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Optimal Placement of Capacitor Bank in Distribution Network in the Present of

Harmonic

Hablillah Bin Mohd hazim

Master of Electrical Engineering, University Technology of Malaysia Email: subzeerow@yahoo.com

ABSTRACT

There are varieties of optimization methods to solve the problem of optimal capacitor placement in distribution network. However, in the present of harmonic constrain; it’s still very less done. Most of the studies made for ideal conditions where the harmonics was not taking into account. However it should be remembered that the actual situation in distribution network, we cannot avoid the existence of harmonic. Hence this paper was written with regard to harmonic interference. Fuzzy logic (FL) used in this study because it was seen as the best method for a capacitor with constraints of only one placement in 18 bus distribution system. (Refer IEEE 18 bus circuit for test and simulation). The use of other complex methods such as Particle Swarm Optimization (PSO) , Genetic Arithmetic (GA) , Artificial Bee Colony (ABC) and other perceived more suitable for systems with hundreds or even more bus. Fuzzy Logic (FL) was used to obtain the best capacitor location and its value while Fast Decouple Load Flow (FDLF) is the mainstay in the study of system performance. Fuzzy Logic (FL) and Fast Decouple Load Flow (FDLF) conducted using m.file and validated using Power World. Further analysis is carried out to analyze the impact of capacitor in the presence of harmonics in the system which

may cause resonance by using SIMULINK software. This is completely different to the methods undertaken by researchers in the past where their study for the optimal capacitor placement in distribution networks in the presence of harmonics, done using harmonics power flow (HPF). It was very differ where this project based on the probability of the existence of resonance combined with usual fast decouple load flow (FDLF) methods.

INTRODUCTION 1.1 Introduction

Power flow studies are the basis of power system analysis and design associated with the distribution of power. It is very important for current operations, scheduling, and planning for the future economy. Performance analysis system primarily involving buses are very much needed coupled with the actual situation of the system which cannot run away from interfering of harmonic. Thus the use of computer software is an alternative in solving complex system. Enhanced by the use of new methods such as optimization to improve the voltage profile and reduce economic loss and therefore more economical.

Optimization method is broken down into four main categories which are analytical

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methods, numerical programming, artificial intelligence and heuristic methods. Each method is further divided into other parts. [1] As there are many optimization methods, thus critical reviews only made on six methods of ant colony (AC), simulation anneal (SA), fuzzy logic (FL), particle swarm optimization (PSO), artificial bee colony (ABC) and genetic algorithm (GA), which are all included in the category of Artificial Intelligent.

To express a deviation from a pure sine wave usually the term harmonics components is used .Together with the use of the term “Harmonics” is the name of the famous mathematician Fourier who developed a mathematical way to investigate a complex wave and to express it in a form that is simple and useful. Harmonics are harming many consumers in the power supply networks .According to new standards today the level of harmonics in the supply network is limited. Due to harmonics existence available power is reduced. These are the main reasons why nowadays we hear more about harmonics and other kind of disturbances in the power supply network. Together with the growth in awareness to harmonics, two phenomenon are: 1) Many people began to deal with harmonics. 2) Many new terms were added to the existing technical vocabulary. [2] 1.1.1 Resonance and Problem

Formulation

Resonance is defined as a situation where the impedance magnitude of the circuit exceeds the maximum or minimum allowed. Series resonance occurs in a series RLC circuit with the same inductive and capacitive values. This will cause the impedance to be low and the excitation voltage produces a high current. This current will flow against the source and continue to other routes that should not be.

The same situation occurs in parallel RLC circuit with the equal inductive and capacitive values. Resonance or close to

resonance phenomenon contributes to the many problems of harmonic disturbances occurring in the power system.

(a)

Figure 1.1: Resonance Circuit a) Series Resonance b) Parallel Resonance

Parallel resonance occurs when the

power system presents a parallel combination of power system inductance and power factor correction capacitors at the nonlinear load. The product of the harmonic impedance and injection current produces high harmonic voltages.

