［ Control of Power Demand & Supply and Grid Power System ］

Program for the Development ofAutonomous Distributed Voltage
Control Technologies for PowerDistribution Networks (OptimalControl Technology Demonstration
Project for the Next-Generation
Power Transmission andDistribution Networks)
Keywords

Takayuki Tanabe,
Hironori Nakashima,
Takanori Hayashi

Power distribution network, Voltage control, Autonomous distribution, Optimization, Simulation

Abstract

Meidensha Corporation took part in an “Optimal Control Technology
Demonstration Project for the Next-Generation Power Transmission andDistribution Networks” sponsored by the Agency for Natural Resources andEnergy under the Ministry of Economy, Trade and Industry Japan. The grant tothis project was given during Fiscal 2010 to Fiscal 2012. We engaged in promoting
technical development for advanced voltage control technologies for power distribution networks. Presently, voltage control in power distribution networks is
managed by the control functions based on each terminal information level ofeach voltage control unit. Primarily, these control functions are based on theassumption that power ﬂow is directed to the demand side; therefore, there isindication that there will be some difﬁculty in voltage control in the event thatmany photovoltaic power resources are installed extensively on the demandside. Considering such challenges, we have promoted its technical development
for effective control parameters which aim to maintain system voltage in theregal range. This is based on the fundamental functions of the said independent
distributed resource control.

1 Preface
With the growing demand for the reduction ofgreenhouse gas emissions, in April 2009 theJapanese Government set up a photovoltaic power
generation system introduction target in order torealize 28 GW by ﬁscal 2020, which is a very challenging goal (1). In March 2011, Japan was hit by The
Great East Japan Earthquake causing tremendous
damage. As a result, nuclear power stations wereforced to shut down plants despite the fact that
nuclear energy offers a high effect of reduction ofgreenhouse gas emissions. In addition, the long
duration of nuclear power station shutdown has
resulted in repeated power shortage problems.
Under such circumstances, it has sparked publicawareness regarding energy saving and has invited
higher expectation of the use of renewable energy
resources.
The photovoltaic power generation system (PVsystem) is an excellent power resource in terms ofzero carbon dioxide emissions during power generation. On the other hand, its energy source is unstable and we cannot expect it to be a reliable energy
supply source. In addition, the power output isgreatly changed by variations in the solar radiation.
Due to the aforementioned characteristics, the PV
systems involve some concern affecting the powersystems adversely in terms of stable system management. Recently, technologies generally called
the “smart grids” are getting attention. The smart
grids are expected to solve various grid problems by
MEIDEN REVIEW Series No.162 2014 No.3

37

interconnecting with the increasing number ofrenewable energy resources such as PV systems.
In such a situation, the “Optimal Control Technology Demonstration Project for the Next-Generation Power Transmission and Distribution Networks”
commenced(2). It involves demonstration projects
under the grants by the Agency for Natural Resources
and Energy under the Ministry of Economy, Tradeand Industry during Fiscal 2010 to Fiscal 2012.
A total of 28 ﬁrms including 9 power utility companies joined the demonstration projects. The targetof these demonstration projects was to achieve themost effective balanced use of electrical energy interms of supply (grids) and the demand (electricusers) from the standpoint of both the power supply
side and demand side. These demonstration projects are supported by four subsidiary working
groups, each having a mission of promoting technical development toward the establishment of basic
technologies for the Japanese version of smart
grids. We joined this project and worked on the
problem of technical development for the advanced
voltage control technologies for power distribution
networks. This is to solve the challenges at the grid
power side. This paper deﬁnes the challenges broughtby the increasing installations of PV systems, outlines the problem-solving technologies that are being
developed in the said demonstration project, andprovides an example of the demonstration result.

