Energy and Power Engineering, 2013, 5, 717-721
doi:10.4236/epe.2013.54B139 Published Online July 2013 (http://www.scirp.org/journal/epe)
Emergency Control Strategy Based on Multi-agent
Theory under Blackout*
Bin Sun1, Ming Liu1, Luofang Zhu1, Nian Liu2, X ia o yan Qiu2, Zhe Zhuang2
1Guizhou Power Grid Corporation of Dispatch Control Center, Guiyang, Guizhou, China
2School of Electrical Engineering and Information Sichuan University, Chengdu, China
Received March, 2013
ABSTRACT
The multi-agent theory is in troduced and applied in the way to strike the control amount of emergency con trol accord-
ing to stability margin, based on which an emergency control strategy of the power system is presented. The multi-agent
control structure which is put fo rward in this article has three layers: system agent, areal agent and local agents. System
agent sends controlling execution signal to the load-local agent according to the position and the amount of load shed-
ding upload from areal agent; The areal agent judges whether the power system is stable by monitoring and analyzing
the maximum relative power angle. In the condition of instability, determines the position of load-shedding, and the
optimal amount of load-shedding according to the stability margin based on the corrected transient energy function,
upload control amount to system agent; local-generator agent is mainly used for real-time monitoring the power angle
of generator sets and uploading it to the areal agency, local-loads agent control load by receiving the control signal from
system agent. Simulations on IEEE39 system show that the proposed control strategy improves th e system stability.
Keywords: Multi-agent; Corrected Transient Energy Function; Emergency Control; Stability Margin
1. Introduction
With the development of economy, the growing of the
load demand, the increase of grid scale, the continuous
development of the regional interconnection and long-
distance transmission of electricity markets, the grid is
long-running at the limit state, the stability margin is
getting smaller and smaller. When the grid is affected by
the large disturbance, it may cause grid instability, and
longtime power off, even network splitting [1-4]. Emer-
gency control can reduced the extent of the damage to a
minimum after the grid is affected by the large distur-
bance, so, it is an important measure to maintain system
stability [5-8].
In the field of artificial intelligence, Multi-Agent has
good characters of autonomy, reactivity, initiative and
social. It is contributing to emergency control to change
from “Off-line pre-decision-making, real-time match.” to
“Real-time decision-making, real-time execution”. Lit-
erature [9] applies the Multi-agent technology to the
power system black start. Reference [10] proposed the
method changed from centralized management to dis-
tributed coordinated management through the Multi-
Agent system approach. Article [11] shows the Multi-
criteria hierarchical emergency control system is condu-
cive to independent autonomous effect between the lay-
ers.
In the literature, multi-agent theory is introduced into
the way based on the stability margin to strike control
amount of the emergency control, proposes emergency
control strategy based on multi-agent technology[12-15],
the multi-agent control organizational structure has three
layers: system agent, areal agent and local agents.
2. Multi-agent Control Organizational
Structure
The multi-agent control org anization al structu re has three
layers: system agent, areal agent and local agents. The
primary responsibility of system agency is receiving the
data of load shedding position and the amount of load
shedding an d to issue a contro l signal to local load Agent;
the main responsibility of areal agent is to received and
processed the data quickly and accurately, and to deter-
mine load shedding position and the amount of load
shedding; the primary responsibility of local agency is to
real-time detecting the state of each generator group, to
transmute real-time testing data is to the regional agency,
and to control the load. The multi-agent control organ-
izational structur e is as shown in Figure 1.
*The project supported by GuiZhou Power Grid Corporation (12H-
0594),Technology Project of Science & Technology Department of Si-
chuan Province (No.2011GZ0036 )