Series resonance occurs when the system inductance and capacitors are in series, or nearly in series, with respect to the nonlinear load point.

(a)

Figure1.2: Practical Example of Resonance Circuit

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Equation 1.1 to Equation 1.4 shows the formula that related to resonance that sued in this study.

푓 = 1

2휋√퐿퐶=

푓푤 √퐿퐶

= 푓푋푋 퐻푧

1.1 Where f1 is the fundamental frequency, XC is the capacitor’s reactance at the fundamental frequency, and XL is the inductor’s reactance at the fundamental frequency. Relations between harmonic resonance, hr , resonance frequency, fr and the fundamental frequency, f1 :

ℎ = 푓푓 =

푀푉퐴푀푉퐴 =

푀푉퐴푄 =

푋푋

1.2

푋 = 푋 ℎ = 퐾푉푄

1. 3 ℎ = ℎ

1.4

The resonance can cause nuisance tripping of sensitive electronic loads and high harmonic currents in feeder capacitor banks. In severe cases, can cause additional heating, capacitor failure, oscillating torque, increase losses, equipment degradation and loss of life. All circuits containing both capacitance and inductance have one or more natural resonant frequencies. When one of these frequencies corresponds to an exciting frequency being produced by nonlinear loads, harmonic resonance can occur. Voltage and current will be dominated by the resonance frequency and can be highly distorted. [3] 1.2 Problem Statement

The present of hormonic in distribution network are due to many causes and usually give negative impact neither to

generation side nor consumer side. All circuit containing capacitor and inductor has one or more resonance frequencies which is generated on the right frequency (called frequency resonance, fr) associated with the right reactance and capacitance in the system. High potential occuring of resonance due to existing of nonlinear load especially from power electronics devices. Resonance will course the harmonic current generated from nonlinear load propagate in the system coursing additional heating in the system, capacitor failure, oscillating torque, increasing losses, equipment degradation and loss of life. To improve the power and voltage profile, load flow need to study properly to find the performance of the system and additional of capacitor bank to the system usually necessary. Thus the additional of capacitor bank by considering its placement and its value in the system must avoid the occurring of resonance. 1.3 Objective and Scope

The main objective of this project is to find the optimal placement of capacitor bank in distribution network with the presence of harmonic by using the fuzzy logic (FL) where it is one of the optimization method.

The scope of the project is to use a fuzzy logic (FL) to find the value and the best location of capacitor placement where it must avoid the parallel and serial resonance from occur. The capacitor placement and it value aimed to improving the voltage profile with constrain 0.9 pu to 1.1 pu and reduce power loss. This capacitor placement and it value then analyzed to determine the potential of resonance from occur where the additional of serial reactance probably necessary which is base on Equation 1.1 until Equation 1.4 explained previously in Resonance and Problem Formulation, section 1.1.1.

To simplify the calculation and simulation, the connection will made only with using capacitor in parallel connection.

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Parallel connection is more practical in the event of damage to the capacitor; it will have less impact on the network than in series connection. Parallel capacitors are safer and more reliable than series connections. There is no advantage in total energy storage to choose one of these circuits over another. But! There may well be a time when you need lower capacitance such as a faster timing pulse and higher voltage than your parts on hand can provide. [4]

LITERATURE REVIEW 2.1 Ant Colony

An analogy between the way the ants finding food and combinatorial optimization has created a new computing paradigm called ant colony meta-heuristic. The ants are leave around some quantity an aromatic substance called pheromone, by observing the way they look for the best way to get the food. The quantity of pheromone depends on the path length and quality of food sources found. The ants choose a certain path which related to the intensity of the pheromone. Pheromone trail evaporates over time if no more pheromone is placed around it. Other ants can observe the pheromone trails which are attracted to follow. Therefore, the path is marked and will therefore attract more ants. Pheromone trail on the path that leads to the location of the food resource and close to the nest will become more frequent and therefore will grow faster. Thus, the best solution which has a denser pheromone, the higher probability being selected. The behavior described by real ant colonies can be used to solve combinatorial optimization problems by simulation; artificial ants searching the solution space base on simulated of real ant behavior to find their food location. Adapted to the objectives aimed the quality of the food source. [5]

