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

Optimal Operation Plan forDistribution Network Systems
Linking with Many Renewable
Energy Resources
Keywords

Takayuki Tanabe,
Yoshinobu Ueda,
Toshihisa Funabashi

Distribution network system, Distribution voltage control, Battery energy storage system, Controllable load, Optimization calculation

Abstract

Recently, the renewable energy resources such as Photovoltaic (PV) power
and wind power have been increasingly linked to distribution network systems.
As a result, there is concern over the charge to resultant complex power ﬂows
from conventional simple ones that were in only one direction power ﬂow. As
such, there is a risk that the operation of distribution network systems may cause
adverse effects on power supply programs for transmission network systems.
Our research proposes a coordinated control method for controllable loads
located on the consumer side and a reactive power control approach with theuse of interconnection inverters to be installed between existing voltage control
devices (substation LRT and SVR) and PV generation systems. This occurs after
the introduction of Battery Energy Storage Systems (BESS) which would beapplied to the coupling point between the distribution network system and thetransmission network stream. This project is able to maintain appropriate voltage on a distribution network and stabilize power ﬂows at the coupling point.

1 Preface
Recently in Japan, the introduction of distributed
energy resource of renewable energy is actively
promoted in order to realize a low carbon society.
Power generating systems using renewable energy
are attracting a great deal of attention because they
do not generate any carbon dioxide and they use
renewable sources of energy. The power yield,
however, tends to be greatly affected by meteorological conditions which make it difﬁcult to maintainthe distribution voltage within a proper range if such
resources are grid-connected with the distribution
network system in a large quantity. Furthermore,existing distribution network systems are being built
on the assumption that the power ﬂows run fromupstream to downstream. There is no such consideration against a voltage in the end of feeder
increase in a distribution network system as a resultof an interconnection with distributed energy resources. As a result, the interconnection of a large
amount of distributed energy resources can bringabout a variety of technical challenges such as theoccurrence of reverse power ﬂows toward an upperstream power system(1).
This paper proposes a method of an effective
grid power distribution operation planning methodwith due consideration to battery energy storagesystems, interconnection inverters for distributed
energy resources, existing voltage control devices,and controllable loads.

2 Grid Power Distribution System Model
Fig. 1 shows a model of the grid power distribution system represented in this paper. The node
numbers encircled in the diagram denote that alarge number of Photovoltaic (PV) energy resources
are presumed to be interconnected with the grid. PV
energy resources are anticipated to increase in thefuture due to the reduction of introduction costs andthe concern over the rising power utility charges.
Table 1 shows various constants of a distribution
network system model. The system capacity andnominal voltage assumed in this table are 5MVA
and 5.5kV, respectively.
According to the Electricity Utility Law, the supply voltage is required to be maintained within aMEIDEN REVIEW Series No.162 2014 No.331Residential lot

V＊On-load tap-changing transformer 1

21
Distribution
substation

2223－＋PIcontroller
24On-load tap-changing transformer 212131415

Office area

Qmax Qmin

3233

34

Pref35
Calculation ofoutput enabledrange: On-load tap-changing transformer: Node where distributed type generators are located

Grid Power Distribution System Model

A model of the grid power distribution system presumed in thispaper is shown. The node numbers encircled in the diagram denotethe assumption that PV power systems are interconnected.

Various Constants of a Grid Power Distribution
System ModelVarious constants of a grid power distribution system model
used in this paper are deﬁned.
Battery energy storage capacity

4.0pu (20MWh)

Battery inverter capacity

0.3pu (1.5MW )Impedance of each line

0.04 ＋ j0.04pu

Rated power output of PV generation
system0.08pu (400kW )Inverter capacity of PV power system

0.08pu (400kW )range of 202 ±20V or 101 ±6V for low voltage
power receiving. In this paper, the range of 101 ±6V
for 100V supply is adopted. The voltage range to be
maintained in the distribution network system onhigh-voltage side is assumed to be 6380V (0.967pu)
to 6600V (1.0pu) (2).

2.1 PV Power Generation System
In this paper, we propose an adoption of reactive power control for the electricity consumer side.
In this case, there are a large number of interconnection inverters of PV power systems that aregrid-connected. Fig. 2 shows a conceptual diagramof the PV power system. The reactive power control
by the interconnection inverters is assumed to bepossible independent of the generated active poweroutput. It is also assumed that the generated activepower output is never restricted. By using the optimization approach discussed in the next section,
voltage control command values are determined inorder to realize reactive power control.

