiently with water conservation of 4.87%. Variation in water conservation from 1.14% to 4.87% with number of units in operation is shown in Fig. 7. 117
  10. 10. International Journal of Advanced Research in Engineering and Technology (IJARET), ISSN 0976 – 6480(Print), ISSN 0976 – 6499(Online) Volume 4, Issue 7, November – December (2013), © IAEME Fig. 5. Variation in water conservation below rated head 6. CONCLUSION The concept of demand based optimal generation of a hydroelectric power plant is developed on the basis of operation of turbines at maximum efficiency and applied to a multi-unit hydroelectric power plant. It is found that variation in water conservation varies with the head and number of units to be operated. Maximum upto 4.87% saving in water is achieved when head is below the rated head. Towards the end of summer season, water level in reservoir is low and hence conservation of water becomes crucial. It is also found that in all the cases, saving in water is maximum with lesser number of units in operation. Using above information, the utilities may coordinate with river control authorities and Load Dispatch Centre for operation of the units at maximum turbine efficiencies. In summer when scarcity of water is more and demand of electricity is increased, the role of water management becomes critical to ensure its optimum utilization. The operation of turbines at maximum efficiency minimizes vibrations and cavitation which reduces wear-tear and in-turn maintenance cost. 7. ACKNOWLEDGEMENT The authors gratefully acknowledge Dr. Appu Kuttan K. K., Director, Maulana Azad National Institute of Technology, Bhopal, India for his encouragement in carrying out research work. The authors are thankful to NHDC Ltd. for cooperation and sharing of data on Indira Sagar Hydroelectric Project. NOMENCLATURE Et Etmax FRL Hlh Hmax Hmin Hnet LD MDDL efficiency of turbine max. turbine efficiency Full Reservoir Level (m) Elevation of reservoir (m) maximum head limit (m) minimum head limit (m) net head (m) load demand (MW) Minimum Draw Down Level 118
  11. 11. International Journal of Advanced Research in Engineering and Technology (IJARET), ISSN 0976 – 6480(Print), ISSN 0976 – 6499(Online) Volume 4, Issue 7, November – December (2013), © IAEME m n Pgeach Pgmax Pgmin Pi Pt POL PTLi Q Qi Qmax Qmin Qrated ti T1 T2 T3 T4 Vstart_los Vstop_los no. of units in operation no. of units in power plant output of each generator (MW) unit maximum output limit (MW) unit minimum output limit (MW) output of ith unit (MW) output of turbine (MW) part/over load (MW) power transfer loss discharge (cumecs) discharge of ith turbine (cumecs) maximum discharge limit of a turbine (cumecs) minimum discharge limit of a turbine (cumecs) minimum discharge limit of a turbine (cumecs) time of operation of ith turbine (s) time to achieve 90% of rated speed from standstill (30 s) time to reach synchronous speed and synchronizing (60 s) time to load the unit after synchronizing (30 s) stopping time (60 s) loss of water in one start-up (m3) loss of water in one shut-down (m3) REFERENCES [1] A.L. Diniz, P.P.I. Esteves, and C. Sagastizábal, A mathematical model for the efficiency curves of hydroelectric units, IEEE PES General Meeting, Tampa, FL, 2007, 1-7. [2] A. Mahor, and S. Rangnekar, Short term optimal generation scheduling of Narmada cascaded hydro electric system,” Hydro Nepal, 7, 2010, 71-80. [3] J.P.S. Catalão, S.J.P.S. Mariano, V.M.F. Mendes, and L.A.F.M. Ferreira, Scheduling of headSensitive cascaded hydro systems: A nonlinear approach, IEEE Transactions on Power Systems, 24(1), 2009, 337-346. [4] C. Li, E. Hsu, A.J. Svoboda, C. Tseng, and R.B. Johnson, Hydro unit commitment in hydrothermal optimization, IEEE Transactions on Power Systems, 12(2), 1997, 764-769. [5] O. Nilsson, and D. Sjelvgren, Variable splitting applied to modeling of start-up costs in short term hydro generation scheduling,” IEEE Transactions Power Systems, 12(2), 1997, 770-775. [6] O. Nilsson, and D. Sjelvgren, Hydro unit start-up costs and their impact on the short term scheduling strategies of Swedish Power Producers, IEEE Transactions Power Systems, 12(1), 1997, 38-44. [7] S.R. Awasthi, V. Prasad, and S. Rangnekar, Operational strategies to increase generation of large hydroelectric power plants, Water and Energy International Journal of CBIP, 70(8), 2013, 7-11. [8] Bilal Abdullah Nasir, “Design of High Efficiency Pelton Turbine for Micro-Hydropower Plant”, International Journal of Electrical Engineering & Technology (IJEET), Volume 4, Issue 1, 2013, pp. 171 - 183, ISSN Print : 0976-6545, ISSN Online: 0976-6553, [9] Deepika Yadav, R. Naresh and V. Sharma, “Fixed Head Short Term Hydro Thermal Generation Scheduling Using Real Variable Genetic Algorithm”, International Journal of Electrical Engineering & Technology (IJEET), Volume 3, Issue 2, 2012, pp. 430 - 443, ISSN Print : 0976-6545, ISSN Online: 0976-6553. 119

×