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International Journal of Electrical Engineering and Technology (IJEET), ISSN 0976 –
6545(Print), ISSN 0976 – 6553(Online) Volume 4, Issue 3, May - June (2013), © IAEME
1
INCLUSION OF ENVIRONMENTAL CONSTRAINTS INTO SITING
AND SIZING TECHNIQUES FOR LOCALIZED GAS TURBINES
DISTRIBUTED GENERATION
Ibrahim Helal
1
, Mohamed Abdel-Rahman
2
, MayYoussry
3
1
Department of Electrical Engineering, Ain Shams University
2
Department of Electrical Engineering, Ain Shams University
3
Egyptian Electricity Utility & Consumer Protection, Regulatory Agency
ABSTRACT
The restructuring of electricity markets resulted in an increasing amount of distributed
generation (DG) connected to the distribution networks to face load growth and demand
bottlenecks.
The typical approach to meet the increasing demand is to build additional central
power generating stations or to expand the existing ones. Transmission and distribution T&D
networks, in such a case, represent significant cost both fixed and running. In contrary, the
DG can provide better service at lower cost in many applications by avoiding the extra cost,
besides providing higher reliability level for customers. One of the used technologies for DG
is the gas turbine technology. The problem, however, with DG is to reach the optimal sizing
and siting of the units. As well as the environmental impact produced by the exhaust gases of
the DG units. In order to ensure the environmental benefits of the DG units, this paper
investigates the inclusion of emissions as a constraint of the DG siting and sizing process
with present siting and sizing techniques.
Consequently, this paper introduces the emissions environmental constraint based on:
(i) the units emission factors, (ii) the power supplied by the network and (iii) the power
supplied by the DG units. The model has been applied to a real case system data.
Keywords: Distributed generation (DG), optimal placement, optimal power flow, sizing &
siting of DG units, CO2 emissions, and emission factors.
INTERNATIONAL JOURNAL OF ELECTRICAL ENGINEERING
& TECHNOLOGY (IJEET)
ISSN 0976 – 6545(Print)
ISSN 0976 – 6553(Online)
Volume 4, Issue 3, May - June (2013), pp. 01-18
© IAEME: www.iaeme.com/ijeet.asp
Journal Impact Factor (2013): 5.5028 (Calculated by GISI)
www.jifactor.com
IJEET
© I A E M E
International Journal of Electrical Engineering and Technology (IJEET), ISSN 0976 –
6545(Print), ISSN 0976 – 6553(Online) Volume 4, Issue 3, May - June (2013), © IAEME
2
List of Symbols
DG Distributed generation
f(x) The objective function
G(x) The equality constraints
H(x) The inequality constraints
i The bus index
N The total number of system buses
C1 The active power component in the unit investment cost (Egyptian
Pound/MW/hr).
C2 The reactive power component in the unit investment cost (Egyptian
Pound/MVAr/hr).
Pgi
max
The maximum active that can be generated (MW).
Qgi
max
The maximum reactive power that can be generated (MVAr).
C3 The running cost of generated reactive power (Egyptian Pound/MVAr/hr).
Pgi The active DG generated power (MW).
Qgi The reactive DG generated power (MVAr).
C4 The market price for active power (Egyptian Pound/MWh/hr).
C5 The market price for reactive power (Egyptian Pound/MVAr/hr).
Ps The system active power (MW).
Qs The system active power (MVAr).
Ploss The active power losses (MW).
Qloss The reactive power losses (MVAr).
PD The active power demand (MW).
QD The reactive power demand (MVAr).
Ps
max
the max distribution substation capacity (MW).
∆Vi Maximum permissible voltage drop at bus i.
pfi Power Factor of DG unit at bus i.
K1 CO2 emission factor of the centralized power stations.
K2 Gas turbine CO2 emission factor.
Psb The system power for the base case without using any DG units (MW).
FE The fuel energy (GJ)
FQ Fuel quantity (ton/year).
FHV Fuel heating value (GJ/ton).
EQ Emission quantity in (ton/year).
ER Emission rate in (ton/GJ).
EQVCO2 The equivalent CO2 emission quantity (ton/year).
GWP Global warming potential factor.
EF The emission factor (ton /year).
ECO2 CO2 emissions in (ton/GWh).
GGE Gross generated energy (GWh/year).
1. INTRODUCTION
A typical power system has hierarchical structure composed of generation,
transmission and distribution. Under the move towards deregulation, individual entities may
be allowed to generate power on the distribution level, given the attainment of the required
licenses from the concerned regulatory body [1]-[3].
International Journal of Electrical Engineering and Technology (IJEET), ISSN 0976 –
6545(Print), ISSN 0976 – 6553(Online) Volume 4, Issue 3, May - June (2013), © IAEME
3
The trend of distributed generation started to emerge in the beginning of this century
[4]. Internal combustion engines, micro turbines, combustion gas turbines, fuel cells, photo
voltaic solar panels and wind turbines are examples of distributed generation technologies
[1]-[3]. Renewable resources are gaining popularity. However, still fossil fuel dependent
technologies are wide spread and in large use. Therefore, a concern may arise is to ensure that
the spread of fossil fuel generators, including gas turbines technology, does not result in
environmental deterioration.
In order to reach an optimum distribution networks as far as energy losses are
concerned, distribution companies have to perform detailed studies to ensure optimal
planning and operation of their systems, should they decide to use distributed generation. The
choice of the candidate load buses to install DG units and the determination of their
corresponding capacities is typically a problem that undergoes extensive investigations to
ensure the optimal network operation, i.e. minimum losses and costs with power quality and
reliability improvement.
Nevertheless, the earlier methods stopped short from considering the environmental
impact on the siting and sizing of DG units. In order to fill this gap, this paper proposes
considering the environmental impact of DG in the form of an emissions constraint. The
paper presents a formulation methodology to consider the emissions both from the DG units
and the centralized network. The approach is dependent on the utilization of emission factors
for both the centralized and decentralized units. The developed methodology has been
applied to a practical power network of 106 distribution drop points, assuming that all DG
units are of the same type.
The paper is structured in five sections including this introductory section. Section II
presents a DG generic siting and sizing model with technical constraints to obtain the optimal
sizing and siting of the DG units. Section III depicts the environmental constraint
formulation. Section IV applies the proposed concept to Case study network configurations.
The conclusions are summarized in Section V.
2. (DG) GENERIC OPTIMIZATION MODEL DESCRIPTION
Fig. (1) shows a typical DG connection topology. The connected loads are served by
both the DG and the distribution network. The mode of operation may differ from one case to
another. It may be peak shaving in one case, or base load in another. The customer side may
even engage in an import and export of energy with the network. For this proposal, it is
assumed that the local generation supplies the base load whereas the network covers the rest
of the demand as well as the system losses.
Fig. (1) A typical DG, load and network topology
International Journal of Electrical Engineering and Technology (IJEET), ISSN 0976 –
6545(Print), ISSN 0976 – 6553(Online) Volume 4, Issue 3, May - June (2013), © IAEME
4
The mathematical formulation of the optimization, for the siting and sizing of DG
units, problem results in a system of non linear algebraic equations [5], and [6]. The objective
function is to minimize both the hourly cost including losses and capital costs of the system.
The model considers load flow equations, system constraints. Provided the non-linearity of
the objective function and the constraints, the optimal solution of the model is achieved
iteratively, e.g., gradient method. In all cases, a feasible solution must not violate system
constraints such as capacity limits of active and reactive power sources and environmental
restrictions. The model solution provides the optimal sizing of the DG units.
Nevertheless, many sizing and siting methods have been developed to optimize
system operation [7], and [9]. The loss reduction technique is used in this work to find the
candidate load buses for DG installation [7]. A complementary technique should be used to
find out the optimal location of the optimal DG size.
The problem is a general minimization problem with constraints modeled as in
Equation (1).
[5], and [6]
Minimize f(x)
Subject to: g(x) = 0 (1)
h(x) ≤ 0
Where x is the vector of control and state variables. Control variables are DG active and
reactive power outputs. The state variables are voltage and angles of load buses.
For this work all DG units are assumed to be gas units and have similar characteristics.
Following are the details of the optimization model.
2.1 Objective Function Formulation
The objective function presents: (i) the investment cost, (ii) the running cost of the
DG units, (iii) the cost of the electrical power supplied by the utility and (iv) the cost
associated with network losses. The individual components of the objective function are:
2.1.1 DG fixed cost
The fixed cost of distributed generation is
n
f = ∑ (c1Pgi
max
+c2Qgi
max
) (Egyptian Pound/hr) (2)
i=1
2.1.2 DG running cost
The running cost of the distributed generation is
n
f = ∑ (ai + biPgi + ciPgi
2
) + c3Qgi Egyptian Pound/hr) (3)
i=1
(3) is a quadratic cost function expressing the DG running costs due to active power
generation where, ai, bi and ci are the generator constants in Egyptian Pound/hr, Egyptian
Pound/MW/hr and Egyptian Pound/MW2
/hr.
2.1.3 Cost of system power
The cost of the utility supplied power is
f = c4Ps + c5Qs (Egyptian Pound/hr) (4)
International Journal of Electrical Engineering and Technology (IJEET), ISSN 0976 –
6545(Print), ISSN 0976 – 6553(Online) Volume 4, Issue 3, May - June (2013), © IAEME
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2.1.4 Cost of system losses
The system losses cost is
f = c4Ploss + c5Qloss (Egyptian Pound/hr) (5)
Where, Ploss and Qloss are calculated from load flow analysis as the algebraic sum of active
and reactive power losses in all system branches [10].
