proceeding iwre2013

8/12/2019 Proceeding IWRE2013

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2013 International Workshop on Renewable EnergyTable of Content

Table of ContentTable of ContentTable of ContentTable of Content

Table of Content ....................................................................................... 1

Welcome message .................................................................................... 3

en!e ....................................................................................................... "

International Workshop on Renewable Energy 2013 #ea$ership ............... %

&ession 1 ................................................................................................... '

Implementation of renewable energy in power system ........................... 'Insulation Condition Monitoring and Diagnostics in Grid-connected Renewable Energy Systems ..... 7

Integration of Renewable Energy Sources to Small Power Systems ................................................. ! " #wo-Stage Model Calculated Distribution System Planning Integrated Distribution Generator ... $

P%oto&oltaic 'ower system in (ietnam and )a'an* 'otential and de&elo'ment .............................. +

Grid connected P( system facing &oltage sags , solutions to "&oid nwanted disconnection ........ !

Electricity Su''ly to a /ocal0Isolated "rea by Means of Renewable Energy ..................................... !!

"nalysis of (oltage Sags and Protection Coordination in Distribution Systems wit% Sensiti&eE1ui'ment ......................................................................................................................................... $

&ession 2 ................................................................................................. '(

Technical) economic an$ policy iss!es for renewable energy .................. '(

Renewable Energy De&elo'ment in (ietnam .................................................................................... 7

#ec%nical Issues for 2ew and Renewable Energy De&elo'ment in (ietnam ..................................... 3

Medium-term and S%ort-term Electricity Demand 4orecasting ........................................................ 3$

Reconstruction of Syrian Electric Power Infrastructures by Renewable Energy ............................. 557

Current Problem 4aced in (ietnam "ssociated wit% t%e Integration of Small 6ydro and ind Energy


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2013 International Workshop on Renewable EnergyTable of Content

Design and ;'timi>ation of a Micro-cogeneration System sing a ?Double Effect? Stirling Engineand a #ubular /inear Induction Generator ...................................................................................... ==3

/ig%tning Induced ;&er&oltage in #%e Control System of " ind #urbine ..................................... = !

Im'lementation Su'er&isory Controller for 6ybrid ind Microgrid System sing "da'ti&e 2euralMimo Model .................................................................................................................................... =+3

Modeling of Corona Disc%arge and Its "''lication to /ig%tning Electromagnetic Pulse Com'utations ......................................................................................................................................................... =$$

2ew "lgorit%ms for Im'ro&ing t%e Reliability of ireless Sensor 2etwor@ in Renewable EnergySystems ............................................................................................................................................ =75

&ession " ............................................................................................... 2+%

Win$) solar an$ ti$al energy ................................................................. 2+%

Direct a&e Energy Con&erters. Case of SE"RE( 'roing and Placing Distributed Generators in a 2etwor@ System ..... $

Grid Integration Study of ind Power in Ain% #%uan Pro&ince ....................................................... 3


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2013 International Workshop on Renewable EnergyWelcome messa e

Welcome messageWelcome messageWelcome messageWelcome message

It is a great &leasure and $onor to welcome you to t$e 1+*uu 5ibrary is on your left


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2013 International Workshop on Renewable EnergyIWRE 2013 Leadershi

International Workshop on Renewable Energy 201 !ea"ership

International committee

Chairman ) Top Tran+ an 3Hanoi University of Science and Technology, Vietnam

Co+chairs,

Eman!el -oang 3Ecole Normale Suprieure de Cachan,France

arc /etit 3Supelec, France

&tephan stier 3 nstitut National !olytechni"ue de Toulouse, France

Technical committee

-ami$ en hme$ 3#cole Normale Suprieure de Cachan, France

iet g!yen+ !an+-oang 3Hanoi University of Science and Technology, Vietnam

4hanh ach+5!oc 3Hanoi University of Science and Technology, Vietnam

ernar$ 6o!rnet 3#cole Normale Suprieure de Cachan, France

Toan /h!ng , University of Ne$ South %ales, &ustralia

T!an g!yen+ nh 3 nstitute of Energy, Vietnam

&on Tran+Thanh 3Electric !o$er University, Vietnam

T! !+/han 3Vietnam National University, Ho Chi 'inh City, Vietnam

#ocal organi7ing committee

Thinh /ham+-ong 3Hanoi University of Science and Technology

inh Tr!ong+ goc 3Hanoi University of Science and Technology

T!ng g!yen+ !an 3Hanoi University of Science and Technology

-!y g!yen+8!c 3Hanoi University of Science and Technology

T!ng #e+8!c 3Hanoi University of Science and Technology


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2013 International Workshop on Renewable EnergySession 1

#ession 1#ession 1#ession 1#ession 1

C$airs)Prof. "ran 'an "o&3 Hanoi University of Science and Technology

Prof. !=i$iro !metani3 *oshisha University


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Implementation of renewable energy in power systemSession 1

4eynote #ect!re

Insulation Condition Monitoring and Diagnostics in Grid-connectedRenewable Energy Systems

/rof. /h!ng Toan

University of Ne$ South %ales, Sydney, &ustralia

Abstract - "$e dri%e for clean energy and sustainability $as led to t$e emerging trend of integration ofRenewable Energy ?RE@ systems into eBisting electricity grids. 0orldwide trends s$ow t$e &ro&ortion

of grid-connected generation from renewable energy ?$ydro3 solar3 wind3 etc@ is steadily increasing.

"$e im&act of $ig$ &enetration of distributed RE into t$e electricity grid &resents new c$allenges to

t$e reliable o&eration of t$e infrastructure3 e.g. cables3 transformers3 etc. "$is &resentation gi%es an

o%er%iew of %arious tec$nical issues im&osed on t$e insulation systems of &ower &lant eAui&ment. 6f&articular concern are t$e increased ris= to t$e insulation caused by $ig$-freAuency switc$ing

transients and o%er%oltages generated by &ower electronic interfacing. "$e $ig$er degree of

generation intermittency will affect &lant o&eration3 t$ermal stress &attern3 and t$us insulation ageing.

6%er t$e years3 one of t$e =ey researc$ acti%ities at 2 S0 $as been t$e de%elo&ment of insulation

diagnostic tec$niAues and on-line conditioning monitoring systems. Muc$ of t$is wor= can be utili:ed

to assist in e%aluating t$e insulation &erformance under new o&erating en%ironments. "$is will bediscussed in t$e tal=.


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2013 International Workshop on Renewable Energy (IWRE)

Insulation Condition Monitoring andDiagnostics in Grid-connected RenewableEnergy Systems

Toan PhungUniversity of New South Wales, Australia

2 October, 2013 8


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Renewable Energy Resources in Vietnam

Solar Energy : Solar radiation is ~2.4 to 5.6 kWh/m 2/day in Northernregions, and ~4 to 5.9 kWh/m 2/day in Southern and Central areas.

Wind Power : long coast line (up to 3000km) with average windspeeds of 5.6m/s. Capacity is estimated about 513 GW.

Biomass Energy : with 20% of GDP contributed by Agriculture,Biomass Power is forecasted potential of 1000-1600 MW.

Geothermal Energy : more than 300 hot springs with temperaturerange from 30C to 148C. Potential capacity of 1,400 MW.

Hydro Power : Vietnam is appraised of potential of small and largehydro power plants.

(Source: http:/www.laurea.fi/en/connect/results/Documents/Vietnam%20Fact%20Sheet.pdf accessed 19/09/2013)

9
http://www.laurea.fi/en/connect/results/Documents/Vietnam%20Fact%20Sheet.pdfhttp://www.laurea.fi/en/connect/results/Documents/Vietnam%20Fact%20Sheet.pdf


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Source: http://en.openei.org/wiki/Vietnam accessed 19/09/2013Solar Radiation Distribution in selected Asian regions 10
http://en.openei.org/wiki/Vietnamhttp://en.openei.org/wiki/Vietnamhttp://en.openei.org/wiki/Vietnam


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Wind Resource Distribution in VIETNAMat 80m height

Source:https://www.esmap.org/sites/esmap.org/files/MOIT_Vietnam_Wind_Atlas_Repor

t_18Mar2011.pdf accessed 19/09/2013 11
https://www.esmap.org/sites/esmap.org/files/MOIT_Vietnam_Wind_Atlas_Report_18Mar2011.pdfhttps://www.esmap.org/sites/esmap.org/files/MOIT_Vietnam_Wind_Atlas_Report_18Mar2011.pdfhttps://www.esmap.org/sites/esmap.org/files/MOIT_Vietnam_Wind_Atlas_Report_18Mar2011.pdfhttps://www.esmap.org/sites/esmap.org/files/MOIT_Vietnam_Wind_Atlas_Report_18Mar2011.pdfhttps://www.esmap.org/sites/esmap.org/files/MOIT_Vietnam_Wind_Atlas_Report_18Mar2011.pdf


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Australia generates ~1.5% of global greenhouse gas emissions.On per capita basis, one of world's largest polluters.