Figure 2.1: Ant Colony Description

J.Nikoukar and M.Gandomkar from

Electrical Engineering Department, Islamic Azad University, Saveh, IRAN has been using this method for capacitor placement in distribution networks in present of harmonic with a selection of capacitor values between 5,10,15,25 kVar at a voltage of 380 V is carried out by 22 bus circuit radial distribution network where the cost constraints taking into account. Simulation using MATLAB. [6] 2.2 Simulation Anneal

Simulated annealing (SA) is based on the analogy with the annealing of metal or crystal. SA depends on three important parameters which are the initial temperature (T), cooling rate (β) and the final temperature (Tmin). The temperature is controlled by a

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cooling schedule at each iteration. Cold temperature is a focus on solutions. This situation is freely changing to other circumstances where the maximum temperature is limited; it next will change to low temperatures. Simulated annealing (SA) is a very powerful where as it has been used as a stochastic optimization technique. In theory, it could lead to a global optimization solution with probability one.

Figure 2.2: Simulation Anneal Description

Ramon A. Gallego, José Alcir

Monticelli, and Rubén Romero in their paper titled "Optimal Capacitor Placement in Radial Distribution Networks" using the Simulation Anneal (SA) as one of the method for the solution of non-polynomial problems. Hybrid solution approach uses Tabu Search and Simulated annealing (SA) performed at 135 buses and 9 bus systems with cost constraints are considered. For the case of a fixed capacitor placement, load flow for each load level in accordance with the objective function and feasible configuration is computed while the unfeasible configuration is removed. [7]

2.3 Particle Swarm Optimization

Particle swarm optimization (PSO) is a technique to search using a population of particles, corresponding to individuals. Each particle represents a candidate solution correlation to the problem of reactive power. In a Particle swarm optimization (PSO) system, particles change their positions by flying randomly in a multi-dimensional search

space until it reaches the position that has not changed, or until the limit is exceeded calculations.

Figure 2.3: Particle swarm optimization (PSO) Description

Paper titled "Optimal Capacitor Placement Considering Voltage-stability margin Particle Swarm Optimization with Hybrid" by Taegyun Kim and Lee Byongjun Hwachang Song using the Particle swarm optimization (PSO) as a part of the solution method. Studies using optimal power flow (OPF) associated with the particle swarm optimization (PSO) is tested on circuits with nonlinear loads system bus 39. Studies found that the computational time quite slow. [8]

2.4 Genetic Algorithm

Genetic algorithms (GA) generally consist of a fitness function, the selection and change. The most important operator in genetic variation is genetic mutation and cross-over, able to replicate chromosomes as their location changes and also changes a few bits from them (repetition). Finally

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chromosomes will be generated with the maximum fitness of the function to generate global optimal point.

Figure 2.4: Genetic algorithms (GA)

Description Mohammad A. S. Masoum, Marjan

Ladjevardi, Akbar Jafarian, and Ewald F. Fuchs use genetic algorithms (GA) for capacitor placement in distribution networks where the Newton Raphson harmonic power flow is selected as the basis load flow where it will compute the correction and force the appropriate mismatch to zero. Nonlinear load is introduced and injected into a balanced 3 phase system. Nonlinear load models made by assuming the relationship between current and voltage harmonics are given in the frequency domain or a time domain which are the V(h) and I(h), v (t) and i(t). [9] 2.5 Fuzzy Logic

Fuzzy logic (FL) optimization technique is based on Fuzzy Sets Theory (FST), introduced by Zadeh in 1965 associated with a logical argument. Fuzzy set theory provides a solution for any lack of uncertainty in the data. Fuzzy logic (FL) furthermore has much advantage and used in engineering for optimization process of the capacitor. To apply fuzzy logic (FL) to solve this problem, it is necessary to identify the key variables that have an influence on the

decisions that need to take into account the quantity of the values in the relevant level.