Therefore, the final form of the objective function is
n
f(x) = ∑ (c1Pgi
max
+c2Qgi
max
)
i=1
n
+ ∑ (ai + biPgi + ciPgi
2
)
i=1
+ c3Qgi + c4Ps + c5Qs
+ c4Ploss + c5Qloss (Egyptian Pound/hr) (6)
2.2 Equality Constraints
The equality constraints g(x) are represented by the power balance constraints, where
the total active power generation must cover the total power demand and the power losses as
in
n n
∑Pgi + Ps = ∑PDi + Ploss (7)
i=1 i=1
The same applies for reactive power, where the reactive power supplied by the generators
should be in balance with the reactive power consumed or produced throughout the system.
Nevertheless, for reactive power flow and voltage stability considerations, this balance
should not only be globally attained throughout the system but should hold at each bus within
the network
n n
∑Qgi + Qs = ∑QDi + Qloss (8)
i=1 i=1
The demand data PDi & QDi are given. They can be hourly values. Nevertheless, this requires
reformulating the whole problem as a sum for the whole study period. For the sake of
simplicity and being on the conservative side, PDi and QDi are considered at the system peak
to represent the system most severe operating conditions.
2.3 Inequality Constraints
The inequality constraints h(x) reflect the limits of DG as well as the limits needed to ensure
system security. (9) to (13) represent the inequality constrains of the optimization model.
The upper and lower bounds of DG generated power (Pg &Qg) are
Pgi
min
≤ Pgi ≤ Pgi
max
(9)
Qgi
min
≤ Qgi ≤ Qgi
max
(10)
The upper limit of substation capacity is
Ps ≤ Ps
max
(11)
Other technical constraints such as voltage & Power factor limits are also considered in this
model.
Maximum permissible voltage drop is
∆Vi ≤ 0.01 p.u (12)
International Journal of Electrical Engineering and Technology (IJEET), ISSN 0976 –
6545(Print), ISSN 0976 – 6553(Online) Volume 4, Issue 3, May - June (2013), © IAEME
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The conservative value of the voltage limit is to compensate for the simplifications and
uncertainties in the developed approach and the used parameters.
Power factor constraint
According to the main stream of operation guidelines worldwide, the load power factor is
limited between 0.95 leading to 0.90 lagging power factors [11].
-0.95 ≤ pfi ≤ 0.9 (13)
3. ENVIRONMENTAL CONSTRAINT FORMULATION
All DG units and centralized power stations produce significant amounts of CO2
emissions. Therefore, an environmental constraint is considered in the DG optimization
model to ensure that using DG units will not result in the increase of the total system
emissions. The environmental constraint is
n
K1Ps + ∑K2Pgi ≤ K1Psb (14)
i=1
It is assumed to be a linear inequality constraint based on the emission factors of both
centralized and DG units. To calculate the emission factors for both centralized power
stations and DG units, both fuel energy and emission quantities must be determined. The Fuel
energy is
FE = FQ * FHV (15)
In some cases the centralized power stations use different types of fuel. In this case
fuel energy is calculated for each fuel type separately according to its heating value.
The emission quantity for each fuel type is
EQ = ER * FE (16)
Appendix (A) summarizes the emission rate for each fuel type.
Consequent to emission quantity calculation for each fuel type, all greenhouse gases
emissions are converted to their equivalent CO2 as follows
EQVCO2 = GWP * EQ (17)
Where, GWP for each greenhouse gas emission is listed in Appendix (B).
Upon converting all greenhouse gases emissions to their equivalent CO2 emissions, emission
factor is easily calculated by
EF =ECO2 / GGE (18)
Where ECO2 is the total equivalent annual CO2 emissions and GGE is the total annual
generated energy.
4. CASE STUDY
The optimization model described in the preceding sections has been applied to a
distribution network in a typical industrial zone. Appendix (C) depicts the utilized sizing and
siting approach. The cost data are given in Appendix (D). Fig. (2) shows the distribution
network considered for the case study. The network consists of 106 buses and 116 power
lines of 11 KV.
International Journal of Electrical Engineering and Technology (IJEET), ISSN 0976 –
6545(Print), ISSN 0976 – 6553(Online) Volume 4, Issue 3, May - June (2013), © IAEME
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Bus number (1) represents the transmission substation. It is considered as the slack
bus. Buses number (43), (67) and (91) are P-V buses (generator bus) with a controlled
voltage of (1p.u).
The generated power at each bus of the P-V buses is assumed to be one forth of the
total loads. All other buses are considered P-Q buses as the loads are known, with 0.85 power
factor. The base voltage is 11 KV. The base power is 100 MVA. Analysis is carried out at
system peak load as it is the worst operational condition. The results are summarized in the
following sections.
Fig. (2) Case Study Distribution Network
4.1 Base Case Solution (without DG)
The load flow solution for the base case (without DG) is summarized below:
• The delivered power by the utility is equal to 50.6 MW.
• System active losses are 5.5 MW.
• The system CO2 emission is 58 ton/hr.
• The initial cost is 6740Egyptian Pound/hr.
International Journal of Electrical Engineering and Technology (IJEET), ISSN 0976 –
6545(Print), ISSN 0976 – 6553(Online) Volume 4, Issue 3, May - June (2013), © IAEME
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As can be noticed in Table (1) buses (from bus no (50) to bus no (63) & from (67) to (90))
exceed the lower limit of voltage by 1% (the permissible level is from 0.99 to 1.01 p.u.).
Table (1) Initial Bus Voltage
Bus
No.
|V|
Bus
No.
|V|
Bus
No.
|V|
1 1.00 37 1.00 73 0.98
2 0.99 38 1.00 74 0.98
3 0.99 39 1.00 75 0.98
4 0.99 40 1.00 76 0.98
5 0.99 41 1.00 77 0.98
6 0.99 42 1.00 78 0.98
7 0.99 43 1.00 79 0.98
8 0.99 44 1.00 80 0.98
9 0.99 45 1.00 81 0.98
10 0.99 46 1.01 82 0.98
11 0.99 47 1.01 83 0.98
12 0.99 48 1.01 84 0.98
13 0.99 49 0.99 85 0.98
14 0.99 50 0.98 86 0.98
15 0.99 51 0.98 87 0.98
16 0.99 52 0.98 88 0.98
17 0.99 53 0.98 89 0.98
18 0.99 54 0.98 90 0.98
19 0.99 55 0.98 91 1.00
20 0.99 56 0.98 92 1.01
21 0.99 57 0.98 93 1.01
22 0.99 58 0.98 94 1.00
23 0.99 59 0.98 95 1.00
24 0.99 60 0.98 96 1.00
25 0.99 61 0.98 97 1.00
26 0.99 62 0.98 98 1.01
27 0.99 63 0.98 99 1.01
28 0.99 64 0.99 100 1.01
29 0.99 65 0.99 101 1.01
30 0.99 66 0.99 102 1.01
31 0.99 67 1.00 103 1.01
32 0.99 68 0.98 104 1.01
33 0.99 69 0.98 105 1.01
34 0.99 70 0.98 106 1.01
35 0.99 71 0.98
36 0.99 72 0.98
4.2 Optimal sizing & siting without environmental constraints
DG units are ranked according to their impact on the system losses reduction. The DG unit at
certain bus that reduces system losses most effectively has the highest priority. DG units are
installed one by one at the candidate load buses according to their priorities till the system
losses are constant or increased. Table (2) shows the ranking of the system load buses
according to their effect on losses reduction after applying a generation of 10 MW at each
bus.
International Journal of Electrical Engineering and Technology (IJEET), ISSN 0976 –
6545(Print), ISSN 0976 – 6553(Online) Volume 4, Issue 3, May - June (2013), © IAEME
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Table (2) Bus Ranking
Bus No.
Ploss
(MW)
Ranking Bus No.
Ploss
(MW)
Ranking Bus No.
Ploss
(MW)
Ranking
1
Slack
Bus
---- 28 5.54 63 55 4.92 39
2 5.39 49 29 5.54 64 56 4.92 38
3 5.25 46 30 5.54 65 57 4.92 35
4 5.54 53 31 5.54 66 58 4.92 36
5 5.54 54 32 5.54 67 59 4.87 25
6 5.54 55 33 5.54 68 60 4.84 20
7 5.54 56 34 5.54 69 61 4.87 27
8 5.54 57 35 5.54 70 62 4.86 24
9 5.54 58 36 5.54 71 63 4.88 28
10 5.54 59 37 5.54 Rejected 64 5.11 40
11 5.54 60 38 5.55 Rejected 65 5.17 42
12 5.54 61 39 5.55 Rejected 66 5.22 44
13 5.54 62 40 5.55 Rejected 67
Gen.
Bus
---
14 5.54 Rejected 41 5.56 Rejected 68 4.84 21
15 5.54 Rejected 42 5.56 Rejected 69 4.84 19
16 5.54 Rejected 43 4.91 30 70 4.87 26
17 5.54 Rejected 44 5.15 41 71 4.81 16
18 5.54 Rejected 45 5.19 43 72 4.82 18
19 5.54 Rejected 46 5.24 45 73 4.85 22
20 5.54 Rejected 47
Gen.
Bus
--- 74 4.77 2
21 5.54 Rejected 48 5.32 47 75 4.77 3
22 5.54 Rejected 49 4.91 31 76 4.77 4
23 5.54 Rejected 50 4.89 29 77 4.77 5
24 5.54 Rejected 51 4.92 37 78 4.77 6
25 5.54 Rejected 52 4.92 32 79 4.77 1
26 5.54 Rejected 53 4.92 33 80 4.77 7
27 5.54 Rejected 54 4.92 34 81 4.77 9
DG units are installed one by one at the load buses according to their ranking priorities, while
losses are calculated at each run as depicted in Table (3). Losses are decreasing due to DG
installation until bus number (89). At this bus the losses start to increase. Therefore, as
indicated in the table, buses no (79, 74, 75, 76, 77, 78, 80, 82, 81, 83, 84, 87, 85, 88, 86 & 71)
are the candidate optimal buses to locate the DG.