About 24.4 tonnes of CO 2e per person in a year (2012)

About twice OECD average and > 4 times world average

Sources of Australias emissions:

Source: Department of Climate Change and Energy Efficiency Australias Emission Projections 2010

Renewable Energy in Australia

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Renewable Energy Resources in Australia

Abundant, high quality renewable energy resources, widely distributedacross country including solar, wind, wave and bioenergy resources.

Solar Power : highest solar radiation per m 2 of any continent on earth.Receive annual average of equivalent to 16 billion GWh of solar energy.

Wind Power : some of the best wind resources on earth. Coastal regionswith high wind resources (speeds >7.5m/s). Annual estimate of 273 TWh.

Biomass Energy : Australia is appraised potential of bioenergy resource islarge. It is forecasted to reach 72,629 GWh per year.

Hydro Power : driest inhabited continent on earth, over 80% of landmassreceives annual average rainfall of


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Annual average solar radiation (in MJ/m 2)and currently installed solar power stations

with capacity of >10 kWSource: Australian Energy Resource Assessment

Annual capacity of Solar Energy

installed in AustraliaSource: Clean Energy Report Australia 201214


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Wind Speed Distribution in Australia(at 70m height)

Source: Wind Resource Assessment in Australia - 2003

Development of Wind Power Generationin Australia

Source: http://www.thewindpower.net/country_en_16_australia.php

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http://www.thewindpower.net/country_en_16_australia.phphttp://www.thewindpower.net/country_en_16_australia.phphttp://www.thewindpower.net/country_en_16_australia.php


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420MW Macarthur Wind Farm, Victoria, Australia

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420MW Macarthur Wind Farm

140 x 3MW turbines, currently the largest wind farm in thesouthern hemisphere.

Cost AUD1 billion, construction took 2.5 years, operationalsince late Jan. 2013.

Wind turbine output: 480-690V, convert by WTSU transformerto a collector voltage of 13.8-46kV.

~100km of underground 33kV cable and OH lines connectingturbines to the wind farm sub-station.

33kV/132kV wind farm sub-station with 2 x 280MVA parallelstep-up transformers.

14km of 132kV OH lines to Tarrone sub-station whereconnection to 500kV line was made.

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Installed capacity by

fuel type (MW)June 2010

Australias per capita electricityconsumption: ~22% > OECD average

Capacity of grid-connectedgeneration = 54.3GW

Capacity of embedded and non-gridgeneration = 5.9GW

Total generation (2010-11) =228,067 GWh

Black coal: 50.7%

Brown coal: 24.2%Natural gas: 15.5%Hydro: 7.0%Wind: 2.6%Oil and other:


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Some technical issues from grid-connected RES

Wind and Large Solar (Bulk System Connected Generation)Steady state and transient stability analysisLoad/generation coincidence (peak load and variability of source)Regulation requirementsIntegration with Automatic Generation Control (AGC)

Incorporation of renewable resource forecastingOperating practice to enable high penetration

Distributed Solar and Small Wind (Distributed Generation)Voltage and VAR regulationPower Quality (Harmonics, Flicker, DC Injection)

Unintentional islandingProtection design and coordinationEquipment groundingLoad and generation imbalanceEnergy storage and storage controls

Ref.: Ben Kroposki, National Renewable Energy Laboratory19


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Impacts on power losses and efficiency

Transformers:Core loss (iron loss)

Hysteresis lossEddy current loss

Winding loss (copper loss)

Cables:Dielectric loss

Skin effect: higher frequency reduced skin depth higherresistance higher Ohmic loss

Increased power lossLower efficiencyHigher operating temperature

Derating of equipment

2 2

1 2nm m P k fB k f B

22 tan P fCV

21


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Impacts on insulation from RES

Harmonics:increase real power lossinsulation temperature riseaccelerate ageing (Arrhenius law)

High-frequency switching spikesincrease likelihood of partial discharges (PD).detection of PDs during HF transient is a challenge.

HV-DCenabling technology for access to remote RES, e.g. off-shore wind farms, Europe Multi-terminal DC Super Gridselectric stress under DC very different from that under ACspace charge

temperature effect is very significant 22


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Electrical insulation materials

Power system components: transformers, overhead transmissionlines and cables, switchgear, rotating machines

Choice of electrical insulation varies for particular applicationand voltage level

Wide range of electrical insulating materialsGases: air, Nitrogen, Hydrogen, SF 6, SF6 mixture, vacuum, etcLiquids: mineral oils, synthetic hydro-carbons, etcSolids: resins, polymers, ceramic, etcComposites

Electrical breakdown strengthReal power loss: leakage current loss, dielectric loss (AC only),partial discharge (PD)

Condition of insulation critical factor to equipment life23


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Condition monitoringAsset Maintenance Strategies

Corrective maintenance (CM): reaction only when failureoccursTime-based maintenance (TM): preventive maintenance in fixedtime periodsCondition-based maintenance (CBM) : preventive maintenancedepending on actual conditions

Extend asset lifetimes through condition monitoring

On-line condition monitoring: Smart Grid

24


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CIGRE TF15.11/33.03.02

Role of insulation condition assessmentwithin risk assessment.

Vales Point power station Transformer

blast and fire SMH 9Nov06 25


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Partial Discharges (PD)Localized electrical discharge that only partially bridges insulationbetween conductors

Due to presence of small defects or design flaws which create alocalized region of excessive electric stress that exceeds breakdownstrength of the insulation

Example: electric stress in cables

Typical maximum operating stress: ~ 3kV/mm (for MV) to ~6 kV/mm (HV)

MV cables (3.8/6.6 19/33kV XLPE singlecore screened and PVC sheathed)

27


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Stress profile (without void)

Stress profile (with void)

Electric stress enhancement in a gas void within a solid dielectric:

28


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On-line condition monitoring of PDs in cables

Significant interference and background noise detectionsensitivity is a challenge

Measured (apparent) PD magnitude < true PD magnitude

Extensive use of signal processing

Cable joints, main cable insulation, cable terminations

Different types, different ages, different operating history

Data processing: trend analysis, phase-resolved pattern, PD pulsesequence

Data mining

PD fault classification, location expert systems

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General configuration of the Partial Discharge Monitor (PDM) system

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PDM-I system:Suitable for good SNR situationUp to 12 channels multiplexedFast quasi real-time monitoring

PDM-II system:

Suitable of noisy locationsDual simultaneous channelsSoftware-based PD extraction

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2013 International Workshop on Renewable Energy

(IWRE)

34



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Integration of Renewable Energy Sources to Small Power Systems

Toshihisa 9!nabashi

'eidensha Corporation+ %aseda University, To yo, -apan

Abstract - "$is &resentation deals wit$ c$allenges and countermeasures for integration of renewableenergy sources to &ower systems3 es&ecially to small &ower systems suc$ as microgrids and small

remote islands. C$allenges include demand and su&&ly control met$od considering uncertainty of

generations and loads es&ecially forecasting &ower out&uts of renewable energy sources. !lso in t$is

&a&er we deal wit$ &ower out&ut fluctuations mitigating tec$nologies for renewable energy sources.

Efforts are &erformed as demonstration &ro ects and as standardi:ation of microgrid tec$nologies. I

li=e to consider $ow we could collaborate toget$er to de%elo& and commerciali:e integration of

renewable energy sources to small &ower systems.



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! "wo-Stage Model Calculated Distribution System Planning

Integrated Distribution Generator. . Thang 1( #. T. /hong 1( 8. 5. Thong 2( . 5. 4hanh 2

. Thai Nguyen University of Technology (TNUT), Vietnam/ Hanoi University of Science and Technology, Vietnam

Abstract - Recently3 t$e distribution system design and &lanning $as c$anged due to t$e im&acts of DGand electricity mar=et restructuring. "$erefore3 t$is &a&er &ro&oses a two stages model for o&timi:ing

&lanning of distribution system wit$ t$e &resence of DG. "$e &ro&osed model can determine o&timal

u&grading si:ing and timeframe of eAui&ment in distribution system. >esides3 o&timal dis&lacement3

si:ing3 tec$nology and installation &eriod of DG are also determined. "$e modelHs t$e ob ecti%efunction is minimum life cycle cost for t$e &lanning sc$eme. "$e constraints are used to guarantee t$e

tec$nical and economic indicators of t$e system. "$e calculation &rogram is made in G!MS

en%ironment. "$e feasibility and effecti%eness of t$e &ro&osed model are %erified by t$e result of

a&&lying it to a test system.

Keywords: Planning of Distribution System ?DS@3 Distributed Generator ?DG@


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A Two-Stage Model Calculated Distribution SystemPlanning Intergrated Distribution Generator

V. V. Thang and L. T. PhongDepartment of Electric Power Systems

Thainguyen University of Technology (TNUT)Thainguyen, Vietnam

[email protected]

D. Q. Thong and B. Q. KhanhDepartment of Electric Power Systems

Hanoi University of Science and Technology (HUST)Hanoi, Vietnam

[email protected]

Abstract - Recently, the distribution system design and planninghas changed due to the impacts of DG and electricity marketrestructuring. Therefore, this paper proposes a two stages modelfor optimizing planning of distribution system with the presenceof DG. The proposed model can determine optimal upgradingsizing and timeframe of equipments in distribution system.Besides, optimal displacement, sizing, technology and installationperiod of DG are also determined. The models the objectivefunction is minimum life cycle cost for the planning scheme. Theconstraints are used to guarantee the technical and economic

indicators of the system. The calculation program is made inGAMS environment. The feasibility and effectiveness of theproposed model are verified by the result of applying it to a testsystem.

