The Journal of Engineering Research (TJER), Vol. 15, No. 1 (2018) 01-13

DOI: 10.24200/tjer.vol15iss1pp1-13

Effect of Considering Transmission Losses in Economic
Dispatch – A Case Study of Oman’s Main Interconnected

System

M.H. Albadi*, F.N. Al Farsi, N. Hosseinzadeh, and A. H. Al Badi

Department of Electrical and Computer Engineering, Sultan Qaboos University, P.O. Box 33, Muscat 132, Sultanate of

Oman.

Received 18 September 2016; Accepted 26 January 2017

Abstract: Economic dispatch is an important optimization problem in power system planning. This
article presents an overview of the economic dispatch formulation, its objective, loss coefficient
determination, and a case study. In the case study, different scenarios of the economic dispatch in the
main interconnected system (MIS) of Oman were considered to highlight the importance of
considering losses in the optimization process.

Keywords: Economic dispatch; Loss coefficients; Power systems; Main interconnected system.

دراسة حالة الشبكة الرئيسة -لألمحال االقتصادي التوزيع الفاقد على احتساب تأثري

املرتبطة يف سلطنة عمان

،ف. ن. الفارسي، ن. حسني زاده، أ. ح. البادي*لبادي ا .م.ح

املقالة على تقديم حملة يعد التوزيع االقتصادي لألمحال هواملشكلة االهم يف ختطيط نظام الكهرباء. تعمل هذه :امللخص

عامة عن صيغة االتوزيع االقتصادي لألمحال وحتديد هدفها و معامل الفقدان و دراسة حالة. و يتم اخذ االعتبار يف دراسة

احلالة هذه، سيناريوهات خمتلفة للتوزيع االقتصادي لالمحال يف النظام الرئيسي املرتابط يف عمان و ذلك لتسليط الضوء

احتساب الفواقد املرتتبة على عملية التحسني.على أهمية

.الشبكة الرئيسة ،أنظمة الطاقة ،معامالت الفقدان،: التوزيع االقتصادي املفتاحية الكلمات

* Corresponding author’s e-mail: mbadi@squ.edu.om

M.H. Albadi, F.N. Al Farsi, N. Hosseinzadeh and A. H. Al Badi

Symbols and Abbrevations

IPP : Independent Power Producer

LFC : Load Frequency Control

MIS : Main Interconnected System of Oman

OETC : Oman Electricity Transmission Company

OPWP : Oman Power and Water Procurement Company

SAOC : Closed joint stock company

𝑎𝑗 , 𝑏𝑗 , & 𝑐𝑗 : Coefficients of the quadratic cost function

𝐵, 𝐵0, & 𝐵00 : Coefficients of the B-loss formula

𝐹𝑙
𝑡 : Apparent power flowing through transmission line l during the interval t

𝐹𝑙
𝑚𝑎𝑥 : Upper limit of the power flow along line l

𝐹𝑐𝑜𝑠𝑡 : Total operating cost

𝐹𝑗 : Operating cost of generation unit j

𝑁𝑔 : Total number of generation units in the power system

𝑃𝐷 : Total power demand

𝑃𝑗 : Output power of generation unit j

𝑃𝑗
𝑚𝑖𝑛 : Minimum output limit of unit j

𝑃𝑗
𝑚𝑎𝑥 : Maximum output limit of unit j

𝑃𝐿 : Total power losses

𝑆𝑗
𝑡 : Spinning reserve contribution of unit j during time interval t

𝑆𝑅𝑡 : System spinning reserve requirement for interval t

Effect of Considering Transmission Losses in Economic Dispatch – A Case Study of Oman’s Main Interconnected System

