LUẬN VĂN CAO HỌC HỆ THỐNG ĐIỆN CẢI THIỆN CHẤT LƯỢNG ĐIỆN ÁP VÀ GIẢM TỔN THẤT TRONG HỆ THỐNG LƯỚI PHÂN PHỐI HÀ NỘI CÓ XEM XÉT ĐẾN NGUỒN PHÂN TÁN VÀ BỘ TỤ

Tổn công suất và sụt điện áp luôn luôn là vấn đề chính liên quan tới giá trị thực của ngành điện lực. Nghiên cứu về những phương pháp giảm tổn thất công suất và cải thiện chất lượng điện áp đã được tiến hành nhiều năm. Trong phương pháp nghiên cứu ngày, tác giả mong muốn hiện tại phương pháp luận được ứng dụng cho lợi ích lưới điện trong nhóm tổn thất điện năng và sụt điện áp. Phương pháp sẽ tìm ra vị trí tối ưu nguồn phân tán và những bộ tụ điện trong hệ thống lưới phân phối. Có hai phần trong nghiên cứu này, phần thứ nhất tìm ra dung lượng tối ưu của nguồn phân tán và vị trí để đạt tổn thất công suất tác dụng bé nhất trong hê thống. Có nhiều nguồn phân tán khác nhau, nguồn phân tán chủ yếu chỉ cung cấp công suất tác dụng và công suất phản kháng, DG cung cấp công suất tác dụng nhưng chi phối cân xứng với công suất phản kháng, chúng được quan tâm tới việc giải quyết những vị trí tối ưu của nguồn phân tán. Phần thứ hai những bộ tụ điện được đặt vị trí tối ưu. Phương pháp luận sẽ được liên hệ với các lộ đường dây của một trạm phân phối trong công ty điện lực Hà Nội. Những lộ đường dây này có mô hình như 40 bus hệ thống và 62 bus hệ thống.

IMPROVING VOLTAGE PROFILE AND REDUCING LOSS IN

THE HANOI POWER DISTRIBUTION SYSTEM

CONSIDERING DISTRIBUTED GENERATIONS AND CAPACITOR

BANKS

CẢI THIỆN CHẤT LƯỢNG ĐIỆN ÁP VÀ GIẢM TỔN THẤT TRONG

HỆ THỐNG LƯỚI PHÂN PHỐI TP HÀ NỘI

CÓ XEM XÉT ĐẾN NGUỒN PHÂN TÁN VÀ BỘ TỤ

A thesis submitted in partial fulfillment of the requirements for the

Degree of Master of Engineering in

Energy

Asian Institute of TechnologySchool of Environment, Resources and Development

The author would like to express his deepest gratitude to his advisor,the chairman of the thesis examination committee, Dr Mithulananthan.N

The author would also like to thank Dr Weerakorn O and Prof Sam R.Shretha for their kindness in serving as members of examinationcommittee and for their valuable suggestions and advice throughoutthis study

The author wishes to convey his thank to the Electricity of Vietnam forgenerously granting the scholarship so that he could pursue thisvaluable master degree

The author also thanks Ha Noi Power Company (HPC) for providinghim the opportunity to pursue this valuable master degree, to the staffand officers of HPC, for their assistance during the data collectionphase

Many thanks are also sending to the faculty and staff members ofEnergy Program, especially to Mr Pukar Mahat, for their help duringthe study

The author thanks to all of my Vietnamese classmates, Ninh, Dung,Minh, Hieu, for their kindly support

Finally, the author would like to express his deepest appreciation to hisfamily – his parents, his wife, and his son for their utmost support,encouragement and understanding during his study in AIT

Power losses and voltage drop are always major concerns to electricity utility.Study about the methods to reduce power loss and improve voltage profile hasbeen carried for many years

Nowadays, the interest in distributed generation around the world is sharplyincreasing DGs are predicted to be a major component of future powersystem with all the benefits that come with them If placed properly, they willimprove the system in various ways, and of course, reduce power loss andvoltage drop So, it becomes essential to place them in such a way that allparties associated with them will be benefited

In this study, the author would like to present the methodology to improve theutility grid in term of power loss and voltage drop The method will find outthe optimal DG and capacitor banks in distribution system There are twoparts in this study The first one finds the optimal DG size and the location tominimize real power loss in the system Different DG types, namely DGsupplying real or reactive power only, DG supplying real power butconsuming proportionate reactive power, are considered to solve the optimal