Law in Japan, the terminal voltage at the receiving
end of each electricity user is required to be maintained within the range of 101 ± 6V. In circumstanceswhere many PV systems are not connected, one
manages the grid only focusing on the voltage drops
against the voltage control allowance range of 12V;
however, if many PV systems are under-connected,
a voltage rise is caused by reverse power ﬂows andthe voltage control allowance is relatively reduced
as a result. Fig. 1 shows the challenge of a voltage
rise in power distribution networks.
According to the relevant rules for the systeminterconnection of distributed energy resources,
these power sources causing reverse power ﬂows
are required to have the power restricting function(voltage rise suppression function) to reduce thepower generation output by controlling both active
and reactive power whenever the voltage is raised
above the preset level (4). Due to the effect of thisprovision, there is no serious maintenance problem
due to the voltage rise. Without the power control of
distribution network, we will lose distribution energy
resources like PV resources.

2.2 Problem of an Increase in Power Flow
Deviation
In the future when the use of heat pumps for air
conditioning becomes popular and electric vehicles
are widely used, such new demand for energy willtake advantage of economical nighttime power inJapan. It produces hot water or charges the power
at night. A large-scale cluster of PV systems and theuse of more power in the heating and power production will invite the expansion of power ﬂow deviationin the daytime which makes it more difﬁcult to pro-

2 Various Challenges in Voltage
Control for Power Distribution Networks
Among the Japanese governmentʼs introduction target of 28 GW of PV systems by Fiscal 2020,
it is concerned that approximately 70%
is related to residential application(3).
There are many problems anticipated
Voltageto arise as a result of mass introduccontrol
widthtion of PV systems. The following
paragraphs will outline such problems
incurred in power distribution networks
where general power users such as
residential uses are interconnected.

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MEIDEN REVIEW Series No.162 2014 No.3

107V

Fig. 1

Output voltage(bank in common)

Avoidance ofvoltage deviation

Feeder (A)Feeder (B)

95V

Power
distribution
substation

2.1 Problem of Voltage Rise
When a large number of PV systems are inter-connected to power distribution networks, an unusual voltage
rise is caused by reverse power ﬂows.
According to the Electric Utility Industry

Low-voltage

High- voltage Output suppression function in operation
Feeder (A): Residential area
distribution line

Feeder (B): Commercial area

Problems of Voltage Rise in Distribution Networks

The diagram shows problems in distribution networks anticipated when photovoltaic
power systems are introduced in a large quantity.

vide the adequate voltage control. In power distribution networks, electric power is fed through multiple
feeders from the same transformer bank. If a power
network region with different load characteristics isinter-connected to the same transformer bank, there
will be the increase of power ﬂow deviation among
the feeders. In such a case, it is anticipated thatvoltage control becomes difﬁcult to perform if it is
attempted only at a substation level. If energy
resource and electrical energy modes of use arediversiﬁed, we can expect a load leveling effect inthe overall power network. There will, however, besome difﬁculty in voltage control in a local level
power distribution system. To meet such needs, it isnecessary to grasp the condition of power ﬂows in
feeder lines adequately and establish an adequate
control approach and suitable allocations of control
devices to attain precise control of voltage.

2.3 Problem of Voltage Regulation
In PV systems, the generated power output
changes greatly in responding to changes in solar
positioning. It is anticipated that frequent power output changes can be relieved to a certain extent by aleveling effect in considering the overall power
demand and supply balancing of the grid. On a local
level and its distribution line network scale, there isa risk of frequent voltage ﬂuctuations as a result of
power output changes.

3 Advancement of Voltage Control
Technologies for Power Distribution
Networks
3.1 Outline of Present Control Technologies

3.2 Program for the Advancement of Voltage
Control Technologies
With the wider implementation of PV systems
in the future, this demonstration project assumes
the scenario to improve the voltage control technologies for power distribution networks so that thepresent autonomous distributed control system canbe upgraded into a higher level. In order to realize
this scenario, development, demonstration, andevaluation of a new control system have been covered by multiple ﬁrms. Fig. 3 shows the scenario
under the demonstration project.
Presently, the said voltage control equipment
is operated under autonomous distributed control
based on the self-terminal information and on theﬁxed pre-set values for control. In the current situation, most power distribution networks are designed
to collect telemetry data only at the power-supplying
point of each distribution substation. A new system
High-voltage
feeder line
Section switch
6600V
Pole
transformer

