optimal operation of wind/electric utility interconnecte

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Optimal Operation of Wind/Electric Utility

Interconnected Electrical Power SystemUsing Neural Network

Faculty of Engineering, Elminia University,

Elminia, Egypt



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This paper introduces an application of an artificialThis paper introduces an application of an artificial

neural network on the operation control of theneural network on the operation control of the

WTG/ utility grid to improve system efficiency andWTG/ utility grid to improve system efficiency andreliabilit .reliability.

Object of this paper



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This paper focus on a hybrid system consists of

wind system accompanied with battery storage

interconnected with utility grid taking intoaccount the variation of wind speed and load

demand during the day. Different feed forward

neural network architectures are trained andtested with data containing a variety of operation

patterns. A simulation is carried out over one year

using the hourly data of the load demand and

wind speed at El'Zafranna site, Egypt as a case

study.



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The WES can be either connected to EU withoutBS or connected to EU with BS. The WES without batteries operates only when wind speeds and the

EU supply present but do not supply local loads ithe EU fails and if the wind speeds become low.

If the WTG's exceed local load and excess power isexported, if they are less than local load theshortage will be supplied from the EU. If the EUfails the inverter disconnect from the EU, local loadcan be supplied from the battery and from WES.The battery will discharge if WTGs are less than

local load and be charged when they exceed localload. WES with BS ensures that all renewableenergy generated can be utilized.



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The WES connected to EU with BS is extremely popular for

homeowners and small businesses where backup power is

required for critical loads, uninterruptible power supply, cost

saving and power quality improvement, telecommunications

backup and other necessities [2], [3], [4], [5]. The BS can

then be recharged from future excess generation or during off- peak hours. Storage energy can be provided for local load or

critical loads when market prices are the highest and consume

when they are the lowest.



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This paper describes a renewable energy system that

can provide a total energy of 432*106 kWh to feed the

load demand. The system has been designed to supply

continuous power of 100 MW load and has the

following capabilities:

• Maximizes the electric power produced by the WES

by detecting and tracking the point of maximumpower.

• Stores the future excess generation or during off-

peak hours electric energy in lead-acid batteries.• Controls the charge and discharge processes of the

batteries by using NN.

• connects the load demand to the BS when the WES

and EU s stem fail.



WES Connected To EU With BS

In this type of intertie system, the load

demand has a WES, EU and BS as shown inFig. 1. If load demand requirements exceedthe WES, the shortfall is automatically

made up by the EU. If the EU power fails,power will be drawn instantly from thebackup batteries to support the loaddemand. Switching time in case of EUfailure is so fast. The connection operationhas been done by a neural network. Powerflows from the system shown in Fig. 1 must

satisfy (1). (1) (t)LP(t) batP(t)gP(t)

WESP =±±



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S 3 W b

S 2 W b

S 1 W b

E U

F i l t e r

L o a d

S t e p - u p

T r a n s f o r m e r

B u s b a r

B u s b a r

~

S t e p - d o w n

T r a n s f o r m e r

I n p u t

O u t p u t

N N f o r W T G / E U

a c c o m p a n i e d w i t h B S

G . B . I . G .

W i n d S p

D C / A CA C / D C

B a t t e r y S t o r a g e

( B S )

S 4 W b

Vd c w

ig. 1. General configuration of the WES/EU/Binterconnected system.



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The operation of the four switches shown in Fig. 1 canThe operation of the four switches shown in Fig. 1 canbe summarized as shown in following Table .be summarized as shown in following Table .

Generated power vs.Generated power vs.

Load demandLoad demandS4WbS4WbS3WbS3WbS2WbS2WbS1WbS1WbModeMode

PPWESWES < P< P

LL

i.e wind speed is very lowi.e wind speed is very low11OFFOFFONONOFFOFF11

PPWESWES > P> P

LL

i.e. wind speed is highi.e. wind speed is high11OFFOFFOFFOFFONON22

PPWESWES > P> PLL

i.e. wind speed is very highi.e. wind speed is very high11ONONOFFOFFONON33

PPWESWES =0=000OFFOFFONONONON44



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Fig. 2. The daily load curves for January, April, July and October [6].