DG placement problem In the second part, the capacitor banks are optimallyplaced

The methodology will be carried out with the primary feeders of onesubstation in Ha Noi Power Company These feeders are modeled as 40 bussystem and 62 bus systems

List of abbreviations

CAPO – Optimal Capacitor placement

DG – Distributed Generation

EVN – Electricity of Viet Nam

E2 – Long Bien distribution substation

HPC – Ha Noi Power Company

Tables of Contents Chapter Title

4 Optimal Placement of the Distributed Generation 25

4 Vị trí tối ưu của nguồn phân tán Error! Bookmark not defined

4.1 Optimal DG Placement to Reduce Loss 25

List of figures

Figure 5-2: Flow chart to find the optimal DG size and the location to reduce

Figure 6-2: Real power loss when DG installed at each bus with optial size

Figure 6-5: Real power loss when DG installed at each bus with optial size

Figure 6-6: Voltage profile before and after DG installed type 2 case 983-E2

42

Figure 6-8: Real power loss when DG installed at each bus with optial size

Figure 6-9: Voltage profile before and after DG installed type 1 case 979-E2

45

Figure 6-11: Real power loss when DG installed at each bus with optial size

Figure 6-12: Voltage profile before and after DG installed type 2 case 979-E2

47Figure 6-13: Voltage profile of feeder 983E2 before capacitor placement -

Figure 6-16: Voltage profile of feeder 979E2 before and after capacitor

List of tables

Table 6-1: Ranking of buses for loss reduction type 1 case 983-E2 ( Appendix

Table 6-2: Ranking of buses for loss reduction type 1 case 983-E2 (Appendix

1. Introduction

1.1 Background

Electric power distribution system engineering has been designed to deal withproblems related to the rapidly expanding distribution system, loadmanagement and reduction of distribution loss Voltage drop and power lossare major concerns for utilities as they limit the load ability of feeders andreduce revenue All utility have found and applied the optimal method toimprove voltage drop and power loss

Traditionally, there are many options available for reducing loss and voltagedrops such as network reconfiguration, load balancing, introduction of highervoltage level, reconductoring, and capacitor installation Among them,capacitor placement is one of most economical options for loss reduction,especially in distribution systems of developing countries

Recently, the application of small generators, called Distributed Generation(DG) has been considered to address the issue of loss reduction in distributionsystem DGs have some advantages to replace capacitor banks in order toimprove voltage profile and power loss DGs can supply both real andreactive power DGs can also keep the voltage at some buses in stable byadjusting reactive power smoothly and automatically However, DGs alsohave some disadvantages such as coordination protection, high initial cost…This would be lead to a question that which option would be the best amongall the alternatives available?

Distributed Generation (DG) includes the application of small generators,typically ranging in capacity from few kW to as high as 10,000 kW, scatteredthroughout a power system, to provide the electric power needed by electricalcustomers[1] Distributed Generation (DG) uses small-scale power generationtechnologies to generate electricity in close proximity to its utilization point

DG technology portfolios typically include small or micro hydro powerplants, wind turbines, photovoltaic, fuel cells, reciprocating engines,combustion gas turbines and micro turbines

This study presents the methodology to find the best solution for improvingvoltage drops and power loss in distribution system The first part presents amethod using MATLAB software to develop a program that finds optimal DGsizes and the locations to take part in the distribution networks in order toimprove voltage profile and minimize loss The second part uses PSS/ADEPTsoftware to find the optimal capacitor banks placement

1.2 Statement of problem

Hanoi Power Company (HPC) is a utility that serves almost 450,000customers in seven urban districts and seven rural districts of Ha Noi In therecent years, HPC had implemented a lot of management methods andupgrading projects to reduce voltage drop, technical and non-technical powerloss However, regardless of all the attempts made, losses are running atunacceptable percentage, about 11%

At presently, the growth of energy consumption in Ha Noi is very high Inorder to meet customer demand, Ha Noi distribution network needs to beplanned to improve quantity and quality of electricity supply to meet socialand economical development of Ha Noi in coming years

Two effective options to reduce power loss and voltage drops are using shuntcapacitors to compensate reactive power in primary feeders and using DG as

an alternative Now there is a few shunt capacitors installed in primaryfeeders On the other hand, distributed generation is a new term with VietNam, so there is no DG installed in HPC network at that time

For a long time, capacitor bank is contributed in the whole distribution systemoperation However, with number of benefits that installation of DGs in thedistribution system can bring [see 2.3.2], the DG alternative becomes veryattractive to achieve the objectives