Keyword: Planning of Distribution System (DS), DistributedGenerator (DG)

I. I NTRODUCTION In the past decade, distribution system planning had major

changed due to the impact of competitive electricity market,DG technological development and environmental pollutions.In particular, DG connecting directly to DS or directlysupplying to customers is used as a popular planning approach.These sources normally use electric generating technologiessuch as gas turbines, combined heat and power, Fuel Cells,solar energy and wind energies. Therefore, the benefits of DGincluding reduction of transmission and distribution cost,

power loss and enhancement of flexibility and reliability of DS,improvement of differential voltage at nodes as well asreduction of environmental pollution [1]. However, DG

requires high investment, makes increasing the complexity inmeasurement and relay protection as well as operation of DS[2]. Besides, DG using renewable energy resources has thenaturally variable power according to primary energy.

Many planning models of the DG integrated distributionsystem are already been researched and proposed. The authorsin [3] presented a long term DS planning model in order to

the objective function including the total investing andoperating costs of DG, feeders and substation transformersupgrading costs, energy expenses and minimum interruptibleload costs. In this research, effects of DG technology are alsonot mentioned in selecting variables. The objective function ofthe two-stage DS planning model in [5] includes the minimumof total costs for upgrading feeders, substation transformers andDG construction, energy expenses purchased from market andenvironmental pollution costs. Similarly, [6] introduced a DS

planning model determining optimized equipment sizing andtimeframe required for DS upgrading. The selection issuesoptimal displacement, sizing, installation period andtechnology of DG to meet the demand growth are presented in[6]. Besides, the model uses the objective function that isminimum life cycle cost for the distribution system planningintroduced in [7]. The model finds best distribution system

planning scheme to maximize the overall benefits and costs inthe life cycle of the system. In previous studies, the power ofDG is always assumed to be constant without regarding to thenatural variability of DG capacity which depends on the

primary energy, this is not practical. Therefore, this paper proposes an optimized DS planning model that integratesoutput power characteristics of DG, characteristics of loaddemand and electricity price.

The next parts of this paper are organized as follows.Section II introduces a mathematical model with objectivefunction and constraints. Section III shows calculation resultsfrom the 7-bus DS. Conclusion is presented in Section IV.

II. THE MATHEMATICAL MODEL

In competitive electricity market, DS are managed bydistribution companies. These companies can buy electricalenergy completely from electricity market or combine withinvesting DG in order to meet load demands in future. So,economic and technical indices of planning project are changedwhich affects considerably to time, upgrading capacity offeeders and substations when DG are chosen in DS planning


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model is added in the second stage plan to more closely reflectthe required investments and production schedules.

A. The Mathematical Model of First Stage1) Objective Function

The objective function of proposed model is to minimizetotal life cycle cost of the investment project during calculation

period as shown in equation(1). The total cost is calculated at base year with equation 1/ (1 ) t r + and discount rate r.

( )1

1.

(1 )

T

t t t t t t t t

J CF CS CDG EDG ES RN Minr

t T

== + + + + +

+

"

(1)

Where, componentt CF is upgrading costs of feeders for

year t with fixed capital cost (C FF) and variable capital cost(CFC) as shown in equation(2).

ij. ,1 1

( . . )

, ,

N N FF FC

t ij t ij t i j i

CF L C C F

ij N i j t T

a= = +

= +

"

(2)

Substation transformers upgrading costs in year t withfixed capital cost (C SF) and variable capital cost (C SC) is

presented in equation(3).

, ,1

( . . )

,

NS SF SC S

t i t i t i

S

CS C C S

i N t T

g =

= + D

"

(3)

Electrical energy purchased cost from electricity market is presented in equation(4).

. , , , . , , ,1 1 1ES . .( . . )

, , ,

NS SS H S S S S

t s P P h i t s h Q h i t s hi s h

S

D k P Q

i N t T s SS h H

r r = = == +"

(4)

The equation (5) is new investment costs in year t withtechnologies k of DG. Beside, electrical energy purchased costfrom electricity market and costs for fuel, operation andmaintenance of DG depending per technology k, operationseason s and time h are shown in equation(5) and (6).

, , ,1

.

, ,

DG DG N K DG DG

t i k i k t i k

DG DG

CDG C P

i N k K t T =

=

"

(5)

. , , , , . , , , ,1 1 1 1

( . . )

, , , ,

DG DG N K SS H DG DG DG DG

t s P k i k t s h Q k i k t s hi k s h

DG DG

EDG D P Q

i N k K t T s SS h H

r r = = = =

= +

"

(6)

, ,, , ,

1 1 ,

( ) ( ). .

( ).

, ,

DG DG

F S kh F kh S

t t t F S

DG K N kh k DG k DG DG

i k i k t k i DG k

DG DG

t T t T RN CF CS

T T

t T C P

T

i N k K t T

= =

- -= +

-+

"

(7)

2) The constraints

a) Constraints for power flowThe output power characteristics of each DG technology

using renewable energy resources fluctuate by time of day andseason in year so the power of DG is also determined by eachhour, season and specially, each technology k of DG. Hence, anonlinear power flow representation in (8) is used in this stage.

, , , , , , , , , ,1

, , , , , , , , , , , , , ,1

, , , , , , , , , ,1

, , , , , , , , , , , , , ,1

. . .cos( )

. . .sin( )

,

DG

DG

K DG S

i k s t h i s t h i s t hk

N

ij t i s t h j s t h ij t j s t h i s t h j

K DG S i k s t h i s t h i s t h

k

N

ij t i s t h j s t h ij t j s t h i s t h j

P P PD

Y U U

Q Q QD

Y U U

i j

q d d

q d d

=

=

=

=

+ - =

- -

+ - =

- - -

"

, , , , DG N k K s SS h H t T

(8)

Where,, , , , DGi k s t h P and , , , ,

DGi k s t hQ are output power of DG

introduction in(9).

, , , , , , , ,

, , , , , , , ,

.

os .

DG DG DGi k s t h i k t k s h

DG DGi k s t h k i k s t h

P P k

Q c P j

==

(9)

b) Limit capacity constraints of DGThese constraints allow computed DG capacity at nodes in

limit of DG technology, and it ensures annually upgrading power corresponding to equipment parameters as shown in(10).

, , , ,max , , , ,

, , , , 1 , , , , 1

0 0 tan .

1, , ,

DG DG DG DGi k t i k i k t k i k t

DG DG DG DG DG DGi k t i k t i k t i k t

DG DG

P P Q P

P P P Q Q Q

t i N k K t T

j

- -

= + D = + D"

(10)

c) Upgrading section constraints of feederThermal limits are imposed to limit the loading of feeders

and these limits take into consideration the new feederinvestments. So, the feeders upgrading constraints andupgrading power satisfying equipment parameters are shownin(11). A step increase of feeder capacity at year t

ij( ) F SD is


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Then, feeder capacity needs to meet in order to supply power to the loads present in (12) and upgrading section is

selected by equation(13) with current density J.* *

, , 1 ij, 1, , F F F

ij t ij t t S S S t ij N t T -= + D " (12)*

,ij, ,. 1, ,3 .

F ij t

t ij t

dm

S F t ij N t T

U J a " (13)

d) Addition capacity constraints for substationThese constraints allow to maximize the use of existing

substations capacity and to satisfy upgrading power

corresponding to equipment parameters. A substation capacityaddition step size

i,( )S t S D is used to set substation sizes as in

equation(14) with the maximum and minimum allowablecapacity which a substation can be upgraded.

ax *, , 1 i,

i, min i,t

i, i,t

( )

.

.

1, ,

m S S i t i t t

S S t

S t

S S S

S S

S M

t i NS t T

g

g

- + DD DD

"

(14)

e) Constraints of limited nodal voltageTechnical requirement constraints of limited nodal voltage

are given in equation(15). Voltages at substation nodes areassumed constantly.

min , , , max

, , ,

, , ,

, , ,

i s t h L

i s t h S

U U U i N s SS t T h H

U constan i N s SS t T h H

"

= " (15)

The decision variables of model include real and binaryvariables so calculation results must be corrected by standardequipment in fact and used as parameters in second stage.

TABLE I. S ETS A ND I NDICES

No Symbol Definition1 N Set of buses in distribution system2 i, j Bus (i, j N)3 NL Set of load buses in distribution system4 NS Set of substation buses in distribution system5 NDG Set of DG buses in distribution system6 t, T Planning year and overall planning period (t T)7 h, H Hour and hours per day (h H)8 k,K DG Technology and total technology of DG (k K DG)9 s,SS Season and total seasons in year (s SS)

B. The Mathematical Model of Second StageThis stage takes the input parameters obtained from the first

stage. Hence, equations of objective function are presented as(16) and decision variable DG power is

, , DGi k t P .