LRT
Transformerbank
66/6.6kVPower distribution
substation

High-voltage
electricity user

Low-voltage
electricity

Fig. 2～－STATCOM
SVR
Low-voltage
feeder line
210～105V

Other feeders

Power transmission
systemAs shown in Fig. 2, major voltage
control products used in the power distribution networks (feeder lines) are: onload tap-changing transformers (LRT:Load Ratio control Transformers) installed in power distribution substations, Step Voltage Regulators (SVRs)
installed in the middle of feeder lines,
and static synchronous compensators(STATCOMs), etc.(5).
The LRT is capable of regulating
the secondary voltage of a distribution
transformer in a “step-by step” mannerby changing a tap position changer.
The control system of the LRT is mainlyclassiﬁed into three categories: the ﬁrst

is the Line Drop Compensation (LDC) system bywhich the target range voltage is regulated in linewith the load current, the second is the program control system for voltage control according to the preset hourly-based patterns, and the third is a combination of the aforementioned two systems. The SVR
is used to control the line voltage in the downstream
power network system starting from the SVRʼsinstallation point in a “step-by-step” manner. The
LDC system is adopted for the SVR control. The
STATCOM is equipment that controls reactive power
continuously and at a high speed by using a selfexcitation type power converter. It is capable ofbi-directional control, i.e. up and down of voltage
level by phase delaying or advancing direction.

Low-voltage
electricity

High-voltage
Low-voltage
electricity user electricity user

Configuration of Distribution Networks and Voltage Control
Equipment

Voltage control equipment generally used in distribution networks is shown.

MEIDEN REVIEW Series No.162 2014 No.3

39

Large-scale useof PV systems
Autonomous distributed
type (at present)

Dead end?

Autonomous distributed
type (Advanced)

Dead end?

For power distribution
Control equipment devised based on
network:
・Installation of sensors sensor data:
・Autonomous control by optimal setup
・Adjustment of com・Optimal device distribution
munication network
Concentration type
Advancing of voltage
control equipment
and control systems

Control equipment
based on sensor data:
・Feedback control
・Optimal device allocation

autonomous distributed control are adequately conﬁgured. Further, we anticipate the migration scenario in the future be from the autonomous distributed
control to a central control system under which thevoltage control equipment is operated directly froma remote place. Among such a scenario, we took
the program to develop the advanced system for theautonomous distributed control system.

3.3 Advancement of Autonomous Distributed
Control Technologies

At an early introductory stage of PV systems,
implementation of voltage control is considered
possible through new installation and extension ofFig. 3 Scenario under the Demonstration Project
voltage control equipment. When PV systems become
A scenario for the working group is shown, which was estabmore popular, it is anticipated that there will belished by all participants attending the sub-working group. Eachcases when it is difﬁcult to cope within the given
discussed the issues on voltage control technologies for power
distribution systems as a part of the programs for the Demcluster of PV systems so long as conventional
onstration Project.
autonomous distributed control is carried out. For
solutions, we have proposed to improve
the situation by easily performing theClaiming for
Computation
secondfor optimal
DB manageremote operation control through thecomputation
simulation
ment (offline)
adjustment of control parameters ofAutomated
Set valueDBsystem (online)
support (offline)
the autonomous distributed control
equipment. We believe that it is aneffective measure that we take timely
Set value feedback
control of parameters according to theSet values are changed
conditions of season, time range, andwhen needed for timezone, season, climate, etc.
weather condition. In this advancement
approach (1), the database of past reSTATCOM
LRT
SVR
SVR
LRT
cords voltage proﬁles for feeder lines are
ID2
ID1
being referenced and control parameLoad Load Load
Load Load
Load Load
Loadters of LRT and SVR are optimized
Sensorswitch (ON state)using the ofﬂine support tools. Fig. 4
Sensor switch (OFF state)shows the advancement approach (1)Control only with self-terminal information
for autonomous distributed control.
When the control parameters are optiFig. 4 Advancement Approach (1) for Autonomous Distributed Control
mized, we can realize the control perA conceptual diagram of the overall system is shown for approach (1) which is informance with due consideration totended to advance the autonomous distributed voltage control. It is assumed thatvoltage control equipment is made to remain presently in the equivalent situation ofvoltage proﬁles of total feeder lines,
autonomous distributed control, but the control parameters are optimized only ineven in the case of control logic based
conditions where gradual modiﬁcation is left possible.
on local-terminal information. In addition, by making the obtained control
to continuously collect the telemetry data by senparameters remotely controllable under the givensors on feeder lines at several places is beginninggrid situation, we can ﬂexibly manage the power
to be built. This demonstration project is carried on
ﬂower change by the increase of PV system cluster
the assumption that such information from the senor by the seasonal change. In the upgrading
sor on the feeder line can be acquired. At the initialapproach (1), the feedback control loops do notadvancement level, we assume that voltage control
include any power distribution automation systems;
equipment is properly arranged and that control
therefore, it does not require either a higher speed
parameters of the voltage control equipment for
information network or advanced redundancy.