International Journal of Electrical Engineering and Technology (IJEET), ISSN 0976 –
6545(Print), ISSN 0976 – 6553(Online) Volume 4, Issue 3, May - June (2013), © IAEME
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Table (3) Results of siting DG units at each bus
DG Siting
Ploss
(MW)
Ps
(MW)
Siting DG at Bus (79) 5.4 49.5
Siting DG at Bus (79)&(74) 5.3 48.4
Siting DG at Bus (79),(74)&(75) 5.1 47.2
Siting DG at Bus (79),(74),(75)&(76) 5 46.1
Siting DG at Bus (79),(74),(75),(76)&(77) 4.9 45
Siting DG at Bus (79),(74),(75),(76),(77) &(78) 4.8 43.9
Siting DG at Bus (79),(74),(75),(76),(77),(78) &(80) 4.7 42.8
Siting DG at Bus (79),(74),(75),(76),(77),(78), (80)
&(82)
4.6 41.7
Siting DG at Bus (79),(74),(75),(76),(77),(78) ,(80)
,(82)&(81)
4.5 40.6
Siting DG at Bus (79),(74),(75),(76),(77),(78) ,(80),
(82),(81)&(83)
4.34 39.44
Siting DG at Bus (79),(74),(75),(76),(77),(78), (80)
,(82),(81),(83)&(84)
4.3 38.4
Siting DG at Bus (79),(74),(75),(76),(77),(78), (80)
,(82),(81),(83),(84)&(87)
4.25 37.4
Siting DG at Bus (79),(74),(75),(76),(77),(78), (80),
(82),(81),(83),(84),(87)&(85)
4.2 36.3
Siting DG at Bus (79),(74),(75),(76),(77),(78), (80)
,(82),(81),(83),(84),(87),(85)&(88)
4.1 35.2
Siting DG at Bus (79),(74),(75),(76),(77),(78), (80)
,(82),(81),(83),(84),(87),(85),(88)&(86)
4.08 34.18
Siting DG at Bus (79),(74),(75),(76),(77),(78), (80),
(82),(81),(83),(84),(87),(85),(88),(86) &(71)
3.9 33
Siting DG at Bus (79),(74),(75),(76),(77),(78), (80),
(82),(81),(83),(84),(87),(85),(88),(86) ,(71)&(89)
4 32.1
Consequent to siting DG units at candidate buses, optimization model is run to obtain the
proposed DG capacity at each bus. A standard size of 1MW is selected for each DG unit. The
optimal solution in this case is to generate the maximum capacity of DG units at all buses.
Table (4) shows that the voltages drop for all buses after installing DG units are within the
permissible limits.
International Journal of Electrical Engineering and Technology (IJEET), ISSN 0976 –
6545(Print), ISSN 0976 – 6553(Online) Volume 4, Issue 3, May - June (2013), © IAEME
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Table (4) Bus voltages after installing DG
Bus
No.
|V|
Bus
No.
|V|
Bus
No.
|V|
1 1.00 37 1.00 73 0.99
2 0.99 38 1.00 74 0.99
3 0.99 39 1.00 75 0.99
4 0.99 40 1.00 76 0.99
5 0.99 41 1.00 77 0.99
6 0.99 42 1.00 78 0.99
7 0.99 43 1.00 79 0.99
8 0.99 44 1.00 80 0.99
9 0.99 45 1.01 81 0.99
10 0.99 46 1.01 82 0.99
11 0.99 47 1.01 83 0.99
12 0.99 48 1.01 84 0.99
13 0.99 49 0.99 85 0.99
14 1.00 50 0.99 86 0.99
15 0.99 51 0.99 87 0.99
16 0.99 52 0.99 88 0.99
17 0.99 53 0.99 89 0.99
18 0.99 54 0.99 90 0.99
19 0.99 55 0.99 91 1.00
20 0.99 56 0.99 92 1.01
21 0.99 57 0.99 93 1.01
22 0.99 58 0.99 94 1.01
23 0.99 59 0.99 95 1.01
24 0.99 60 0.99 96 1.01
25 0.99 61 0.99 97 1.01
26 0.99 62 0.99 98 1.01
27 0.99 63 0.99 99 1.01
28 0.99 64 0.99 100 1.01
29 0.99 65 0.99 101 1.01
30 0.99 66 0.99 102 1.01
31 0.99 67 1.00 103 1.01
32 0.99 68 0.99 104 1.01
33 0.99 69 0.99 105 1.01
34 0.99 70 0.99 106 1.01
35 0.99 71 0.99
36 0.99 72 0.99
After installing DG units at the candidate load buses the system supplied power is 33 MW.
The system active losses are 3.9 MW. The system losses in this case are reduced by nearly
29% compared to the base case. The system hourly cost is 6350 Egyptian Pound/hour. Cost
reduction due to DG installation is 6%. The CO2 emissions are 59.5 ton/hr which is increased
by 2.7 %.
International Journal of Electrical Engineering and Technology (IJEET), ISSN 0976 –
6545(Print), ISSN 0976 – 6553(Online) Volume 4, Issue 3, May - June (2013), © IAEME
12
4.3 Optimal sizing and siting with environmental constraints
The system shown in Fig. (2) is tested while considering the environmental
constraints. The emission factors for both central power station and DG units are calculated
in Appendix (E). Table (5) summarizes the results of adding DG unit to the candidate load
buses according to their priorities in Table (2).
Table (5) Siting DG units at each bus under environmental constraint
DG Siting
Ploss
(MW)
Ps
(MW)
Siting DG at Bus (79) 5.5 50.2
Siting DG at Bus (79)&(74) 5.4 49.4
Siting DG at Bus (79),(74)&(75) 5.35 49.6
Siting DG at Bus (79),(74),(75)&(76) 5.27 49.1
Siting DG at Bus (79),(74),(75),(76) &(77) 5.2 47.8
Siting DG at Bus (79),(74),(75),(76) ,(77)
&(78)
5.1 46.4
Siting DG at Bus (79),(74),(75),(76)
,(77),(78)&(80)
5.1 46.4
These results indicate that system losses become constant after installing DG at bus (80),
while the optimal DG capacities are obtained and tabulated in Table (6).
Table (6) Results of the DG optimization model for the case study with environmental
constraints.
Bus No. Pg (MW) Qg (MVAR)
Generator at bus (79)
1 0.484
Generator at bus (74) 0 0
Generator at bus (75) 1 0.484
Generator at bus (76) 0.95 0.48
Generator at bus (77) 0 0
Generator at bus (78) 0.7 0.349
International Journal of Electrical Engineering and Technology (IJEET), ISSN 0976 –
6545(Print), ISSN 0976 – 6553(Online) Volume 4, Issue 3, May - June (2013), © IAEME
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The results show that system losses are 5.1 MW. Losses reduction is 7.3%. System
costs are 6618 Egyptian Pound/hr. The system hourly costs are reduced by 1.8%. System CO2
emission is 57.7 ton/hr after installing DG, i.e. no violation for the environmental constraints.
The cost reduction may be lower than the case in section C (without environmental
constraints). This shows that under environmental restrictions DG may not impact system
cost reduction effectively. However, technical losses reduction and voltage profile
improvement are evident. Table (7) shows voltage levels of the system after installing DG
units at the candidate load buses. All voltage tolerances are within the permissible limits of
±1%.
Table (7) Bus voltages after installing DG under environmental constraint
Bus No. |V| Bus No. |V| Bus No. |V| Bus No. |V|
1 1.00 28 0.99 55 0.99 82 0.99
2 0.99 29 0.99 56 0.99 83 0.99
3 0.99 30 0.99 57 0.99 84 0.99
4 0.99 31 0.99 58 0.99 85 0.98
5 0.99 32 0.99 59 0.99 86 0.98
6 0.99 33 0.99 60 0.98 87 0.99
7 0.99 34 0.99 61 0.99 88 0.99
8 0.99 35 0.99 62 0.99 89 0.98
9 0.99 36 0.99 63 0.99 90 0.98
10 0.99 37 1.00 64 0.99 91 1.00
11 0.99 38 1.00 65 0.99 92 1.00
12 0.99 39 1.00 66 0.99 93 1.01
13 0.99 40 1.00 67 1.00 94 1.00
14 1.00 41 1.00 68 0.99 95 1.00
15 0.99 42 1.00 69 0.98 96 1.00
16 0.99 43 1.00 70 0.99 97 1.00
17 0.99 44 1.00 71 0.99 98 1.01
18 0.99 45 1.00 72 0.99 99 1.01
19 0.99 46 1.01 73 0.99 100 1.01
20 0.99 47 1.01 74 0.99 101 1.01
21 0.99 48 1.01 75 0.99 102 1.01
22 0.99 49 0.99 76 0.99 103 1.01
23 0.99 50 0.99 77 0.99 104 1.01
24 0.99 51 0.99 78 0.99 105 1.01
25 0.99 52 0.99 79 0.98 106 1.01
26 0.99 53 0.99 80 0.99
27 0.99 54 0.99 81 0.99
International Journal of Electrical Engineering and Technology (IJEET), ISSN 0976 –
6545(Print), ISSN 0976 – 6553(Online) Volume 4, Issue 3, May - June (2013), © IAEME
14
5. CONCLUSIONS
In this paper a formulation for the environmental impact of DG is introduced. The
emissions are evaluated based on the use of conversion factors. An additional constraint is
added to the optimization planning problem. The approach is based on the minimization of
total system cost (capital and operational) subject to particular constraints related to system
and units' capacities, operational performance and CO2 emission.
