Optimal Peak Shaving Operation Of Hydro Electric Engineering Essay

Hydro electric power Station converts the possible energy of H2O caput that stored at a reservoir in to electrical energy. It is economical to use all the available hydro potency associated with a hydro electric power station because of virtually nonexistent coevals cost. Owing to this advantage electric public-service corporation gives premier accent on the committedness of hydro unit. On the contrary, rainfall, reservoir size & A ; the watercourse flow are the chief restrictions of hydroelectric power.

The thought of optimum usage of hydro-electric energy is briefly discussed in [ 1 ] . The writers of the paper investigated the impacts of thorough usage of hydro power station on the dependability and production cost in BPS. This paper considers the generalized forced outage rate of the hydro unit alternatively of existent closure of the units throughout the probe period that may non convey the existent consequence.

Q.Ahsan & A ; MR. Bhuiya proposed a technique of imitating energy limited hydro unit using all the exchangeable H2O caput in [ 2 ] .

The chance denseness map of H2O caput in kaptai reservoir and multi province theoretical account of that power station is developed in [ 3 ] . The item information about hydro-electric power coevals, power deficit, power demand and load-shedding in Bangladesh is presented in [ 4 ] .

This paper presents the impacts of optimum peak shaving operation of hydro electric power station on the decrease of sever burden casting in peak burden hours sing the existent shutdown status of the hydro units throughout the last one twelvemonth ( 2011 ) . The paper besides investigates the different manners of use of hydro potency and their impacts on burden direction system.

II. POWER CRISIS SCENARIO IN BANGLADESH

The day-to-day electric burden in BPS is non even throughout the twenty-four hours, it varies from clip to clip that shown in figure 01 [ 5 ] [ 6 ] . Figure 01 depicts that, at 6.00 autopsy burden starts to increase and it reaches at the extremum at 10.00 autopsy. It is seen that the demand of electricity is monolithic at extremum hours which is around 5100MW doing burden sloughing of 1300 MW and this peak burden varies from season to season of a twelvemonth.

Fig 01: burden curve of BPS for a typical summer twenty-four hours in 2011

As the demand is higher than the coevals, the BPS is forced to restrict electric demand during the peak hours normally flushing of the twenty-four hours throughout the twelvemonth and all the hours of the twenty-four hours in summer. Although the installed capacity of the bring forthing units of BPS is higher than the demand, nevertheless a large sum of installed capacity is ever disappeared due to care and overhauling of the units because of old age. Furthermore the hydro potency of kaptai reservoir is non being exploited decently because of unplanned care and operation of the hydro units. If it could be guarantee the proper planning in the operation of hydroelectric power station there would be an chance to increase the coevals and the decrease of burden casting during peak burden hours.

III. HYDRO ELECTRIC POTENTIAL IN

Bangladesh

There is merely one hydro-electric power bring forthing station in Bangladesh, situated at Kaptai in Rangamati. It has five bring forthing units with combined coevals capacity of 230 MW. The rated capacity of the reservoir at Kaptai is 5.25 million acre-ft with a maximal H2O caput of 109 foots ( from mean sea degree ) [ 6 ] . The electricity coevals of 230 MW can be obtained at a H2O degree of 96 foot and the coevals becomes zero at 66 ft H2O caput

Mathematical Model

A simple equation for the transition of H2O caput of Kaptai reservoir in to electricity in Megawatt is presented in equation ( I ) [ 3 ] .

( I )

where, is station end product in megawatt and represents H2O caput in pess.

The fluctuation of H2O caput is random and distinct in nature. To change over this possible caput, a chance denseness map ( PDF ) of H2O caput is indispensable. The PDF of H2O caput in footings of delta map for all sorts of hydro unit is shown in equation ( two ) [ 2 ] .

Where the PDF of H2O caput is obtained from historical informations. The electricity coevals with exchangeable H2O caput is presented in equation ( three ) .

In world the bring forthing units are non 100 % dependable. Some units may be out of service due to care and overhauling or forced shutdown. Sing all the factor the existent end product is given by equation ( four )

( four )

( V )

Where, and are the available coevals capacity of the units and electrical capacity of H2O caput severally. The equation ( V ) gives the exact PDF theoretical account of end product capacity of any hydro bring forthing unit [ 2 ] . The end product PDF theoretical account of kaptai hydro power station is developed in [ 3 ] which is shown in figure 02.

Degree centigrades: Usersal-aminDesktopHydro chart – Copy.jpg

Fig 02: Probability Density Function with regard to Generation Capacity of Hydro Potential

IV. HYDRO ELECTRIC POWER GENERATION IN DIFFERENT MODES OF OPERATION

To look into the impacts of hydro coevals through different manner on the peak hr burden casting the monthly PDB coevals, possible hydro potency and hydro coevals through different manners are given in table 01.

Table 01: Peak hr ‘s hydro power coevals in different manners of Operation in 2011

Calendar months

Actual Generation by PDB ( MWh )

Possible Hydro Generation

( MWh )

Mode A

( MWh )

Mode B

( MWh )

Mode C

( MWh )