In recent years, many researches and studies show that DGs provide variousbenefits to the system when they are properly planed and operated On theother hand, improper placement and operation will degrade the power quality,reliability and control of the power system, also may lead to even higher loss.Thus, feasibility studying about DGs should be also carried out as goodoptions in planning period

1.3 Objectives of Study

The main objectives of this study are to find the optimal solution to reducepower loss and improve voltage profile of HPC distribution system.PSS/ADEPT software is used to find optimal capacitor placement, and aMATLAB program will be used to find optimal DG size and location so as tominimize power loss and voltage drop Then the author will evaluate andcompare the results of two options

Specifically, objectives of the study are as follows:

1 To calculate power loss and voltage drops of the existing main primarydistribution system of HPC

2 To develop a program that find optimal DG size and location tominimize power loss and improving voltage profile in the network

3 To find optimal capacitor placements and sizes in primary feeders forimproving voltage profile and reducing power loss.

4 To evaluate and to compare the solutions, i.e capacitor placements and

DG placements and give some conclusions and recommendation on themost appropriate option for power loss reduction

1.4 Scope and limitations

This study focuses on the optimal method in installation DG into distributionsystem This also implements the reduction of power loss and voltage drop byplacing shunt capacitor banks in the primary feeders

The distribution system in Hanoi has been rehabilitated Some distributionsubstation has been reconfigured in primary feeders Therefore, this study willdeal with one distribution substation that has high power loss and poorvoltage profile in primary feeders

Because of time limited, and the secondary system of the distributionsubstation is too large, so this study considers the matter only in the primarysystem

The limitations of work for this study can be summarized as follows:

1- Existing transmission and distribution system in Hanoi PowerCompany will be used in the study

2- This study is implemented in one of distribution substation of HanoiPower distribution network

3- Only power balance constraint is considered

4- DG in this study implies small size generation at the distributionlevel and these DGs must have ability to generate reactive power

1.5 Expected results

This thesis studies the methods how to reduce power loss and voltage drop indistribution system by compensating reactive power using shunt capacitorbanks and DGs The expected results are the followings:

1 Examination of one existing distribution substation loss and capabilities

of reduction in power loss as well as improvement of voltage profile

2 Desirable locations and sizes of DGs

3 Desirable locations and sizes of shunt capacitors

4 Expected loss reduction, voltage profile improvement

With the results will be obtained, the author expect that HPC will put thesemethods in operation to reduce power loss and to improve voltage profile

At present, the author viewpoint is that the optimal capacitor placementmethod is more feasible than the optimal DG placement method Further, the

author expects that the second method will be applied in HPC network in nearfuture.

2. Literature review

Reducing voltage drop and power loss is one of the biggest challenges inelectric power utility of developing countries The electricity demand isgrowing sharply As a result of this, a poor voltage profile as well as higherloss can be reality if no proper measures are put in placed While the utilitiesare not having sufficient funds for expansion their grid and source, it isnecessary to reduce power losses

This chapter will review the literature of power loss and voltage dropdistribution network and methods to reduce them Distributed generationdevelopment and application, and load flow in distribution system are alsoreviewed in this chapter

2.1 Distribution network power loss

Electric power distribution system is the part of power system that deliversenergy directly from suppliers to customers operating at several voltage levels[1] In the situation of increasing scarcity of resource and escalating cost ofenergy supply, the important of energy conservation and reduction in loss inthe system is felt vital

Power system loss reduction is one of principle ways of achievingconservation in the electric power supply sector In the process of deliveringelectricity to customers, loss is occurred in generation, transmission, anddistribution system In the literature, there are many reports that discuss aboutloss In distribution system, the grid is almost in radial so the level voltages,load density are the main factors concerning about the system loss

Distribution network power loss includes both technical and non-technicalloss In this study, only the first one is considered Technical losses are naturaland consisting mainly of power dissipation in the electrical systemcomponents such as transmission lines, power transformers, measurementsystems, etc It is possible to compute and control and provided the powersystem in question consists of known quantities of loads Using computationtools for calculating power flow, loss and equipment status in power systemshas been developed in nearly years Improvements in information technologyand data acquisition have made the calculation and verification easier

Losses depend on various factors, such as load density, inadequate designs,and improper maintenance, etc There may be significant proportion ofunaccounted loss due to inaccuracy in meters, flat rate tariff structure, error ofcustomer billing, pilferage of energy and unauthorized use of electricity Most

of them fall under non-technical losses The reduction in system loss can

result in substantial saving in energy as well as increase in the power capacitysupply.

