DEMAND BASED OPTIMAL PERFORMANCE OF A HYDROELECTRIC POWER PLANT

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

109

DEMAND BASED OPTIMAL PERFORMANCE OF A HYDROELECTRIC

POWER PLANT

Shambhu Ratan Awasthi1, Vishnu Prasad

2,

Saroj Rangnekar3

1Department of Energy, Maulana Azad National Institute of Technology, Bhopal, India

2Department of Civil Engineering, Maulana Azad National Institute of Technology,

Bhopal, India 3Department 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.

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, pp. 109-119 © IAEME: www.iaeme.com/ijaret.asp Journal Impact Factor (2013): 5.8376 (Calculated by GISI) www.jifactor.com

IJARET

© I A E M E



110

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 (3)

2.2 Bounds Reservoir level : MDDL ≥ Hlh ≤ FRL

Turbine discharge : Qmin < Q < Qmax

Unit output : Pgmin < Pgeach < Pgmax

Head : 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.



111

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 m3

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.



112

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



113

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

capacity 12.22 Billion m

3

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 = 259.855 m

Average plant discharge = 498.25 cumecs

Cumulative volume of water released in 24 h = 43.0488 million m3

No. of start-ups =10

No. of shut-downs = 9

Water loss in start-ups = 10 x 5700 = 57,000 m3

Water loss in shut-downs = 9 x 7000 = 63,000 m3

Water utilized in generation = 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).



114

Table 2 : Plant Discharge and Duration of Operation

Units in

operation

(No.)

Tail water

level (m)

Net head

(m)

Maximum

turbine

efficiency

Plant

discharge

(cumecs)

Duration of

operation

(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

operation

(No.)

Output of

each unit

(MW)

Total output

of units

(MW)

Duration of

operation

(hr)

Total water

required

(million m3)

Total water

conserved,

(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



115

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’.





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 = 6


Water loss in start-ups = 6 x 5700 = 34200 m3

Water loss in shut downs = 6 x 7000 = 42000 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.


Units in

operation

(No.)

Tail water

level (m)

Net head

(m)

Maximum

turbine

efficiency

Plant

discharge

(cumecs)

Duration of

operation

(hr)

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 3.44

6 195.507 58.995 0.95075 1406.87 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.



116

Table 5 : Water Conservation in Power Generation of 2.15 MU

Units in

operation

(No.)

Output of

each unit

(MW)

Total output

of units

(MW)

Duration of

operation

(hr)

Total water

required

(million m3)

Total water

conserved

(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’.





Average plant discharge = 446 cumecs

Cumulative volume of water released in 24 h = 38.5344 million m3

No. of start-ups = 6


Water loss in start-ups = 6 x 5700 = 34200 m3

Water loss in shut-downs = 5 x 7000 = 35000 m3

Total water loss in start-ups and shut-downs = 69200 m3

= 0.0692 million m3




117

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.


Units in

operation

(No.)

Tail water

level (m)

Net head

(m)

Maximum

turbine

efficiency

Plant

discharge

(cumecs)

Duration of

operation

(hr)

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

Units in

operation

(No.)

Output of

each unit

(MW)

Total

output of

units (MW)

Duration of

operation

(hr)

Total water

required,

(million m3)

Total water

conserved,

(million m3)

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.



118

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 efficiency of turbine

Etmax max. turbine efficiency

FRL Full Reservoir Level (m)

Hlh Elevation of reservoir (m)

Hmax maximum head limit (m)

Hmin minimum head limit (m)

Hnet net head (m)

LD load demand (MW)

MDDL Minimum Draw Down Level



119

m no. of units in operation

n no. of units in power plant

Pgeach output of each generator (MW)

Pgmax unit maximum output limit (MW)

Pgmin unit minimum output limit (MW)

Pi output of ith

unit (MW)

Pt output of turbine (MW)

POL part/over load (MW)

PTLi power transfer loss

Q discharge (cumecs)

Qi discharge of ith

turbine (cumecs)

Qmax maximum discharge limit of a turbine (cumecs)

Qmin minimum discharge limit of a turbine (cumecs)

Qrated minimum discharge limit of a turbine (cumecs)

ti time of operation of ith

turbine (s)

T1 time to achieve 90% of rated speed from standstill (30 s)

T2 time to reach synchronous speed and synchronizing (60 s)

T3 time to load the unit after synchronizing (30 s)

T4 stopping time (60 s)

Vstart_los loss of water in one start-up (m3)

Vstop_los 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 head-

Sensitive 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 hydro-

thermal 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.

DEMAND BASED OPTIMAL PERFORMANCE OF A HYDROELECTRIC POWER PLANT

Documents

Transcript of DEMAND BASED OPTIMAL PERFORMANCE OF A HYDROELECTRIC POWER PLANT