kaisar r. khan mcneese state university lake charles, la 70605

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Costing of energy Costing of energy generation of multi area generation of multi area interconnected systems interconnected systems with conventional as well with conventional as well as renewable sources as renewable sources Kaisar R. Khan McNeese State University Lake Charles, LA 70605

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Costing of energy generation of multi area interconnected systems with conventional as well as renewable sources. Kaisar R. Khan McNeese State University Lake Charles, LA 70605. Outline. Introduction Proposed Numerical Model Wind Profile and Modification of the model - PowerPoint PPT Presentation

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Page 1: Kaisar R. Khan McNeese State University Lake Charles, LA 70605

Costing of energy generation of multi area Costing of energy generation of multi area interconnected systems with conventional interconnected systems with conventional

as well as renewable sourcesas well as renewable sources

Costing of energy generation of multi area Costing of energy generation of multi area interconnected systems with conventional interconnected systems with conventional

as well as renewable sourcesas well as renewable sourcesKaisar R. Khan

McNeese State UniversityLake Charles, LA 70605

Page 2: Kaisar R. Khan McNeese State University Lake Charles, LA 70605

OutlineOutline• Introduction• Proposed Numerical Model• Wind Profile and Modification of the model• Evaluation of EEG for a Two Area Interconnected System with

Wind Generating Units• Results for the system with PV generation• Conclusion

Page 3: Kaisar R. Khan McNeese State University Lake Charles, LA 70605

Two Area Interconnected SystemTwo Area Interconnected SystemTwo Area Interconnected SystemTwo Area Interconnected System

X Y TC

X and Y resembles the two geographically isolated utility systems but electrically interconnected by a tie line with capacity TC. Each system is having a projected hourly load pattern with generating unit (SOU/JOU) to meet its own demand first and then they can export some of the generated energy if they have excess and the other system has demand.

Page 4: Kaisar R. Khan McNeese State University Lake Charles, LA 70605

Renewable Energy Sources in the Interconnected System

Renewable Energy Sources in the Interconnected System

• Renewable energy sources are driving a great deal of research effort in different dimension in power system. It is primarily due to the minimum cost of energy generation and environmental friendliness.

• Solar, wind, hydro, geothermal, wave are few example of energy sources that are feasible alternative to the conventional fossil fuel burning electric generating unit.

• Inclusion of renewable generating unit to harvest solar/wind energy requires special attention to evaluate expected energy generation (EEG) as its availability is random (depending on the wind/solar profile).

• Wind profile is affected by the seasonal, weather and hourly variation of wind. Similar characteristics has been observed for solar irradiance.

Page 5: Kaisar R. Khan McNeese State University Lake Charles, LA 70605

OutlineOutline• Introduction• Proposed Numerical Model• Wind Profile and Modification of the model• Evaluation of EEG for a Two Area Interconnected System with

Wind Generating Units• Results for the system with PV generation• Conclusion

Page 6: Kaisar R. Khan McNeese State University Lake Charles, LA 70605

The evaluation Procedure of the expected energy The evaluation Procedure of the expected energy generated by a unitgenerated by a unit

The evaluation Procedure of the expected energy The evaluation Procedure of the expected energy generated by a unitgenerated by a unit

1. Evaluate the expected export. Modify the demands of the exporting and the importing systems as well as the tie line capacity

2. Evaluate the expected share transfer from a JOU to the system where the unit is not located. Accordingly modify only the tie line capacity. For conventional unit this step is not necessary.

3. For unit with renewable (wind/solar) energy source modify the capacity according to hourly generation data and follow the above two steps used for conventional units. For the sake of simplicity we consider our renewable generation unit is considered as separately owned.

4. Obtain the expected unserved energy. If the committed unit is a JOU the evaluation of unserved energies of both the systems is required because both of them generate energy.

5. Convolve the unit [4,5].

6. Recalculate the unserved energy after the convolution of the unit.

7. Calculate the EEG of each unit which is the deference of two unserved energies evaluated before and after the convolution.

Page 7: Kaisar R. Khan McNeese State University Lake Charles, LA 70605

Export or ImportExport or ImportExport or ImportExport or Import1) Export Using Tie Line:

A system will export to the other interconnected system to meet their excess demand only when the exporting system has surplus capacity and residual tie line capacity permits the export.

2) Export Without Using Tie Line:

Since the JOU is located in system Y the export from the share of system X to system Y does not require the tie line. The amount of export depends

on the expected unserved demand of system Y and the portion of share, which has not been transferred to system X, and it may be evaluated as

the method mentioned in the previously reported results*

For unit with renewable energy source modify the capacity according to hourly generation data.

