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1 Seema Thakur (st107641) Advisor: Dr. Weerakorn Ongsakul Optimal Generation Scheduling of Cascaded Hydro-thermal and Wind Power Generation By Particle Swarm Optimization Master’s Thesis Energy

1 Seema Thakur (st107641) Advisor: Dr. Weerakorn Ongsakul Optimal Generation Scheduling of Cascaded Hydro-thermal and Wind Power Generation By Particle

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Page 1: 1 Seema Thakur (st107641) Advisor: Dr. Weerakorn Ongsakul Optimal Generation Scheduling of Cascaded Hydro-thermal and Wind Power Generation By Particle

1

Seema Thakur(st107641)

Advisor: Dr. Weerakorn Ongsakul

Optimal Generation Scheduling of Cascaded Hydro-thermal and Wind Power Generation By

Particle Swarm Optimization

Master’s Thesis

Energy

Page 2: 1 Seema Thakur (st107641) Advisor: Dr. Weerakorn Ongsakul Optimal Generation Scheduling of Cascaded Hydro-thermal and Wind Power Generation By Particle

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Introduction

Contribution to Research

Benefits of the Proposed Innovative Approach

Methodology

Problem Formulation

Results & Discussion

Conclusion

Recommendation

Outlines

Page 3: 1 Seema Thakur (st107641) Advisor: Dr. Weerakorn Ongsakul Optimal Generation Scheduling of Cascaded Hydro-thermal and Wind Power Generation By Particle

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Introduction Bulk amount of electrical energy cannot be stored. So, in real time, the generation

from different power plants should match with the power demand.

Electricity generating companies and power systems have the problem of deciding how best to meet the varying demand for electricity, which has a daily and/or weekly cycle. 

Generation scheduling is the process of allocating the required load demand between the available generation units such that the cost of operation is minimized, while honoring the operational constraints of the available generation resources. There have been many algorithms proposed for the scheduling.

A typical system is composed of hydro and thermal generating units. The generation scheduling done for such a system is called hydrothermal scheduling.

It helps to minimize the total fuel cost and also for the optimal utilization of the available natural renewable resources.

Considering the aspect of near future, integrating wind energy in an existing hydrothermal system seems to be an attractive option.

Page 4: 1 Seema Thakur (st107641) Advisor: Dr. Weerakorn Ongsakul Optimal Generation Scheduling of Cascaded Hydro-thermal and Wind Power Generation By Particle

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Contribution to Research

Generation scheduling is a challenging task due to its complex mathematical behavior. Thus, various optimization techniques have been used in the past but they have various drawbacks.

So far the research has been done for generation scheduling of hydro-thermal system or wind-thermal system. But no works has been done for a system having all the three generations.

In this research work, an innovative approach called Particle Swarm Optimization (PSO) is introduced for the generation scheduling of different systems incorporating all three different types of generation to optimize the generation cost.

In addition , the effectiveness of different versions of PSO is evaluated in this work.

The proposed simulation model has been tested in test systems as well as in the real power system of Nepal.

Page 5: 1 Seema Thakur (st107641) Advisor: Dr. Weerakorn Ongsakul Optimal Generation Scheduling of Cascaded Hydro-thermal and Wind Power Generation By Particle

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Cost reduction

Maximization of renewable energy use (hydro and wind)

Reduction of thermal generation : Reduction of GHG emission.

(Without any extra monitory investment )

Benefits of the Proposed Innovative Approach

Page 6: 1 Seema Thakur (st107641) Advisor: Dr. Weerakorn Ongsakul Optimal Generation Scheduling of Cascaded Hydro-thermal and Wind Power Generation By Particle

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Methodology

The approach is inspired by the social behavior of animals such as fish schooling and bird flocking.

A set of unknown variables are randomly initialized in a feasible region and the best solution is selected.

The solution tries to converge depending upon its distance from the best solution.

In each iteration within the runtime of the program, the solution converses and gives the best solution.