Generally, the loss in distribution system is higher in comparing withtransmission system According to EVN report, in 2004, the shares of loss aretechnical distribution loss 61%, non-technical loss 5%, and transmission loss34%

Traditionally, there are number of solutions to reduce distribution systemlosses, such as network reconfiguration, load balancing, introduction of highervoltage level, reconductoring, and capacitor installation, etc Among these,capacitor placement is considered as one of the most economical option.Nearly years, distributed generation has been considered as the goodalternative with various benefits

2.2 Distributed Generation

2.2.1 Development of Applications DGs

Trend in supplying electricity, for few decades now, is mainly through thehierarchical systems include generation, transmission, and distributionsystem In recent year, with the development of new technologies, many types

of Distribution Generation are successfully applied, mainly in developedcountries

Although having lot of challenges, more and more DGs are coming to themarket basically with electricity liberalization This is clearly indicated byincreasing share of DG in electricity market In the United State, for example,

DG resources or on-site generation cover more than 30% of installed capacity.This trend is likely to accelerate as deregulation of electric power markets ismaterialized According to International Council on Large Electric System(CIGRE) report, contribution of DGs in Denmark and the Netherlands hasreached 37% and 40% respectively [29] Electric Power Research Institute’s(EPRI) study forecasts that 25% of new generation will be distributed by 2010and similar study by Natural Gas Foundation believes that the share of DG innews generation will be 30% by the year 2010 [33]

Energy policies worldwide are encouraging installation of DGs in bothtransmission and distribution networks along with large scale powergenerating plants But, the fact is that the distribution systems were notplanned to support the installation of these power generating units in it Manystudies have reported that this type of integration may create technical andsafety problems [34]

In the literature, a large number of terms and definitions are used to designatedistributed generation For instance, in Anglo-Saxon countries the term

“embedded generation” is often used, in North American countries the term

“dispersed generation”, and in Europe and parts of Asia, the term

“decentralized generation” are used to denote the same type of generation

This thesis will follow the general definition proposed: Distributed generation

is an electric power source connected directly to the distribution network andusually at the customer side

Further, distributed generation may be defined as a generating resource, otherthan central generating station, that is placed close to load being served,usually at customer side It may be connected to the supply side or demandside of meter It may also be defined as any modular generator located at ornear the load center It can be renewable source like micro hydro, solar, windand photovoltaic or fuel based like fuel cells and micro turbine It may beunderstood as small-scale electricity generation

Among various benefits, DGs can offer significant lower cost and higherreliability than the electricity grid Grid along with DGs can result in betterperformance than either could alone [3] In wholesale power market, customerowned DGs can reduce prices volatility by responding to the extreme priceswings [27] Despite all these benefits, lack of technology maturation,interconnection requirements, permitting and siting, and building andelectrical codes are hampering the development of the DGs and these barriersare expected to be overcome by the restructuring of electricity industry [28].DG’s penetration in power system is increasing, and in the future powersystem might look like the one shown in Figure 2.2 (Source: DistributedUtility Associates)

2.2.2 Benefits of DG

construction of new transmission lines, increasing customer demand forhighly reliable electricity, electricity market liberalization, and concernabout climate change [26]

in response to incremental increases in power demand and avoidtransmission and distribution (T&D) capacity upgrades by locating powerwhere it is most needed [36]

transmission and distribution line loss, and improve power quality andsystem reliability [32]

increase the efficiency of energy utilization and thus may reduce globalemissions at lower costs [38], [39]

of generation and also provide ancillary service [38], [39]

• DG may level the load curve, improve the voltage profile across the feederand reduce the loading of the branches [40].

equipment, provide local voltage support and increase economical benefitswith DG [41]

market and thus create price reduction [41]

which leads to reduction in demand [42]

isolating a particular part of the system from the utility supply and thus canprevent the sensitive equipments from voltage dips [43]

enhance the system reliability and security [44]

2.2.3 Distribution Generation Technologies

There are different types of DGs from the constructional and technologicalpoints of view The different types of distributed generation are shown inFigure 2-1 Some suitable DGs for HNC network are fuel cells, microturbines, photovoltaic, and reciprocating engines

Figure 2-2 shows the present and future of power generation

Figure 0-1: Distributed generation types and technologies.

Figure 0-2: Present and the future of power generation.