Figure 2.5: Fuzzy Logic Description M. A. S. Masoum , A. Jafarian , M.

Ladjevardi , E. F. Fuchs , and W. M. Grady in the research entitled "Fuzzy Approach for Optimal Placement and Sizing of Capacitor Banks in the Presence of Harmonics" using this approach. Given the presence of harmonic currents and voltages in the system and the constraints the voltage limit, the size, number and location of capacitors to be installed and power quality limits based on the IEEE -519 standards. Buses selected for fixed capacitor placement using sensitivity constraints and the objective function with respect to reactive power injection at each bus. Alpha cuts process imposed on each iteration to ensure the achievement of the objective function constraint. It was tested on IEEE 18 bus distorted circuit. Nonlinear bus was introduces to generate harmonic involving harmonic voltage V(h) and harmonic current, i(h). Solutions achieved by forcing the entire system power (combination of all active and reactive power of the fundamental and harmonic) to zero using the Newton Raphson harmonics load flow. Therefore the test for the possibility of existing resonance is not required. [10]

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2.6 Past Research Paper Comparison Table 2.1: Past Research Paper Comparison

Condition Past Research Paper

Capacitor placement with constrain:

Ideal condition

Computa-tion time

Switchin

g capacitor

Number of

capacitor

THD

Harmon

ic resonanc

e

Saving/cost

ACO [6] √ Tabu Search + SA [7]

√ √

Comparison GA, MSS, MSS-LV & fuzzy [9]

√ √ √ √ √

Fuzzy + MSS [10] √ √ √

Comparison ACO, PSO & Fuzzy [11]

√ √

ACO [13] √ ACO [14] √ √ ACO [15] √ Fuzzy + PSO [16] √ √

ABC [17] √ Comparison ABC, GA, PSO & PS-EA [18]

√ √

Harmonic Search Algorithm [19]

√ √

Ant Colony Optimization [20]

√ √

Comparison GA, GA-FL, MSS, MSS-LV & fuzzy [21]

√ √ √ √

GA [22] √ GA [23] √ √ √ Fuzzy + Ant [25] √

From the critical reviews and the

comparison that has been made, it found that most of the studies done over the ideal condition. An ideal condition practically does not exist at all but only in simulation software. Besides, many of the focus are aimed for the savings and costs. Considering the actual situation, there are non-linear loads connected to the network, so the harmonic resonance must be considered.

Fuzzy Logic (FL) used in this study

because it was seen as the best method for a capacitor with constraints of only one placement in 18 bus distribution system. (Refer IEEE 18 bus circuit for test and simulation). The use of other complex methods such as Particle Swarm Optimization (PSO) , Genetic Arithmetic (GA) , Artificial Bee Colony (ABC) and other perceived more suitable for systems with hundreds or even more buses.

RESEARCH METHODOLOGY AND RESULT

3.1 FUZZY LOGIC, FAST DECOUPLE AND PROJECT METHODOLOGY

This project is conducted based on the power flow study combined with fuzzy logic systems. Power flow is used to obtain the voltage profile and losses via analysis and fuzzy logic is used to get the value and the best location for the placement of capacitors to improve the voltage profile and losses.

The power flow used is the Fast Decouple Load Flow (FDLF) method, the easier analysis and the faster computation time compared to the Newton Raphson and Gauss Seidel method. The following is how FDLF is carefully done by emphasizing the processes and related formulas. Computation is performed in which the appropriate corrections of mismatches forced to zero. (See Equation 3.1 to Equation 3.9 for related formulation to fast decouple load flow)

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Current entering bus i: 퐼 = 푌 푉