PSO

Figure 1: Fish schooling and Bird flocking

Page 7: 1 Seema Thakur (st107641) Advisor: Dr. Weerakorn Ongsakul Optimal Generation Scheduling of Cascaded Hydro-thermal and Wind Power Generation By Particle

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Problem Formulation

Fig: Schematic diagram of a typical power system

The objective is to minimize the total operating cost

Minimize,

Subjected to various physical limitations,

T

t

I

itii PFCTC

1 1, )(

Page 8: 1 Seema Thakur (st107641) Advisor: Dr. Weerakorn Ongsakul Optimal Generation Scheduling of Cascaded Hydro-thermal and Wind Power Generation By Particle

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Problem FormulationII. Constraints

a. Power Balance Constraints

b. Hydro power generation limits

c. Hydro plant water discharge limits

d. Reservoir water storage limits

e. Initial and final reservoir water storage volume

f. Hydro power generation constraints

g. Hydraulic continuity constraints

h. Thermal power generation limits

i. Ramp response rate limit on thermal generation units

j. Spinning reserve limits

k. Power output limits on wind energy system

Page 9: 1 Seema Thakur (st107641) Advisor: Dr. Weerakorn Ongsakul Optimal Generation Scheduling of Cascaded Hydro-thermal and Wind Power Generation By Particle

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Results & Discussion

Page 10: 1 Seema Thakur (st107641) Advisor: Dr. Weerakorn Ongsakul Optimal Generation Scheduling of Cascaded Hydro-thermal and Wind Power Generation By Particle

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GS[3] SA[16] FEP[21 ] PSO[21] PSO[22] PSO-TVIW (proposed)

SPSO-TVAC (Proposed)

709300

709400

709500

709600

709700

709800

709900

Comparison of results with previous works

Methods

Co

st (

$)

0

400

800

1200

1600

2000

1 2 3 4 5 6

Time Intervals

Pow

er

genera

tion (

MW

)

Hydro (MW) Thermal (MW)

Generation level of plants with time interval

Test 1: A Simple System with a Hydro and a Thermal Generating Unit

Page 11: 1 Seema Thakur (st107641) Advisor: Dr. Weerakorn Ongsakul Optimal Generation Scheduling of Cascaded Hydro-thermal and Wind Power Generation By Particle

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Test 2: A system with Four Cascaded Hydro and Three ThermalGenerating Units

SA [2] EP [2] PSO [2] CPSO (Proposed)

PSO-TVIW (proposed)

PSO-TVAC (proposed)

SPSO-TVAC (proposed)

36,000

38,000

40,000

42,000

44,000

46,000

48,000

Comparative results on test system with different approaches

Methods

Co

st (

$)

Page 12: 1 Seema Thakur (st107641) Advisor: Dr. Weerakorn Ongsakul Optimal Generation Scheduling of Cascaded Hydro-thermal and Wind Power Generation By Particle

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BPSO PSO-TVIW PSO-TVAC SPSO-TVAC 39000

39400

39800

40200

40600

41000

With/Without wind power generation

Without wind power generation With wind power generation

Methods

Co

st (

$)

BPSO PSO-TVIW PSO-TVAC SPSO-TVAC 39000

39400

39800

40200

40600

41000

Without wind power generation

Without wind power generation

Methods

Co

st (

$)

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 2402468

101214

0

100

200

300

400

500

600

Forecasted Wind Velocity Test System [25]

Time Interval (hr)

Win

d ve

loci

ty (m

/s)

Win

d Po

wer

( kW

)

Page 13: 1 Seema Thakur (st107641) Advisor: Dr. Weerakorn Ongsakul Optimal Generation Scheduling of Cascaded Hydro-thermal and Wind Power Generation By Particle

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Convergence characteristics of the proposed approached of all PSO schemes without considering wind generation in the system.

0 10 20 30 40 50 60 70 80 90 1003.8

3.9

4

4.1

4.2

4.3

4.4

4.5x 10

4

Iterations

To

tal G

en

era

tion

Co

st $

CPSO

PSO-TVIWPSO-TVAC

SPSO-TVAC

Convergence characteristics of the proposed approached of all PSO schemes considering wind generation in the system.