B. SUN ET AL.
718
3. Emergency Control Strategy
In the normal state the electromagnetic torque of the ge-
nerator output keep balanced with the mechanical torque
of the prime mover Input, after large interference, Gen-
erator set power becomes imbalance, it changes the gen-
erator power, the speed and the relative angle between
the rotors. If the generator relative motion gradually in-
creases, the generator will be out of Step, even the sys-
tem will become unstable. So, the stability of the power
system is closely related to generator angle.
Because the transient stability of the system usually
has relationship with maximum relative angle max

between the generator rotor, areal agency uses the max-
imum relative angle as the standard to determine whether
the system is instability, detects the op eration state of the
power system according to the angle data local generator
agent upload, and strikes the optimum amount of load
shedding by stability margin based on the modified en-
ergy function. Control strategy shown in Figure 2.
Figure 1. The multi-agent control organizational structure.
Figure 2. Multi-agent control strategy.
3.1. System Stability Analysis
According to maximum relative angle max

between the
generator rotor, In this paper, using the maximum rela-
tive swing angle method determines system stability.
Defining transient stability constraint conditions is:

2
2
,
(( ),)max( )( )0
eiei
ij
JTuT T 
e

 

 (1)
e is the integral end moments, T

is transient sta-
bility angle threshold. In the actual system, it can be se-
lected 180-270 based on experience.

is pending mul-
tiplier. It can be determined in accordance with the fol-
lowing provisions:
When


22
,
max()(), =0
ie ie
ij TT
 



When


22
,
max()(), =1
ie ie
ij TT






(( ),)
e
J
Tu

can be regarded as a characterization sys-
tem transient stability indicators.
For the performance index function, define new simu-
lation termination value

, this value determines the
end time , determine it according to the following
rules. m
T
If, 0
22
,[,]
max{[ ( )( )]}
eie je
ijtT TTT





when
0
2
,[,]
max{[()()] }
eie je
ijtT TTT

 
across termination value 2

at the first time，the first
moment is taken as .
m
T
If,
0
22
,[,]
max{[ ( )( )]}
eie je
ijtT TTT 2






take it as
=
me
TT
3.2. The Optimum Load Shedding Amount
Based on Modified Energy Function
After System is disturbed, For System leading unit A and
the remaining sets B, consider the eq uations of motion of
the rotor.
1()
11
()
i
Amiei
iA
AT
mA eACOI
AT
M
PP P
MM
PP P
MM




COI
(2)
1()
11
()
i
B
mi eiCOI
iA
B
mB eBCOI
BT
M
PP P
MM
PP P
MM




T
(3)
The dynamic equation betwee n generators A and B is:

B. SUN ET AL. 719
()(
eq eq
eqmA eAmB eB
AB
AB
MM
d)
M
PP PP
dt MM
P



(4)
And =AB

 , multiply

at both side, consider
the relationship =

 .
2
1
2
2
1
2
sep
ae sep
t
eq tAB
t
t
eq AB
tt
d
MP
dt
d
MP
dt
const








 (5)
Defining corrected transient energy function is
2
1
2sep
KE PE
eq tAB
VV V
M
Pd






 (6)
A sudden change in the operational status of the sys-
tem did not happen next time, the correction energy
function of the system is conserved.
According to the definition of the energy margin, the
energy difference between the critical energy and the
energy of system at the fault clearing time is energy mar-
gin.
cr cl
VV V (7)
2
min 2
() ()
(()(() ()
r
cl clr
CTEM TCTPE B
CTPE tCTKE tCTKET

 ))
(8)
The first term is critical energy, the second term is the
energy at the fault clearing time. For stable fault trajec-
tory, General system trajectory will pass through zero, so
min 2
()0
r
CTKET 
2
()
() (()( ))
r
cl cl
CTEM T
CTPEBCTPE tCTKE t  (9)
And
2
()
() ()
r
cl cl
CTEM T
CTPE tCTKE t  (10)
The mean the ability that the system
absorb effective after the fault is cut at the mo-
ment of . This energy can be expressed as:
()
cl
CTPE tCT
cl
tKE
1
2
1
min 1
()
((())(()))(()(
(() ())
cl
n
i cli clclcl
i
cl r
CTEM t
ttt ttt
CTKE ttCTKET
 



