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A Healer Reinforcement Approach to Smart Grid Self-Healing by Redundancy Improvement
Alireza Shahsavari, Alireza Fereidunian, Hamid Lesani
f School of Electrical and Computer Engineering, University of Tehran, Tehran, Iran.
2 Electrical Engineering Faculty, K. N Toosi University of Technology and School of ECE, University of Tehran, Tehran, Iran.
Abstract- Smart Grid is expected to heal the electricity distribution system to improve its reliability, known as self
healing capability. Self-healing can be performed in system
level (like restoration and local generation), in component level,
or by reinforcing the healer system reinforcement (called as
healer healing). Smart Grid literature chiefly focuses on the
two former approaches; while, the latter has gained less
attention despite merit. A proper healer reinforcement method is expanding redundancy, in both control and protection
subsystems. The redundancy expansion and the consequent
self-healed distribution network is anticipated to express lower
outage times, thus higher reliability and increased social
welfare. This paper investigates the effect of redundancy
expansion on reinforcement of the Smart Grid healer, by
reliability modeling of protection and control subsystems. The
positive effect of the proposed healer reinforcement approach
on the overall Smart Grid reliability is shown on RBTS4, and
the results are discussed then.
Keywords-Smart Grid, Self-healing, Healer Reinforcement;
Reliability Modeling; Redundancy Expansion; Non-Dominated
Solutions.
NOTATION
The notation used throughout this paper is reproduced below for quick reference.
nust. ! Aline
J Atrans. J Abusbar J Lline J Ltrans. J LBusbar J r.line !)
r.trans. !)
r.busbar !)
In!
Life cycle of study;
Number of load points;
Average annual time that the load point i is out of supply (h/yr);
Average load per customer in load point i (kW/cust.);
Number of customers in load point i (kW/cust.); Lines failure rate of section j (f/km.yr);
Transformers failure rate of section j(f/yr);
Busbar failure rate of section j (f/yr);
Length of section j lines (km);
Number of transformer in section j ;
Number of bus bars in section j ;
Average outage time of section per fault in
section j lines (hIt);
Average outage time of section per fault in
section j transformers (hIt);
Average outage time of section per fault in
section j busbar (hIt);
Inflation rate;
Int wfes
wfomm
wfnd
w[C
wfPC
JCRes JCcomm JCind JCPC JCCPC ENS CENS TCENS
TCR TPJ RB
Interest rate;
Residential load coefficient;
Commercial load coefficient;
Industrial load coefficient;
Public customer load coefficient;
Critical public customer load coefficient;
Residential customers interruption function;
Commercial customers interruption function;
Industrial customers interruption function;
Public customers interruption function;
Critical public customers interruption function;
Energy Not Supplied per year (kWh/yr);
Cost of Energy Not Supplied per year($ US/yr);
the Total Cost of Energy Not Supplied during
life cycle of study;
Economic Factor;
the Average Interruption Cost for load point i ($ US/kW);
Total Cost of Redundancy expansion;
Total Planning Investment;
Redundancy expansion Benefit.
I. INTRODUCTION
H IGH reliability requirement is considered as the main challenge in modern grids; specifically in electric power distribution systems which are in charge of delivering
the electrical energy to the consumers. Smart grid satisfies
this reliability requirement this obstacle by the self-healing
capability [1].
A self-healing system uses information, sensing, control
and communication technologies to handle issues and unwanted events by eliminating or minimizing their
disadvantageous effect for maximizing reliability [2, 3].
Self-healing can be performed in system level (like local
generation and capability of automatic fault detection, isolation, and service restoration), in component level, or by
healer system reinforcement which we named it as healer
healing. In [4], we introduced a novel framework for self
healing methodologies.
Healer reinforcement method is developed into wide area approaches. A pragmatic approach is improving its
redundancy, in both control and protection subsystems.
From the Sfstem configuration point of view, the
redundancy improvement leads to achieve a self-healer
distribution network. The consequent self-healed
distribution network anticipated to express lower outage
times, in both frequency and duration of interruptions, thus
higher reliability and increased social welfare.