1. Introduction

Power systems have different types of
generation facilities and load profiles. To
maintain the stable operation of power systems,
the aggregated output of online generation units
and the total demand must be balanced in real
time. When the net generation is higher than the
net demand, the system frequency increases and
vice versa (Zhu 2015). The total loads in power
systems experience different chronological
variations: seasonally, on weekends and
weekdays, and within each day (during peak
and off-peak hours) (Albadi and El-Saadany
2011). Variations in demand occur even on a
second-by-second basis. To cope with these
chronological variations, the outputs of the
different online generation units experience
cycles of operation according to the forecasted
net load.
Power systems have different operational
planning time frames: unit commitment (weeks
and days) (Padhy 2004), economic dispatch
(hours) (Gaing 2003), and frequency regulation
(minutes and seconds) (Kumar and Kothari
2005). Unit commitment is the optimum
selection of online dispatchable generation units
to satisfy different operating constraints. Once
online generation units are selected, economic
dispatch is used to schedule the output of each
unit to follow hourly load variations. It is worth
mentioning that different utilities conduct
economic dispatch at different time intervals.
Some utilities have an hourly dispatch while
others consider shorter dispatch intervals.
During real-time operation, the mismatch
between demand and scheduled generation is
covered using regulation services. These include
turbine-governor control and load frequency
control (LFC).

Figure 1 shows a system that consists of Ng
number of generating units serving an aggregate
electrical load. Since the combined capacity of
these units is normally higher than that of the
load, there exists an infinite number of output
combinations to satisfy the load. The objective of
the economic dispatch is to determine the output
of each generation unit so that the total
operating cost is minimized while relevant
constraints are satisfied (Zhu 2015). Other
objectives of the economic dispatch include the
minimization of emissions, the maximization of
profit by reducing the total cost, and the
maintenance of system stability and security.

If the transmission network of the power
system under study is considered, the total

demand that the generation units must satisfy
includes transmission losses (George 1943). The
value of transmission losses is a function of the
economic dispatch decision variables, which can
be determined using power-flow techniques
(Saadat 1999). However, transmission losses can
be included in the optimization procedure using
different methods. One of these methods is the
loss coefficient technique.
The main contributions of this article includes
modeling and simulating the main inter-
connected system (MIS) of Oman for economic
dispatch purposes, calculating the loss
coefficients of the system, and including losses in
the economic dispatch of the MIS.
Following this introduction, the article
presents a review of the economic dispatch
formulation in section II. System data are
presented in section III, and simulation results
are discussed in section IV. Finally, the
conclusions are presented in section V.

2. Economic Dispatch Formulation

2.1 Mathematical Formulation of Econo-
mic Dispatch

The objective function of an economic
dispatch problem is to minimize the total
operating cost (𝐹𝑐𝑜𝑠𝑡 ), which is the summation of
individual generation units’ operating/fuel costs
(𝐹𝑗 (𝑃𝑗 )) (Zhu 2015).

𝐹𝑐𝑜𝑠𝑡 = ∑ 𝐹𝑗 (𝑃𝑗 )
𝑁𝑔
𝑗=1

(1)

The operating cost of each generation unit is
given as a function of its output power (𝑃𝑗 ) and
is modeled as a quadratic function.

𝐹𝑗 (𝑃𝑗 ) = 𝑎𝑗 + 𝑏𝑗 𝑃𝑗 + 𝑐𝑗 𝑃𝑗

2 (2)

where 𝑎𝑗 , 𝑏𝑗 , and 𝑐𝑗 represent the cost

coefficients of the jth generating unit,

𝑃𝑗 represents the real output of the jth generating

Boiler/Burner Turbine Generator Fuel

PLoad

Figure 1. Generating units serving an electrical

load.

M.H. Albadi, F.N. Al Farsi, N. Hosseinzadeh and A. H. Al Badi

unit (in MW), and 𝑁𝑔 is the total number of
generation units in the power system under
study. These cost coefficients can be obtained
from the heat rate data of generation units at
different operating points and the price of fuel.

The optimization problem has the following
constraints:
 Power balance constraints

∑ 𝑃𝑗
𝑁𝑔
𝑗=1

= 𝑃𝐷 + 𝑃𝐿 (3)

where 𝑃𝐷 is the power demand and
𝑃𝐿 represents the power losses.

 Generation unit limit

𝑃𝑗
𝑚𝑖𝑛 < 𝑃𝑗 < 𝑃𝑗

𝑚𝑎𝑥 𝑗 = 1 … 𝑁𝑔 (4)

where 𝑃𝑗
𝑚𝑖𝑛 and 𝑃𝑗

𝑚𝑎𝑥 are unit j minimum and

maximum limits, respectively.