•Kaisar R Khan, Q. Ahsan and M. R Bhuiyan, “Expected Energy Production Cost of Two Area interconnected Systems with Jointly Owned Units” Electric Power System Research journal (Elseiver),vol. 69, pp. 115-122, April 2004

Page 8: Kaisar R. Khan McNeese State University Lake Charles, LA 70605

LOLP EvaluationLOLP Evaluation LOLP EvaluationLOLP Evaluation

• Follow the step 1-5 mentioned before.• Recalculate the unserved energy after the convolution

of the unit. If the unserved energy is less than or equal to zero then that segment is already served and will not include in LOLP calculation. Sum of the zero-th moment of probability of all the segment where unserved energy

after convolving the generator is greater than or equal to zero is our LOLP.

0 ESE where k, jiPLOLP

Page 9: Kaisar R. Khan McNeese State University Lake Charles, LA 70605

OutlineOutline• Introduction• Proposed Numerical Model• Wind Profile and Modification of the model• Evaluation of EEG for a Two Area Interconnected System with

Wind Generating Units• Results for the system with PV generation• Conclusion

Page 10: Kaisar R. Khan McNeese State University Lake Charles, LA 70605

Wind GenerationWind Generation Wind GenerationWind Generation

• The energy output from a wind turbine depends on the wind profile. If the wind speed is too low or too high then the wind generators are out of service. For that reason the availability of the generator depends on the wind profiles that are useable for electrical generation.

• Also the output power varies linearly with the wind speed and the probability distribution function (PDF) of the wind generators availability. The PDF follows the Weibull distribution.

• We consider wind generators having multi states of output powers and probability of being available.

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Page 11: Kaisar R. Khan McNeese State University Lake Charles, LA 70605

Wind Profile Measured at SUNY Canton Weather Station

Wind Profile Measured at SUNY Canton Weather Station

0

0.01

0.02

0.03

0.04

0.05

0.06

0.07

0.08

0.09

0.1

Frac

tion

of F

requ

ency

1 3 5 7 9 11 13 15 17 19 21 23 25 27 29 31 33 35 37 39 41 43 45 47 49 51 53 55 57 59 61 63 65 67

Windspeed (mph)

Data f(Weibull): Shape Parameter = 2 , Scale Parameter= 9

0

2

4

6

8

10

12

Dec-08 Jan-09 Feb-09 Mar-09 Apr-09

Win

d S

pee

d, m

ph

h=30m h=20m

(a) (b)

0

0.01

0.02

0.03

0.04

0.05

0.06

0.07

0.08

0.09

0.1

Frac

tion

of F

requ

ency

1 3 5 7 9 11 13 15 17 19 21 23 25 27 29 31 33 35 37 39 41 43 45 47 49 51 53 55 57 59 61 63 65 67

Windspeed (mph)

Data f(Weibull): Shape Parameter = 2 , Scale Parameter= 9

0

2

4

6

8

10

12

Dec-08 Jan-09 Feb-09 Mar-09 Apr-09

Win

d S

pee

d, m

ph

h=30m h=20m

(a) (b)

(a) Wind speed measured at two different heights (30 m solid line, 20 m dashed line) and (b) Annual Wind speed Distribution of 2008 Modelled using Weibull Distribution

Page 12: Kaisar R. Khan McNeese State University Lake Charles, LA 70605

OutlineOutline• Introduction• Proposed Numerical Model• Wind Profile and Modification of the model• Evaluation of EEG for a Two Area Interconnected System with

Wind Generating Units• Results for the system with PV generation• Conclusion

Page 13: Kaisar R. Khan McNeese State University Lake Charles, LA 70605

Two Area Interconnected System Example:Two Area Interconnected System Example:

Hourly load demand for both systems and the global demand Hourly load demand for both systems and the global demand Two Area Interconnected System Example:Two Area Interconnected System Example:

Hourly load demand for both systems and the global demand Hourly load demand for both systems and the global demand

5 10 15 20 25200

400

600

800

1000

1200

1400

1600

1800

2000

Hour

Lo

ad

. M

W

Load of System XLoad of System YGlobal Load

XTC

Area Area

Y

Page 14: Kaisar R. Khan McNeese State University Lake Charles, LA 70605

EEG for individual unit committed in loading order EEG for individual unit committed in loading order with a tie line capacity of 450 MWwith a tie line capacity of 450 MW

EEG for individual unit committed in loading order EEG for individual unit committed in loading order with a tie line capacity of 450 MWwith a tie line capacity of 450 MW

•Loadingorder

•Type of unit

•Capacity(MW)

•FOR •Location •Owner-ship

•Expected energy generation(GWh)

•1 •Wind 1 •Variable 175(max)