The model is applied to a real distribution network composed of 106 distribution drop
points. Optimal sizing and siting of the DG units is obtained by solving the environmentally
constrained optimization model. The results show that without violating the permissible CO2
emission level, DG still can provide lower cost and losses together with complementary
power supply to local loads on the level of distribution networks.
Appendix A
Emission Factors for electric utility and industrial combustion systems [12]
Emission Rates (g/GJ energy input)
Utility applications CO2 CO CH4 NOX N2O
Natural gas boilers 56100 19 0.1 267 N/A
Gas turbine,
combined cycle
56100 32 6.1 187 N/A
Gas turbine, simple cycle 56100 32 5.9 188 N/A
Residual oil boilers 77350 15 0.7 201 N/A
Distillate oil boilers 74050 15 0.03 69 N/A
Coal, spreader stoker 94600 121 0.7 326 0.8
Coal, fluidized bed 94600 N/A 0.6 255 N/A
Coal, pulverized 94600 14 0.6 857 0.8
Coal, tangentially fired 94600 14 0.6 330 0.8
Coal, pulverize, wall fired 94600 14 0.6 461 0.8
Wood-fired boilers 26260 147 0.8 112 N/A
International Journal of Electrical Engineering and Technology (IJEET), ISSN 0976 –
6545(Print), ISSN 0976 – 6553(Online) Volume 4, Issue 3, May - June (2013), © IAEME
15
Appendix B
Global Warming Potential Factors [13]
Trace Gas GWP Trace Gas GWP
Carbon
Dioxide
1 HFC-134 1,000
CCl 4 1300 HFC-134a 1300
CFC- 11 3400 HFC-143 300
CFC-113 4500 HFC-143a 3800
CFC-116 >6200 HFC-152a 140
CFC-12 7100 HFC-227ea 2900
CFC-l 14 7000 HFC-23 9800
CFC-l 15 7000 HFC-236fa 6300
Chloroform 4 HFC-245ca 560
HCFC- 123 90 HFC-32 650
HCFC- 124 430 HFC-41 150
HCFC-141b 580 HFC-43-lOmee 1,300
HCFC-142b 1600 Methane 21
HCFC-22 1600 Nitrous Oxide 310
HFC- 125 2800
Sulphur
hexafluoride
23900
Appendix C
DG Sizing & Siting Technique
Many approaches have been developed to determine optimal sizing and siting of DG
units in electrical distribution networks.
The losses-reduction-based technique [7] is used in this paper to determine the
candidate load buses for DG installation. This technique considers primarily considers the
DG impact on total system losses reduction. The bus that reduces system losses most
effectively will have the highest priority for distributed generation installation.
Consequent to the choice of the DG candidate buses, the optimization model is used to
determine the distributed generation units' output powers. The optimal siting can be
determined as listed below.
International Journal of Electrical Engineering and Technology (IJEET), ISSN 0976 –
6545(Print), ISSN 0976 – 6553(Online) Volume 4, Issue 3, May - June (2013), © IAEME
16
Step 1
Perform load flow calculations to obtain the initial conditions of the system, i.e. power
supplied by the system and system losses.
Step 2
Start with adding a generation of 10 MW at each bus, only one bus at a time, and recalculate
system losses each time. This capacity is justified as being a typical unit capacity used to
check the impact of DG units on loss reduction.
Step 3
Rank system buses according to their effect on system losses reduction with higher rank for
the bus having more impact on loss reduction. The buses that provide losses higher than the
base case (without DG) should be rejected from the ranking list.
Step 4
Add DG units at the load buses according to their priority obtained in step 3. Recalculate
system losses after each installation until losses are seemed to be increased or constant.
Step 5
Once the optimal siting is determined in step 4, the optimization model is solved to obtain the
optimal sizing of DG at each of the optimal locations.
Fig. (3) illustrates the main steps to obtain the optimal sizing of each DG unit at each bus.
Fig. (3) A flowchart depicting the sizing technique utilized in the proposed approach
C a lcu la te syste m lo sse s in th is ca se
C h e ck syste m
co n stra in ts
S u b stitu te lo sse s in to o b je ctive
fu nctio n
M in im ize th e o b je ctive Fn
S e le ct th e n e a re st sta n d a rd size o f D G u n its to
th e o b ta in e d so lu tio n fo r e a ch b u s
F in a l so lu tio n o b ta in e d
R u n o p tim iza tio n m o d e l to fin d syste m
co sts
S to p
N o
Y e s
S ta rt
S e t in itia l va lu e s fo r P g i, Q gi, P s,Q s
fo r th e o b jective fu n ctio n
S o lve L o a d flo w e qn
u sin g S a m e
in itia l co n d itio n s
International Journal of Electrical Engineering and Technology (IJEET), ISSN 0976 –
6545(Print), ISSN 0976 – 6553(Online) Volume 4, Issue 3, May - June (2013), © IAEME
17
Appendix D
Cost Data
Based on the case study, electricity price is subsidized such that the average price (csa) is
0.022 $/kWh. The reactive power cost is set to be equal zero in this case study. The gas
turbine technology is used for DG units due to its low emissions. Investment cost of gas
turbine vary from (600–900 $/KW). An average price of 750 $/KW is used. The payback
period is assumed as 10 years. DG units operate as base load units, the total fixed DG costs is
set to be 8.5 $/MW-hr. Operating and maintenance cost is assumed to be 0.0055 $/kWh. Price
of natural gas is 0.045 $/m3 for the case study. The fuel consumption rate of DG is assumed
to be 250 gm/kWh.
Appendix E
Applying Equation (15) to Equation (18), the central power station emission factor (K1) is
equal to 1.14 ton/MWh. DG units are assumed to have fuel consumption rate of 250 gm/kWh,
calorific heat value of 38.5 MJ, service hours of 8000 hrs and load factor of 75%, emission
factor (K2) is 1.35 ton/MWh.
REFERENCES
[1]Carpinelli, G.; Celli, G.; Pilo, F.; Russo, A. "Distributed Generation Siting and Sizing
Under Uncertainty", IEEE Power Tech Proceedings, Vol. 4, 2001.
[2]Arijit Bhowmik, Arindam Maitra, S. Mark Halpin, and Joe E. Schatz, "Determination of
Allowable Penetration levels of Distributed Generation Resources Based on Harmonic Limit
Considerations", IEEE Transactions On Power Delivery, Vol. 18, April 2003.
[3]Panagis N. Vovos, Aristides E. Kiprakis, A. Robin Wallace and Gareth P. Harrison,
"Centralized and Distributed Voltage Control: Impact on Distributed Generation
Penetration", IEEE Transactions On Power Systems, Vol. 22, February 2007.
[4]Joos G., Ooi B.T.; McGillis D.; Galiana F.D. and Marceau R.; "The Potential of
Distributed Generation to provide Ancillary Services", IEEE Power Engineering Society
Summer Meeting, Vol. 3, July 2000.
[5]Walid El-Khattam, Kankar Bhattacharya, Yasser Hegazy,and M. M. A. Salama, "Optimal
Investment Planning for Distributed Generation in a Competitive Electricity Market". IEEE
Transactions on power systems, Vol. 19, August 2004.
[6]Panagis N. Vovos, Aristides E. Kiprakis, A. Robin Wallace, and Gareth P. Harrison.
"Centralized and Distributed Voltage Control: Impact on Distributed Generation
Penetration". IEEE Transactions on power systems, Vol. 22, February 2007.
[7]T. Griffin, K. Tomsovic, and D. Secrest A. Law. "Placement of Dispersed Generations
Systems for Reduced Losses". Proceedings of the 33rd Hawaii international Conference on
System Sciences – 2000.
[8]Walid El-Khattam, Y.G Hegazy,and M. M. A. Salama, "An Integrated Distributed
Generation Optimization Model for Distribution System Planning". IEEE Transactions on
power systems, Vol. 20, May 2005.
[9]Hasan Hedayati, S. A. Nabaviniaki, and Adel Akbarimajd. "A Method for Placement of
DG Units in Distribution Networks". IEEE Transactions on power delivery, Vol. 23, July
2008.
International Journal of Electrical Engineering and Technology (IJEET), ISSN 0976 –
6545(Print), ISSN 0976 – 6553(Online) Volume 4, Issue 3, May - June (2013), © IAEME
18
[10]Enrico Carpaneto, Gianfranco Chicco, and Jean Sumaili Akilimali, "Branch Current
Decomposition Method for Loss Allocation in Radial Distribution Systems With Distributed
Generation", IEEE Transactions On Power Systems, Vol. 21, August 2006.
[11]Shangyou Hao. "A Reactive Power Management Proposal for Transmission Operators".
IEEE IEEE Transactions On Power Systems, Vol. 18, November 2003.
[12]Intergovernmental panel on climate change (IPCC) guidelines for national greenhouse
gas inventories. (www.ipcc-nggip.iges.or.jp)
[13]United Nations Environment Programme (UNEP) guidelines for calculating greenhouse
gas emissions for buisness and non commercial organizations.
(www.unep.org/publications/ebooks)
[14] Dr.T.Ananthapadmanabha, Maruthi Prasanna.H.A., Veeresha.A.G. and Likith Kumar.
M. V, “A New Simplified Approach for Optimum Allocation of a Distributed Generation
Unit in the Distribution Network for Voltage Improvement and Loss Minimization”,
International Journal of Electrical Engineering & Technology (IJEET), Volume 4, Issue 2,
2013, pp. 165 - 178, ISSN Print : 0976-6545, ISSN Online: 0976-6553.
[15] Om Prakash Mahela and Sheesh Ram Ola, “Optimal Placement and Sizing of Ht Shunt
Capacitors for Transmission Loss Minimization and Voltage Profile Improvement: The Case
Of Rrvpnl Power Grid”, International Journal of Electrical Engineering & Technology
(IJEET), Volume 4, Issue 2, 2013, pp. 261 - 273, ISSN Print : 0976-6545, ISSN Online:
0976-6553.