 Spinning reserve requirement
∑ 𝑆𝑗

𝑡 ≥𝑛𝑗=1 𝑆𝑅
𝑡 𝑡 = 1 … 𝑁 (5)

where 𝑆𝑗

𝑡is the spinning reserve contribution

of unit j during the time interval t, and 𝑆𝑅𝑡 is the
system spinning reserve requirement for interval
t. 𝑆𝑗

𝑡 can be expressed as 𝑃𝑗
𝑚𝑎𝑥 − 𝑃𝑗

𝑡 where 𝑃𝑗
𝑡 is

unit j output during time t.

 Network security constraints (voltage limit
constraints, e.g. +/- 10% in the MIS (OETC
2010).

 Line capacities

𝐹𝑙
𝑡 ≤ 𝐹𝑙

𝑚𝑎𝑥 ; 𝑡 = 1 … 𝑁𝑇 (6)

where 𝐹𝑙
𝑡 is the apparent power flowing

through transmission line l during the interval t,
and 𝐹𝑙

𝑚𝑎𝑥 is the upper limit of the power flow
along line l.
It is worth mentioning that these limits are
thermal limits of the transmission lines and can
be found in OETC capability statement (OETC
2014.

2.2 Loss Formula
When transmission line distances are small,

transmission losses can be ignored and the
optimal dispatch of generation units can be
achieved without considering the transmission
system losses. However, in large interconnected
systems, transmission losses play a major role in
the optimal dispatch of generation units. Hence,
the transmission line losses of large networks
need to be considered in the optimal dispatch of
generation units.

There are several methods by which losses
become part of the dispatch decision. George

was the first to develop the simplest form of the
loss equation (George 1943):

𝑃𝐿 = ∑ ∑ 𝑃𝑚 𝐵𝑚𝑛 𝑃𝑛

𝐾
𝑚=1

𝐾
𝑛=1 (7)

Alternatively,

PL = ∑ ∑ B𝑖𝑗 P𝐺𝑖 P𝐺𝑗
NG
j=1

NG
i=1 (8)

where B𝑖𝑗 and 𝐵mn are called loss coefficients.

Attempts to obtain a more accurate
expression of power system losses were made by
adding linear terms and a constant to the
original expression. These resulted in the B
matrix loss formula, which was introduced in
the beginning of 1950s as a practical method for
the computation of losses and incremental losses
(Wood and Wollenberg 2012). After the addition
of linear terms and a constant to the original
expression, the following loss formula was
obtained:

𝑃𝐿 = 𝑃

𝑇 [𝐵]𝑃 + 𝐵0
𝑇 + 𝐵00 (9)

where

𝑃 is the vector of all generator bus net MW,
[𝐵] is the square matrix of the same dimension
as P,𝐵0 is the vector of the same length as P, 𝐵00
is the constant.

This equation can be rewritten as follows:

𝑃𝐿 = ∑ ∑ 𝑃𝑖 𝐵𝑖𝑗 𝑃𝑗 + ∑ 𝐵𝑖0𝑃𝑖 + 𝐵00𝑖𝑗𝑖 (10)

Alternatively, it can be rewritten as follows:

𝑃𝐿 = ∑ ∑ 𝑃𝑚 𝐵𝑚𝑛𝑃𝑛
𝐾
𝑚=1

𝐾
𝑛=1 + ∑ 𝑃𝑛𝐵𝑛0

𝐾
𝑛=1 + 𝐵00 (11)

There are three main methods for obtaining

the loss formula coefficients (George 1943; Hill
and Stevenson 1968; Yang, Hosseini, and
Gandomi 2012). The first method is the tensor
analysis method (Yang, Hosseini, and Gandomi
2012), the second method is the 𝐴𝑗𝑛 method (Hill

and Stevenson 1968), and the third method is the
Kron-Kirchmayer method, which Kron
developed and Kirchmayer adapted (Abdelaziz
et al. 2008; Saadat 1999; Wood and Wollenberg
2012).

Kron 1951) presented the mathematical
formulation of the tensor analysis method, and
Hill and Stevenson (1968) explained the
mathematical formulation of the 𝐴𝑗𝑛 method.