•Variable •Y •SOU •3.348

•2 •Hydro •120 •0.032 •X •SOU •2.7878

•3 •Steam Turbine1 •720 •0.069 •X •SOU •16.087

•4 •Steam Turbine2 •806+40 •0.097 •X •JOU •10.99

•5 •Combined Cycle •140 •0.15 •X •SOU •0.1473

•6 •Gas Turbine •142 •0.33 •X •SOU •0.20

•7 •Diesel Engine •9 •0.1 •Y •SOU •0.012

•8 •Barge Mounted •18 •0.15 •Y •SOU •0.016

•9 •Gas Turbine •167 •0.27 •Y •SOU •0.072

•Total •2337 •------ •------- •------- •33.667 (Global generation)

Page 15: Kaisar R. Khan McNeese State University Lake Charles, LA 70605

100 200 300 400 500 600 700 8001.5

2

2.5

3

3.5

4

4.5

5

Tc, MW

Exp

, GW

h

Fixed Genration ModelMultistate Generation Model

(a) (b)

100 200 300 400 500 600 700 80033.2

33.25

33.3

33.35

33.4

33.45

33.5

33.55

33.6

33.65

33.7

Tc, MW

EE

G, G

Wh

Fixed Genration ModelMultistate Generation Model

Expected Energy GenerationExpected Energy Generation

(a)Global EEG and (b) Expected Global Export with tie line capacities of the two area interconnected system having wind generators

•Kaisar Khan, Ahmed Arkaoub, Mohammed Youssef and Mike J. Newtown, “Evaluation of Loss of Load Probability and Expected Energy Generation in Multi-Area Interconnected Systems with Wind Generating Units”, Journal of Energy and power Engineering 8(2014) 805-811.

Page 16: Kaisar R. Khan McNeese State University Lake Charles, LA 70605

2 4 6 8 10 12 14 16 18 20 22 240

1

2

3

4

5

6

7

8

9

Hour

% L

OL

P

Fixed Genration ModelMultistate Generation Model

LOLP of the interconnected system with wind generators

LOLP of the interconnected system with wind generators

Page 17: Kaisar R. Khan McNeese State University Lake Charles, LA 70605

Effect of TC variation on LOLPEffect of TC variation on LOLP

0 5 10 15 20 250

1

2

3

4

5

6

7

8

9

Hour

% L

OLP

TC=400 MW

TC=300 MW

TC=200 MW

TC=100 MW

0 5 10 15 20 250

1

2

3

4

5

6

7

8

9

Hour%

LO

LP

TC=400 MW

TC=300 MW

TC=200 MW

TC=100 MW

•(a) •(b)

Page 18: Kaisar R. Khan McNeese State University Lake Charles, LA 70605

OutlineOutline• Introduction• Proposed Numerical Model• Wind Profile and Modification of the model• Evaluation of EEG for a Two Area Interconnected System with

Wind Generating Units• Results for the system with PV generation• Conclusion

Page 19: Kaisar R. Khan McNeese State University Lake Charles, LA 70605

Hourly Load and Expected Generation of BPSHourly Load and Expected Generation of BPS

Page 20: Kaisar R. Khan McNeese State University Lake Charles, LA 70605

Expected Energy Generation IExpected Energy Generation I

•Kaisar R. Khan, Ahmed A. Arkoub and Quamrul Ahsan, “Evaluation of expected energy generation in multi-area interconnected systems with photo voltaic generating units”, International Journal of Environmental Studies, DOI:10.1080/00207233.2013.798499

Page 21: Kaisar R. Khan McNeese State University Lake Charles, LA 70605

Expected Energy Generation IIExpected Energy Generation II

(a)Global EEG (b & c) Expected Global Export with tie line capacities of the

two area interconnected system having solar generators

Page 22: Kaisar R. Khan McNeese State University Lake Charles, LA 70605

Effect of TC variation on EEGEffect of TC variation on EEG

Page 23: Kaisar R. Khan McNeese State University Lake Charles, LA 70605

OutlineOutline• Introduction• Proposed Numerical Model• Wind Profile and Modification of the model• Evaluation of EEG for a Two Area Interconnected System with

Wind Generating Units• Results for the system with PV generation• Conclusion

Page 24: Kaisar R. Khan McNeese State University Lake Charles, LA 70605

ConclusionsConclusionsConclusionsConclusions• A model has been developed to evaluate the reliability and

expected energy generation of a two area interconnected system with wind generation.

• The model also can successfully include the stochastic behavior of wind/solar generating units. This will give designer

or system planners better ideas of how to include renewable generators for reliable and economic expansion of

interconnected networks. • The results show that even though renewable generators are

economic but that will add more uncertainty while meeting the demand. Proper scheduling of generation is required to

maximize the use of the wind energy resource.