40

MEIDEN REVIEW Series No.162 2014 No.3

cation of the setup value is ignored in
the case of an optimal setting. In the
DB management (offline)
case of the latter, simulation is perAutomated
Set
value
formed for various power ﬂow patternsDBsystem (online)
support (offline)
and the most optimal parameter isdetermined when the aggregated valueof voltage control errors becomes minSet value feedback
imized. In so doing, we determined theInformation of voltage,current, and position
setting value. There are two(2) optimization approaches: the ﬁrst approachis a method to solve an exact analytic
STATCOM
LRT
SVR
SVR
LRT
ID2
ID1
solution for objective function, and thesecond is an approximate solution
Load Load Load
Load Load
Load Load
Load
Sensormethod to determine improved combiswitch (ON state)
Sensor switch (OFF state)nations by making the evaluation valActive use of information at other terminals
ues of various parameter combinations. In many realistic cases, due toFig. 5 Advancement Approach (2) for Autonomous Distributed Control
the complexity of the objective funcA conceptual diagram of the overall system is shown for approach (2) intended totion, it is difﬁcult to get the exact anaadvance the autonomous distributed voltage control. It is assumed that voltage conlytic solution. As such, a certain methtrol equipment is available for the autonomous distributed control, but telemetry
values at the self-terminals and on feeder lines can be utilized. Management andod of approximate solution is generally
control approach are the same for advancement approach (1).
adopted. In the parameter optimization
problem covered in this paper, a timeWhen a PV system cluster is increased, it isbased proﬁle in voltage distribution determinedassumed that it may be a situation where voltage
according to a control parameter is deemed as the
proﬁles cannot be precisely grasped by only using
evaluation value. For this reason, it is necessary to
self-terminal information. In such a case, it is conperform time response simulation of the power dissidered effective to adopt an approach to actively
tribution network in order to deﬁne the evaluation
use telemetry data at another point in addition tovalue. Since a certain amount of computing time isself-terminal information of voltage control equiprequired for the time response simulation, the numment. In the advancement approach (2), normal
ber of combinations of trial parameters is extremely
time voltage control is based on autonomous dislimited when determining the most optimal solution(approximate solution) within realistic computing
tributed control. Even in the advancement approach(2), it is assumed that no power distribution automatime. As such, selecting what simulation shall betion systems are included in the feedback control
conducted under what combination of the parame()
loops. Fig. 5 shows the advancement approach 2ters is a vital element for optimization approach. For
for autonomous distributed control.
the method of selecting the best combinations ofparameters, there are many proposals in regard to
3.4 Optimization Approach for the Control
the metaheuristic approach. Fig. 6 shows the operParameters
ation ﬂow of optimization where both simulation andIn the case of LDC control adopted for themetaheuristic approach are employed. For operapresent LRT and SVR, it is operated within the destion of optimization, some combinations of proper
ignated control value of estimated voltage level forparameters are initially chosen. Simulation is perthe center of the demand area. This control is based
formed with these combinations in order to obtainon the telemetry values of voltage and current availan evaluation value. Based on the result, anotherable at the self-terminal. The estimated voltage levelcombination of parameters is newly determined tois determined based on the line impedance, voltperform simulation so that a new evaluation valueage, and current against the load level target point.
can be obtained. This process is repeated until the
Since the control setup value is determined from theoperation is completed after reaching a combinationline impedance, it requires the understanding of aof parameters producing the best evaluation value.
physical implication. Conversely, the physical impliSuch parameter combination is then regarded as
Claiming forsecondcomputation