Reliability requirement specifies the degree of
redundancy enhancement. On the other hand, it is conceivable that overall budget is run over by ting up high degree of ra:lundalt pcths. Thus, it is necessary to do a compromise between reliability requirement and investment
of redundancy expansion. Economically, the utility cost will
generally increase as consumers are provided with higher
reliability. On the other hand, the consumer costs associated
with supply interruptions will decrease as the reliability
increases. The total costs to society will therefore be the sum
of these two individual costs. This total cost exhibits a
minimum and so an optimum or target level of reliability is
achieved.
From the reliability aspect, enhancing the redundancy in
control subsystem is expected to influence on duration of an
interruption and by enhancing it in protection subsystem expected to influence on both duration and frequency of an
interruption. The redundancy enhancement in control
subsystem decreases SAIDI (System Average Interruption
Duration Index) and in protection subsystem decreases both
SAIFI (System Average Interruption Frequency Index) and
SAIDI.
All in all, healer reinforcement approach by using of
redundancy approach possesses some technical and
economical benefits. For instance, improving overall
reliability indices and decreasing total cost of energy not supplied. However, it incurs more installation cost
maintenance. Hence, it is necessary to economically analyz; the healer reinforcement by redundancy approach.
In [3], reliability models for protection and control
subsystems are presented and different redundancy schemes
are checked. However the impact of redundancy expansion
?n overall reliability did not discussed. In [4, 5], redundancy
m some parts of the protective system is examined and
A.Abbarin and Fotuhi-Firuzabad extended a Markov model
and examined redundancy and protective components
effects. In [7], a technical novel framework is introduced for
redundancy approach in both control and protection
subsystem.
This.
paper .investigates the effect of redundancy
expansIOn on remforcement of the Smart Grid healer, by reliability modeling of protection and control subsystems. The positive effect of the proposed healer reinforcement approach on the overall Smart Grid reliability is shown on RBTS4. The effect of redundancy expansion is checked in both subsystems individually on RBTS4. Also the economical and technical effects of redundancy expansion on subsystems are investigated and best solution is selected by using non-dominated solution, the results are discussed then. In section 2, by modifying these models different redundant paths have been defined. Next in section 3 reliability achievements of implementing redundanc; approach has been presented and possible redundant sets have been introduced as a Non-Dominated solution and final redundant set has been selected through max-min approach.
2
II. METHOD
A. Research Methodology
For evaluating the overall smart grid reliability and the
positive effect of redundancy expansion on reinforcement of
the Smart Grid healer, the reliability of protection and
control subsystems should be modeled. Reliability modeling
for protection and control systems and different redundant
schemes are presented, in section 2.3.
Figure. l shows the flowchart of the overall and load point
base reliability evaluation. In this flowchart, ARPM and
ARTM represent Auto-Restoration Probability Matrix and
Average Restoration Time Matrix, respectively. ARPM is
calculated by conditional probabilities and depends on the
allocated automatic and manual switches, protection devices
and probability of their successful operation [8]. In [3]
ARPM is calculated by using RadPow software base on
event tree, while in this article, reliability evaluations are
simulated in a home developed program. ARTM is
calculated by conditional probability and depends on
switching time and the calculated ARPM. Redundancy
influences the values of protection and control block in the
flowchart; therefore, redundancy affects the system reliability.
Feeders' Evaluation
Figure.I.Flowchart of the reliability evaluation
B. Problem Formulation
As mentioned before, the economical and technical
effects of redundancy expansion on subsystems are
investigated in this paper by using prepared models and
evaluation flowchart. For investigating technical impact of
redundancy expansion some reliability indices are
examined, for instance, SAIFI, SAIDI, CAIDI, AENS and
ASAI, which are expressed in [9, lO]. To evaluate the
economical the impact of the proposed healer reinforcement
by components redundancy expansion on the system
reliability, total cost of energy not supplied (TCENS) during
the life cycle is examined, which is expressed as:
ny LP TCENS = L L CENSi x (EF) n (1)
n=l i
Where n is the number of years, i is the load point numbers and EF is the economic factor for evaluation of present worth/cost factor which changes the cost of time
study to current cost. The CENSi and the EF are written as:
AlC-(U) CENS = ENS x ! ! ! ! Ui
E F = _1
_+
_I
_n.:....f
1 + Int
(2)
(3)
(4)
In equation (2), AICi(Ui) is computed by equation eq.(5), j is the faulted section.