32

InverterMax. power
follow-up
31

Table 1dq
conversion

16

Storagebatteries

Power
distribution
systemP, Q

Qref
11Fig. 1

VMEIDEN REVIEW Series No.162 2014 No.3

Fig. 2

P
Solar batteries

Reactive Power Control System with Interconnection Inverters of the PV Power System

A conceptual diagram of the reactive power control system isshown. This system employs the interconnection inverters of thePV power system assumed in this paper. Control is carried out
according to the control schedule determined on the basis of theoptimization calculation.

2.2 Battery Energy Storage System
In this case, a battery energy storage system is
introduced and applied to the interconnecting point
between the distribution network system and theupper stream grid power system for the leveling ofactive and reactive power ﬂows at the grid interconnecting point. This system has been establishedon the assumption that its operation follows up thecontrol command values determined on the basis ofoptimization calculation in the same manner as for
PV power systems.

2.3 Controllable Load
Since the capacity of the battery energy storage system becomes very large in the case of anactive power ﬂow control where only batteries areused (3), a cooperated control method is proposed inthis paper with the use of controllable loads (whichis recently attracting general attention in the ﬁeldof smart grid technologies). Controllable loads
are comparable with electric vehicles, electric hotwater dispensers, and such equipment working withelectric power consumed on electricity consumer
side where control is made ﬂexibly by using information technologies. The controllable load describedin this paper assumes that it becomes smaller whenpower consumption of the grid power system as awhole is larger, and that it becomes larger as power
consumption in the overall grid power system issmaller.

3 Decision Approach for Control
Command Values
3.1 Formulation of Optimization Subject
As described above, our research aims at theoptimal operation of grid power distribution systems
such as transformer tap position control by meansof existing voltage control devices, reactive power
control with the use of connecting inverters available in PV generation systems, control of active andreactive power by using a battery energy storage
system installed at the grid interconnecting point,and cooperated control of active and reactive powerassuming that controllable loads are located onelectricity consumer side. Based on the forecast
amount of sunlight and predicted values of power
demand for the next day, an optimal schedule isestablished according to the control command values. The objective function and the constrained conditions for optimization calculation are speciﬁed below.
[Objective function]
min: F (PB, QB, PCL, QCL, QG, TK) ＝ΣΣPLinxli( 1)[Constrained conditions]
Vmin

Vi(2)

Vmax

PB2 ＋ QB2

(3)

SB

CB24min

CB24CBmin

CBPG2 ＋ QG2

CB24max

(4)

CBmax

(5)

SG(6)

Pf minPf

Pf max(7)

Qf minQf

Qf max(8)

Tmin

TkTmax(9)

PCLminPCL

PCLmax(10)

QCLminQCL

QCLmax(11)

ΔWL024PCLup ＋ 0 PCLdown ΔWU
24(12)

Where, the respective variables are as follows:n: Total number of control command switchover actionsx : Total number of lines
PLi : Distribution loss o Line i
Vi : Voltage at i -th nodeVmin, Vmax: Upper and lower limits of node voltage

Pf : Tidal flow of active power at grid interconnecting pointmin
Pf : Lower limit of active power ﬂow band
width at grid interconnecting pointmax
Pf : Upper limit of active power ﬂow band
width at grid interconnecting point
Qf : Power ﬂow of reactive power at grid interconnecting point
Qf min: Lower limit of reactive power ﬂow band
width at grid interconnecting point
Qf max: Upper limit of reactive power ﬂow band
width at grid interconnecting point
PG, QG : Active and reactive power output of PV
generation systems
SG: Interconnection inverter capacity of PV powersystems
PB, QB : Active and reactive power output frombattery energy storage systems
SB : Interconnection inverter capacity of storage
batteries
CB : Battery energy residual rate
CBmin, CBmax: Upper and lower limits of batteryenergy residual rate
CB24: Battery energy residual rate in 24 hours
CB24min, CB24max: Upper and lower limits of battery energy residual rate in 24hoursTK : Tap position of each transformer
Tmin, Tmax: Upper and lower limits of tap positions
PCL : Active power consumption in controllableloads
PCLmin: Lower limit of active power consumption
in controllable loads
PCLmax: Upper limit of active power consumption in controllable loads
QCL : Reactive power consumption in controllable loads
QCLmin: Lower limit of reactive power consumption in controllable loads
QCLmax: Upper limit of reactive power consumption in controllable loads
up
PCL : Active power consumption increment incontrollable loadsdownPCL: Active power consumption decrement
in controllable loads
ΔWL, ΔWU : Limits of controllable load increment and decrement
In order to suppress extreme changes in active
and reactive power at a grid interconnecting pointand establish preferable control ﬂexibility in overall
MEIDEN REVIEW Series No.162 2014 No.333