Computationfor optimal
simulation

MEIDEN REVIEW Series No.162 2014 No.3

41

Combination of
optimal parameters

Execution of
optimization

Evaluation
values

A metaheuristic approach
is applied to a combinationof past parameters andevaluation values in orderto determine the next
combination of parameters.

4.1 Method of Evaluation
Combination of parameters

Simulation

Conditions ofsimulation

Decision of evaluation valuesby mimic calculation

Fig. 6

Operation Flow of Optimization

An operation ﬂow diagram is shown for the optimization of control parameters.

the best solution.
For the solution of optimization problems discussed in this paper, operation for optimization usedin the said operation ﬂow is based on the Particle
Swarm Optimization (PSO) algorithm and the operation logic(6) developed by Waseda University, Japan.
For operation for simulation, the BFS method has
been applied and the time-based response power
tidal ﬂow calculation program(7) that we developed,
is used.
When the control parameters are optimized
during autonomous distributed control, it is essential to select the load and the power generating pattern carefully. If optimization is carried out using various demand-supply patterns, the acquired control
parameters will have a wide application range; however, the time to conduct optimization operation will
become very long and there is a risk that we may
not be able to obtain an optimal solution from operation repeated with limited trials. Consequently, patterns should be selected considering demand-supply
patterns with as little data as possible. It is vital toseek both the solvability improvement for the optimization operation and the reduction of operation time.

4 Evaluation of Autonomous
Distributed Type Voltage Control
In order to evaluate a scenario for advancing
voltage control technologies, we veriﬁed further to
see what level of PV system cluster could be tolerated
in the power network system in the event that weapplied a speciﬁc control technology. In the para-

42

MEIDEN REVIEW Series No.162 2014 No.3

graphs below, we discuss the veriﬁcation results on
our scope of research: the autonomous distributed
control (current system) and the autonomous distributed control (advanced system).

At the beginning of veriﬁcation, we adopted afeeder line model as shown in Fig. 4. This model isbased on the assumption that three different
demand areas are covered by a single transformerbank in the model system conﬁguration. The ﬁrst
community is the “commercial area” where demandfor electric power is large in the daytime. The second community is the “residential area” where thefeeder line span is short and power is assumed to
be fed to densely populated area. The third community is the “agricultural area” where the feeder line
span is long and electric power is fed to few houses
scattered in the area. In the “commercial area,”demand for power is large in the daytime while it issmall at night. In the “residential area” and the “agricultural area,” daytime demand is small, reverse
tidal ﬂow from PV systems occurs, and demand islarge at night. Accordingly, this model is subject toconfronting a situation where a voltage proﬁlebetween feeders is extremely ununiform and somefeeders may have long line length. This model has
therefore, been devised in consideration of extreme
conditions from a viewpoint of voltage control. Thismodel is a combination of feeder line models also
described in a report of the Electric Technology
Research Association(8). Fig. 7 shows the power
distribution system model used for the veriﬁcation
project.
For the “commercial area,” a load pattern has
been assumed where power demand is large in thedaytime. For the load patterns and PV power generation patterns in the “residential area” and the “agricultural area,” an average household load patterns
and telemetry values of sunlight are used. These
data were obtained from the demonstration project (9) of the NEDO (New Energy and Industrial
Technology Development Organization) implemented
in Ohta City, Gunma Prefecture, Japan. The number of houses is assumed to be 2000 for the “residential area” and 1500 for the “agricultural area.”
We adopted a uniformly distributed model where
the number of houses is set up and assigned toeach node in proportion to the feeder line length.
The capacity of photovoltaic power systems perhouse is assumed to be 3.5kW. We introduced the