Furthermore, George (George 1943) explained
Kron-Kirchmayer method. Many researchers
have used the Kron-Kirchmayer method to

Effect of Considering Transmission Losses in Economic Dispatch – A Case Study of Oman’s Main Interconnected System

determine the loss coefficients (Dike, Adinfono
and Ogu 2013; Su and Lin 2000; Yang, Hosseini
and Gandomi 2012). The same method was used
to find the loss coefficients for the system under
consideration, that is, the main interconnected
system of Oman. Once the coefficients were
obtained, it was possible to determine the
economic dispatch. It is worth mentioning that
loss coefficients are load-specific; therefore, they
should be updated for different loading
conditions.

3. Systems Data

The test system (the main interconnected system
of Oman) data were obtained from two sources:
the Oman Power and Water Procurement
Company SAOC (OPWP) (OPWP 2016a) and
the Oman Electricity Transmission Company
SAOC (OETC) (OETC 2016).

3.1 Generation Units
The transmission system is supplied with
electricity generated at eleven gas-based power
stations (open cycle and closed cycle) at Ghubra,
Rusail, Sur, Wadi Al Jizzi, Manah, Al Kamil,
Barka I, Barka II, Barka III, Sohar I, and Sohar II.
In addition, the transmission system is
connected directly to large customers with
generation facilities, for instance, Sohar
Aluminium, PDO, Sohar Refinery, OMCO, and
OMIFCO (OETC 2014).
Some details of the existing generation units
are available in the recent issue of “OPWP 7-
year statement 2016-2022” (OPWP 2016b) and in
previous issues. Other details are available in
OETC’s “Five-Year Annual Transmission
Capability Statement (2014-2018)” regarding the
MIS system (OETC 2014). Table 1 shows a
summary of the eleven power stations
connected to the MIS of Oman and their net
generation capacity in 2014.
The fuel cost coefficients of all the generation
units were based on estimated values from the
heat rate curves received from OPWP. It is
worth mentioning that, to preserve
confidentiality, the heat rate values were
indicative rather than actual. A price of
$1.5/MMBtu for the fuel (natural gas) was used
to obtain the fuel cost data. Then, a curve-fitting
technique was used to obtain the fuel cost
parameters for each generation unit. An
example of a single-cycle generation unit is
shown in Table 2 and Figure 2. The same
procedure was conducted for all generation
units in the system.

3.2 Transmission System
The OETC owns and operates the MIS’s
transmission network. Moreover, the OETC is
responsible for balancing generation and
demand at all times of the day for the
economic dispatch of power. It accomplishes
this role through the OETC Load Dispatch
Centre (LDC), which is located in Al Mawaleh,
Muscat. Currently, the system has three voltage
levels: 132 kV, 200 kV, and 400 kV. The
transmission system data are available in the
OETC’s 5-year annual capability statements, for
instance, the 2014-2018 statement (OETC 2014).
A summary of the transmission system in 2014
is shown in Table 3.
The OETC transmission system is also
interconnected with the Sohar Aluminium
system at 220 kV and the PDO transmission
network at 132 kV via a single-circuit overhead
line. The available data include the length of
every line (km) between the substations, the
resistance (Ω/km), the inductive reactance
(Ω/km), and the capacitive susceptance
(µS/km).
The power-flow model of the transmission
system was built in MATLAB. Details of the
MIS transmission system data are given in the
appendix (Tables A1 and A2).

4. Simulation Results

A case study of the Main Interconnected
System of Oman was conducted, and it included
losses within the dispatch decision. It is worth
mentioning that this simulation was conducted
to determine the optimal dispatch for the peak-
hour load of 2014.
The Lambda (λ) iteration method, based on
Lagrange relaxation, is used to solve this
optimization problem. This method starts by
assuming an initial value for the system
incremental fuel cost (λ), and calculating output
power of all generation units (Pj) as a function
of λ. Then, the value of λ is updated based on
Newton-Raphson method considering the
power balance mismatch. The process continues
until the prescribed tolerance is reached (Saadat
1999).
The load data for all buses were obtained
from the OETC annual capability statement
(OETC 2014). The details of the load are given in
the appendix (Table A3). The MATLAB
software package was used in this study.
Three scenarios were considered in the
economic dispatch.

M.H. Albadi, F.N. Al Farsi, N. Hosseinzadeh and A. H. Al Badi

Table 1. Power stations connected to the MIS of Oman.