3.2 Particle Swarm Optimization
Particle Swarm Optimization (PSO) is a kind ofoptimization approach developed on the basis of a
speciﬁc concept: when birds, insects, or a school ofﬁsh search for food, and when a particle (individual)
discovers an efﬁcient route to acquire it, other particles can follow the discovered route from wherever
they are at the moment. This modeling is performed
based on a particle swarm having a position and aspeed in a multi-dimensional space. According to
the retrieval algorism, positional information is34

MEIDEN REVIEW Series No.162 2014 No.3

exchanged with swarm members and particle position and speed are repeatedly adjusted. Positionand speed are updated with the use of the expressions below.
Vk＋1 ( i ) ＝ w・Vk ( i ) ＋ c1・rand1・( pbest ( i ) －Sk ( i ) ＋c2・rand2・(gbest－Sk ( i ))(13)

Sk＋1 ( i ) ＝ Sk ( i ) ＋ Vk＋1 ( i )(14)

Where, the respective variables are as follows:
Vk＋1 ( i ): Speed of Particle i at k-th trial
rand1, rand2: Uniform random numbers given
within a range of 0 ～ 1
Sk＋1 ( i ): Retrieval point for Particle i at k-th trial
w: Inertial weight
c1: Weighting for retrieval to the best particle
positionc2: Weighting for retrieval to the best group
positionpbest : Best solution obtained in the particle
gbest : Best solution obtained in a group

4 Result of Simulation
In order to verify the effectiveness of the proposed method, simulation of power ﬂow calculation
has been carried out with a grid power distribution
system model shown in Fig. 1. For this simulation,
an optimal control command schedule is established, using a one-hour mean value of PV generation output in Fig. 3 as a predicted value for the nextday. The results of the simulation conducted under
the application of the proposed method are shown

0.01
PV power output Pi (pu)

distribution network system, a bandwidth is set up
for the power ﬂow at the grid interconnecting point.
For our research, the bandwidth for the active power
ﬂow is kept constant at average load power ±0.1pu(500kW). The bandwidth for the reactive power ﬂow
is set up so that the power factor at the grid interconnecting point can be maintained within the rangeof 0.8 to unity. As aforementioned, power ﬂow control has been devised to serve controllable loads
such as in electric vehicles and all-electric homes.
In this case, changes in active and reactive powerﬂows are controlled within the predetermined bandwidth at the system connecting point.
The control command schedule is established
for the duration of 24 hours in the increments of onehour. In the state that all restrictive conditions havebeen satisﬁed, the objective function is minimized
so that power distribution losses can be suppressed
throughout the system. There are many restrictiveconditions; such as voltage restriction in a grid power
distribution system, bandwidth restriction of active
and reactive power ﬂows intended to suppresschanges in tidal ﬂows at the grid interconnecting
point, restriction of interconnection inverter capacity
in PV power systems, restriction of interconnection
inverter capacity in battery energy storage systems,
restriction of battery energy residual rate intended
to suppress rapid deterioration of battery energy
storage systems (CBmin ＝ 20%, CBmax ＝ 80%), restriction of battery energy residual rate in 24 hours
needed in consideration of operation on next day(CB24min ＝ 40%, CB24max ＝ 60%), restriction of upperand lower limits for transformer tap-changing, restriction of upper and lower limits for active power consumption in controllable loads, restriction of upperand lower limits for reactive power consumption incontrollable loads, and restriction of upper andlower limits in regard to variations in active power
consumption throughout 24 hours.

0.08
0.06
0.04
0.02
002

468

10 12 14 16 18 20 22 24Time (h)Fig. 3

PV Power Output

A predicted value of PV power output for the next day is shown,which is determined by the simulation described in this paper.
A one-hour mean value is deﬁned based on this diagram. It isused as a predicted PV generation output for control commandscheduling.

10.99
0.98
0.97
0.96
0.95

05101520

Battery output andpower output PB, QB (pu)Each node voltage Vi (pu)

1.01

0.4
0.3
0.2
0.1
0－0.1
－0.2
－0.3
－0.4

PB0QB510Time (h)Fig. 4

Distribution Voltage at Each NodeFig. 7

0.8
0.6
0.4
0.2
0－0.2
051015

Active and Reactive Power Outputs from Battery
Energy Storage Systems

20

0.2
0.15
0.1
0.05
0－0.05
－0.1
－0.15
－0.2

PCL

05Time (h)Fig. 50.8

Fig. 80.6
0.40.20－0.2
5101520Time (h)Fig. 6101520

Reactive Power Flow at the Grid Interconnecting
Point

Active and Reactive Power Control byControllable Loads

The diagram shows the controllable capacity of controllable
loads and the control values of active and reactive power. Thecontrollable loads are operated in coordination with the charge/
discharge mode of battery energy storage systems.