10

11

12

13

15

16

14

Pole transformer
tap setting
6750V

Commercial area
【A02】

6600V
6450V

21

26

31

33

37

2000 houses

22
20

LRT

25

30

32

36

13
10

11

17

12

Residential area
【C02】

PV
introduction
area

38

15

14
23

27

24

28

16

18

19

34
29
35

38

1500 houses
39

24
10

11

SVR

12
Aglicultual
area
【D22】

14

28

15

31

37
SVR

18

17

SVR

19

16 40

34

46

25

20

21

49

22

23

55

52

43
27

26

Fig. 7

13

29

30

33

32

35

36

42

45
44

41

48

47

50

51

54

53

56

57

Power Distribution System Model for Verification

This is an explanatory diagram of a power distribution system model structured for the performance veriﬁcation of the proposed control
approach.

PV systems only by one, starting with a house locatedat the edge of the feeder line. As far as practicallypossible, we made a conﬁguration under very distressed power network conditions. It is assumed
that the LDC control system is adopted for the LRTcontrol system and the LDC control system of the
distributed power resource is adopted for the SVR
control system. It is also assumed that three SVR
units are installed in the “agricultural area.”
In autonomous distributed control using thepresent system is assumed, the feeder line voltage
at the time of 0% PV introduction is conﬁgured at aﬁxed value for optimal setting that can be maintained in a proper range. For autonomous distributed
control where the advancement approach (1) isassumed, control parameters are programmed tobe modiﬁed adequately to an optimal ﬁgure in eachseason along with the rise of PV introduction rate. In
any case, if a 30-minute mean value of all node voltages is kept within the adequate range, such a condition is regarded as acceptable. Otherwise, it isregarded not acceptable. The adequate range ofvoltage mentioned above is 103V to 107V assumingthat the high-voltage feeder line voltage is converted
into a low-voltage side. When performing optimization of the advancement approach (1), the four types

Table 1 Result of Evaluation
Regarding the autonomous distributed control of the present approach and that of the Advancement Approach (1), the result of
evaluation is summed up for the introduction level of photovoltaic
power systems obtained from simulation.
PV
introduction
rate
(%)

Present approach(Fixed setup system)

Upgrading Approach (1)[Dynamic setup system]

SummerseasonSummerseasonMiddleseason

10

0

0

11

0

0

12

0

0

13

0

0

14

0

0

15

0

2

16

0

0

17

0

0

18

0

4

19

1

13

20

8

18

Middleseason
0

0

0

0

30

0

1

40

1

16

Note: Figures in the table denote the days when voltage deviation occurs
within one month.
: Limit introduction level: Occurrence of voltage deviation: No evaluation

MEIDEN REVIEW Series No.162 2014 No.3

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Table 2

Assumption of PV Introduction Goal and PV
Penetration Rate

The table below provides the summary of goal for the introduction of PV power generation systems in the future that are anticipated by the Demonstration Project.
PV introduction goal

Rate of diffusion to
general homes(No. of houses)

2020

28 GW

Approx. 1/5 (20%)

2030

53 GW

Approx. 1/3 (33%)

of day patterns, a sunny day, cloudy day, andchangeable days (two types), are selected as thepower generation patterns for the PV systems. At
the time of our evaluation, we evaluated load andpower generation patterns based on the telemetry
data for one month of the summer season and one
month of middle season.
As a reference for this demonstration project,
the PV introduction rate for general housing isassumed as the values speciﬁed in Table 2 when
the PV systems saturation will reach as high as 28 GW
in Fiscal 2020 and 53 GW in Fiscal 2030. This reference value was set under the assumption that thegoal rate of PV introduction for general housing is
70%, the number of houses throughout Japan is 30
million, and a mean PV capacity per home is 3.5kW(28 GW × 0.7 / 3.5kW ＝ 5.6 million homes; 30 million
homes / 5.6 million homes ≒ 5.36 ≒ 1/5). Table 2
shows the target PV introduction number and thepredicted PV penetration rate.