*2 ij. ,

1 1 1

*, , , , ,

1 1 1

. , , , . , , ,1 1 1

1. ( . . )

(1 )

( . . ) .

( . . )

DG DG

T N N FF FC

ij t ij t t t i j i

N K NS SF SC S DG DG

i t i t i k i k t i i k

NS SS H S S S S

s P h i t s h Q h i t s hi s h

J L C C F r

C C S C P

k P Q

a

g

r r

= = = +

= = =

= = =

= ++

+ + +

+ +

. , , , , . , , , ,1 1 1 1

( . . ) DG DG N K SS H

DG DG DG DG s P k i k t s h Q k i k t s h

i k s hk P Qr r

= = = =+ + (16)

*ij. ,

1 1

*, ,

1

, ,, , ,

1 1 ,

( ). ( . . )

( ). ( . . )

( ).

, , , ,

DG DG

F N N FF FC kh F

ij t ij t i j i F

S NS SF SC S kh S

i t i t iS

DG N K kh k DG k DG DG

i k i k t i k DG k

DG

t T L C C F

T

t T C C S

T

t T C P Min

T ij N k K t T s SS h H

a

g

= = +

=

= =

-+ +

-+ +

-+

"

2) The constraints

a) Constraints for power flow and limited nodal voltageThese constraints are similar in first stage and presented on

equations(8)(15).

b) Limit capacity constraints of feeder and substationTo ensure the after upgrading feeders are not overloaded by

thermal limit, load flow on feeder need observe as equation(17)and substation capacity must observe as equation(18).

, , , max. ,

1, , , ,

F F ij t s h ij t S S

t ij N t T s SS h H

"

(17)

, , , ax. ,

1, , , ,

S S i t s h m i t S S

t i NS t T s SS h H

"

(18)

c) Limit capacity constraints of DGThe investment location and period of DG was determined

from first stage so these constraints allow selected DG capacityaccording to new limits as(19).

*, , max . , , , , ,0 0 tan . DG DG DG DGi k t i k i k t k i k t

DG DG DG DG DG DG

P P Q P j


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TABLE II. P ARAMETERS

No Symbol Definition

1 r Discount rate (%)2 CFF Fixed capital cost of Feeder ($/km)3 CFC Variable capital cost of Feeder ($/km.mm 2)4 L i,j Length of Feeder (km)5 Yi,j,t, qi,j,t Magnitude and Angles of admittance matrix element (pu)6 CSF Fixed capital cost of Substation ($/Substation)7 CSC Variable capital cost of Substation ($/MVA)

8 i, DG

k C New investment cost for DG i, technology k ($/M)

9 PS hr Active power purchased cost from market ($/kWh)

10 QS hr Reactive power purchased cost from market ($/kVAh)

11 . DG P hr O&M cost and Fuel cost of DG for active energy ($/kWh)

12 . DGQ hr O&M and Fuel cost of DG for reactive energy ($/kVAh)

13 PD i,s,t,h Active power demand at bus (kW)14 QD i,s,t,h Reactive power demand at bus (kVAr)

15 ax . , DGm i k P Maximum power limit of DG i, t echnology k (MW)

16 Cosj k Power factor of DG with technology k17 *ax . ,

DGm i k P New maximum power limit of DG in second stage (MW)

18 *ij, t F Standard section of Feeder in planning year t (mm 2)

19*ij, F t S Maximum capacity need upgrading of Feeder (MVA)

20 min F S D Capacity ramp-up limit for Feeder (MVA)

21 max.ij, F

t S Maximum capacity limit of standard Feeder (MVA)

22 *i,S t S Maximum capacity need upgrading of Substation (MVA)

23 minS S D Capacity ramp-up limit for Substation (MVA)

24 max.i,S

t S Maximum capacity limit of standard Substation in

planning year t (MVA)25 J Current density at thermal limit (A/mm 2)

26 M Big number used maximum limit of variables in MIP and

MINLP models27 U max Maximum voltage limit at bus (pu)28 U min Minimum voltage limit at bus (pu)29 DPDG Active power ramp-up limit for DG (MW)30 DQDG Reactive power ramp-up limit for DG (MVAr) 31 , ,

DGk s hk Output power factor of DG with technology k

32 k P Variation factor of the price of electricity33 D S Total day per season

TABLE III. V ARIABLES

No Symbol Definition

1 ij, t F Upgrading section of Feeder (mm 2)

2 i,S t S D Addition capacity for Substation (MVA)

3 i, , DGk t P New investment capacity of DG (MW)

4 i , , ,S s t h P Active power purchased from electricity market (kW)S

III. R ESULTS A ND DISCUSSIONS

A. Diagram and Parameters of distribution systemThe 7-bus and 22kV voltage radial diagram is investigated

in this research as figure 1 and is connected to 110kVsubstation. The total active power and reactive power at the

base year are 6465kW and 5091kVAR, respectively.

B. Assumptions in analyisThis research utilizes some economic and technical

assumptions for the ease of computation:

Planning period is 10 years and annual developing rateof load demand is constant, 10% per year

The constructing cost of 110kV substation includingfixed costs and variable costs is 0.2M$ and0.05M$/MVA, respectively [5]. Similarly, theupgrading costs of 22kV feeders consist of 0.15M$/kmand 0.001M$/MVA.km

The effects of DG technology are represented byinvestment, operation and fuel costs. Two DGtechnologies, photovoltaic (PV) and small hydrosources, are used in this research with thecorresponding capital costs to be 5.0M$/MW and1.5M$/MW.

Average O&M costs depend on used technology andthe life of DG such as table IV. The assumption life offeeder is 20 year.

TABLE IV. A VERAGE O&M COSTS A ND LIFESPAN OF DG

Average O&M costsNo Technology Active power

($/kWh)Reactive power

($/kVAr)

Lifespan(years)

1 PV 5 0 202 Small hydro 5 1 30

Energy prices purchasing from electricity marketthrough substations are specified in terms of the threetime blocks of peak, intermediate and base price astable V.

TABLE V. E NERGY PRICES PURCHASE FRO M ELECTRICITY MARKET

Figure 1. Diagram of test distribution system

Substation

1 5 6

2 3 4

7


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Areas of upgrading of substation transformers andfeeders are not limited

Constraint of limited load nodes voltage changes from0.9pu to 1.1pu, and it should be 1.05pu at substationnode

Decided variables in the model are continuous in orderto reduce the complexity of the model. Hence, theyshould be rounded to match real equipments.

C. The output power characteristics of DGThe output power of PV depends on the intensity of solar

radiation and its performance. The power of 1MWp PV with25% performance calculated basing on the given solar radiationintensity is presented as figure 2.

Small hydro power depends on the nature of the primaryenergy source. Therefore, the output power characteristics of1MW small hydro are shown as figure 3.

D. Analysis results and disscussionsThe feasibility of the proposed model and efficiency of DG

are investigated in two cases. Case A: DG is not consideredwhen calculating DS planning. Case B: DG is integrated in theresearching model.

The results of calculating showed that case A need toupgrade substation with a 10MVA capacity. In contrast,investment to upgrade substation in case B is deferred becauseof the load demand increasing in the future is provided by DG.

economic and technical efficiencies are gained. In contrast, thePV is not selected due to a very high investment cost.

TABLE VI. F EEDERS UPGRADING DECISIONS

Feeder section upgrading in each year (mm 2)Feeder

1 2 3 4 5 6 7 8 9 10Case A

1-2 702-33-41-5 505-62-7

Case Bij

Economic indices are compared between case B and case Aas in table VIII. The case B holds a better economic index.Cost of DG investment and equipment upgrading (feeders andsubstation) are more expensive than those of case A about2.17M$ due to a very high cost of DG investment. However,O&M and electric energy expenses have been decreased by4.26M$ because of very low O&M expenses of small hydro.Therefore, the efficiency gets higher at final years of planning

period. Total l ife cycle cost of case B is cheaper than these ofcase A by 3.47M$, equal to 17.2%.

TABLE VII. DG I NVESTMENT DECIDED

DG capacity invested in each year (MW) DGtechnology Bus 1 2 3 4 5 6 7 8 9 10

2PV74 1Small

hydro 6 1

Total 2.0MW

The technical indicators of DS are also improved when DGis integrated on DS planning. The power loss at maximizingload demand times is reduced 1.8% in 7 th planning years soelectric energy loss decreased 3210.0MWh during planning

period. Total of electric energy purchased from market is alsodecreased 97,740.0MWh corresponding to 25,402.6tons areCO2 emission, which contributes to the decrease ofenvironmental pollution.