AICi(Ui) = wfesICRes(Ui) + wfomm I Ccomm (Ui)
+w{nd ICrnd(Ui) + wfc ICpc(Ui) + wfPC ICcpc(UJ (5)
The IC represents interruption cost function for each kind of consumers. In (6), the total cost of redundancy approach and upcoming costs is computed. Also by using (7) benefit
of implementing redundancy in distribution system is
computed.
TCR = TCENS + TPI
RB = TCRnon-redundant - TCRredundant
C. Reliability Modeling for Redundancy
(6)
(7)
Figure.2 shows smart grid subsystems including control,
protection and IT infrastructure interacting with legacy
system [12]. Protection and control systems in contingencies
conditions are responsible for isolating faulted zone and
supply restorable zones, for minimizing the duration of
interruption and to limit the impact of fault [7, 11], thus the
overall smart grid reliability depends on successful
operation of protection and control systems. In this section, protection and control subsystems reliability models are
presented and different redundancy extensions are
implemented.
Control and Protection Power Distribution System System (The Legacy System)
IT Infrastructure of Smart Grid Figure.2. Smart Grid Sub-systems [12]
J) Protection System Reliability Modeling
Protection system is the most important factor to the
secure operation of the electrical power networks, induding
3
di stri buti on systems. A rei i ci:lI e prota::ti on system improves the overall network reliability. The probctlility for a prota::tion system to operate responding to a fault depends on the rei i aI:li I i ty of its components One etfa::ti ve approcrll for improving the prota::tion system's relial:lility is
enhancing its ra::tundancy.
a. Feeder Protection (Breakers) Reliability Modeling
For a normally dosa::l breaker the operaing and failure states are [3]:
1- Passes currents from in its closed state; 2- Opens successfully when requested to do so; 3- Fails to open when requested to do so; 4- Opens inadvertently when not requested. State 1 and 2 are the desirable conditions and 3 and 4 are
the unwanted ones. 1 and 4 refer to dependability and
security of the protection system [13]. In [9] these two aspects of reliability in redundant protections system have
been discussed.
Figure3 represents the protection system in term of its
components block diagrams. These blocks related to feeder
protection in which the digital relay unit (DRU) includes the
electronic circuits of signal conditioning and the digital
processing relay system. The auxiliary relay unit (ARU)
contains trip relay (TR) and the associated power supply
unit (PSU).
1
................................ : PR :ARt:j ..
1---F"Ti-.
Figure.3.Block diagram of the base protection scheme, adapted [3]
When a permanent fault occurs, all components should
operate correctly, i.e., failure in each block causes fault in
protection operation. From the reliability point of view, all
components are series and the reliability block diagram
(RBD) of the basic protection scheme is shown in figure.4.
Figure.4. Reliability block diagram of the basic protection scheme.
In the basic protection scheme, any failure in each block
causes malfunction in protection operation. Consequently,
back up protection operates and both faulted and faultless
feeders experience outage. The probability of malfunction in
protection scheme reduces by redundancy enhancing in
components. In order to see different redundant protection schemes, for preventing from unnecessary repetition,
figure.5 shows only sample of reliability block diagram
cases. Cases 2-5 comprise one redundant component in
sequence for Breaker, DRU, ARU, and CT.
Case 6 comprises two DRUs and two ARUs which
prepare two paths; the system is operating if at least one
path is functioning. Case 7 has two breakers and two CTs and prepares 4 paths; the system is functioning if at least one
of breakers and one of CTs are functioning. Figure.6 shows
the even tree of case 8, it consist of two DRUs and two
ARUs and prepares 4 paths; the system is functioning if at
least one of DR Us and one of ARUs are functioning. Case 9
and case 10 are equal to (n-l) index of reliability, case 10 in
components layer and case 9 in system layer. Assuming the
failure events of the components blocks are independent,
also the probability of each basic component operation is
equal to tablel and the probability of each redundant
component operation is 0.95% of the basic component.
Table2 shows the probabilities of base case and redundant
protection cases operation.