Jan

18273

33136.75

33033.63

20150

20150

Feb

12527

22603.875

22603.88

14800

14800

Mar

15292

20333.875

20333.88

19349

20150

Apr

11812

14244.375

14244.38

14244.38

19500

May

8567

11647.875

11647.88

11647.88

21750

Jun

14880

17091.375

17091.38

17091.38

27000

Jul

20586

25957.75

25957.75

25957.75

27900

Aug

22997

36231.625

34187.13

27900

27900

Sep

23009

46265.625

34500

27000

27000

Oct

25021

45348.875

33350

26100

26100

Nov

20855

39366.25

32200

25200

25200

Dec

23851

38991.25

35650

27900

27900

Entire

217670

351219.5

314799.9

257340.4

285350

The possible Hydro potency indicates that there is adequate proviso to bring forth electrical energy from available H2O caput. But the existent scenario is that there is no adequate bring forthing capacity of the power station to bring forth that sum of energy. By sing the bing highest bring forthing capacity which is 230 MW, a alteration has been done in the rating procedure that indicates ‘Mode A ‘ . This manner of operation shows that coevals ne’er exceeds 230 MW holding a H2O caput of higher potency. For different grounds like forced shut down, care and passing etc, it is non possible to run all the bring forthing unit at a clip and that is why the existent generating capacity is considered in ‘Mode B ‘ alternatively of installed capacity of the power station. In all the above mentioned three instances of rating from column 3 to 5. The electricity coevals is considered as same in all the hours in a peculiar twenty-four hours. To bring forth highest hydro power at peak hr ‘s farther alteration has been done in the rating procedure that is shown in ‘Mode C ‘ . In this manner of operation highest sum of energy is generated in peak burden hours sing H2O caput and available bring forthing capacity and remainder of the hydro potency is utilized in other portion of the twenty-four hours.

The tabular array clearly reveals that the evaluated energy in all the four instances during peak burden hours is higher than the existent coevals of BPDP through conventional procedure of operation.

To analyze a clear position of increase in hydro energy coevals through all the manner of rating in comparing with the existent coevals a chart is presented in fig.03.

Fig 03: Annual Increase in Hydro Generation

The fig. shows that if there was adequate generating capacity to use the available hydro potency it would hold been possible to increase the hydro coevals by 61 % over the existent coevals of 2011. Although it is non possible at this minute but sing all the restraints the other runing manner like A, B & A ; C show a important addition in hydro energy coevals. As ‘Mode C ‘ is the peak shaving manner of operation, it gives a 26 % increase in energy coevals over the conventional one which gives a promising consequence for the decrease of burden sloughing.

V. IMPACT OF OPTIMAL HYDRO ELECTRIC POWER GENERATION ON PEAK LOAD SHEDDING

Under the consideration of hydro electric coevals on burden sloughing, the different manners of operation mentioned supra have different impact on extremum burden casting. As the evaluated consequences of different manners of operation give increased hydro coevals, there would be a decrease in burden casting in extremum hours that has been presented in table 02.

The tabular array below shows monthly staying burden casting with one-year sum at different manners compared with the existent burden casting.

Table 02: Extremum hours load casting by using different manners of alteration

Calendar months

Load Shedding in MWh

Actual

For Possible Hydro Resource

For Mode A

For Mode B

For Mode C

Jan

46345.7

31481.95

31585.08

44468.7

44468.7

Feb

61577.4

51500.525

51500.53

59304.4

59304.4

Mar

124751.15

119709.275

119709.3

120694.2

119893.2

Apr

77041.175

74608.8

74608.8

74608.8

69353.18

May

67865.2

64784.325

64784.33

64784.33

54682.2

Jun

75376.375

73165

73165

73165

63256.38

Jul

62298.575

56926.825

56926.83

56926.83

54984.58

Aug

60991.8

47757.175

49801.68

56088.8

56088.8

Sep

58633.375

35376.75

47142.38

54642.38

54642.38

Oct

322934.9

302607.025

3146059

3218559

3218559

Nov

2354.5

-16156.75

-8990.5

-1990.5

-1990.5

Dec

4272.51

-10867.74

-7526.49

223.51

223.51

Entire

964442.66

830893.16

867312.8

924772.3

896762.7

Load casting with possible hydro resource coevals gives lowest sum of unserved energy. A sum of 830893.16 MW-h burden casting would happen if the entire Hydro potency of the reservoir could be used in order to bring forth power. It is besides observe from the one-year sum the other manner of operation gives a good sum of decrease in burden casting. In the month of November and December negative numerical value indicates inordinate hydro coevals that caused off burden higher cost top outing units. To convey a clear perceptual experience on the decrease of burden casting a chart is presented in fig.04.The consequence of presenting different manner of hydro coevals on burden sloughing can be clearly understood by the chart.

Fig 04: Percentage of decrease in Load casting

Harmonizing to the figure, if it was possible to utilize entire hydro resource so the burden sloughing could be reduced by 13.84 per centum and if ‘Mode A ‘ was applied so the burden casting would hold been reduced by 11.69 % . But these two techniques can non be taken under consideration for some ground which is mentioned earlier. By Appling ‘Mode B ‘ alteration technique the burden sloughing could be reduced by 4.57 % . ‘Mode B ‘ is a possible technique but its decrease of burden sloughing is lower than ‘Mode C ‘ . Morever, Mode B does non guarantee optimum use of hydro resource during peak hours. The targeted extremum casting ‘Mode C ‘ gives 7.32 % decrease of burden casting during peak hours with a numerical value of 67679.96 MWh in the twelvemonth of 2011.

VI. Decision

Load casting is one of the major jobs in BPS and it becomes more terrible at the extremum hours. In this instance, Hydro potency can play a critical function to cut down top out hr burden casting every bit good as entire burden casting. The evaluated consequence of different manner of operation of hydro station that investigated in this paper gives a promising consequence to cut down. The magnitude of burden casting, particularly in peak shaving ‘Mode C ‘ which could give 7.32 % decrease of burden casting in extremum hours in the twelvemonth of 2011 with an sum of 67679.96 MWh energy. If the bing hydro power station is operated in planned manner to cut down the burden sloughing, this will be really much helpful for the entire power coevals system to better the dependability.