MW, but nowadays we can generate electricity through small modular with amicro-gas turbine of 200 kW sizes [3] They have the capability of operatingindependent of the grid and have black start capability when supplied withbatteries [27] Like fuel cells and reciprocating engines, they can also regulatethe bus voltage at which they are connected

* Advantages:

technologies

* Disadvantages:

output and fuel efficiency

b Reciprocating Engines

Reciprocating engines are the most widely used type of power source fordistributed generators They use diesel or natural gas as their fuel Almost allengines used for power generation are four-stroke and operate in four cycles

* Advantages

* Disadvantages

fuel cells and micro-turbines

c Photovoltaic

The basic unit of PV is a cell that may be square or round in shape, made ofdoped silicon crystal Cells are connected to form a module or panel andmodules are connected to form an array to generate the required power Cellsabsorb solar energy from the sunlight, where the light photons force cellelectrons to flow, and convert it to dc electricity Normally an array, cellsconnected in series, provides 12V to charge batteries

d Wind Turbines

Wind energy is not a new form it has been used for decades A wind turbineconsists of a rotor, turbine blades, generator, drive or coupling device, shaft,and the nacelle (the turbine head) that contains the gearbox and the generatordrive The wind rotates the windmill-like blades, which in turn rotate theirattached shaft This shaft operates a pump or a generator that produceselectricity Although, the energy characteristics of larger wind turbine farmsare closer to the centralized energy sources, small wind turbines (working asmodules) can be combined with PV and battery systems to serve the load of25–100 kW [3] A generator driven by wind turbines can produce only realpower because the synchronous generator requires that a very constantrotational speed be maintained while it cannot be met by “constant-speed”wind turbine

* Advantages

as proton exchange membrane or polymer electrolyte membrane fuel cell(PEMFC), alkaline fuel cell (AFC), direct methanol fuel cell (DMFC),phosphoric acid fuel cell (PAFC), molten carbonate fuel cell (MCFC) andsolid oxide fuel cell (SOFC) Like the reciprocating engines, they can regulatethe voltage of the bus at which they are connected.

* Advantages:

* Disadvantages

2.2.4 Standard Sizes of Distributed Generation on Market

The typical available sizes per module of DG on the market in [32] will helpsystem planners to select the correct size that they need Table 3.1 shows therange of capacity for DG of different technologies

Table 0-1: Available capacities of DG for various technologies

7 Photovoltaic arrays 20 Watt – 100 kW

2.3 Distribution Power Flow Algorithms

In order to analysis DG in the distribution system, the first step is to run adistribution load flow with DG The results can be analyzed to see thetechnical viability of a DG in the distribution system

Load flow is very important in power system operation and planning as itprovides the picture of steady state operating condition It is desirable to knowthe system operating condition at different loading levels for efficient andreliable operation of the power system Many real time and planningapplications require an efficient and robust power flow algorithm NewtonRaphson and fast decoupled power flow solution techniques, being used fordecades now, to solve transmission system and well behaved power systemcannot be used directly in the distribution system, as it may lead toconvergence problem [51], [52] This is basically due to the difference incharacteristics of the transmission and distribution systems Furthermore,introduction of DGs has changed the way the distribution system is operated.For all these reasons distribution load flow algorithm needs to be more robustand faster even for the static studies [53]

Distribution systems usually fall into the category of ill-conditioned powersystems with its special features such as radial or weakly meshed topologies,high R/X ratio of the distribution lines, unbalanced operation and loadingconditions, non-linear load models and dispersed generation, etc Numerousefforts have been made to develop power flow algorithms for distributionsystems

Recently many researchers have paid attention to obtain the load flowsolution of distribution network In [52], compensation-based power flowmethod is presented by D Shirmohammadi for meshed systems And the

method was extended to a dispersed generation system with PV nodecompensation in [54] by G X Luo and A Semlyen By adding voltagecorrection, it was illustrated that the iterative process power flow calculation

is faster and reliable [55]

Luo et al [54] presented a compensation method for weakly meshednetworks This method started from a network structure analysis to find theinterconnection points Then it breaks these interconnection points using thecompensation method so that the meshed system structure could be changed

to simple tree-type radial system This method is also suitable for the systemwith multiple voltage control buses

A general load flow method for distribution systems presented by M.H.Haque in [57] proposed a new approach for meshed networks with more thanone feeding node The method first converts the multiple-source meshnetwork into an equivalent single-source radial type network by settingdummy nodes for the break points at distributed generators and loopconnecting points Then the traditional ladder network method can be appliedfor the equivalent radial system Following each of the iterations of theequivalent radial system, the power injected at the break points must beupdated by an additional calculation through a reduced order impedancematrix