Power
Plant

Net
Power
Generatio
n (MW)

Remarks

Al Kamil 282 Al Kamil is an IPP and was commissioned in 2002. The station comprises
three GE PG9171E gas turbines (site rating: 94.1 MW) operating in open
cycle

Manah 273 The United Power Company owns Manah. When commissioned in 1996, it
was the first IPP to be built in Oman. The station comprises three GE
PG6541B gas turbines (with each site rated at 28.8 MW) and two GE
PG9171E gas turbines (ratings of 93.5 MW)

Wadi Al
Jizzi

324 Wadi Al Jizzi Power Station comprises eleven gas turbines (with gross site
ratings in the range of 19.2-32.5 MW) and all operate in open cycle. The
units were installed progressively from 1982.

Sohar I 605 Sohar I Power Plant is an IPP and was commissioned in 2007. There are
three gas turbines, each with a 138.7-MW capacity, and a steam turbine
with a 220-MW capacity. All units have been operational since 2007.

Sohar II 745 Sohar II Power Plant is an IPP and was commissioned in 2012. There are
two gas turbines, each with a 247.5-MW capacity, and a steam turbine with
a 249.9-MW capacity. They have all been operational since 2013.

Barka I 434 AES (ACWA now) commissioned Barka 1 in 2003. It was developed as an
independent water & power plant (IWPP). The power plant comprises two
Ansaldo V94.2 gas turbines (manufactured under licence from Siemens)
and a steam turbine operating in combined cycle.

Barka II 681 Barka II is an independent water & power producer (IWPP) and was
commissioned in 2009. There are three gas turbines, each with a 130-MW
capacity, and two steam turbines, each with a 161-MW capacity.

Barka III 745 Barka III is an IPP and was commissioned in 2012. There are two gas
turbines, each with a 247.5-MW capacity and a steam turbine with a 249.9-
MW capacity. They have all been operational since 2013

Sur 2000 Sur is an IPP and was commissioned in 2014. There are five gas turbines,
each with a 244.4-MW capacity, and three steam turbines with capacities
ranging between 156.8 and 310.7 MW.

Rusail 687 The power station has eight Frame 9E gas turbines installed and operating
in open cycle. The gross site rating of the units varies from 81.5 MW to 95.9
MW. The units were installed progressively between 1984 and 2000.

Ghubra 406 Ghubra power plant has 2 steam turbines (each with a 29.2-MW rating) and
12 gas turbines (with ratings ranging from 16-88.6 MW).

Table 2. Example of estimated cost curve data

for a 90-MW single-cycle generation
unit.

Operating
point
from
rating

Heat Rate
(MBtu/kWh)

Fuel
Consumption
(MMBtu/hr)

Fuel
Cost
($/hr)

30 % 16,467 395.5 593.20
65 % 10,784 630.8 946.26
100 % 10,431 938.8 1408.2

Figure 2. Estimated fuel cost parameters of a

single-cycle generation unit.

Effect of Considering Transmission Losses in Economic Dispatch – A Case Study of Oman’s Main Interconnected System

In Scenario 1, losses were considered and
calculated using B-coefficients in the Kron-
Kirchmayer method.

 Scenario 2 involved simulating the current
practice in the MIS, where losses are
considered as a fixed load and are not
included in the optimization procedure.

 Scenario 3 involved simulating the system
performance when network losses were not
considered at all in the dispatch procedure.

Figures 4 and 5 show the output of power
generation for different units in the Rusail,
Ghubra, Al Kamil, Manah, and Barka I power
plants. Figure 4 shows the optimal output of
power generation units for the Sohar I, Sohar II,
Barka II, Barka III, and Sur power plants in the
three scenarios.
There are some differences between the
outputs of the generation units in the three
scenarios. It is clear that the total dispatched
power when the network losses are considered
as a fixed load (Scenario 2) is higher than the
total dispatched power associated with the two
other scenarios in most of the power plants.
It is worth mentioning that considering losses
in the optimization process (Scenario 1) requires
slightly more execution time than other