It is assumed here

that the load demandvaries monthly. Thismeans that eachmonth has daily loadcurve different from

other months.Therefore, there aretwelve daily loadcurves through the

year. Fig. 2 shows thedaily load curves foranuary, April, Julyand October [6].

Load Characteristic



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System Simulation

A new computer program has been

proposed and written using Matlabsoftware to simulate the system shown inFig. 1. The flowchart of this program is

shown in Fig. 3.



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F o r t i m e = 1 : 1 : 2 4 h r

E n d

B a t t e r i e s a r ec h a r g e d i . e .

S 4 W b = 1a n d t h e l o a d i s f e d

f r o m g r i d

I f W i n d s p e e d

( t ) < L i m i t o r

I n v e r t e r

f a i l u r e

y e s

N o

I f w i n d s p e e d

( t ) > L i m i t o r

PW E S

( t ) > PL

( t )

F e e d t h e l o a d

S 1 W b = O N

I f S O C ( t ) >

0 . 8 * s i z e o f b a t t e r y

N oy e s

S u r p l u s p o w e r s e n dt o E U

S 3 W b = O N

y e s

N oS u r p l u s p o w e r s e n d

t o B a t t e r y

S 4 W b = 1 ,

S 1 W b = O N

I f S O C ( t ) >

0 . 2 * s i z e o f

b a t t e r y

y e s

L o a d f e e d f r o m

b a t t e r y S 1 W b = O N ,

S 4 W b = 0

N o

L o a d f e e d f r o m

E U ; S 1 W b = O F F ,

S 2 W b = O N

F o r i = 1 : 1 : 1 2 m o n t h

S t a r t

R e a d H o u r y w i n d s p e e d ,

P a r a m e t e r s o f W T G , H o u r l y

L o a d d e m a n d

ig. 3. Flowchart of the operational modes of

Th i f hi



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The inputs of this program are:

1- Hourly wind speed.

2- Characteristic of WES module

3- Hourly load demand

The outputs of this program are:

1- Generated power from WES.

2- Monthly surplus energy.3- Monthly deficit energy. 4- Size of battery

5- State of batteries charge.

The output of this program is used to be the input of NN.

The outputs of NN are four trip signals that sent toswitches S1Wb, S2Wb, S3Wb and S4Wb.

P d N k



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Proposed Network Figure 4 shows the structureof the proposed three layers

NN. X1, X2, X3, X4 and t arethe five-input trainingmatrices and representbatteries state of charge,

electrical power generatedfrom WES, electrical powerfor EU, load demand andtime respectively.

The network consists of 5 input layers, 7 nodesin hidden layers and four nodes in output layerwhich sigmoid transfer function. The network

has been found after a series of tests andmodifications.

Fig. 4. Structure of theproposed three layers NN.



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Figures 6 displays the optimal operation of the WES/EU

accompanied with BS hour by hour through the day which

represents the month of January.

. 6 Optimal operation of the WES/EU/BS to f

the load demand during January (winter)



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Figure 7 reveals state of charge for BS which corresponding

to the optimal operation of the WES/EU accompanied with

BS through the months of January and July respectively.

Fig. 7 State of charge of WES/EU/BS during January

(winter) and July (summer)



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From Fig. 6, Fig. 7 and Fig. 9 (January) it can be

noticed that the trip signal which produced from NN

sent to switch S1Wb at hours 5, 8, 9, 10, 11, 12, 13,

14, 15, 16, 17, 18, 19 and 22. This means that the

WES or BS feed the load demand at these hours. On

the other hand, switch S2Wb (for example) equal to 1

at hours 1, 2, 4, 5, 6, 7, 8, 9, 10, 14, 20, 21, 23 and 24.This means that the EU should supply the load

demand at these hours. On the other hand, the power

injected to EU through switch S3Wb at hours 11, 12,15, 16, 17 and 18.



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ig. 9 Outputs of Neural Network for January



2020

Finally, battery storage will be on state of charge

through switch S4Wb at hours of 1, 2, 3, 4, 6, 7, 8,

9, 10, 11, 12, 14, 15, 20, 21, 23 and 24. On theother hand, the BS will be discharged through the

hours of 5, 12, 13, 16, 17, 18, 19 and 22. Then the

BS can feed the load demand only during these

hours accompanied with WES.



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