Salama et al [58] have presented a very simple but robust method - the ladderformula Essentially, the ladder network method treats the radial system astwo basic element types: the network natural elements (impedance) andvoltage control current sources (system loads) at each load node The forwardsweep is mainly a voltage drop calculation from the sending end to the far end

of a feeder or a lateral; and the backward sweep is primarily a currentsummation based on the voltage updates from the far end of the feeder to thesending end

Berg et al.[59] presented a backward method which used a backwardprocedure to update the equivalent impedance at the sending end The mainidea of this method is to treat the load as constant impedance So if theequivalent impedance is convergent, the whole system convergence will bereached This method is very costly and quite sensitive to the system loadlevel and load distribution, as well as the system structures

Baran et al.[60] presented a forward method In this method, the sending endvoltage becomes the main concern of the system convergence Voltage dropand the information on system structure have been considered in the forwardsweep The voltage-sensitive load current can be included in the systemmodel However, this method still has disadvantages Oriented from laddernetwork concepts, the 'branch flow equations' are essentially solved by a

Newton-Raphson approach which makes this method complex and costly.Sometimes the influence of the load distribution would cause slowconvergence.

2.4 Shunt Capacitor Placement

Capacitors have been very commonly used to provide reactive powercompensation in distribution systems They are provided to minimize powerand energy losses and to maintain the voltage profile within the acceptablelimits The amount of compensation provided is very much linked to theplacement of capacitors in the distribution system which is essentiallydetermination of the location, size, number and type of capacitors to be placed

in the system

The capacitor placement problem is a well researched topic and has beenaddressed by many authors in the past Initially, the problem of capacitorlocation has been handled with analytical methods The famous “two-thirds”rule [1] advocates for maximum loss reduction As this rule, a capacitor rated

at thirds of the peak reactive load should be installed at a position thirds of the distance along the total feeder length Although it is easy tounderstand, this method had some unrealistic assumptions, such as uniformload, uniform conductor sizes, etc Thus, to achieve more accuracy results, itshould have more effective methods

two-More recently, thanks to robustness of computer, some methodologies havebeen proposed, such as mixed integer programming; linear programmingmodels; methods based on heuristic search techniques such as geneticalgorithms [12]–[20]; fuzzy approach [21]– [22]; simulated annealing; expertsystems, artificial neutral networks (ANN)

For optimal capacitor allocation, the savings function would be the objectivefunction and the locations, sizes, number of capacitors, bus voltages, andcurrent would be the decision variables

In most of these approaches, the objective function is considered as anunconstrained maximization of savings due to energy loss reduction and peakpower loss reduction against the capacitor cost [6]-[12] Others haveformulated the problem with some variations of the above objective function.Some of the early works have not considered capacitor cost in the

formulation Some others have included system capacity release and load

growth into the problem formulation

GA is a well tool to use in optimal capacitor placement [12-14], [18-20] and it

is the fact that GA has been successfully applied to the capacitor placementproblem In this method, the parameter sets (sizes and locations) are coded

GA operation will select a population of the coded parameters with highest

level and perform a combination of mutation, crossover to generate the betterset of parameters.

A technique applying fuzzy set theory [21], [22] is also applied to solve theproblem In this technique, voltage and power loss indices are modeled bymembership functions and a fuzzy expert system containing a set of heuristicrules that performs the inference to determine a capacitor placementsuitability index of each node Capacitor would be placed at the node withhighest suitability

Based on all of the method above, many programs are developed to solve theproblem of optimal capacitor placement Most of current commercial software

is using numerical programming method to solve the optimal capacitorproblem

Among these, the PSS/ADEPT software written by Shaw Power Technologiesproved an efficient tool for optimal capacitor placement in distribution systemthat considers both fixed and switched capacitors, as well as economicsconcerns [24]

2.5 DG Placement Techniques

With more and more DGs coming into distribution system, it is alwaysdesirable to place them properly Proper placement will reduce distributionsystem loss, also provide free available capacity for power transmission andreduce equipment stress By proper DG placement, we can defer investment

in transmission line expansion as well as improve overall efficiency of thepower delivery In case of heavily loaded feeder, transmission corridors can

be relieved Furthermore power quality can be improved by the properplacement of DGs

A near optimal placement technique to reduce the system loss has beenpresented in [53] By this technique, loss sensitivity of load bus is calculated.The buses are ranked according to their loss sensitivity and size of DG in thatbus is kept increasing until the loss starts to increase DG is placed in the buswhich gives the most loss reduction after placement In case of thedistribution system, four feeders are chosen based upon the transmissionsystem study and DGs of fixed sizes are placed in one or more of thesefeeders This method is basically about finding the location and does not givethe size of the DG and furthermore, loss sensitivity of buses changes as weincrease the size of the DG