scenarios. A comparison of the number of
iterations and execution time for the three
scenarios are presented in Table 4.
Figure 5 shows the total dispatched power in
MW for the three scenarios. It is clear that the
overall power generation output when one
considers the losses as a fixed load (Scenario 2)
is higher than the optimal dispatch power
generation when one considers the network loss
using B coefficients (Scenario 1) by 48 MW. This
result demonstrates that transmission losses
should be considered in the economic dispatch
process in the MIS.
Figure 6 shows the overall fuel cost
comparison of Scenarios 1 and 2. The overall
cost of power generation when one considers
the losses using B coefficients (Scenario 1) is
lower than the overall cost of the optimal
dispatch of power generation when one
considers the losses as a fixed load (Scenario 2)
by $645.62/hr. However, as was mentioned, the
generation units’ cost data were merely
indicative values, not their actual values.
Figure 7 presents a comparison of the results
of the current dispatch practice and those of the
proposed dispatch practice that considers the
network losses for each power station in the
MIS.

Table 3. OETC transmission system assets.

Asset Size Quantity/Units

Overhead
Transmission
Lines

220 kV 1,454.4 Circuit-km

132 kV 3,051.06 Circuit-km

Underground
Cables

220 kV 61.6 Circuit-km

132 kV 98.681 Circuit-km

Transformer
Capacity

220/132 8,630 MVA

220/33 320 MVA

132/33 10,541 MVA

132/11 150 MVA

Interconnection
Grid Stations

220

Five

Grid Stations 220/132 Two

220/33 One

220/132/33 Seven

132/33 Forty

132/11 One

M.H. Albadi, F.N. Al Farsi, N. Hosseinzadeh and A. H. Al Badi

Figure 3. Dispatched power for the three scenarios (Rusail, Ghubra, Al Kamil, Manah, and Barka I
power plants).

Figure 4. Dispatched power for the three scenarios (Sohar I, Sohar II, Barka II, Barka III, and Sur

power plants).

Figure 5. Comparison between the three scenarios’ total dispatched power values.

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Scenario 2

Effect of Considering Transmission Losses in Economic Dispatch – A Case Study of Oman’s Main Interconnected System

Figure 6. Comparison between the overall costs associated with Scenario 1 and Scenario 2.

Figure 7. Comparison of the current dispatch practice and the proposed dispatch practice.

Table 4. Computational requirements of

different scenarios.

Scenarios Scenario
1

Scenario
2

Scenario
3

Number of
iteration

9 6 5

Execution
time

6.03 s 5.74 s 4.97 s

Simulation results show that the outputs of
some power plants, such as Sohar II, Barka III,
Barka II, and Manah, are more in line with
Scenario 1 (the proposed practice) than the
current practice of OETC LDC. On the other
hand, the current practice results in the
production of more power in other power
plants, for instance, the Rusail, Ghubra, Wadi Al
Jizzi, Al Kamil, Barka I, and Sohar 1 power
plants.
These differences are attributable to (1) the
inclusion of losses in the optimization
procedure of Scenario 1 and (2) failure to consi-

der water production and voltage support
requirements in the simulation.

5. Conclusion

In this paper, the economic dispatch problem,
its formulation, and its objectives and
constraints were reviewed. The main
interconnected system (MIS) of Oman was
modelled to find the optimal dispatch of power
generation at a selected hour on a selected day
using the MATLAB software package.
Furthermore, different methods for obtaining
network loss coefficients were discussed. The
loss coefficients of the MIS were determined
and the optimal dispatch of the power
generation units was found, taking the losses
into consideration. This was compared with the
current practice of dispatching generation units.
It was demonstrated that considering the losses
in the optimization procedure resulted in the

F
u

e
l

C
o
st

(
T

h
o
u

sa
n

d
s

$
/h

Scenario 1

Scenario 2

200

400

600

800

P
o
w

e
r

P
la

n
t

o
u

tp
u

t
(M

W
)

OETC LDC Dispatch

Simulation Results of Scenario 1

M.H. Albadi, F.N. Al Farsi, N. Hosseinzadeh and A. H. Al Badi

reduction of the total dispatched power,
reducing the cost by $645/hr.

Conflict of Interest

The authors declare no conflicts of interest.

Funding

No funding was received for this research.

Acknowledgment

The authors would like to acknowledge the
Oman Electricity Transmission Company
(OETC) and the Oman Power and Water
Procurement Company (OPWP) for supporting
this work and for providing the data used in the
simulation.