TABLE VIII. E CONOMIC I NDICES COMPARISON

No Cost Case A Case B

ComparisonB and A Note

1 Total life cycle cost (M$) 20.21 16.74 -3.47

2 Feeder and Substationupgrading cost (M$) 1.26 0.43 -0.83

3 O&M and Electrical energyt (M$) 19.89 15.63 -4.26 t a l

l i f e c y c l e

ts i s r e

d u c e

d -

1 7 . 2

%

Figure 3. The output power characteristics of small hydro

0

0.2

0.4

0.6

0.8

1

1.2

1 2 3 4 5 6 7 8 9 10 11 12 13 1 4 15 16 17 1 8 1 9 20 2 1 22 2 3 24

hour

T h e o u

t p o w

e r o f s m a l l h y d

r o ,

M W

Summer Winter

0

0.05

0.1

0.15

0.2

0.25

0.3

0.35

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24

hour

T h e o u t p o w e r o

f P V

, M W

Summer

Winter

Figure 2. The output power characteristics of PV


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IV. CONCLUSIONS

Recently, the DS planning has been changed significantly by the impacts of DG and environmental policies. DG hasmany benefits for DS as enhancement of flexibility andreliability, bus voltage improvement, reduction oftransmission cost and power loss as well as reduction ofenvironmental pollution. However, the investment cost ofDG is expensive and DG power that uses renewable energyresources is natural variability according to primary energyso the planning and operation calculation of DS will be more

difficult. Therefore, this study proposed a new two-stageoptimized model that is integrated DG in DS planning. In

this model, equipment sizing and timeframe required forupgrading equipment for DS well as select DG technologieswith power variable constraints of DG can be determined.The objective function is minimizing total life cycle cost ofthe investment project. Calculation results showed that the

proposed model is suitable in large DS planning calculationsand the planning together with using DG provided bettereconomic and technical indicators.

APPENDIX A. DATA OF LOADS

No Bus PD 0 (kW)

QD 0 (kVAr)

No Bus PD 0 (kW)

QD 0 (kVAr)

1 1 - - 5 5 1070 8732 2 743 458 6 6 1830 16083 3 1525 1217 7 7 647 4284 4 650 507 Total 6465 5091

* Where: PD 0, QD 0 - active and reactive power demand at bus in ba se year of planning period

APPENDIX B. DATA OF FEEDER PARAMETERS

No Bus i - Bus jF ij

(mm 2)Smax.ij

(MVA)L ij

(km)Rf ij ( )

Xf ij ( )

1 1-2 50 8 2.3 1.362 0.9612 2-3 50 8 2.2 1.302 0.9203 3-4 35 6.67 3.3 2.551 1.4164 1-5 35 6.67 3.5 2.706 1.5025 5-6 35 6.67 1.7 1.314 0.7296 2-7 35 6.67 1.2 0.928 0.515

* Where: S max - Thermal limit capacity for Feeder

R EFERENCES

[1] Thomas Ackermann, Goran Andersson, Lennart Soder, Distributedgeneration: a definition, Electric Power Systems Research 57, 2001

[2] S. Wong, K. Bhattacharya and J.D.Fuller, Comprehensive frameworkfor long-term distribution system planning, Proc. IEEE PES AnnualGeneral Meeting, Tampa, USA, 2007

[3] Algarni, A.A.S.; Bhattacharya, K., A Novel Approach to DiscoPlanning in Electricity Markets: Mathematical Model, Power SystemsConference and Exposition, 2009. PSCE '09. IEEE/PES

[4] El-Khattam, W.; Hegazy, Y.; Salama, M., An integrated distributedgeneration optimization model for distribution system planning, PowerEngineering Society General Meeting, IEEE, 2005

[5]

S. Wong, K. Bhattacharya1and J.D. Fuller, Electric power distributionsystem design and planning in a deregulated environment, IETGeneration, Transmission & Distribution, 2009

[6] V.V.Thang, D.Q.Thong, B.Q.Khanh, A New Model Applied to thePlanning of Distribution Systems for Competitive Electricity Markets,The Fourth International Conference on Electric Utility Deregulationand Restructuring and Power Technologies (DRPT) 2011, Shandong,China, 2011

[7] Su. H, Zhang. J, Liang. Z, Niu. S, Power Distribution NetworkPlanning Optimization Based on Life Cycle Cost, 2010 ChinaInternational Conference on Electricity Distribution, 13-16 Sept. 2010

[8] Richard E. Rosenthal, GAMS - A User's Guide, GAMS Development

Corporation, Washington, USA, 2010.



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P$oto%oltaic &ower system in 'ietnam and (a&an) &otential and

de%elo&ment T!ng #e 8!c 1( !an -oang iet g!yen 1( -asegawa Ik!o 2

. *epartment of electric po$er systems, School of Electrical Engineering, HanoiUniversity of Science and Technology, 0. *ai Co Viet, Hanoi, Vietnam

/Vietnam Ta1uchi Electric Co2, 3td, 3ot .4, *ai *ong Hoan Son ndustrial !ar , 5ac Ninh

!rovince, Vietnam

Abstract )

Pur&ose "$is &a&er see=s to e%aluate t$e solar energy &otential of 'ietnam. In com&are wit$ (a&an3

country $as t$e strongly de%elo&ment in t$e domain &$oto%oltaic &ower system3 we $a%e s$own t$e

solar energy &otential of 'ietnam.

Design met$odology a&&roac$ "$e a&&roac$ ta=es t$e researc$ of a real P' system in "abuc$i

'ietnam Com&any) Electricity &roduction3 economic analy:e

indings "$e &a&er s$ows t$e efficient of t$e installation Grid-Connected P$oto%oltaic System in

/anoi area.

6riginality %alue E%aluation t$e efficient of t$e Grid-Connected P$oto%oltaic System in /anoi area is

a &rereAuisite for in%est t$e furt$er researc$.

Keywords: P' &ower system3 Grid-Connected P$oto%oltaic System in /anoi


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PHOTOVOLTAIC POWER SYSTEM IN VIETNAM ANDJAPAN: POTENTIAL AND DEVELOPMENT

Tung Le Duc 1, Xuan Hoang Viet Nguyen 1 and Hasegawa Ikuo 2

1 Department of electric power systems, School of Electrical Engineering, Hanoi University of Scienceand Technology, 01 Dai Co Viet, Hanoi, Vietnam

2 Vietnam Tabuchi Electric Co., Ltd, Lot 13, Dai Dong Hoan Son Industrial Park, Bac Ninh Province,Vietnam

Email: [email protected]

ABSTRACT

Purpose This paper seeks to evaluate the solar energy potential of Vietnam. In compare with Japan,country has the strongly development in the domain photovoltaic power system, we have show thesolar energy potential of Vietnam.

Design/methodology/approach The approach takes the research of a real PV system in TabuchiVietnam Company: Electricity production, economic analyze

Findings The paper shows the efficient of the installation Grid-Connected Photovoltaic System inHanoi area.

Originality/value Evaluation the efficient of the Grid-Connected Photovoltaic System in Hanoi areais a prerequisite for invest the further research.

Keywords PV power system, Grid-Connected Photovoltaic System in Hanoi

1. INTRODUCTION E NERGY production is a challenge of great importance for the coming years. Indeed, the energy

requirements are increasing. Today, much of the world's energy is supplied from fossil sources. Theconsumption of these sources gives rise to gases emissions, greenhouse effect and thus to an increasein pollution. In addition that the fossil fuel resources are limited.
mailto:[email protected]:[email protected]:[email protected]:[email protected]


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In the past 10 years, the use of renewable energy sources is seen as the solution to energydemands of the future. In recent years, there are an exponentially implementation of distributedgeneration (DG), in particular renewable energy (Photovoltaic, Wind) .

Photovoltaic technology has now become a major factor in the electricity sector globally. At least110 TWh, 110 billion kWh in 2013 will be produced by photovoltaic systems already installed. If thisrepresents approximately 0.5% of the electricity demand in the world, some countries have achievedsignificant percentages quickly (see Fig.1 and Table 1) [1]-[2]

Major sources of commercial energy in Vietnam are coal, petroleum, and hydropower.Significant number of households is using traditional solid fuels in residential sector for heating, lightand cooking. Vietnam for instant is net exporter of energy due to its oil and coal resources. However,in the future, the energy problems in Vietnam will be not out of trajectory of the world. The researchand the using solar PV technology are urgent issues. In this paper, the potential and development ofPV system of Vietnam is analyze in compare with Japan-a power country of PV technology (Part 2).In part 3, a research of a Grid-connected PV system is presented.

2. C OMPARE OF SOLAR ENERGY BETWEEN VIETNAM AND J APAN Vietnam has good constant solar sources, with roughly 2,000-2,500 hours of sunshine per year. In

the southern and central areas, solar radiation levels range from 4 to 5.9 kWh/m 2/day. The solar energyin the north is estimated to vary from 2.4 to 5.6 kWh/m 2/day.