The optimal location to place a DG, with unity power factor, in a radial ornetworked system is presented in [62], with loss minimization objective It isbased on bus admittance matrix, generation information, and load distribution

of the system This technique is basically concerned with finding the optimal

location not the optimal size A practically useful point of the technique is that

it considers time varying load

Celli et al in [63] have proposed a multi-objective technique to solve DG

placement and sizing problem with the aim of reducing cost of energy loss,cost of network upgrading and cost of purchased energy Genetic algorithmand ε-constrained method is used to find the size and place to place the DG inthe distribution system Though the paper considers the various economicparts related to DG placement and sizing, it is computationally demandingdue to the use of GA

In [64], optimal DG sizing and placement model is presented with the aim ofminimizing the investment cost and operating cost of the DG Proposedmethodology aims to minimize the capital investment and operation cost ofdistribution company along with payment made toward the loss reduction,power generated and cost of the power purchased from the grid and it alsocompares the cost of network expansion with the DG installation Thistechnique sometimes gives the solutions which are not practical and henceplanner experience decisions are required

A genetic algorithm (GA) based distribution generation placement technique

to reduce overall power loss in distribution system is presented in [65] B-losscoefficient is used to find the system loss The technique uses GeneticAlgorithm Toolbox and both the optimal size and location can be found from

it Three more genetic algorithm based method for determining the DG sizeand location is presented in [79] Another genetic algorithm based DGplacement technique is presented in [48] This algorithm finds the optimalsize and place where we can install DG, so as to reduce the system loss Thetechnique is used to solve the DG placement problem in medium voltagedistribution system GA is suitable for multi-objective problem and gives nearoptimal solution but it is computationally intensive and suffers from excessiveconvergence time and premature convergence

3. Distribution Load Flow

Distribution load flow study is an important part of distribution systemsanalysis and is used in operational as well as planning stages Many real timeapplication in the distribution automation system such as networkoptimization, reactive power planning, switching, state estimation and soforth, need the support of a robust and efficient power flow method Such apower flow solution method must be able to model the special features ofdistribution system This chapter will present two sections relating todistribution load flow

3.1 Distribution System Characteristics

Distribution system is the heart of power system, as it constitute of majorportion of any power system The characteristics of distribution systems are asfollows:

Distribution network plays the role of providing energy to end usersconnected at low or medium voltage and still considered as a meretermination of the transmission grid They are characterized by unidirectionalpower flow and simple protection ensuring safe and economical operation ofthe power system With DG installation in the distribution system, thestructure of the distribution system will change The new generation mediumvoltage distribution network will have:

The inability of the conventional load flow techniques coupled with the aboveraised issues demands a power flow technique that gives the status of thedistribution system for planning and operation purpose

To run a load flow, it is necessary that we appropriately model the differentcomponents in the distribution system The following sections will show howlines, loads, DGs and capacitors can be modeled for load flow algorithm.

3.2 Modeling system elements

3.2.1 Line Modeling

Distribution feeder consists of three-phase over head or underground cable.The feeder can be represented by a single line π or T representation forbalanced load Figure 3-1 shows the single phase π representation of a linesection

Figure 0-1: Model of a line section for single phase (π) representation.

If we consider all three phases separately and represent the line section as inFigure 3-2, then the line impedance can be represented by a 3x3 matrix asgiven by equation 3-1

Shunt Admittance (YK)

Node

i

Node j

Node j

Figure 0-2: Model of a line section.

cb k

ca

k bc k

bb k

ba

k ac k

ab k

aa K

Z Z

Z

Z Z

Z

Z Z

Z Z

, ,

,

, ,

,

, ,

,

(0-3)

where,

k – line section

3.2.2 Load Modeling

Loads can be a combination of constant power, constant current and constant

load current There are the following load models:

V

S I

S S

S S

0 0

0 0

0 0

(0-5)

Lic Lib Lia

y y

y Y

0 0

0 0

0 0

(0-8)

(1) Constant power

[ 1]*

)

= Lppi i T

1 1 0

0 1 1

S S

S S

0 0

0 0

0 0

(0-11)

(2) Constant current

Lppi T

y y

y Y

0 0

0 0

0 0

V V

V V

(0-16)

3.2.3 Shunt Capacitor Modeling

Shunt capacitor will be modeled as the constant Y or ∆ connected load asabove

3.2.4 Distributed Generation Modeling

With more and more DGs coming in the distribution system, it is important tomodel them properly Distributed generators’ nodes can be classified as

constant PQ or PV nodes For PQ units, the models are identical with constant power load models, except that the current is injected into the bus For PV units, the connected bus is modeled as a PV node If the computed reactive

power generation is out of the reactive generation limits, then the reactive

power generation is set to that limit and the unit acts as a PQ node.