References

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Effect of Considering Transmission Losses in Economic Dispatch – A Case Study of Oman’s Main Interconnected System

Appendix

Table A-1. MIS 2014 Overhead Line Data.

From
Substation

To
Substation

Voltage
(kV)

Length
(Km)

R
[Ω/km]

X
[Ω/km]

B
[µS/km]

Barka Power station Filaj 220 10 0.0258 0.321 3.82
Barka Power station Filaj 220 10 0.0258 0.321 3.82
Filaj Airport Heights 220 34 0.0258 0.321 3.82
Airport Heights Misfah 220 16 0.0258 0.321 3.82
Misfah MSQ 220 26 0.0258 0.321 3.82
Misfah Jahloot 220 54.9 0.0258 0.321 3.82
MIS SIS 220 107 0.0258 0.321 3.82
SPS SIS 220 38 0.0258 0.321 3.82
Al Wasit SIS 220 66 0.0258 0.321 3.82
Blue City MIS 220 45.3 0.0258 0.321 3.82
Filaj Blue City 220 33.2 0.0258 0.321 3.82
Al Wasit Ibri 220 145 0.0258 0.321 3.82
Sohar IPP-2 SIS 220 36.9 0.0258 0.321 3.82
Barka IPP-3 Misfah 220 58.2 0.0258 0.321 3.82
Al Kamil JBB Ali 132 55 0.04283 0.2821 3.98
Al Kamil Mudharib 132 51.2 0.04283 0.2821 3.98
Al Kamil Sur 132 73.1 0.04283 0.2821 3.98
Barka Main Filaj 132 6.3 0.04283 0.2821 3.98
Dank Al Hail 132 52.6 0.04283 0.2821 3.98
Filaj Muladha 132 46.5 0.04283 0.2821 3.98
Izki Mudaybi 132 62.1 0.04283 0.2821 3.98
Izki Nizwa 132 31.1 0.04283 0.2821 3.98
Manah Nizwa 132 19.7 0.04283 0.2821 3.98
Airport Heights Seeb Main 132 7.8 0.1472 0.4111 2.6
MIS Khabourah 132 53.4 0.04283 0.2821 3.98
Mabalah Barka Main 132 11.6 0.04283 0.2821 3.98
MS Qaboos Jahloot 132 44 0.04283 0.2821 3.98
MS Qaboos Wadi Adai 132 8.2 0.04283 0.2821 3.98
Mudhabi Mudharib 132 60.1 0.04283 0.2821 3.98
Muladha MIS 132 11.4 0.04283 0.2821 3.98
Nizwa Bahla 132 32 0.0857 0.3948 2.85
Nizwa Ibri 132 123.5 0.04283 0.2821 3.98
Rusail Mabalah 132 13.1 0.04283 0.2821 3.98
Rusail Sumail 132 31.2 0.04283 0.2821 3.98
Rustaq Muladha 132 29.5 0.04283 0.2821 3.98
SIS Sohar Grid 132 27.5 0.04283 0.2821 3.98
Sohar Grid Wadi Jizzi 132 24.7 0.04283 0.2821 3.98
Sumail Izki 132 61 0.04283 0.2821 3.98
Wadi Adai Al Falaj 132 3 0.04283 0.2821 3.98
Wadi Jizzi Al Wasit 132 36.7 0.0972 0.3168 3.8
Wadi Kabir Wadi Adai 132 6 0.0857 0.3948 2.85
Manah Adam 132 47 0.04283 0.2821 3.98
Boushar MS Qaboos 132 1.7 0.04283 0.2821 3.98
Ghubrah MS Qaboos 132 1.7 0.04283 0.2821 3.98
Wadi Jizzi Liwa 132 28 0.04283 0.2821 3.98
Liwa Shinas 132 20 0.04283 0.2821 3.98
Khabourah Saham 132 40 0.04283 0.2821 3.98
Saham SIS 132 30 0.04283 0.2821 3.98