3.1 Expressed in polar form:

퐼 = ⃒푌 ⃒⃒푉 ⃒∠ 휃 + 훿

3.2 Complex power at bus i:

푃−푗푄 = 푉∗퐼

3.3 푃−푗푄 = ⃒푉 ⃒∠ − 훿 ⃒푌 ⃒⃒푉 ⃒∠ 휃 + 훿

3.4

푃−푗푄 = ⃒푉⃒∠ − 훿 ⃒푌 ⃒⃒푉⃒∠ 휃 + 훿

3.5 Separate real and imaginary part:

푃 = ⃒푉⃒⃒푉 ⃒⃒푌 ⃒푐표푠 휃 − 훿 +훿

3.6 푄 = − ⃒푉⃒⃒푉 ⃒⃒푌 ⃒푠푖푛 휃 − 훿 +훿

3.7

The Jacobian matrix:

⎣⎢⎢⎢⎢⎢⎢⎡ ∆푃

( )

⋮∆푃( )

− − −∆푄( )

⋮∆푄( ) ⎦

⎥⎥⎥⎥⎥⎥⎤

=

⎣⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎡ ∆휕푃( )

휕훿

⋮∆휕푃( )

휕훿− −− −∆휕푄( )

휕훿

⋮∆휕푄( )

휕훿

⋯∆휕푃( )

휕훿⋱⋮

⋯∆휕푃( )

휕훿− −− −

⋯∆휕푄( )

휕훿⋱⋮

⋯∆휕푄( )

휕훿

∆휕푃( )

휕⃒푉 ⃒⋮

∆휕푃( )

휕⃒푉 ⃒−− − − −−

∆휕푄( )

휕⃒푉 ⃒⋮

∆휕푄( )

휕⃒푉 ⃒

⋯∆휕푃( )

휕⃒푉 ⃒⋱⋮

⋯∆휕푃( )

휕⃒푉 ⃒− −− −−

⋯∆휕푄( )

휕⃒푉 ⃒⋱⋮

⋯∆휕푄( )

휕⃒푉 ⃒ ⎦⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎤

⎣⎢⎢⎢⎢⎢⎢⎡ ∆훿( )

⋮∆훿( )

−− − −∆⃒푉 ( )⃒

⋮∆⃒푉 ( )⃒⎦

⎥⎥⎥⎥⎥⎥⎤

3.8

In short form: ∆푃

∆푄=

퐽 퐽

퐽 퐽

∆훿

∆⃒푉⃒

3.9 Where J2 and J3 = 0

This Fast Decouple then simulated via MATLAB m.file and the program shown in APPENDIX C until APPENDIX F This program is a program that works as fast decouple, the basic program for this project which is associated with other programs such as load flow program, y bus program, output bus program and line flow program that attached in the APPENDIX G until APPENDIX I. FDLF simulation results are then compared with using the Power World software for verification. As the Fuzzy Logic (FL) may not be carried out using Power World, thus the MATLAB m.file used instead. Beside, PowerWorld also used for the output comparison after the optimization run. Capacitor value and its location are obtained using FL then tested by using PowerWorld and FDLF. This process was simplified in the flow chart in Figure 3.1.

Figure 3.1: Project Algorithm

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In this project, FL used to get the best capacitor value and it location where it will produce the least amount of losses while increasing the voltage profile of the distribution system. Only one location and one of the best capacitor values allocated to this project. The values of capacitor incorporated into the data bus at any of the tested values ranging from 0.1 to 10 Mvar. The values of these capacitors are tested at bus 2 to bus 18. Any change in the value of the capacitor will result in a loss of apparent power and different voltage profiles. In this project, the change of losses is taken as a reference to facilitate the program. In theory, the lower losses, the better voltage profiles that will be produced. Hence every loss that results will be compared and the most minimal loss is the objective of this process. The algorithms for FL described in more detail next:

Fuzzy logic (FL) to find cap value and location

1. test bus 2 with 0.1 until 10 Mvar cap and read the losses data

2. Repeat step 1 for bus 3 until bus 18

3. Select the capacitor value for the lowerst value of Ploss and Qloss which are correlation to bus location.

Taking into account the potential of

resonance which may occur due to a combination of the resonance frequency, fr caused by the presence of nonlinear loads, the values of capacitance, XC can also be caused by a capacitor bank and reactance, XL can be caused by the existence of a transformer; by the value of the capacitor and its locations obtained using the FL should be analyzed to determine whether additional components necessary to be added to the system. This is done based on the formula described in the problem description and also verified by Simulink software.