4.2 Result of Evaluation
The following eight simulation cases were
evaluated:( 1) For conventional control system, the LRT control system is assumed to be LDC.
( 2 ) For the advancement approach (1), the LRTcontrol system is assumed to be LDC.
( 3 ) For the advancement approach (1), the LRTcontrol system is assumed to be of program control
type.
( 4 ) For the advancement approach (1), the LRTcontrol system is assumed to be of a combination of
LDC and program control type.
( 5 ) For the advancement approach (1), the photovoltaic power systems are assumed to be addedwith reactive power control that lowers voltage.
( 6 ) For conventional control system, the voltage
control range is assumed to be 103V to 107V.
( 7 ) For the advancement approach (1), the voltage
control range is assumed to be 103V to 106V and44

MEIDEN REVIEW Series No.162 2014 No.3

STARCOM is added to the residential area.
( 8 ) For the advancement approach (1), the voltage
control range is assumed to be 103V to 106V and
SVR is added to the residential area.
Fig. 5 shows the result of comparison of PV
introduction rates obtained from evaluation. The
power distribution network model under study thistime is the distressed power network condition
where voltage rise and voltage drop occur at thesame time. Therefore, the effect of voltage control
by LRT is difﬁcult to ascertain. As a result, there isno clear performance difference by the LRT control
system.
When we added reactive power control lowering voltage in the PV systems, the PV introduction
rate rises as high as 40%.
In the case that voltage control equipment(SVR or STATCOM) is added, control performanceis improved substantially, and the addition of SVR isespecially effective.
Although not covered in this paper, theadvancement approach (2) also produced almost
the same level of results. We assume this is due tothe distressed power network for the preset conditions of the power distribution network model.
While under the conventional control systems,
by using the PV introduction, the rate will stay ataround 14%, and the adoption of the advancement
approach (1) improved the PV introduction rate up to
30%. Such result conﬁrms that by adopting theadvancement approaches, we will be able to reachthe introduction target in Fiscal 2020. Fig. 8 shows
the demonstration results.

5 Postscript
This paper introduced issues related to voltage
control for distribution networks arising out as aresult of higher infusion of PV systems in the future.
We also showed a scenario leading to the solutionof these issues. In regard to the advancement
approach for autonomous distributed control whichis considered as effective in a process of the scenario, this paper also outlined the approach andshowed the simulation results under the said
approach. The demonstration project is under the
grant by the Agency for Natural Resources andEnergy under the Ministry of Economy, Trade andIndustry. We received the guidance of Professor
Hayashi from Waseda University and support from
distribution network-related engineers from power《References》
Conventional method

14

Proposed methodwith scheduling control
in LRTwith scheduled LDC
control in LRTwith Q-control by
PV-PCSand Ruling Parties regarding “Measures against Economic Crisis”:
April 2009 (in Japanese)( 2 ) Akihiko Yokoyama et al.: “Verification of Optimum Control
Technologies on Next-Generation Power Transmission Systems,”
Denki Hyouron, October 2011 (in Japanese)( 3 ) Ministry of Economy, Trade and Industry: “Introduction Scenario(Estimate) for Photovoltaic Power Systems,” New and Renewal

Operation
voltage range
103V to 107V

30
30
40

Conventional method2

Adding STATCOM

Operation
voltage range
103V to 106V

10

Adding SVR

30
0

Fig. 8( 1 ) Ministerial Conference on Economic Measures by the Government
30

40
60
20
Rate of PV penetration (%)

80

Result of Demonstration

The result of veriﬁcation is shown in regard to the comparison ofpresent and advancement approaches of LRT control systems,
and the effect of other measures (measures by reactive power
control in PCS for PV and additional installation of voltage control equipment).

utility companies. We could continue to study withsuch support. We would like to work on various
technical developments to enable us to meet largescale use of renewable energy resources in the
power network.
・All product and company names mentioned in this paper are
the trademarks and/or service marks of their respective owners.

Energy Subcommittee of the Advisory Committee for Natural
Resources and Energy, No.36 Distributed Documents for the discussion, 2009 (in Japanese)( 4 ) The Japan Electric Association: “Grid Connection Rules JEAC
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