))
(11)
The
1
2
1(( ())( ()))( ()())
n
i cli clclcl
i
tttttt  

 

means the incremental of system transient correction
energy at the moment of to ,
cl
ttcl tt
)CTKEmin1 (( (
cl r
CTKE tT))


means the system absorb effective after the fault
is cut at the moment ofCTKE
+
cl
tt

. For the unstable trajectory,
min1 is not zero. So, the stable trajectory sta-
bility margin expressed as:
()
r
CTKE T
2
1
2
1
min 1
()
((())(()))(()(
(()())()
r
n
i cli clclcl
i
clr cl
CTEM T
tttttt
CTKE ttCTKETCTKE t
 


 
))
(12)
In fact, it uses the partly flat characteristic of correc-
tion potential interface. If consider is very small, the
transient correction potential of both 1
e and is al-
most equal. The utility improved template completely
avoiding pseudo fault points. For the stable failure closes
to instability, we can strike a fault stability margin just
after two systems simulation.
tB
The modified potential energy function to overcome
the nonlinear of traditiona l hybrid method of the stability
margin curve, the curve of the system stability margin is
smooth at different resection amount after stabilization
measures action.
Optimal amount of load shedding
Based on the characteristics of the energy margin with
the amount of load shedding curve, we can get stability
margin and 1 according to fault simulation and
energy function analysis at two kind amount of load
shedding 0 and 1. Strike the active load shedding
capacity limit which meet system transient stability by
using the energy margin interpolation law.
()CTEF P
PP
1
1
01
()
() ()
cr
CTEMPP
PP
CTEM PCTEM P

  (13)
Only when the system occur instability failure, do the
emergency control measures be used, therefore, accord-
ing to the margin curve linear features in the unstable
region, the amount of load resection cr can be stroked
by unstable margin interpolation of different resection
amount o f and .
P
0
P1 P
4. Analysis of Examples
In order to verify the effectiveness of the proposed me-
thod, simulate on IEEE39 system, System as shown in
Figure 3.
Assume that the fault is a three-phase fault, fau lt loca-
tion is selected at generator bus or load bus bar. Simula-
tion results as shown in Table 1.
From the simulation results, the control measures can
ensure the stability of the system, the multi-agency the-
ory in power system emergency control has a positive
effect on system stability.

B. SUN ET AL.
720
Figure 3. 10, 39-bus system diagram.
Table 1 result of load shedding scheme in IEEE39 sy ste m.
Fault
location Resection line Critical clearing time /s Actual fault clearing time /s Shutdown generator
Load shedding program
（Load node number,
The amount of load shedding）
results of the
control measures
3 3-4 0.27~0.28 0.29 37 18；-1.0324-j0.2765 Stable
6 5-6 0.16~0.17 0.24 31 4；-0.6244-j0.2856 Stable
10 10-13 0.21~0.22 0.24 32,39 12；-0.4332-j0.1004 Stable
15 14-15 0.19~0.22 0.23 32,37 15；-0.7420-j0.2519 Stable
17 17-18 0.22~0.23 0.33 37 18；-1.2654-j0.5750 Stable
23 22-23 0.24~0.25 0.28 36 22；-0.8861-j0.4021 Stable
5. Conclusions
In the literature, multi-agent theory is introd uced into the
way based on the stability margin to strike control
amount of the emergency control, proposes emergency
control strategy based on multi-agent technology, the
multi-agent control organizational structure has three
layers. It is achieved systems state data real-time interac-
tion, show multi-Agen t has good ch aracters of autonomy,
reactivity, initiative and social. It is contributing to
emergency control to change from “Off-line pre-deci-
sion-making, real-time match.” to “Real-time decision-
making, real-time execution”.
Simulations on IEEE39 system show that the proposed
control strategy improves the system stability.
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