The assumption made for parameter values outside the field of study but indirectly related to the project are as follows: Short circuit MVA for this system, MVASC = 100 MVA Fundamental frequency, f1 = 50 Hz Line voltage, kVline = 12.5 kV (base on bus data as in Table 3.1(a)) Table 3.1: (a) Bus data. (b) line data. (c) load data

(a)

(b)

10

(c)

Table 3.1 shown the input parameter which consist of bus data, line data and load data. All these data inserted to the IEEE 18 bus test circuit and run via MATLAB m.file, Power World and SIMULINK. SIMULINK simulations were conducted in two situations. In the first situation, the simulation is done without optimization where the harmonic currents injected into the system using a nonlinear load but no additional capacitor done. THD data was taken and compared with the second situation, where in the second situation, the optimization process takes place. Additional made on the certain bus with the capacitors value and its location that obtained by using the Fuzzy Logic (FL) from the previous process. Project methodology is summarized by the following step:

1) Test using Power World circuit to get the voltage profile and losses without capacitor banks

2) Test using Fast Decouple load flow through MATLAB m.file to get the voltage profile and loss

3) Compare the results from Step 1 and Step 2 for confirmation

4) Run Fuzzy Logic (FL) through m.file to get the location and size of capacitors to increase the voltage profile and reducing loss. Capacitor value selected between 0.1 Mvar to 10 Mvar.

5) Repeat Step 1 and Step 2 but with the addition of capacitor banks obtained using the Fuzzy Logic (from Step 4) into the system and compare them for confirmation.

6) Test the effect of harmonics using SIMULINK circuit where the harmonic currents injected at bus 9 without putting a capacitor bank. Harmonic signal is taken to monitor whether the resonance occurs.

7) Repeat Step 6 but with the addition of capacitor banks (obtained in Step 4) into the system.

8) Repeat Step 4 to Step 7 with new capacitor size and placement if the resonance still occur after the placement of capacitor bank

9) End 3.2 Simulation and Result The simulation was tested on 18-bus IEEE distorted system used for simulation and analysis. (See Figure 3.2). The result will be focusing on power quality improvement which are reduction of power losses and improve voltage profile. The result is as Table 3.2 until Table 3.6.

Figure 3.2: 18-bus IEEE distorted system used for simulation and analysis

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Circuit as shown in Figure 3.2 is developed and tested using Power World and SIMULINK. Since Power World (student version) does not have the resources of nonlinear load, thus the SIMULINK is used instead for analysis of the existence of harmonics in the system and the possibility of resonance. Table 3.2: Simulation result by Power World

(a) Voltage profile result before optimization

(b) Losses profile result before optimization

(a)

(b)

Table 3.2 shows the result after the Power World simulation run without capacitor placement Found the total MW loss is 0.03 MW (0.02 + 0.01; highlighted in red) and the total Mvar loss is by 0.28 Mvar (0.16+0.02+0.1+0.1+0.2+0.1+0.1+0.1+0.2+0.1; highlighted in green). Table 3.3: Voltage profile and losses result before optimization using m.file

Table 3.3 shows the result after the MATLAB simulation run without optimization (no capacitor added). Found the total MW loss is 0.0479 MW and the total Mvar loss is by 0.2943 Mvar. The next process is the use of Fuzzy Logic to get the value and location of capacitors. This is done by manipulating the m.file fast decouple program as attached on APPENDIX J.

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Table 3.4: Fuzzy Logic result

Table 3.4 shows that the simulation of fuzzy logic has selected index 684 as the best choice for the size and capacitor placement of 8.4 Mvar should be connected to the bus 8.