[16] S.Neelima and Dr. P.S.Subramanyam, “Effect of Load Levels on Sizing and Location of
Capacitors in Distribution Systems”, International Journal of Electrical Engineering &
Technology (IJEET), Volume 3, Issue 3, 2012, pp. 31 - 42, ISSN Print : 0976-6545,
ISSN Online: 0976-6553

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Inclusion of environmental constraints into siting and sizing

  • 1. International Journal of Electrical Engineering and Technology (IJEET), ISSN 0976 – 6545(Print), ISSN 0976 – 6553(Online) Volume 4, Issue 3, May - June (2013), © IAEME 1 INCLUSION OF ENVIRONMENTAL CONSTRAINTS INTO SITING AND SIZING TECHNIQUES FOR LOCALIZED GAS TURBINES DISTRIBUTED GENERATION Ibrahim Helal 1 , Mohamed Abdel-Rahman 2 , MayYoussry 3 1 Department of Electrical Engineering, Ain Shams University 2 Department of Electrical Engineering, Ain Shams University 3 Egyptian Electricity Utility & Consumer Protection, Regulatory Agency ABSTRACT The restructuring of electricity markets resulted in an increasing amount of distributed generation (DG) connected to the distribution networks to face load growth and demand bottlenecks. The typical approach to meet the increasing demand is to build additional central power generating stations or to expand the existing ones. Transmission and distribution T&D networks, in such a case, represent significant cost both fixed and running. In contrary, the DG can provide better service at lower cost in many applications by avoiding the extra cost, besides providing higher reliability level for customers. One of the used technologies for DG is the gas turbine technology. The problem, however, with DG is to reach the optimal sizing and siting of the units. As well as the environmental impact produced by the exhaust gases of the DG units. In order to ensure the environmental benefits of the DG units, this paper investigates the inclusion of emissions as a constraint of the DG siting and sizing process with present siting and sizing techniques. Consequently, this paper introduces the emissions environmental constraint based on: (i) the units emission factors, (ii) the power supplied by the network and (iii) the power supplied by the DG units. The model has been applied to a real case system data. Keywords: Distributed generation (DG), optimal placement, optimal power flow, sizing & siting of DG units, CO2 emissions, and emission factors. INTERNATIONAL JOURNAL OF ELECTRICAL ENGINEERING & TECHNOLOGY (IJEET) ISSN 0976 – 6545(Print) ISSN 0976 – 6553(Online) Volume 4, Issue 3, May - June (2013), pp. 01-18 © IAEME: www.iaeme.com/ijeet.asp Journal Impact Factor (2013): 5.5028 (Calculated by GISI) www.jifactor.com IJEET © I A E M E
  • 2. International Journal of Electrical Engineering and Technology (IJEET), ISSN 0976 – 6545(Print), ISSN 0976 – 6553(Online) Volume 4, Issue 3, May - June (2013), © IAEME 2 List of Symbols DG Distributed generation f(x) The objective function G(x) The equality constraints H(x) The inequality constraints i The bus index N The total number of system buses C1 The active power component in the unit investment cost (Egyptian Pound/MW/hr). C2 The reactive power component in the unit investment cost (Egyptian Pound/MVAr/hr). Pgi max The maximum active that can be generated (MW). Qgi max The maximum reactive power that can be generated (MVAr). C3 The running cost of generated reactive power (Egyptian Pound/MVAr/hr). Pgi The active DG generated power (MW). Qgi The reactive DG generated power (MVAr). C4 The market price for active power (Egyptian Pound/MWh/hr). C5 The market price for reactive power (Egyptian Pound/MVAr/hr). Ps The system active power (MW). Qs The system active power (MVAr). Ploss The active power losses (MW). Qloss The reactive power losses (MVAr). PD The active power demand (MW). QD The reactive power demand (MVAr). Ps max the max distribution substation capacity (MW). ∆Vi Maximum permissible voltage drop at bus i. pfi Power Factor of DG unit at bus i. K1 CO2 emission factor of the centralized power stations. K2 Gas turbine CO2 emission factor. Psb The system power for the base case without using any DG units (MW). FE The fuel energy (GJ) FQ Fuel quantity (ton/year). FHV Fuel heating value (GJ/ton). EQ Emission quantity in (ton/year). ER Emission rate in (ton/GJ). EQVCO2 The equivalent CO2 emission quantity (ton/year). GWP Global warming potential factor. EF The emission factor (ton /year). ECO2 CO2 emissions in (ton/GWh). GGE Gross generated energy (GWh/year). 1. INTRODUCTION A typical power system has hierarchical structure composed of generation, transmission and distribution. Under the move towards deregulation, individual entities may be allowed to generate power on the distribution level, given the attainment of the required licenses from the concerned regulatory body [1]-[3].
  • 3. International Journal of Electrical Engineering and Technology (IJEET), ISSN 0976 – 6545(Print), ISSN 0976 – 6553(Online) Volume 4, Issue 3, May - June (2013), © IAEME 3 The trend of distributed generation started to emerge in the beginning of this century [4]. Internal combustion engines, micro turbines, combustion gas turbines, fuel cells, photo voltaic solar panels and wind turbines are examples of distributed generation technologies [1]-[3]. Renewable resources are gaining popularity. However, still fossil fuel dependent technologies are wide spread and in large use. Therefore, a concern may arise is to ensure that the spread of fossil fuel generators, including gas turbines technology, does not result in environmental deterioration. In order to reach an optimum distribution networks as far as energy losses are concerned, distribution companies have to perform detailed studies to ensure optimal planning and operation of their systems, should they decide to use distributed generation. The choice of the candidate load buses to install DG units and the determination of their corresponding capacities is typically a problem that undergoes extensive investigations to ensure the optimal network operation, i.e. minimum losses and costs with power quality and reliability improvement. Nevertheless, the earlier methods stopped short from considering the environmental impact on the siting and sizing of DG units. In order to fill this gap, this paper proposes considering the environmental impact of DG in the form of an emissions constraint. The paper presents a formulation methodology to consider the emissions both from the DG units and the centralized network. The approach is dependent on the utilization of emission factors for both the centralized and decentralized units. The developed methodology has been applied to a practical power network of 106 distribution drop points, assuming that all DG units are of the same type. The paper is structured in five sections including this introductory section. Section II presents a DG generic siting and sizing model with technical constraints to obtain the optimal sizing and siting of the DG units. Section III depicts the environmental constraint formulation. Section IV applies the proposed concept to Case study network configurations. The conclusions are summarized in Section V. 2. (DG) GENERIC OPTIMIZATION MODEL DESCRIPTION Fig. (1) shows a typical DG connection topology. The connected loads are served by both the DG and the distribution network. The mode of operation may differ from one case to another. It may be peak shaving in one case, or base load in another. The customer side may even engage in an import and export of energy with the network. For this proposal, it is assumed that the local generation supplies the base load whereas the network covers the rest of the demand as well as the system losses. Fig. (1) A typical DG, load and network topology
  • 4. International Journal of Electrical Engineering and Technology (IJEET), ISSN 0976 – 6545(Print), ISSN 0976 – 6553(Online) Volume 4, Issue 3, May - June (2013), © IAEME 4 The mathematical formulation of the optimization, for the siting and sizing of DG units, problem results in a system of non linear algebraic equations [5], and [6]. The objective function is to minimize both the hourly cost including losses and capital costs of the system. The model considers load flow equations, system constraints. Provided the non-linearity of the objective function and the constraints, the optimal solution of the model is achieved iteratively, e.g., gradient method. In all cases, a feasible solution must not violate system constraints such as capacity limits of active and reactive power sources and environmental restrictions. The model solution provides the optimal sizing of the DG units. Nevertheless, many sizing and siting methods have been developed to optimize system operation [7], and [9]. The loss reduction technique is used in this work to find the candidate load buses for DG installation [7]. A complementary technique should be used to find out the optimal location of the optimal DG size. The problem is a general minimization problem with constraints modeled as in Equation (1). [5], and [6] Minimize f(x) Subject to: g(x) = 0 (1) h(x) ≤ 0 Where x is the vector of control and state variables. Control variables are DG active and reactive power outputs. The state variables are voltage and angles of load buses. For this work all DG units are assumed to be gas units and have similar characteristics. Following are the details of the optimization model. 2.1 Objective Function Formulation The objective function presents: (i) the investment cost, (ii) the running cost of the DG units, (iii) the cost of the electrical power supplied by the utility and (iv) the cost associated with network losses. The individual components of the objective function are: 2.1.1 DG fixed cost The fixed cost of distributed generation is n f = ∑ (c1Pgi max +c2Qgi max ) (Egyptian Pound/hr) (2) i=1 2.1.2 DG running cost The running cost of the distributed generation is n f = ∑ (ai + biPgi + ciPgi 2 ) + c3Qgi Egyptian Pound/hr) (3) i=1 (3) is a quadratic cost function expressing the DG running costs due to active power generation where, ai, bi and ci are the generator constants in Egyptian Pound/hr, Egyptian Pound/MW/hr and Egyptian Pound/MW2 /hr. 2.1.3 Cost of system power The cost of the utility supplied power is f = c4Ps + c5Qs (Egyptian Pound/hr) (4)