M.H. Albadi, F.N. Al Farsi, N. Hosseinzadeh and A. H. Al Badi

Al Wasit Wadi Sa'a 132 32.0 0.1503 0.4101 2.83
Wadi Sa'a Dank 132 56.5 0.1503 0.4101 2.83
Jahloot Yitti 132 25.1 0.0258 0.321 3.82
Rusail Misfah 132 10.0 0.04283 0.2821 3.98
Misfah Wadi Adai 132 36.0 0.04283 0.2821 3.98
Filaj Nakhal 132 26.0 0.04283 0.2821 3.98
Al Wasit Buraimi 132 30.73 0.04283 0.2821 3.98
MS Qaboos Qurum 132 10 0.04283 0.2821 3.98
Qurum Muttrah 132 10 0.04283 0.2821 3.98
Ibri Dank 132 55 0.04283 0.2821 3.98
Jahloot Quriyat 132 50 0.04283 0.2821 3.98

Table A-2. 2014 MIS cable data.

From
Substation

To
Substation

Voltage
(kV)

Length
(km)

R
[Ω/km]

X
[Ω/km]

B
[µS/km]

SPS SIS 220 3 0.01074 0.312 91.11
SPS Sohar Industrial

Area 'A'
220 3 0.01074 0.321 91.11

Blue City MIS 220 6 0.01074 0.321 91.11
Filaj Blue City 220 6 0.01074 0.312 91.11
Sohar IPP-2 SIS 220 2.6 0.01074 0.321 91.11
Barka IPP-3 Misfah 220 10.2 0.01074 0.321 91.11
Airport Heights Seeb Main 132 9 0.04282 0.08361 122.522
Mawellah Rusail 132 7.3 0.04282 0.08361 122.522
Sohar Industrial
Area 'A'

Sohar Refinery Co. 132 2.2 0.04 0.08 122.52

Wadi Kabir Wadi Adai 132 1.63 0.04 0.143 64.7
Ghubrah Boushar 132 2.323 0.04 0.08 122.52
Boushar MS Qaboos 132 1.5 0.04 0.08 122.52
Ghubrah MS Qaboos 132 4.8 0.04 0.08 122.52
Airport Heights Wave 132 8.806 0.04 0.08 122.52
Al Wasit Buraimi 132 5.47 0.04 0.08 122.52
Qurum Muttrah 132 3.5 0.04 0.08 122.52

Table A-3. Peak Load and Capacitor Data in 2014.

Grid Stations P Load (MW) Q Load (MVAr) Cap (MVAr)

Barka-132 kV 165 16 25
Nakhal-132 kV 62 6 25

Blue City – 220 kV 53 16 0
MIS – 132 kV 141 23 0

Muladah – 132 kV 134 5 30
Rustaq – 132 kV 117 7 0

Khabourah-132 kV 153 23 10
Saham 132 kV 112 15 0

SIA 220 kV -40 -4.9 0
SIA 132 kV 47 8 0

Sohar main 132 kV 164 20 20
Liwa 132 kV 138 24 0

Shinas 85 15 25
Mahdah – 132 kV 12 7 0
Burimi 1 - 132 kV 50 8 0
Burimi 2 – 132 kV 50 8 35
Wadi Saa – 132 kV 11 6 0

Effect of Considering Transmission Losses in Economic Dispatch – A Case Study of Oman’s Main Interconnected System

Dank -132 kV 18 2 10
Al Hail – 132 kV 52 9 10

Ibri – 132 kV 104 9 10
Nizwa and PDO load connected to Nizwa 139 18 0

Bahla 104 9 0
Izki 61 14 0

Adam 39 2 0
Samail 78 17 0

Mudabi 110 18 0
Mudayrib 141 4 0

JBB 143 1 0
Sur and Omifco Load 117 4 0

MSQ – 132 kV 135 16 35
Old Gubrah 20 11 0

New Ghubrah 74 33 0
Bosher – 132 kV 226 36 40

Airport Hight – 132 kV 87 9 30
Mwalleh North – Authibah 14 1 0

Rusail PS – 132 kV 121 34.2 0
Misfah 5 13 0

Wadi Adai 121 19 35
Al Falaj 68 10 35

Wadi Kabeer 110 18 35
Matrah 47 25 0
Qurum 18 9 20

Mwalleh south-1 210 16 20
Seeb 132 kV 133 42 0

Mobillah 104 12 30
Jahloot 76 7 25

Yitti 15 3 0
Quryat 45 -11 0

Figure A-1. MIS transmission system in 2014.