100 iteration need to run for each bus except at bus 1. Thus, 1700 iterations are needed for the entire 17 bus tested. By setting the index 1 to index 100 located under bus 2, index 101 to 200 under bus 3 and so on until the last index of 1700s. Several data that generated by Fuzzy Logic shown in APPENDIX K

To confirm that the Fuzzy Logic chooses the best size and placement of capacitor, all 1700s data generated by the FL iteration plotted into Excel as Figure 3.3.

Figure 3.3: Area that consist of lowest losses Figure 3.3 show the best index which

produces the lowest loss is between the ranges of 600 to 800. As compared by the naked eye also appears that no other index can result in a loss that is lower than the index selected by this FL. Thus proving that the best index is at 684 that generate only 0.2161 MW and 0.0351 Mvar losses.

Capacitor values and locations chosen then once again put in Power World to be simulated separately in Figure 3.4

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Figure 3.4: Circuit with 8.4 Mvar capacitor installed at bus 8

Figure 3.4 shows that 8.4 Mvar capacitor connected to the bus 8 and the simulation results are shown in the Table 3.5.

Table 3.5: (a) Voltage profile result after an

8.4 Mvar capacitor installed at bus 8 using

Power World (b) Losses profile result after 8.4

Mvar capacitor installed at bus 8 using Power

World

(a)

(b)

Table 3.5 shows the results for the addition Mvar done at bus 8. If examined, found that there was a decrease of loss and increase the voltage profile compared to the profile before the addition of capacitors. Note that the new real losses reduce to 0.02 MW from 0.03 MW and reactive losses reduce to 0.21 Mvar (0.10+0.01+0.01+0.01+0.02+0.01+0.01+0.01+0.02; highlighted in red) from 0.28 Mvar.

To facilitate the observation, the simulation results are focused on the most important data and arranged in Tables 4.1 until Table 4.3 Table 3.6: Comparison before and after optimization for voltage profile via pwd.file

(a) Before addition of capacitor bank

(b) After addition of 8.4 Mvar capacitor bank on bus 8

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(a) (b)

Note in Table 3.6 that the voltage increase until 0.94% (0.9858 to 0.99515 MW; highlighted in red) Table 3.7: Comparison before and after optimization for for losses profile via pwd.file

(a) Before addition of capacitor bank

(b) After addition of 8.4 Mvar capacitor bank on bus 8

(a)

Table 3.7 shows that the real power loss reduce until 33% (0.03 to 0.02 MW; highlighted in red) while reactive power

loss reduce until 25% (0.28 Mvar to 0.21 Mvar; highlighted in blue)

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Table 3.8: Comparison before and after optimization for voltage profile and losses via m.file

(a) Before addition of capacitor bank

(b) After addition of 8.4 Mvar capacitor bank on bus 8

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(a)

Note in Table 3.8 that the voltage increase until 0.94% (0.986 to 0.995 MW; highlighted in red) while real power loss reduce until 27% (0.0479 to 0.0351 MW; highlighted in blue) while reactive power loss reduce until 27% (0.2943 Mvar to 0.2161 Mvar; highlighted in green) 3.3 Potential of Harmonic Resonance

Analysis due to the potential existence of harmonic resonance in the system or caused by nonlinear loads are based on a formula as described in the section of Resonance and Problem Formulation (see Eq. 1.1 until Eq. 1.4) and the parameter in section of Project Methodology previously (see Table 3.1(a),

(b) and (c)), produce results as shown in Table 3.9 Table 3.9: Resonance Analysis Result

Table 3.9 shows for 8.4 Mvar installed at bus 8 then harmonic resonance

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will occur at 3.45033 order and the resonance frequency, fr occurs at 172 516 Hz where the addition of 0.7056Ω XL in series with the capacitor bank probably necessary. Since the lower XL seems there is no XL need to add in the system. This will be verified by using SIMULINK software as in Figure 3.5.