  • 5. International Journal of Electrical Engineering and Technology (IJEET), ISSN 0976 – 6545(Print), ISSN 0976 – 6553(Online) Volume 4, Issue 3, May - June (2013), © IAEME 5 2.1.4 Cost of system losses The system losses cost is f = c4Ploss + c5Qloss (Egyptian Pound/hr) (5) Where, Ploss and Qloss are calculated from load flow analysis as the algebraic sum of active and reactive power losses in all system branches [10]. Therefore, the final form of the objective function is n f(x) = ∑ (c1Pgi max +c2Qgi max ) i=1 n + ∑ (ai + biPgi + ciPgi 2 ) i=1 + c3Qgi + c4Ps + c5Qs + c4Ploss + c5Qloss (Egyptian Pound/hr) (6) 2.2 Equality Constraints The equality constraints g(x) are represented by the power balance constraints, where the total active power generation must cover the total power demand and the power losses as in n n ∑Pgi + Ps = ∑PDi + Ploss (7) i=1 i=1 The same applies for reactive power, where the reactive power supplied by the generators should be in balance with the reactive power consumed or produced throughout the system. Nevertheless, for reactive power flow and voltage stability considerations, this balance should not only be globally attained throughout the system but should hold at each bus within the network n n ∑Qgi + Qs = ∑QDi + Qloss (8) i=1 i=1 The demand data PDi & QDi are given. They can be hourly values. Nevertheless, this requires reformulating the whole problem as a sum for the whole study period. For the sake of simplicity and being on the conservative side, PDi and QDi are considered at the system peak to represent the system most severe operating conditions. 2.3 Inequality Constraints The inequality constraints h(x) reflect the limits of DG as well as the limits needed to ensure system security. (9) to (13) represent the inequality constrains of the optimization model. The upper and lower bounds of DG generated power (Pg &Qg) are Pgi min ≤ Pgi ≤ Pgi max (9) Qgi min ≤ Qgi ≤ Qgi max (10) The upper limit of substation capacity is Ps ≤ Ps max (11) Other technical constraints such as voltage & Power factor limits are also considered in this model. Maximum permissible voltage drop is ∆Vi ≤ 0.01 p.u (12)
  • 6. International Journal of Electrical Engineering and Technology (IJEET), ISSN 0976 – 6545(Print), ISSN 0976 – 6553(Online) Volume 4, Issue 3, May - June (2013), © IAEME 6 The conservative value of the voltage limit is to compensate for the simplifications and uncertainties in the developed approach and the used parameters. Power factor constraint According to the main stream of operation guidelines worldwide, the load power factor is limited between 0.95 leading to 0.90 lagging power factors [11]. -0.95 ≤ pfi ≤ 0.9 (13) 3. ENVIRONMENTAL CONSTRAINT FORMULATION All DG units and centralized power stations produce significant amounts of CO2 emissions. Therefore, an environmental constraint is considered in the DG optimization model to ensure that using DG units will not result in the increase of the total system emissions. The environmental constraint is n K1Ps + ∑K2Pgi ≤ K1Psb (14) i=1 It is assumed to be a linear inequality constraint based on the emission factors of both centralized and DG units. To calculate the emission factors for both centralized power stations and DG units, both fuel energy and emission quantities must be determined. The Fuel energy is FE = FQ * FHV (15) In some cases the centralized power stations use different types of fuel. In this case fuel energy is calculated for each fuel type separately according to its heating value. The emission quantity for each fuel type is EQ = ER * FE (16) Appendix (A) summarizes the emission rate for each fuel type. Consequent to emission quantity calculation for each fuel type, all greenhouse gases emissions are converted to their equivalent CO2 as follows EQVCO2 = GWP * EQ (17) Where, GWP for each greenhouse gas emission is listed in Appendix (B). Upon converting all greenhouse gases emissions to their equivalent CO2 emissions, emission factor is easily calculated by EF =ECO2 / GGE (18) Where ECO2 is the total equivalent annual CO2 emissions and GGE is the total annual generated energy. 4. CASE STUDY The optimization model described in the preceding sections has been applied to a distribution network in a typical industrial zone. Appendix (C) depicts the utilized sizing and siting approach. The cost data are given in Appendix (D). Fig. (2) shows the distribution network considered for the case study. The network consists of 106 buses and 116 power lines of 11 KV.
  • 7. International Journal of Electrical Engineering and Technology (IJEET), ISSN 0976 – 6545(Print), ISSN 0976 – 6553(Online) Volume 4, Issue 3, May - June (2013), © IAEME 7 Bus number (1) represents the transmission substation. It is considered as the slack bus. Buses number (43), (67) and (91) are P-V buses (generator bus) with a controlled voltage of (1p.u). The generated power at each bus of the P-V buses is assumed to be one forth of the total loads. All other buses are considered P-Q buses as the loads are known, with 0.85 power factor. The base voltage is 11 KV. The base power is 100 MVA. Analysis is carried out at system peak load as it is the worst operational condition. The results are summarized in the following sections. Fig. (2) Case Study Distribution Network 4.1 Base Case Solution (without DG) The load flow solution for the base case (without DG) is summarized below: • The delivered power by the utility is equal to 50.6 MW. • System active losses are 5.5 MW. • The system CO2 emission is 58 ton/hr. • The initial cost is 6740Egyptian Pound/hr.
  • 8. International Journal of Electrical Engineering and Technology (IJEET), ISSN 0976 – 6545(Print), ISSN 0976 – 6553(Online) Volume 4, Issue 3, May - June (2013), © IAEME 8 As can be noticed in Table (1) buses (from bus no (50) to bus no (63) & from (67) to (90)) exceed the lower limit of voltage by 1% (the permissible level is from 0.99 to 1.01 p.u.). Table (1) Initial Bus Voltage Bus No. |V| Bus No. |V| Bus No. |V| 1 1.00 37 1.00 73 0.98 2 0.99 38 1.00 74 0.98 3 0.99 39 1.00 75 0.98 4 0.99 40 1.00 76 0.98 5 0.99 41 1.00 77 0.98 6 0.99 42 1.00 78 0.98 7 0.99 43 1.00 79 0.98 8 0.99 44 1.00 80 0.98 9 0.99 45 1.00 81 0.98 10 0.99 46 1.01 82 0.98 11 0.99 47 1.01 83 0.98 12 0.99 48 1.01 84 0.98 13 0.99 49 0.99 85 0.98 14 0.99 50 0.98 86 0.98 15 0.99 51 0.98 87 0.98 16 0.99 52 0.98 88 0.98 17 0.99 53 0.98 89 0.98 18 0.99 54 0.98 90 0.98 19 0.99 55 0.98 91 1.00 20 0.99 56 0.98 92 1.01 21 0.99 57 0.98 93 1.01 22 0.99 58 0.98 94 1.00 23 0.99 59 0.98 95 1.00 24 0.99 60 0.98 96 1.00 25 0.99 61 0.98 97 1.00 26 0.99 62 0.98 98 1.01 27 0.99 63 0.98 99 1.01 28 0.99 64 0.99 100 1.01 29 0.99 65 0.99 101 1.01 30 0.99 66 0.99 102 1.01 31 0.99 67 1.00 103 1.01 32 0.99 68 0.98 104 1.01 33 0.99 69 0.98 105 1.01 34 0.99 70 0.98 106 1.01 35 0.99 71 0.98 36 0.99 72 0.98 4.2 Optimal sizing & siting without environmental constraints DG units are ranked according to their impact on the system losses reduction. The DG unit at certain bus that reduces system losses most effectively has the highest priority. DG units are installed one by one at the candidate load buses according to their priorities till the system losses are constant or increased. Table (2) shows the ranking of the system load buses according to their effect on losses reduction after applying a generation of 10 MW at each bus.
  • 9. International Journal of Electrical Engineering and Technology (IJEET), ISSN 0976 – 6545(Print), ISSN 0976 – 6553(Online) Volume 4, Issue 3, May - June (2013), © IAEME 9 Table (2) Bus Ranking Bus No. Ploss (MW) Ranking Bus No. Ploss (MW) Ranking Bus No. Ploss (MW) Ranking 1 Slack Bus ---- 28 5.54 63 55 4.92 39 2 5.39 49 29 5.54 64 56 4.92 38 3 5.25 46 30 5.54 65 57 4.92 35 4 5.54 53 31 5.54 66 58 4.92 36 5 5.54 54 32 5.54 67 59 4.87 25 6 5.54 55 33 5.54 68 60 4.84 20 7 5.54 56 34 5.54 69 61 4.87 27 8 5.54 57 35 5.54 70 62 4.86 24 9 5.54 58 36 5.54 71 63 4.88 28 10 5.54 59 37 5.54 Rejected 64 5.11 40 11 5.54 60 38 5.55 Rejected 65 5.17 42 12 5.54 61 39 5.55 Rejected 66 5.22 44 13 5.54 62 40 5.55 Rejected 67 Gen. Bus --- 14 5.54 Rejected 41 5.56 Rejected 68 4.84 21 15 5.54 Rejected 42 5.56 Rejected 69 4.84 19 16 5.54 Rejected 43 4.91 30 70 4.87 26 17 5.54 Rejected 44 5.15 41 71 4.81 16 18 5.54 Rejected 45 5.19 43 72 4.82 18 19 5.54 Rejected 46 5.24 45 73 4.85 22 20 5.54 Rejected 47 Gen. Bus --- 74 4.77 2 21 5.54 Rejected 48 5.32 47 75 4.77 3 22 5.54 Rejected 49 4.91 31 76 4.77 4 23 5.54 Rejected 50 4.89 29 77 4.77 5 24 5.54 Rejected 51 4.92 37 78 4.77 6 25 5.54 Rejected 52 4.92 32 79 4.77 1 26 5.54 Rejected 53 4.92 33 80 4.77 7 27 5.54 Rejected 54 4.92 34 81 4.77 9 DG units are installed one by one at the load buses according to their ranking priorities, while losses are calculated at each run as depicted in Table (3). Losses are decreasing due to DG installation until bus number (89). At this bus the losses start to increase. Therefore, as indicated in the table, buses no (79, 74, 75, 76, 77, 78, 80, 82, 81, 83, 84, 87, 85, 88, 86 & 71) are the candidate optimal buses to locate the DG.