Reactive power output
QGi (pu)

Reactive power flow Qi (pu)The result of active power ﬂow simulation is shown, conducted atthe system connecting point. The restrictive conditions are satisﬁed by cooperated control with the aid of battery energy storage
systems and controllable loads.

0QCL

Time (h)Active Power Flow at the Grid Interconnecting
Point－0.4

20

Active and reactive power outputs of battery energy storage systems are shown. It is possible to conﬁrm that batteries arecharged in the daytime when reverse power ﬂows take place andare discharged when no PV power output is available.

Controllable loads
PCL, QCL (pu)

Active power flow Pi (pu)The result of the distribution voltage simulation is shown, which
is anticipated when the proposed method (cooperated control bycontrollable loads, battery energy storage systems, interconnection
inverters of PV power systems, and existing voltage control devices) is adopted. Voltage restrictions are satisﬁed.

－0.4

15Time (h)

0.1
0.08
0.06
0.04
0.02
0－0.02
－0.04
－0.06
－0.08
－0.1

05101520Time (h)Fig. 9Reactive Power Output from Interconnection
Inverters of PV Power Systems

The result of reactive power ﬂow simulation is shown, conductedat the grid interconnecting point. The restrictive conditions aresatisﬁed, similar to the active power ﬂows.

The controllable capacity of interconnection inverters and thecapacity of active and reactive power control are shown for thePV power system. It is possible to examine the effect of compensation for reactive power to raise system voltage while no PV
power output is available.

in Figs. 4 to 10. The respective ﬁgures show thedistribution voltage at each node under the cooperated control by controllable loads: battery energy
storage systems, interconnection inverters of PV
power systems and existing voltage control devices,
active power ﬂow at the grid interconnecting point,
reactive power ﬂow at the system connecting point,

active and reactive power output from battery energy storage system, active and reactive power control by controllable loads, reactive power output
from connecting inverters of PV power systems, andtap positions of existing voltage control devices,
respectively. According to the data, it is possible to
conﬁrm that variations in voltage at each node are
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35

5 Postscript

Tap position Ti (pu)

1.06
1.04
1.02
10.98

Distribution substation
On-load tap-changing transformer 1
On-load tap-changing transformer 20.96
0.9405101520Time (h)Fig. 10

Tap Positions of Existing Voltage ControlDevices

The diagram shows the tap positions of substation LRT andSVR. It is possible to conﬁrm that the voltage rise is suppressedin the daytime and the system voltage is raised at any other time.

This paper described our proposal of optimal
operation approach for the grid power distribution
systems where a large number of renewable energy
resources are accommodated. When the proposed
method is adopted, it is possible to adequately
maintain distribution voltage and level power ﬂows
at the grid interconnecting point. Further, we could
reduce the capacity of battery energy storage systems by using the controllable loads.
・All product and company names mentioned in this paper are
the trademarks and/or service marks of their respective owners.

controlled by tap-position control of existing voltage
control devices, by cooperated reactive power control of the respective control devices and that therestrictive conditions are duly satisﬁed. Leveling ofvariations in power ﬂows at the system connecting
point is attained by active and reactive power control of the battery energy storage system. Whencontrollable loads are adopted, it becomes possible
to perform active and reactive power control on theconsumer side. This contributes substantially to thereduction of capacities of battery energy storage
systems and connecting inverters.

36

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《References》( 1 ) Toshihisa Funabashi: “A New Power Feeding System with
Active Use of Distributed Power Sources,” Preface to the Special
Edition, DenGakuRon B, Vol.130, No.11, p.927, 2010 (in Japanese)( 2 ) Masato Oshiro, Tomonobu Senjyu, Atsushi Yona, Naomitsu
Urasaki, Toshihisa Funabashi: “Distribution Voltage Control inConsideration of Reactive Power Output Sharing,” DenGakuRon B,Vol.130, No.11, pp.972-980, 2010 (in Japanese)( 3 ) Masato Oshiro, Akihiro Yoza, Tomonobu Senjyu, Atsushi Yona,
Toshihisa Funabashi, and Chul-Hwan Kim, “Optimal Operation
Strategy with using BESS and DGs in Distribution System,” KIEE
Journal of International Council on Electrical Engineering, Vol.2,
No.1, pp.20〜27, 2012