Page 14: 1 Seema Thakur (st107641) Advisor: Dr. Weerakorn Ongsakul Optimal Generation Scheduling of Cascaded Hydro-thermal and Wind Power Generation By Particle

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1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 240

200

400

600

800

1000

1200

Pth3

Pth2

Pth1

Ph4

Ph3

Ph2

Ph1

Time Interval (hr)

Pow

er G

ener

atin

(M

W)

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 240

200

400

600

800

1000

1200Pth3

Pth2

Pth1

Ph4

Ph3

Ph2

Ph1

WindTime Interval (hr)

Pow

er G

ener

atio

n (

MW

)

Optimal generation scheduling by SPSO-TVAC for each time interval

Optimal generation scheduling by SPSO-TVAC for each time interval

Page 15: 1 Seema Thakur (st107641) Advisor: Dr. Weerakorn Ongsakul Optimal Generation Scheduling of Cascaded Hydro-thermal and Wind Power Generation By Particle

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Generation Scheduling

for

Nepali Power System

Page 16: 1 Seema Thakur (st107641) Advisor: Dr. Weerakorn Ongsakul Optimal Generation Scheduling of Cascaded Hydro-thermal and Wind Power Generation By Particle

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BPSO TVIW TVAC SPSO_TVAC 30,50031,00031,50032,00032,50033,00033,50034,00034,50035,000

Comparative results from different PSO approaches for the real system model of Nepal

Without wind power generation With wind power generation

Methods

Gen

erat

ion

Co

st (

$)

BPSO TVIW TVAC SPSO_TVAC 30,50031,00031,50032,00032,50033,00033,50034,00034,50035,000

Comparative results from different PSO approaches for the real system model of Nepal

Without wind power generation

Methods

Gen

erat

ion

Co

st (

$)

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 240

5

10

15

20

0100200300400500600700

Forecasted Wind Velocity Kagbeni, Nepal

Time Interval (hr)

Win

d ve

loci

ty (m

/s)

Win

d Po

wer

(kW

)

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 240

5

10

15

20

0100200300400500600700

Forecasted Wind VelocityChussang, Nepal

Time interval (hr)

Win

d ve

loci

ty (m

/s)

Win

d Po

wer

(kW

)

Page 17: 1 Seema Thakur (st107641) Advisor: Dr. Weerakorn Ongsakul Optimal Generation Scheduling of Cascaded Hydro-thermal and Wind Power Generation By Particle

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Hydrothermal generation (MW) schedule by SPSO-TVAC without considering wind generation in the Nepali system

Page 18: 1 Seema Thakur (st107641) Advisor: Dr. Weerakorn Ongsakul Optimal Generation Scheduling of Cascaded Hydro-thermal and Wind Power Generation By Particle

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Figure: Hydrothermal generation (MW) schedule by SPSO-TVAC with the consideration of wind generation in the Nepali system

Page 19: 1 Seema Thakur (st107641) Advisor: Dr. Weerakorn Ongsakul Optimal Generation Scheduling of Cascaded Hydro-thermal and Wind Power Generation By Particle

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Conclusion This research work helps to reduce the GHG emission by reducing the thermal

generation in the system. (Social benefit)

Helps to optimize the generation cost.(Economical benefit)

Maximizes the utilization of renewable resources . (Environmental benefit)

The comparison with the results from the already existing techniques clearly demonstrates that the proposed method gives the best result.

The simulation results for both test model and real system model (Nepali system) illustrate that the proposed SPSO_TVAC is the most efficient approach to find the optimal solution for generation scheduling of hydrothermal system with/without penetration of wind power to the system, considering all the associated constraints.

In this proposed concept , there is no physical system modification necessary in the existing system Results, no additional constructional cost.

Page 20: 1 Seema Thakur (st107641) Advisor: Dr. Weerakorn Ongsakul Optimal Generation Scheduling of Cascaded Hydro-thermal and Wind Power Generation By Particle

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Thank You

Q & A