  • 10. International Journal of Electrical Engineering and Technology (IJEET), ISSN 0976 – 6545(Print), ISSN 0976 – 6553(Online) Volume 4, Issue 3, May - June (2013), © IAEME 10 Table (3) Results of siting DG units at each bus DG Siting Ploss (MW) Ps (MW) Siting DG at Bus (79) 5.4 49.5 Siting DG at Bus (79)&(74) 5.3 48.4 Siting DG at Bus (79),(74)&(75) 5.1 47.2 Siting DG at Bus (79),(74),(75)&(76) 5 46.1 Siting DG at Bus (79),(74),(75),(76)&(77) 4.9 45 Siting DG at Bus (79),(74),(75),(76),(77) &(78) 4.8 43.9 Siting DG at Bus (79),(74),(75),(76),(77),(78) &(80) 4.7 42.8 Siting DG at Bus (79),(74),(75),(76),(77),(78), (80) &(82) 4.6 41.7 Siting DG at Bus (79),(74),(75),(76),(77),(78) ,(80) ,(82)&(81) 4.5 40.6 Siting DG at Bus (79),(74),(75),(76),(77),(78) ,(80), (82),(81)&(83) 4.34 39.44 Siting DG at Bus (79),(74),(75),(76),(77),(78), (80) ,(82),(81),(83)&(84) 4.3 38.4 Siting DG at Bus (79),(74),(75),(76),(77),(78), (80) ,(82),(81),(83),(84)&(87) 4.25 37.4 Siting DG at Bus (79),(74),(75),(76),(77),(78), (80), (82),(81),(83),(84),(87)&(85) 4.2 36.3 Siting DG at Bus (79),(74),(75),(76),(77),(78), (80) ,(82),(81),(83),(84),(87),(85)&(88) 4.1 35.2 Siting DG at Bus (79),(74),(75),(76),(77),(78), (80) ,(82),(81),(83),(84),(87),(85),(88)&(86) 4.08 34.18 Siting DG at Bus (79),(74),(75),(76),(77),(78), (80), (82),(81),(83),(84),(87),(85),(88),(86) &(71) 3.9 33 Siting DG at Bus (79),(74),(75),(76),(77),(78), (80), (82),(81),(83),(84),(87),(85),(88),(86) ,(71)&(89) 4 32.1 Consequent to siting DG units at candidate buses, optimization model is run to obtain the proposed DG capacity at each bus. A standard size of 1MW is selected for each DG unit. The optimal solution in this case is to generate the maximum capacity of DG units at all buses. Table (4) shows that the voltages drop for all buses after installing DG units are within the permissible limits.
  • 11. International Journal of Electrical Engineering and Technology (IJEET), ISSN 0976 – 6545(Print), ISSN 0976 – 6553(Online) Volume 4, Issue 3, May - June (2013), © IAEME 11 Table (4) Bus voltages after installing DG Bus No. |V| Bus No. |V| Bus No. |V| 1 1.00 37 1.00 73 0.99 2 0.99 38 1.00 74 0.99 3 0.99 39 1.00 75 0.99 4 0.99 40 1.00 76 0.99 5 0.99 41 1.00 77 0.99 6 0.99 42 1.00 78 0.99 7 0.99 43 1.00 79 0.99 8 0.99 44 1.00 80 0.99 9 0.99 45 1.01 81 0.99 10 0.99 46 1.01 82 0.99 11 0.99 47 1.01 83 0.99 12 0.99 48 1.01 84 0.99 13 0.99 49 0.99 85 0.99 14 1.00 50 0.99 86 0.99 15 0.99 51 0.99 87 0.99 16 0.99 52 0.99 88 0.99 17 0.99 53 0.99 89 0.99 18 0.99 54 0.99 90 0.99 19 0.99 55 0.99 91 1.00 20 0.99 56 0.99 92 1.01 21 0.99 57 0.99 93 1.01 22 0.99 58 0.99 94 1.01 23 0.99 59 0.99 95 1.01 24 0.99 60 0.99 96 1.01 25 0.99 61 0.99 97 1.01 26 0.99 62 0.99 98 1.01 27 0.99 63 0.99 99 1.01 28 0.99 64 0.99 100 1.01 29 0.99 65 0.99 101 1.01 30 0.99 66 0.99 102 1.01 31 0.99 67 1.00 103 1.01 32 0.99 68 0.99 104 1.01 33 0.99 69 0.99 105 1.01 34 0.99 70 0.99 106 1.01 35 0.99 71 0.99 36 0.99 72 0.99 After installing DG units at the candidate load buses the system supplied power is 33 MW. The system active losses are 3.9 MW. The system losses in this case are reduced by nearly 29% compared to the base case. The system hourly cost is 6350 Egyptian Pound/hour. Cost reduction due to DG installation is 6%. The CO2 emissions are 59.5 ton/hr which is increased by 2.7 %.
  • 12. International Journal of Electrical Engineering and Technology (IJEET), ISSN 0976 – 6545(Print), ISSN 0976 – 6553(Online) Volume 4, Issue 3, May - June (2013), © IAEME 12 4.3 Optimal sizing and siting with environmental constraints The system shown in Fig. (2) is tested while considering the environmental constraints. The emission factors for both central power station and DG units are calculated in Appendix (E). Table (5) summarizes the results of adding DG unit to the candidate load buses according to their priorities in Table (2). Table (5) Siting DG units at each bus under environmental constraint DG Siting Ploss (MW) Ps (MW) Siting DG at Bus (79) 5.5 50.2 Siting DG at Bus (79)&(74) 5.4 49.4 Siting DG at Bus (79),(74)&(75) 5.35 49.6 Siting DG at Bus (79),(74),(75)&(76) 5.27 49.1 Siting DG at Bus (79),(74),(75),(76) &(77) 5.2 47.8 Siting DG at Bus (79),(74),(75),(76) ,(77) &(78) 5.1 46.4 Siting DG at Bus (79),(74),(75),(76) ,(77),(78)&(80) 5.1 46.4 These results indicate that system losses become constant after installing DG at bus (80), while the optimal DG capacities are obtained and tabulated in Table (6). Table (6) Results of the DG optimization model for the case study with environmental constraints. Bus No. Pg (MW) Qg (MVAR) Generator at bus (79) 1 0.484 Generator at bus (74) 0 0 Generator at bus (75) 1 0.484 Generator at bus (76) 0.95 0.48 Generator at bus (77) 0 0 Generator at bus (78) 0.7 0.349
  • 13. International Journal of Electrical Engineering and Technology (IJEET), ISSN 0976 – 6545(Print), ISSN 0976 – 6553(Online) Volume 4, Issue 3, May - June (2013), © IAEME 13 The results show that system losses are 5.1 MW. Losses reduction is 7.3%. System costs are 6618 Egyptian Pound/hr. The system hourly costs are reduced by 1.8%. System CO2 emission is 57.7 ton/hr after installing DG, i.e. no violation for the environmental constraints. The cost reduction may be lower than the case in section C (without environmental constraints). This shows that under environmental restrictions DG may not impact system cost reduction effectively. However, technical losses reduction and voltage profile improvement are evident. Table (7) shows voltage levels of the system after installing DG units at the candidate load buses. All voltage tolerances are within the permissible limits of ±1%. Table (7) Bus voltages after installing DG under environmental constraint Bus No. |V| Bus No. |V| Bus No. |V| Bus No. |V| 1 1.00 28 0.99 55 0.99 82 0.99 2 0.99 29 0.99 56 0.99 83 0.99 3 0.99 30 0.99 57 0.99 84 0.99 4 0.99 31 0.99 58 0.99 85 0.98 5 0.99 32 0.99 59 0.99 86 0.98 6 0.99 33 0.99 60 0.98 87 0.99 7 0.99 34 0.99 61 0.99 88 0.99 8 0.99 35 0.99 62 0.99 89 0.98 9 0.99 36 0.99 63 0.99 90 0.98 10 0.99 37 1.00 64 0.99 91 1.00 11 0.99 38 1.00 65 0.99 92 1.00 12 0.99 39 1.00 66 0.99 93 1.01 13 0.99 40 1.00 67 1.00 94 1.00 14 1.00 41 1.00 68 0.99 95 1.00 15 0.99 42 1.00 69 0.98 96 1.00 16 0.99 43 1.00 70 0.99 97 1.00 17 0.99 44 1.00 71 0.99 98 1.01 18 0.99 45 1.00 72 0.99 99 1.01 19 0.99 46 1.01 73 0.99 100 1.01 20 0.99 47 1.01 74 0.99 101 1.01 21 0.99 48 1.01 75 0.99 102 1.01 22 0.99 49 0.99 76 0.99 103 1.01 23 0.99 50 0.99 77 0.99 104 1.01 24 0.99 51 0.99 78 0.99 105 1.01 25 0.99 52 0.99 79 0.98 106 1.01 26 0.99 53 0.99 80 0.99 27 0.99 54 0.99 81 0.99
  • 14. International Journal of Electrical Engineering and Technology (IJEET), ISSN 0976 – 6545(Print), ISSN 0976 – 6553(Online) Volume 4, Issue 3, May - June (2013), © IAEME 14 5. CONCLUSIONS In this paper a formulation for the environmental impact of DG is introduced. The emissions are evaluated based on the use of conversion factors. An additional constraint is added to the optimization planning problem. The approach is based on the minimization of total system cost (capital and operational) subject to particular constraints related to system and units' capacities, operational performance and CO2 emission. The model is applied to a real distribution network composed of 106 distribution drop points. Optimal sizing and siting of the DG units is obtained by solving the environmentally constrained optimization model. The results show that without violating the permissible CO2 emission level, DG still can provide lower cost and losses together with complementary power supply to local loads on the level of distribution networks. Appendix A Emission Factors for electric utility and industrial combustion systems [12] Emission Rates (g/GJ energy input) Utility applications CO2 CO CH4 NOX N2O Natural gas boilers 56100 19 0.1 267 N/A Gas turbine, combined cycle 56100 32 6.1 187 N/A Gas turbine, simple cycle 56100 32 5.9 188 N/A Residual oil boilers 77350 15 0.7 201 N/A Distillate oil boilers 74050 15 0.03 69 N/A Coal, spreader stoker 94600 121 0.7 326 0.8 Coal, fluidized bed 94600 N/A 0.6 255 N/A Coal, pulverized 94600 14 0.6 857 0.8 Coal, tangentially fired 94600 14 0.6 330 0.8 Coal, pulverize, wall fired 94600 14 0.6 461 0.8 Wood-fired boilers 26260 147 0.8 112 N/A
  • 15. International Journal of Electrical Engineering and Technology (IJEET), ISSN 0976 – 6545(Print), ISSN 0976 – 6553(Online) Volume 4, Issue 3, May - June (2013), © IAEME 15 Appendix B Global Warming Potential Factors [13] Trace Gas GWP Trace Gas GWP Carbon Dioxide 1 HFC-134 1,000 CCl 4 1300 HFC-134a 1300 CFC- 11 3400 HFC-143 300 CFC-113 4500 HFC-143a 3800 CFC-116 >6200 HFC-152a 140 CFC-12 7100 HFC-227ea 2900 CFC-l 14 7000 HFC-23 9800 CFC-l 15 7000 HFC-236fa 6300 Chloroform 4 HFC-245ca 560 HCFC- 123 90 HFC-32 650 HCFC- 124 430 HFC-41 150 HCFC-141b 580 HFC-43-lOmee 1,300 HCFC-142b 1600 Methane 21 HCFC-22 1600 Nitrous Oxide 310 HFC- 125 2800 Sulphur hexafluoride 23900 Appendix C DG Sizing & Siting Technique Many approaches have been developed to determine optimal sizing and siting of DG units in electrical distribution networks. The losses-reduction-based technique [7] is used in this paper to determine the candidate load buses for DG installation. This technique considers primarily considers the DG impact on total system losses reduction. The bus that reduces system losses most effectively will have the highest priority for distributed generation installation. Consequent to the choice of the DG candidate buses, the optimization model is used to determine the distributed generation units' output powers. The optimal siting can be determined as listed below.