MWh/m 2/year


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The Fig.2 shows that the solar energy potential of Vietnam is higher when compare preliminarywith Japan. As opposed to the potential, the PV development of Vietnam is a lot smaller. The total

power of PV system of Vietnam is 4MWp, for instant. Whereas, the total power of PV system in Japan

is 7GWp, and continue to rise sharply in the coming years (Fig.2). The reason for this development isdue to the preferential policies of Japans government: Government enacted the Renewable EnergyLaw in 2011, Feed -in Tariff (FIT) program for renewable energy power generation facilities startedfrom July 2012, Subsidy for measures to support introduction of residential PV systems (budget: 1,2

billion USD for multiple-years), Subsidy for introducing renewable energy power generation systemsas part of restoration measures (budget: 316 million USD), 1096 local governments and municipalitieswere offering subsidy programs for residential PV systems [2]-[3]

0

1,000,000

2,000,000

3,000,000

4,000,000

5,000,000

6,000,000

7,000,000

2005 2006 2007 2008 2009 2010 2011 2012

Annual PV installed capacity

kW

Fig.2. Total power of PV system and annual PV installed in Japan

Thus, Vietnam is still missing the suitable policy of the government for development the PVsystem and renewable energies in general.

In collaboration with Tabuchi Electric Company, the research of technical and economic has been invested. This is the content of part 3.

3. R ESEARCH OF G RID -CONNECTED PV SYSTEM IN VIETNAM


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Let us consider a PV system connected to Grid (Fig.3). The installation power is 9.0 kWp,including five PV arrays (1.8 kW/array). The system is installed at Tabuchi Vietnam Company inHanoi area. The turnkey price of the PV system is 30 000$, in addition of 5000$ to the cost of

maintenance during the lifecycle of PV system (25 years). Japanese Grid connect Standard is used toconnect PV system to Grid.

Its ideal within the plus or minus 45 degrees from due south. Its ideal to set up the solar cell atdue south. But, it can expect 96% amount of generation at the direction of south east and of southwest,if it can generate 100% at due south. For Hanoi area, the PV array is installed in southbound, tilted 5 0 (Fig.4) [4]

Fig.4. Direction & Roof Slope in Hanoi Area

The Fig.5 shows the power production of PV system during one day. The power is high in theafter-noon (from 10h to 15h) and it is proportional with solar irradiance. The total energy productionfor each month is presented in Fig.6. In summer, PV power production is higher than in the winter.

4000

5000

6000

7000

8000


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0.00

100.00

200.00300.00

400.00

500.00

600.00

700.00

800.00

900.00

1,000.00

10 11 12 1 2 3 4 5 6 7 8 9Oct

2012Nov2012

Dec2012

Jan2013

Feb2013

Mar2013

Apr2013

May2013

Jun2013

Jul2013

Aug2013

Sep2013

kWh

Fig.6. Energy production (kWh) from 10/2012 to 9/2013

For instant, there is n ot Feed -in Tariff (FIT) for PV power generation in Vietnam. If the energy price of PV system is 0,075$/kWh (the energy price of EVN), the investors cannot recover capital(Fig.7.a).

a)With energy price 0.075$/1kWh b)With energy price 0.3$/1kWh

Fig.7. Cumulative cash flows graph (Installation PV system in Vietnam)

If the energy price of PV system is 0.3$/kWh (energy price according to studies in NationalMaster Plan on Renewable Energy Development of Vietnam), the investors need 14 years to recover


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Let us consider a similar PV system installed in Japan, we have the support measure by METI(Ministry of Economy, Trade and Industry): 800 $/1kW subsidy, Start of the feed-in Tariff (FIT)

program in July 2012, 0.525$/1kWh for Grid-Connected PV System [2]-[3]. The Fig.8 shows that the

investors need 7 years to recover capital and 20 years later they have 70 000$ profit

Fig.9. Hybrid Power Systems

For the future, the hybrid power system will be used (Fig.9). Hybrid power systems are designedfor the generation and use of electrical power. They are independent of a large, centralized electricitygrid and incorporate more than one type of power source. They may range in size from relatively largeisland grids of many megawatts to individual household power supplies on the order of one kilowatt.In general a hybrid system might contain AC or DC diesel generators, an AC or DC distributionsystem, loads, renewable power sources (wind turbines, microturbines, or photovoltaic powersources), energy storage, power converters, rotary converters, coupled diesel systems, dump loads,load management options, or a supervisory control system.



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Grid connected P' system facing %oltage sags solutions to !%oid

2nwanted disconnection

#e Thi inh Cha!( T!ng #e 8!c

Hanoi University of Science and Technology, 0. *ai Co Viet, Hanoi, Vietnam

Abstract - !mong disturbances on &ower networ=3 grid-connected &$oto%oltaic ?P'@ in%erters are %ery

sensiti%e wit$ %oltage sags t$at can cause disconnections of P' systems. "$is disconnection is

sometimes unwanted3 in &articularly w$en t$e fault is situated on an ad acent feeder su&&lied by t$e

same substation. uture &ower systems wit$ a large s$are of P' systems connected could be se%erely

affected if se%eral of t$e P' systems are tri&&ing at t$e same instant.

"$erefore3 t$e first ob ecti%e in t$is &a&er is to identify unwanted disconnections of P' systems by

analy:ing t$e be$a%ior of grid-connected P' systems facing %oltage sags caused by s$ort-circuits. "$en3

solutions to a%oid unwanted disconnections by using t$e %oltage-times c$aracteristics and modifying

t$e time delay of t$eir decou&ling &rotections are &ro&osed. "$e %alidation by simulations s$ows t$e

efficiency of t$e &ro&osed solutions.

Index Terms - P' system3 'oltage sag3 !nti-islanding &rotection3 2nwanted disconnection.

1


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Abstract Among disturbances on power network, grid-connected photovoltaic (PV) inverters are very sensitive withvoltage sags that can cause disconnections of PV systems. Thisdisconnection is sometimes unwanted, in particularly when thefault is situated on an adjacent feeder supplied by the samesubstation. Future power systems with a large share of PVsystems connected could be severely affected if several of the PV

systems are tripping at the same instant.Therefore, the first objective in this paper is to identify unwanteddisconnections of PV systems by analyzing the behavior of grid-connected PV systems facing voltage sags caused by short-circuits. Then, solutions to avoid unwanted disconnections byusing the voltage-times characteristics and modifying the timedelay of their decoupling protections are proposed. The validationby simulations shows the efficiency of the proposed solutions.

Index Terms PV system, Voltage sag, Anti-islandingprotection, Unwanted disconnection.

I. I NTRODUCTION

he connection of PV systems in the network requires thecoordination of protections between the PV system withtheir disconnection protections and the networks

protections. In order to ensure a good operation of PV systemsand network, several requirements for the connection of PVsystems have been issued. In France, in order to ensure a goodoperation of PV system protection systems, DIN VDE 0126

[1] requires that PV systems connected to LV network aredisconnected within 0,2s if the voltage at the PV inverterterminal lower than 80% or greater than 115% of the nominalvoltage. The decoupling protection for large PV plantsconnected to MV network is divided into different types calledH.1, H.2, H.3, H.4, and H.5. The classification of these types

LV networks). A low voltage caused by voltage sag can provoke a disconnection of PV systems due to their decoupling protection. The disconnection of significant amount of thesePV systems could have local and global impact on the networkoperation, in particular on weak grids.This is why, it is necessary to find an efficient solution whichavoids the unwanted disconnection of PV systems.

The aim of this paper is to:

- Identify the unwanted disconnections of PV systems

- Propose solution for PV systems by taking into account thefollowing requirements: PV systems must remainconnected when a fault occurs on an adjacent feeder fedfrom the same substation but they must be disconnected inthe case of a fault occurring in its zone (the fault on thefeeder where the PV systems are connected).

Firstly, this paper will present modeling of PV systems withdecoupling protection, urban LV and MV networks and their

protection systems. These models enable us to analyze behaviors of the PV system connected to distribution networksfacing disturbances, especially the voltage sags caused bydifferent types of short-circuit. Then, simulations will becarried out in order to identify the cases of unwanteddisconnection of PV systems. Finally, solutions will be

presented to avoid an unwanted disconnection of PV systems by using the voltage-times characteristics and modifying thetime delay of their disconnection protections.

II. M ODELING

A Modeling photo oltaic s stem

T

Grid-connected PV Systems facing Voltage SagsSolution to Avoid Unwanted disconnections

Chau Le-Thi-Minh, Tung Le-Duc Department of electric power systems, School of Electrical Engineering, Hanoi University of Science

and Technology, 01 Dai Co Viet, Hanoi, Vietnam

Email: [email protected]

2


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that the reactive power (Q) is always assigned to 0. For theP/Q control scheme used for PV inverter (Figure 1), the activeand reactive power outputs of the PV inverter are fixed to set-

point values P ref (in function of solar irradiation) and Q ref (=0).The limit of current output (I Dref and I Qref ) is set to 1.1 of itsnominal value.