Fault
CT
Case 6
Case 8
Non-redundant Protection system 1
Non-redundant Protection system 2
Case 9
Case 10
Figure.5. Reliability block diagram of different
redundancy schemes in protection systems
B
o
i ARUI i ARU2 i 0 i
Outcome
i->'---:-----: I: Trips 2: Trips
3: Fails to Trips
-"";""----i 4: Trips 5: Trips
o 6: Fails to Trips
I-'-F _--+-__ +-_-1 7: Fails to Trips F _-+ __ +-_-+ __ +-_-i 8: Fails to Trips
L..:...F __ ---'----'---""'"""---'-----' 9: Fails to TrillS
F
Figure.6. Event tree of case 8
b. Fuses Reliability Modeling
Fuses in automated distribution systems have direct
impact on systems reliability. Fuse in low voltage branches
decreases duration and frequency of interruptions. From the
reliability point view, fuse is independent device and its
reliability block diagram is one block.
2. Control System Reliability Modeling
Distribution automation and control systems consist of
three functions; line's facilities or secondary substations,
primary substations, and distribution control centers (DCC)
4
[3, 14, 15, 17]. Communication systems are non-negligible
and
requisite infrastructures for data exchanges in these three
layers [16]. In this paper, the reliability of automation
control systems is investigated into two layers, local control
system and central control system.
The central control system performs functions, including
control and monitoring of all substation equipments,
accumulate and process local controls data, dispatch control
commands and receive results. The local control system
consists of remote terminal units (RTUs), these devices
exquisite various types of information, execute commands
from the central center and reporting status after
implemented commands to the central center.
A rei i cD! e control systan improves the overall smai gri d rei icDi I ity. The probabi I ity for the control systan to operate responding to a commald depends on the reliability of its
components. One effective approcdl for improving the
control systan rei i cDi I i ty is enhalo ng its redundalCY. Figure.7,8 represents control system consists of local and
central layers in term of component block diagrams. Central
control includes Power Supply Unit (PSU), Central
Processing Unit (CPU), Memory Unit (MU), controller and
Communication Interface (CI). The main components in
local control system are Switching Device (SD), battery and
charger or Power Supply Unit (PSU), power actuator (Drive), Current transformer and Voltage Transformer
(CTIVT), Remote Terminal Unit (RTU) , Fault Passage
Indicator (FPI) and Communication Interface (CI). The
RTU includes central processing unit (CPU), Input / Output
interface (I/O). A typical RTU possess eight digital inputs
(D!) and eight digital outputs (DO), also may equipped with
six analog inputs [3, 11, 14, 15].
Ccntral Computer [ cPu I [ Controller I
I Power Supply I Urnt I Communication I Interface
(a)
Figure.8.(a). Block diagram of the base central control system
(b). Block diagram of the base local control system; adapted [3, II, 14, 15]
In order to achieve a proper operating control system,
each component in both local and central control layers
should operates correctly, i.e., any individual event that
causes failure of each component in local/central control
layers fails the local/central control system. From the
reliability point of view, all components are connected in
series. Assuming failure events are independent, equations
(8) and (9) represent the probabilities of non-redundant local
and central control operation.
P(cent ral cont rol) = P(PSU) P( Cont roller) ' P( CPU) . P(MU) . P( CI)
P(local cont rol) = P(SD) . P( CT) ' P(PSU) P(FPI)
(8)
. P(PA) . P(RTU) . P( CI) (9)
a. Central Control Reliability Modeling
In order to see different redundant central control
schemes, figure.9 shows reliability block diagrams of four
different redundancy schemes in central control system. For
preventing from unnecessary repetition, figure4 shows only
sample of reliability block diagram cases. Cases 2-6 comprise one redundant component in sequence for CI,
PSU, CPU, MU and controller.
Case 7
Case 8
Central control system 1
Central control system 2
Case 9
Case 10
Figure.9. Reliability block diagram of different
redundancy schemes in central control systems
Case 7 comprises two CPUs, MUs, and controller which
prepare two paths, and Case 8 is alike case 2, which
prepares 8 paths; the system is functioning if at least one of
paths is functioning. Case 9 and case 10 are equal to (n-l)
5
index of reliability, case 10 in components layer and case 9
in system layer. Assuming independent failure events for the
components, also considering the probability of each
component operation is equal to table 1 and the probability
of redundant component operation is 0.95% of the basic
component. Table 2 shows the probabilities of base case and
redundant cases operation.
b. Local Control Reliability Modeling
In order to see the effect of redundancy expansion in local
control system, figure. 10 shows reliability block diagrams of
four different redundancy schemes in local control system.
Also case 2-6 comprise one redundant component III
sequence for CI, PSU, RTU, power actuator, and FPI.