  • 16. International Journal of Electrical Engineering and Technology (IJEET), ISSN 0976 – 6545(Print), ISSN 0976 – 6553(Online) Volume 4, Issue 3, May - June (2013), © IAEME 16 Step 1 Perform load flow calculations to obtain the initial conditions of the system, i.e. power supplied by the system and system losses. Step 2 Start with adding a generation of 10 MW at each bus, only one bus at a time, and recalculate system losses each time. This capacity is justified as being a typical unit capacity used to check the impact of DG units on loss reduction. Step 3 Rank system buses according to their effect on system losses reduction with higher rank for the bus having more impact on loss reduction. The buses that provide losses higher than the base case (without DG) should be rejected from the ranking list. Step 4 Add DG units at the load buses according to their priority obtained in step 3. Recalculate system losses after each installation until losses are seemed to be increased or constant. Step 5 Once the optimal siting is determined in step 4, the optimization model is solved to obtain the optimal sizing of DG at each of the optimal locations. Fig. (3) illustrates the main steps to obtain the optimal sizing of each DG unit at each bus. Fig. (3) A flowchart depicting the sizing technique utilized in the proposed approach C a lcu la te syste m lo sse s in th is ca se C h e ck syste m co n stra in ts S u b stitu te lo sse s in to o b je ctive fu nctio n M in im ize th e o b je ctive Fn S e le ct th e n e a re st sta n d a rd size o f D G u n its to th e o b ta in e d so lu tio n fo r e a ch b u s F in a l so lu tio n o b ta in e d R u n o p tim iza tio n m o d e l to fin d syste m co sts S to p N o Y e s S ta rt S e t in itia l va lu e s fo r P g i, Q gi, P s,Q s fo r th e o b jective fu n ctio n S o lve L o a d flo w e qn u sin g S a m e in itia l co n d itio n s
  • 17. International Journal of Electrical Engineering and Technology (IJEET), ISSN 0976 – 6545(Print), ISSN 0976 – 6553(Online) Volume 4, Issue 3, May - June (2013), © IAEME 17 Appendix D Cost Data Based on the case study, electricity price is subsidized such that the average price (csa) is 0.022 $/kWh. The reactive power cost is set to be equal zero in this case study. The gas turbine technology is used for DG units due to its low emissions. Investment cost of gas turbine vary from (600–900 $/KW). An average price of 750 $/KW is used. The payback period is assumed as 10 years. DG units operate as base load units, the total fixed DG costs is set to be 8.5 $/MW-hr. Operating and maintenance cost is assumed to be 0.0055 $/kWh. Price of natural gas is 0.045 $/m3 for the case study. The fuel consumption rate of DG is assumed to be 250 gm/kWh. Appendix E Applying Equation (15) to Equation (18), the central power station emission factor (K1) is equal to 1.14 ton/MWh. DG units are assumed to have fuel consumption rate of 250 gm/kWh, calorific heat value of 38.5 MJ, service hours of 8000 hrs and load factor of 75%, emission factor (K2) is 1.35 ton/MWh. REFERENCES [1]Carpinelli, G.; Celli, G.; Pilo, F.; Russo, A. "Distributed Generation Siting and Sizing Under Uncertainty", IEEE Power Tech Proceedings, Vol. 4, 2001. [2]Arijit Bhowmik, Arindam Maitra, S. Mark Halpin, and Joe E. Schatz, "Determination of Allowable Penetration levels of Distributed Generation Resources Based on Harmonic Limit Considerations", IEEE Transactions On Power Delivery, Vol. 18, April 2003. [3]Panagis N. Vovos, Aristides E. Kiprakis, A. Robin Wallace and Gareth P. Harrison, "Centralized and Distributed Voltage Control: Impact on Distributed Generation Penetration", IEEE Transactions On Power Systems, Vol. 22, February 2007. [4]Joos G., Ooi B.T.; McGillis D.; Galiana F.D. and Marceau R.; "The Potential of Distributed Generation to provide Ancillary Services", IEEE Power Engineering Society Summer Meeting, Vol. 3, July 2000. [5]Walid El-Khattam, Kankar Bhattacharya, Yasser Hegazy,and M. M. A. Salama, "Optimal Investment Planning for Distributed Generation in a Competitive Electricity Market". IEEE Transactions on power systems, Vol. 19, August 2004. [6]Panagis N. Vovos, Aristides E. Kiprakis, A. Robin Wallace, and Gareth P. Harrison. "Centralized and Distributed Voltage Control: Impact on Distributed Generation Penetration". IEEE Transactions on power systems, Vol. 22, February 2007. [7]T. Griffin, K. Tomsovic, and D. Secrest A. Law. "Placement of Dispersed Generations Systems for Reduced Losses". Proceedings of the 33rd Hawaii international Conference on System Sciences – 2000. [8]Walid El-Khattam, Y.G Hegazy,and M. M. A. Salama, "An Integrated Distributed Generation Optimization Model for Distribution System Planning". IEEE Transactions on power systems, Vol. 20, May 2005. [9]Hasan Hedayati, S. A. Nabaviniaki, and Adel Akbarimajd. "A Method for Placement of DG Units in Distribution Networks". IEEE Transactions on power delivery, Vol. 23, July 2008.
  • 18. International Journal of Electrical Engineering and Technology (IJEET), ISSN 0976 – 6545(Print), ISSN 0976 – 6553(Online) Volume 4, Issue 3, May - June (2013), © IAEME 18 [10]Enrico Carpaneto, Gianfranco Chicco, and Jean Sumaili Akilimali, "Branch Current Decomposition Method for Loss Allocation in Radial Distribution Systems With Distributed Generation", IEEE Transactions On Power Systems, Vol. 21, August 2006. [11]Shangyou Hao. "A Reactive Power Management Proposal for Transmission Operators". IEEE IEEE Transactions On Power Systems, Vol. 18, November 2003. [12]Intergovernmental panel on climate change (IPCC) guidelines for national greenhouse gas inventories. (www.ipcc-nggip.iges.or.jp) [13]United Nations Environment Programme (UNEP) guidelines for calculating greenhouse gas emissions for buisness and non commercial organizations. (www.unep.org/publications/ebooks) [14] Dr.T.Ananthapadmanabha, Maruthi Prasanna.H.A., Veeresha.A.G. and Likith Kumar. M. V, “A New Simplified Approach for Optimum Allocation of a Distributed Generation Unit in the Distribution Network for Voltage Improvement and Loss Minimization”, International Journal of Electrical Engineering & Technology (IJEET), Volume 4, Issue 2, 2013, pp. 165 - 178, ISSN Print : 0976-6545, ISSN Online: 0976-6553. [15] Om Prakash Mahela and Sheesh Ram Ola, “Optimal Placement and Sizing of Ht Shunt Capacitors for Transmission Loss Minimization and Voltage Profile Improvement: The Case Of Rrvpnl Power Grid”, International Journal of Electrical Engineering & Technology (IJEET), Volume 4, Issue 2, 2013, pp. 261 - 273, ISSN Print : 0976-6545, ISSN Online: 0976-6553. [16] S.Neelima and Dr. P.S.Subramanyam, “Effect of Load Levels on Sizing and Location of Capacitors in Distribution Systems”, International Journal of Electrical Engineering & Technology (IJEET), Volume 3, Issue 3, 2012, pp. 31 - 42, ISSN Print : 0976-6545, ISSN Online: 0976-6553