3.2.5 Distribution Transformer

General form of the three-phase transformer model is shown in Figure 3-3,

represents secondary voltage

Figure 0-3: General form of 3-phase transformer model.

3.2.6 Network Indexing

The load flow calculation depends much on the way distribution network isnumbered The network served for the load flow, in this thesis, is indexingaccording to the way that the nodes are numbered in the direction from thesource (parent) to the load (child) and from tree to tree A sample network inthe study with numbering of buses is given in Figure 3-4

Figure 0-4: Numbering of buses and branches.

3.3 Load Flow Algorithm

In most of the load flow algorithms, two iterative processes are mainly used.They are backward and forward sweeps The following sections describethese processes and the stopping criteria in brief

3.3.1 Backward Sweep

With flat start (i.e voltage magnitudes and phase angles of 1 p.u and zerorespectively at all the buses), we calculate branch currents During eachbackward sweep process the voltage obtained at forward sweep is keptconstant and updated branch currents are transmitted backward along thefeeder using backward path Backward sweep starts from the extreme branch.The nodal injection current at any node ‘i’ during iteration ‘k’ is given as

) 1 (

*

) 1 ( )

i

i k

V

S I

V is the voltage at node ‘i’ (k-1)thiteration

Si is specific power injected at node ‘i’

Yi is sum of all the shunt elements at node ‘i’

of a line section m as follows

k p k

i k

3.3.2 Forward Sweep

In the forward sweep, we keep the values of current obtained from backwardsweep constant and update the voltage at each node The feeder substationvoltage is kept constant and the voltages at other buses will be updated

At forward sweep, nodal voltages are updated starting from the branches fromthe root node towards to the last.

A forward process is implemented to compute nodal voltages If the branch

‘m’ connecting bus i and bus j, the nodal voltage at bus j is calculated asfollows:

) ( )

( )

m m k i k

k j

k j

V V

V

) ( Im

) ( Re

(0-21)

As the load flow solution is obtained, voltage in each node and current in eachbranch will be known and using this information, we can obtain the real andreactive power loss of the distribution system

The basic steps of load flow algorithm are shown in Figure 3-5

Figure 0-5: Basic steps in the iterative algorithm.

4. Optimal Placement of the Distributed Generation

4.1 Optimal DG Placement to Reduce Loss

The real power loss in the distribution system is very significant from thesystem operation point of view Losses increase the operating cost of a powersystem and determine how we operate various generating plants In addition

to that, thermal loss reduces the overall lifetime of electrical equipment So,loss in the system should be represented as accurately as possible

The loss in the system can be given by equation (4-1) [80], if we know thesystem operating condition

∑∑

= =

− +

+

= n

1 1

) (

) (

i n

j

j i j i ij j i j i ij

j i

j i

j i

V V Sin

V V Cos

ij ij

R B

R A

(0-2)

here,

Rijis the line resistance between bus ‘i’ and ‘j’

Vi and δi are the voltage and angle at bus ‘i’ respectively

The objective of the placement technique is to minimize the loss.Mathematically the objective function can be written as:

generation and demand In sections 4.3.1 to 4.3.4, optimal placement of DGsunder different scenarios will be discussed The scenarios are namely DGsupplying real power only, DG supplying reactive power only, DG supplyingreal power but consuming proportionate reactive power and DG capable ofregulating the bus voltage

4.2 Optimal DG placement when DG Supply Real Power Only

Certain type of DGs like photovoltaic will produce real power only Also aprivate investor will like to run the DG at the unity power factor as it will

result in maximum revenue for the private firm To find the DG size and theplacement, when it supplies real power only; we differentiate equation (4-1)

with respect to Pi We will then get:

j ij n

j

j ij i

L

Q B P

A P

P

1 1

2 2

(0-5)

System real power loss will be minimal if equation (4-5) equals to zero So,

we can write equation (4-5) as:

2

1 1

j ij n

j

j ij i

L

Q B P

A P

j ij j ij i

j ij j ij ii

Pi is the real power injection at node ‘i’, which is the difference

between real power generation and demand at that node If a DG of size

P is the load demand at node ‘i’

From equations (4-8) and (4-9) we get the following relationship:

j ij j ij ii

Di

A P P

, 1