B. Modeling distribution network protections

In order to study the behaviors of PV inverters facingdisturbances, protections of LV network, MV feeder andislanding protections of PV inverters are modelized.For LV network in France, the fault protection is assured by

breakers and fuses. In our study, only the feeder fuse (FD400A) and customers fuses (AD 90A) are used. The customeris protected by breaker and fuse AD and the LV network is

protected by feeder fuse FDFor MV network, an urban distribution network is used. Thereis not auto-recloser in each feeder. When the current exceedsthe set point corresponding to these thresholds ( Rephi >0.8*Iscbi and Rh > 1.2*Icap ), the protection activates andtrips the feeder with the time delay of 500ms.

The PV systems were also equipped with decoupling protection. Typically PV system models have both under/overvoltage (OVP/UPV) and under/over frequency (OFP/UFP)

protection. It means that the PV inverter will be disconnectedif the frequency or amplitude of the voltage at the connecting

point is outside the limits (0.85 and 1.15pu for voltage, 47.5and 50.2 Hz for frequency). For further principles of andOVP/UPV protection methods, see [4]. In addition, zero-sequence voltage protection (Vo>10%Vn) is used to detect thesingle phase fault.

All PV systems connected to LV network respect the standard"DIN VDE 0126". So if the voltage caused by a short circuit islower than 80% or greater than 115% of the nominal voltage,the decoupling protection of PV inverter is activated within200ms. For the PV plant connected to urban MV network, thetype of decoupling protection is H.1 and H.2 (the PV power isin the range of about 500kW to 2 MW) [5,6].

TABLE 1 TYPES OF COUPLING PROTECTION Type H.1 Type H.2 Detection of MV single phase fault

Max of V o Instantaneous10% Vn

Max of VoTemporisationt o + 0,5s 10% Vn

D i f M f V M f V

urban LV network is connected at bus 24 from the MVnetwork. This LV network contains a 20/0.4kV, 400kVAtransformer, two feeders. The residential loads are modeled bysingle-phase loads (RL circuit). Single-phase PV productionsare connected to buses 21, 23 and 24.

Figure 2. Studied distribution network

III. UNDESIRABLE DISCONNECTIONS OF PV INVERTERS

Different types of short circuit and different fault positions are

considered. For each fault position, the three following typesof short-circuits are considered:

- Three phase fault- Phase-to-phase, phase-to-phase to neutral and phase-to-

phase to ground fault- Phase to neutral and phase to ground fault.

By using urban networks (MV, LV network) and the models(PV model, network protections, decoupling protections)developed in the preceding part, the behaviors of grid-connected PV inverters and the identification of unwanteddisconnections of PV inverters are studied in several scenarios.The results obtained by simulations have shown that almostshort-circuits occurring on the LV/MV adjacent feeder,disconnections of PV systems due to the voltage sags are

3


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Figure 3 shows the current at the adjacent feeder L-05. Thefault current increases very strongly and superior to the limit,and the adjacent feeders protection activates after 500ms.

0.2 0.4 0.6 0.8 1 1.2

-400

-300

-200

-100

0

100

200

300

400

500

Time(s)

C u r e n

t ( A )

phase aphase bphase c

Figure 4. Current at the feeder L-06 where PV systems are connected

Figure 4 presents the current at the feeder L_06 where PVsystems are connected in LV network. This current is stillwithin the limits, so L_06 feeder s protection does not activateand this feeder maintain connected to the network.

Figure 5. Voltage of PV system in case of three phases fault

However, it causes a disconnection of all PV invertersconnected in feeder L_06 by decoupling protection of PVinverters because the voltage at the PV connection bus is lowerthan 0.8pu (standard DIN VDE 0126). The figure 5 shows thePV voltage.For the PV system connected to MV network, similar resultsare obtained. When the voltage sag caused by short-circuit are

below 85% nominal voltage, The PV system are connectedi nstantaneous.

The disconnection of PV inverters for faults in adjacent feeder

in MV network is unwanted. Solutions must be found to avoidthis disconnection. In the following part, we propose twosolutions to ensure protection selectivity based on voltage-timecharacteristic and the temporisation of decoupling protection.

IV SOLUTION TO AVOID UNWANTED DISCONNECTIONS FOR

0126. In this part, the solution is to integrate a voltage-timecharacteristic in the decoupling protection for all PV systemsinstead of the limits defined by DIN VDE 0126.In case of fault on the adjacent feeder L_05 in urban MVnetwork, figure 6 shows the PV system voltage (PV connectedto urban feeder L_06 in LV network) for a three-phase shortcircuit in comparison with the proposed voltage-timecharacteristic. During short circuit, the PV system voltage isgreater than the voltage defined by the voltage-timecharacteristic. 500ms after occurrence of the fault, the fault inadjacent feeder is cleared by adjacent feeders protection(L_05). After this action, the voltage in feeder L_06 comes back to a normal value (L_06 feeders protection does not getactivated) and feeder L_06 maintains connection to thenetwork.

0.2 0.4 0.6 0.8 1 1.2 1.40

0.2

0.4

0.6

0.8

1

1.2

Temps (s)

T e n s

i o n

( p u

)

Tension du PVGabarit de tension

Time (s)

V o

l t a g e

( p u

)

0 1 2 300.51

Voltage-time CharacteristicVpv with using the proposed solution

0.2 0.4 0.6 0.8 1 1.2 1.40

0.2

0.4

0.6

0.8

1

1.2

Temps (s)

T e n s

i o n

( p u

)


Time (s)

V o

l t a g e

( p u

)

0 1 2 300.51


Temporisation du protectiondu dpart adjacent

0.2 0.4 0.6 0.8 1 1.2 1.40

0.2

0.4

0.6

0.8

1

1.2

Temps (s)

T e n s

i o n

( p u

)


Time (s)

V o

l t a g e

( p u

)

0 1 2 300.51


0.2 0.4 0.6 0.8 1 1.2 1.40

0.2

0.4

0.6

0.8

1

1.2

Temps (s)

T e n s

i o n

( p u

)


Time (s)

V o

l t a g e

( p u

)

0 1 2 300.51


Temporisation du protectiondu dpart adjacent

Figure 6. PV voltage in comparison with the voltage-time characteristic for a

fault in MV adjacent feeder (feeder L_05, outside of PV zone)

For urban networks, there is no auto-recloser in any feeder.When the current exceeds the protection relay thresholds, thefeeder protection activates and trips the circuit breaker withthe time delay of 500ms. Thus, for the PV connected to MVnetwork, the solution is to increase time delay of decoupling

protection integrated into the PV systems greater than 500ms,in this paper is t 0 +0,5ms for detection of MV single phasefault and t 1 +0,5ms for detection of MV multiphase fault. Byincreasi ng the protection time delay, the adjacent feeders

protection has enough time to trip the fault before thedisconnection protection of PV systems operates. The figure 7shows the PV power in two cases with and without using the

proposed solution.

4


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systems are very sensitive to voltage sags, and in some cases,there are unwanted disconnection of PV systems, in particularfor a fault in LV and MV adjacent feeders. Therefore,solutions by using the voltage-time characteristic for PVsystems connected to LV network and on modifying thetemporisation of decoupling protection for PV systemsconnected to LV network are proposed. The validation bysimulations shows the efficiency of the proposed solutionwhich can avoid unwanted disconnection of PV systems incase of a short circuit outside of PV zones.

VI. R EFERENCES [1] Norme DIN VDE 0126-1- 1, Automatic disconnection device between a

generator and the public low-voltage grid , February 2006. [2] B. Bletterie, R. Brndlinger, H. Fechner, Sensitivity of photovoltaic

inverters to voltage sags Test results for a set of commercial products,18th International Conference and Exhibition on ElectricityDistribution, CIRED, Turin Italy, 2005.

[3] Botjan BLAIC*, Arsen JURASIC, Igor PAPIC, Simulating thedynamic response for a photovoltaic generation system to voltage sags,18th International Conference and Exhibition on ElectricityDistribution, CIRED, Turin Italy, 2005

[4] Ward Bower and Michael Ropp, Evaluation of Islanding Detection Methods for Utility- Interactive Systems in Photovoltaic Systems, Report IEA PVPS T5-09: 2002

[5] Technical reference, Study of the impact on the protection planconnecting a distributed generation in MV network,(ERDF-PRO-RES_09E)

[6] Technical reference, "Installation protection of the generation connectedto the public distribution network" (ERDF-NOI-RES_13E)

[7] Arrt du 23.04.2008 relatif aux prescriptions techniques de conceptionet de fonctionnement pour le raccordement un rseau public dedistribution dlectricit en basse tension ou en moyenne tension duneinstallat ion de production dnergie lectrique



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Electricity Su&&ly to a 5ocal Isolated !rea by Means of Renewable

Energy

. Wang( T. :hang( 6. E. #amas an$ 4. akam!ra

*oshisha University, 6yoto, -apan

Abstract - "$ere eBist a number of countries and area w$ere electricity su&&ly is always in s$ort. !ty&ical eBam&le is a mountain site in !sia and ar East3 and a desert in !frica. In t$e area3 notransmission distribution system is well establis$ed3 and no fuel can be su&&lied. "$us3 alocal dis&ersed electricity generation loo=s most &romised. rom t$is %iew&oint3 &ossible electricitysu&&ly by renewable energy generation is discussed in t$e &a&er) micro-$ydraulic &ower3 wind &owerand &$oto%oltaic solar &ower generation. !ssuming a small %illage wit$ &o&ulation *++ and t$enecessary generation ca&acity of less t$an *+ =03 t$e best c$oice of t$e electricity generation met$od3eit$er small $ydraulic turbine generators3 wind turbine generators or &$oto%oltaic solar is in%estigated.It is de&endent on geological and climate conditions. "$erefore3 t$e in%estigation is carried &ut under%arious conditions3 and t$e cost3 maintenance and life time are discussed. >ased on t$e in%estigations3t$e following remar=s are obtained.

