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Operation and control University of technology education HCMC
power system Faculty of electrical-electronics engineering
U n iv e r s it y o f t e c h n o lo g y e d u c a t io n
Group No 9 H C M C Chapter 9: INTRODUCTION TO ADVANCED TOPIC
F a c u lt y o f e le c t r ic a l – e le c t r o n ic s
1. FACTS
Operation andncontrolr power system
e g in e e in g

2. Steady state
Chapter 9 INTRODUCTION TO
ADVANCED TOPICS
3. Load forecast

4. Conclusion

Nguyễn Anh Toàn
Class: 10025250A

Group No 9 Chapter 9: INTRODUCTION TO ADVANCED TOPIC

1. FACTS
Objectives

2. Steady state Recognize the different types of FACTS controler

Introduction the mathematical analysis for steady state operation

3. Load forecast
Explaint the various methods of load prediction

4. Conclusion


1. FACTS
Agenda

2. Steady state
1 FACTS ?

2 Steady state operation
3. Load forecast

3 Methods for load prediction
4. Conclusion
4 Conclusion


1. FACTS What is a FACTS ?

2. Steady state
Fexible AC Transmission System

Power in lines is controlled in Up gradation of lines is easier.
any desired manner.
Line capacity is increased, Reduced reactive power flow, thereby
3. Load forecast practically upto thermal limits permitting greater active power flow.
By raising transient stabilitv limit, Reduced cost of energy received
system security is enhanced due to enhanced line capacity.

4. Conclusion


1. FACTS Type of FACTS
E1 / δ1 P&Q E2 / δ2
I
P = E1 ( E2 sin(δ )) / X
1
2. Steady state X
STATCOM
E1 / δ1 P&Q E2 / δ2 P = E1 ( E2 sin(δ )) / X ref
1
I
X ref = X − Vinj / I
3. Load forecast
X
SSSC
E1 / δ1 P&Q E2 / δ2 P = E1 ( E2 sin(δ )) / X ref
1
I
4. Conclusion X ref = X − Vinj / I
X
UPFC Q1 = E1 ( E2 cos(δ )) / X


1. FACTS Power Quality

Sinusoidal Sag
1 1

0 0
2. Steady state
-1 -1

0 0.02 0.04 0.06 0.08 0.1 0.12 0 0.02 0.04 0.06 0.08 0.1 0.12

Swell Transient
2
2

3. Load forecast 0 0

-2 -2
0 0.02 0.04 0.06 0.08 0.1 0.12 0 0.02 0.04 0.06 0.08 0.1 0.12

Flicker Harmonic
1 1

4. Conclusion 0 0

-1 -1

0 0.1 0.2 0.3 0.4 0.5 0 0.02 0.04 0.06 0.08 0.1 0.12

Time [sec] Time [sec]


1. FACTS P,Q,U, phase angles Variables

Z=h(X)+n
1 2 3
2. Steady state

3. Load forecast

4. Conclusion


1. FACTS Load prediction
It’s depend Peak load
demand ?

2. Steady state

3. Load forecast

Ltotal = Lbase + Lweather + Lother factors
1 Multiple Regression Methods
4. Conclusion
2 Spectral Expansion Method
3 Scaling a Standar Load


1. FACTS Multiple Regression
Y = a + b1T + b2W + b3 L + b4 P + F (t ) + d

Linear Regression Techniques Nonlinear Regression Method
2. Steady state Y = a0 + a1 X S = f1 (T ) + f 2 (W ) + f3 ( L) + f 4 ( P) + F (t ) + d
n n
Y1 = a0 + a1 X 1 ∑Y
i =1
1 = na0 + a1 ∑ X 1
i =1 f1 (T ), f 2 (W ), f3 ( L), f 4 ( P )
y1 = Y1 − Y
Y 1 = a0 + a1 X
x1 = Y1 − X
3. Load forecast F (t ) + d = x − f1 (T ) − f 2 (W ) − f 3 ( L) − f 4 ( P)
y1 = a1 x1 d = y1 − a1 x1
Plotting a graph of the above relations
D = ∑ d12 = ∑ ( y1 − a1 x1 ) 2
i =1 Grouping these estimates according to
dD the day of the week
= 0 = −2∑ x1 ( y1 − a1 x1 )
4. Conclusion da1 F(t) is known, giving the basic demand
curve.
a=
∑x y XX A = XY
∑x 2


1. FACTS Spectral Expansion Method

- Past load data Predicting a non-stationary process
- Repeat every 24 hours given by an ensemble of sample
2. Steady state - Ensemble of time functions.
series
Pmn = Amn + f1 (Tm ) Bm + f 2 ( Lm )Cm + f3 (Wm ) Dm + .....

3. Load forecast
Pmm (t ) = Pw (t ) + Pd (t ) + pmn (t )
nd
1
Pw (t ) =
nd
∑P
n =1
mn (t )

1 nw
Pd (t ) = ∑ Pmn (t ) − Pw (t )
4. Conclusion nw n =1
K 1
pmn (t ) = ∑ a b f k (t ) + e(t )
k k
2

k =1


1. FACTS Scaling a Standar Load

- Using standar load curve

2. Steady state - The predicted load can be obtained by multiplying the predicted ratio

r (n+k) by the corresponding value of the load on the standard load curve.

3. Load forecast

1− x 3 Four quater hourly periods
r( n + k ) =
1 − x4
∑r
m=0
n−m x n
x: varies between zero and unity
4. Conclusion


1. FACTS Loss of load probability

n  i
p ( xi ) =   q (1 − q ) n −1
n  n!
i   =
2. Steady state r  ( n −r )!r!
Problen:

A
3. Load forecast  3 GENERATOR
 Each 50MW
B
 Probability of failure 0.01
4. Conclusion
C  Failure independently

Find probability distribution of generator capacity ?


1. FACTS Generating probabity distribution

2. Steady state
CAPACITY(MW) PROBABILITY
0 0.000001
50 0.000297
100 0.029403
3. Load forecast 150 0.970299

n  i
p ( xi ) =   q (1 − q ) n −1 n  n!
i    =
r  ( n − )!r!
r
4. Conclusion


1. FACTS Conclution

2. Steady state  The flexibility and adaptability of these new techniques indicate
that they will become part of the tools for solving power quality
problems in this increasingly complex electrical environment.

3. Load forecast

 The implementation and use of these advanced techniques
needs to be done with much care and sensitivity. They should

4. Conclusion not replace the engineering understanding of the electromagnetic
nature of the problems that need to be solved


1. FACTS

2. Steady state

3. Load forecast

NHÓM 9
Nguyễn Anh Toàn-1002525028
4. Conclusion Lê Minh Tùng-1002525033
Huỳnh Ngọc Nhẫn-1002525017

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