(a)

(b)

Figure 3.5: SIMULINK circuit simulation with harmonic current injected (see red

arrow) (a) before optimization (b) after optimization (see

blue arrow; 8.4 Mvar capacitor bank added on bus 8)

* More clear circuit attached on APPENDIX A and APPENDIX B

Figure 3.5(a) shows the circuit of the IEEE 18 bus used for test and simulation in present of harmonic via SIMULINK that used to study the effect on distribution network in present of harmonic. Harmonic current signal injected to bus 9 is shown in Figure 3.6(a) and THD as shown in Figure 3.6(b)

(a)

(b)

Figure 3.6: Harmonics source signal injected to system (a) Harmonic signal (b) Total Harmonic Distortion (THD) Figure 3.6(a) shown harmonic current signal that produced by nonlinear load. This load respected to bus 9 to simulate the propagation of harmonic in the system; while Figure 3.6(b) is a Total Harmonic Distortion (THD) for the signal 3.6(a). Harmonic injection at bus 9 has affected buses and nearby. This has been shown in Figure 3.7 to Figure 3.9

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(a)

(b)

Figure 3.7: Simulation output: signal on bus 17 after SIMULINK simulation (a) Less harmonic on bus 17 (line 17-18) (b) THD for signal (a)

Figure 3.7 shows the presence of some harmonics caused by nonlinear loads from bus 9. This harmonic currents flowing in the line 17-18.

(a)

(b)

Figure 3.8: Simulation output; harmonic signal propagates on bus 18 (line 18-16)

Figure 3.8 shows the presence of harmonics and Total Harmonic Distortion (THD) in line 18-16 is higher than harmonic at line 17-18 due to the nonlinear load of the bus 9. Shown that higher harmonic propagate in phase red and blue.

(a)

(b)

Figure 3.9: Simulation output; higher

harmonic on bus 16 (to load)

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Figure 3.9 shows the presence of harmonics and Total Harmonic Distortion (THD) at bus 16 to the load is higher than harmonic at the previous line. Note that more distortion on phase blue then others. The simulations carried out with reference to Figures 3.7 until Figure 3.9 shows that the harmonics of the bus 9 has spread to other parallel load. Findings also showed the higher harmonic and THD on the buses that have been further from the power source as in Figure 3.11. This shows that the harmonic resonance occurred.

(a)

(b)

Figure 3.10: Simulation output; current

signal at bus 9 (line 9-17) (a) Before adding 8.4 Mvar at bus 8 (b) After adding 8.4 Mvar at bus 8 Figure 3.10 shows the current bus 9 (line 9-17) before and after addition of the capacitor is the same; as well as the previous buses. This shows that they are not impressed with the harmonic currents from nonlinear loads that are connected directly with the bus 9 itself.

Figure 3.11: Harmonics resonance propagate from nonlinear load to the other its parallel load Figure 3.11 shows how the harmonic current path. (See yellow arrow) Simulation shows that this harmonic current decreases as it flows to the source. It does not affect the bus 9 (line 9-17) on the other hand increased again when it is away from the power source. This is based on finding shown in Figure 3.6 until 3.10. The resonance does not give negative impact to the utility but it give negative impact to the other its parallel load which are bus 17, bus 18 and bus 16.

20

(a)

(b)

Figure 3.12: Simulation output; harmonic at affected bus (bus 18 and bus 16) totally removed after optimization Figure 3.12(a) and Figure 3.12(b) shows the current bus 18 (line 18-16) and the current bus 16 (to load) after the addition of capacitors. Note that this signal is available of free distortion. This indicates that the addition of 8.4 Mvar capacitors were able to eliminate the effects of harmonics resonance totally.

CONCLUSION

4.1 Conclusion

From the projects that have been done, based on the findings of the study, it can be concluded that the use of fuzzy logic associated with fast decouple load flow (FDLF) analysis and SIMULINK to analyze the effect of the capacitor with the presence of harmonics in the distribution system which may cause resonance, has achieved the objective function; where the optimal

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