?*@ If t$ere is enoug$ rainfall and t$us a water flow3 a small $ydraulic turbine generator is most&romised. "$e $ydraulic &ower generation is most efficient among ot$ers3 and most reliable &ro%idedt$at t$ere is a continuous water flow. "$e estimated cost of a *+=0 $ydraulic generator station is lesst$an *, million (a&anese Jen3 t$e maintenance is easiest and t$e life time is t$e longest.

?1@ !long a sea coast and in an island3 wind &ower generation is t$e best c$oice because of continuouswinds wit$ t$e a%erage s&eed $ig$er t$an ,m s. /owe%er3 t$e ca&acity of a wind turbine generatornecessitates to be about 1+=0 to assume t$e generating ca&acity of *+=0 considering t$e wor=ingratio. "$is costs about 7 million (a&anese Jen. /owe%er3 if an electricity storage toget$er wit$ a &owerconditioner considering t$e wind fluctuation and t$us t$e out&ut &ower fluctuation is installed3anot$er 1+ million (a&anese Jen is added.


57/419

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!nalysis of 'oltage Sags and Protection Coordination in Distribution


64/419

Systems wit$ Sensiti%e EAui&ment

#e iet Tien

Hanoi University of Science and Technology, Hanoi, Vietnam

Abstract- owadays3 more sensiti%e electronic eAui&ment is widely used in modern &ower systems

suc$ as &ower con%erters and ad ustable s&eed dri%ers. Power Auality $as been a greater interest in

%oltage sags due to t$eir im&acts on t$e &erformance of sensiti%e eAui&ment ?SE@. Malfunction or

failure of t$e eAui&ment t$at leads to wor= or &roduction losses can be caused by %oltage sags. !s a

result3 it is essential to $a%e information on eAui&ment sensiti%ity. If t$e magnitude and duration of

%oltage sag eBceed t$e eAui&ment sensiti%ity t$res$old3 t$e eAui&ment can be malfunctioned3 and suc$

a conseAuence can affect an entire automatic &rocess3 resulting in $ig$ economical losses. Reclosers

and fuses are t$e main o%ercurrent &rotection de%ices in distribution systems. Poor coordination could

ad%ersely im&act on t$e sensiti%e eAui&ment. "$is &a&er &resents a met$od to analy:e t$e im&acts of

%oltage sags and &rotection coordination on sensiti%e eAui&ment. ! fault &osition met$od and

mat$ematical eAuations for &rotecti%e de%ices are used to set u& t$e &rotection setting and to

calculate %oltage sags. 'oltage tolerance t$res$olds and &rotecti%e de%ice c$aracteristics are used to

analy:e &rotection and sensiti%e eAui&ment coordination. >ased on t$e results3 new settings for

&rotecti%e de%ices are done to consider sensiti%e eAui&ment in distribution systems. "$e Roy >illinton

"est System ?R>"S@ bus 1 is used to analy:e t$e im&act of %oltage sags and &rotection coordination

system on t$e sensiti%e eAui&ment in distribution systems.

Index Terms- sensiti%e eAui&ment3 %oltage sag3 &rotection coordination .

Analysis of Voltage Sags and Protection Coordination


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y g gwith Sensitive Equipment

Le Viet TienDepartment of Power Systems, Hanoi University of Science and Technology

Abstract --Nowadays, more sensitive electronic equipment is widely used in modern power systems such aspower converters and adjustable speed drivers. Power quality has been a greater interest in voltage sags due totheir impacts on the performance of sensitive equipment (SE). Malfunction or failure of the equipment that leadsto work or production losses can be caused by voltage sags. As a result, it is essential to have information onequipment sensitivity. If the magnitude and duration of voltage sag exceed the equipment sensitivity threshold,the equipment can be malfunctioned, and such a consequence can affect an entire automatic process, resulting inhigh economical losses. Reclosers and fuses are the main overcurrent protection devices in distribution systems.Poor coordination could adversely impact on the sensitive equipment. This paper presents a method to analyzethe impacts of voltage sags and protection coordination on sensitive equipment. A fault position method andmathematical equations for protective devices are used to set up the protection setting and to calculate voltagesags. Voltage tolerance thresholds and protective device characteristics are used to analyze protection andsensitive equipment coordination. Based on the results, new settings for protective devices are done to considersensitive equipment in distribution systems. The Roy Billinton Test System (RBTS) bus 2 is used to analyze theimpact of voltage sags and protection coordination system on the sensitive equipment in distribution systems.

Index Terms -- sensitive equipment, voltage sag, protection coordination.

I. I NTRODUCTION

OLTAGE sag is a short-duration reduction in rms voltage between 0.1 and 0.9 p.u. with duration from 0.5cycles to 1 min [1-3]. Voltage sags that affect sensitive load are usually caused by faults somewhere ontransmission and distribution systems.

Voltage magnitude and duration are essential characteristics of voltage sag. The magnitude of voltage sagsmainly depends on the fault location and fault type and some other factors such as the pre-fault voltage,transformer connection, and fault impedance [2-3]. The voltage sag magnitude, which is expressed in percent orper unit, is calculated by short-circuit analysis. The voltage sag duration is defined as the flow duration of thefault duration of the fault current in a network. Therefore, the duration is determined by the characteristics of thesystem protection devices such as overcurrent relays, circuit breakers and fuses. Generally, the duration iscalculated by adding the intentional time delay considering protection coordination to the fault clearing time ofeach device.

Much sensitive equipment are used in modern industrial with renewable energy such as computers,programmable logic controllers, adjustable speed drives, and robotics. Many industrial customers using sensitiveequipment suffer from voltage sags. Malfunctioning or failure of this equipment can be caused by voltage sagsthat lead to work or production stops. To analyze these cases, it is essential to have information of the sensitivityof the equipment. If the magnitude and duration of voltage sag exceed the equipment threshold sensitivity, theequipment is damaged, and such damage can effect an entire process at the customer site associate cost.Therefore, characteristics of the sensitivity equipment must be provided by the manufacturer or obtained bytests. System performance, which can be expressed by the expected sag frequency in the site, can be estimated

V

II. P ROTECTION COORDINATION

Fig 1 shows traditional fuse-recloser coordination in distribution systems [6] In recloser function there is an


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Fig. 1 shows traditional fuse recloser coordination in distribution systems [6]. In recloser function, there is aninterval between each operation when the recloser remains open. If the fault is temporary, recloser will clear

before the fuse. If the fault persists after the recloser closes then the fault has to be a permanent one and hencefuse must operate to cut it off.The general coordination is that the fuse should only operate for a permanent fault on the load feeder.

However if the fault is a temporary fault or the fault occurs behind the recloser, the recloser should disconnectthe circuit with fast operation and give the fault a chance to clear. Recloser also provides back up function whena fuse fails to blow up. In order to have a correct operation, the fuse must be coordinated with upstream recloseron the main feeder.

In Fig. 1, the TC curve of the fuse is below slow curve of recloser in coordination range. Therefore, for apermanent fault, fuse will open before recloser will back it up by operating in slow mode and finally lockingout. The coordination curves of recloser and fuse have to be modified. The fuse-recloser coordination rangegraph between max fault I and min fault I . Therefore, as long as the fault current values for faults on lateral feeder

are within coordination range, the fuse-recloser coordination is accepted. We can see that the fast characteristicof the recloser lies below the MM characteristic of fuse between max fault I and min fault I . So, in coordination

range the recloser operates in less time than the time sufficient to damage the fuse.

Fig. 1. Recloser-fuse coordination range.

III. F AULT POSITION METHOD

Fault position method is used to calculate voltage sags in this paper. Bus is selected as the bus where thesensitive equipment is connected. The voltage sag at bus m caused by three-phase fault along the line jk willbe shown as following [8-9].

A fault at a fictitious position p on the line jk

, defined as the ratio of length between bus k and faultlocation to the length of the line jk or kjkp L L p / = . The voltage at bus , when a fault occurs at the

position p between k and j , can be calculated from012012012012 ][ pmpmm I Z V V = (1)

When a three-phase fault occurs, the voltage sag at bus m can be expressed as

prefmppreffault Z 1

(5)


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pref p

pp

mp pref m

fault m V

Z V V 1

= (5)

IV. P ROBLEM DEFINITION AND SOLUTION

The problem addressed in this paper can be stated as follows: Assuming a three-phase fault andcalculating the fault current and voltage in test system, it is determined which protective device interrupts thefau