Local control system 1
Local control system 2
Case 9
Case 10
Figure.lO. Reliability block diagram of different
redundancy schemes in local control systems
As discussed in protection and control modeling, table2
shows the probabilities of base and redundant local control cases operation, assuming independent failure events for the
components, also considering the probability of each
component operation is equal to table 1 and the probability
of redundant component operation is 0.95% of the basic
component.
Tablel. Components reliability, adapted [3]
Control system Protection system
Central Control Local Control
Component Reliability Component Reliability Component Reliability
CT 0.98 5 PSU 0.995 SO 0.990
DRU 0.990 CPU 0.994 PSU 0.995
ARU 0.98 8 MU 0.993 PA 0.992
B 0.993 Controller 0.98 7 CTIVT 0.990
CI 0.997 FPI 0.990
RTU 0.993
CI 0.997
Table2 antICipates the redundancy improves the
probability of successful protection and control operation.
Comparison between case 6 and 8 of protection system (or
case 7 and 8 in control system) illustrates redundant
components connection is extremely important, parallel
connections make more reliable than series. As expected,
redundancy in components layer is more reliable than the
redundancy in system layer, case 9 and 10 indicate that.
Table2. Probabilities of each considered cases operation
Protection System Control System
Case Feeder Fuse
Central Local Control
Protection Control
Base 0.956704 0.90 0.966431 0.943378
Case 2 0.963066 0.91 0.969185 0.946066
Case 3 0.965792 0.92 0.971021 0.947859
Case 4 0.967610 0.93 0.971940 0.949651
Case 5 0.970337 0.94 0.972858 0.950547
Case 6 0.975597 0.95 0.978366 0.952340
Case 7 0.976789 0.96 0.98 7800 0.959456
Case 8 0.976802 0.97 0.990486 0.961405
Case 9 0.990442 0.98 0.991534 0.980680
Case 10 0.997310 0.99 0.998027 0.996561
III. Case Study
A. Example Case
The effect of the proposed healer reinforcement approach
on the overall Smart Grid reliability is shown on RBTS4.
The RBTS has 5 buses (Bus2-Bus6), two buses (Bus2, Bus4) are defined as distribution network. Figure. 1 1 shows
RBTS4 which has three supply points, seven feeders, 38
load points, 4770 customers, and the peak and average load
40 MW and 24.58 MW, respectively. Customers data and
lines length are taken from [18]. Table3 shows components
and lines failure rates and average repair or replacement
time per failure. For evaluating the reliability, auto
switching time and manual switching time are assumed 40 seconds and l.5 hour, respectively. Life cycle of study is
considered 25 years, also inflation rate and interest rate 6%
and 7%, respectively. Figure.I2 shows the Ie s of different customer types.
S3W lIkV I
control facilities prices are exist, component's reliability
cost curve is an upward concavity exponential function [9,
10], Thus the reliability-cost curve for subsystems
consequence of components reliability-cost curve and can be
calculated.
Figure15 shows total cost of redundant planning in central
and local control, as shown minimum TCR consequences of
case 8 for both local and central control, it shows that by
implementing more redundant for instance cases 9 or 10,
planning costs increases more than decreased TCENS.
1.826
1.824
1.822
Vl 1.82 1.818 '" 1.816
1.814
1.812
X 106
L81-..J.--=-,"-- Case 3 Case I
Case 1 ease2 ca';"3 3 -:C"C:C
'4i-
C:;C
"'='5
C:;C
""=6S$s;'::::::::'c Case 5 \ CO\\tt"O
\ , .,:dunda High Redundant LOCal C::, Case 8 Case 9 Case 10 Case 9
Figurel5. Total cost of redundancy of redundant control cases
C. Impact of redundancy in protection system
This section presents impact of redundancy in protection
system base on explained modeling in part "C" of section II.
For investigating the positive impact of redundancy in
protection system on network, the control system is modeled
as the base case. By comparing 100 possible cases
determines that the CENS is reduced about 8% also the
SAID! is reduced about 10%, as shows in figure 16, 17.
7.9
7.7
7.6 8 7.5 U7.4
7.3 7.2 /- Case I ease 2 Case 3 cas;'gh Case 5 Case 6 Cac 7 Case 8 Case 9 Case 10 0.98 I ' Re