International Journal of Emerging Electric Power Systems Volume 9, Issue 2

2008

Article 3

Design of a New Oil Spraying Device for Hot Spot Cooling in Large Scale Electric Power Transformers Kourosh Mousavi Takami∗

∗

Malardalen University, [email protected]

c Copyright 2008 The Berkeley Electronic Press. All rights reserved.

Design of a New Oil Spraying Device for Hot Spot Cooling in Large Scale Electric Power Transformers∗ Kourosh Mousavi Takami

Abstract Hot spot temperature (HST) is the most important parameter in the operation of power transformers. The HST has to be held under a prescribed limit. HST has a considerable effect on the insulation aging. Therefore detecting, monitoring and removing the HST could be a very important and necessary action for utilities. A new design of oil spraying and its effect, along with a thermal management in a transformer cooling system has been studied in this paper. The effect of oil fluid flow on the HST problem has been considered in this paper; and the calculations and simulation have been performed by Ants algorithm. The simulation results have been validated based on a 230/63/20 kV, 250MVA transformer at the Sari substation in Iran, and the results indicate that the new design could mitigate the limitations of transformer loading due to the HST problem. The Ants algorithm have been proposed and applied for accomplishing this task and to give an improved level of accuracy. KEYWORDS: power transformer, ant algorithm, cooling, hot spot

∗

Kourosh Takami is a pHD student at MDH University.

Mousavi Takami: Hot Spot Cooling in Large Scale Electric Power Transformers

I. INTRODUCTION Transformers are one of the main components in the electric power systems. The losses in the transformer core and the windings of high efficiency transformers cause an increase in the operating temperature of the transformer. This increase in the temperature can affect the insulating material used in its windings. Therefore, the Hot spot point could affect life of transformer. It is important to accurately calculate and identify the hot spot point because after it is located, various methods can be used to cool down its temperature. Currently, manufacturers do not use any devices for removing the hot spot point. Rather, they compensate for it by decreasing the loading level, increasing the fan speed and the speed of oil circulation. [1] which might lead to shutting down the transformer or a black out in the network. Assunçlo et al. [2] proposed estimating the top-oil temperature by using a method based on Least Squares Support Vector Machines approach. This estimated top-oil temperature is then compared with the measured data of a power transformer in operation. In their approach, they have only found a model, but not introduced a cooling device. TeNyenhuis et al. [3] presented an accurate calculation of the value of the core hot-spot temperature. They have worked on building factor in the design stage, it is very critical to ensure that hydrogen generation, which can be caused by oilfilm degradation at core hot-spot temperatures of as low as 110–120oC, is limited. K. Eckholz et al. [5] calculated the heat transfer coefficients at the winding surface using heat run test results of various ON- and OD-cooled winding types. Two different general approaches were proposed for ON- and OD-cooled windings. The characteristics of the heat transfer coefficients were calculated for each type of the winding. Further temperature rise experiments with an ONcooled disc winding operated with variable heat flux densities were performed in order to investigate the influence of the heat flux density on the cooling efficiency of the boundary layer [6]. However, the above approaches have only found methods for calculating of heat transfer coefficient, HST and top oil temperature. Instead, the utilities mainly need a device for removing the hot spot problem. Using oil spraying systems decrease the HST and finally can increase the allowable temperature rise in a transformer by more than 65 oC, because the HST is one of major obstacle of transformers for loading. With calculation the flow rate, speed and temperature of oil that would be threw to hot spot, could find the best nozzle cross section, oil pump speed. However, with oil spraying it has been shown in the paper that could decrease or remove the hot spot temperature. The volume of the spray mix applied per area by a sprayer depends on: Nozzle flow rate, width sprayed and travel speed of the sprayer. Before finding a sprayer, proper nozzles must be selected. Nozzles should be matched and replaced as a set Published by The Berkeley Electronic Press, 2008

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International Journal of Emerging Electric Power Systems, Vol. 9 [2008], Iss. 2, Art. 3

except under unusual circumstances. The following study intends to provide a framework for the calculations necessary for oil spraying system effects. II. HIGH PRESSURE NOZZLE DEFINITION The hotspot is the highest temperature area in the transformer based on flux leakage from the windings, so naturally this makes the wax in this location the weakest and most susceptible to failure by over temperature conditions. It is necessary to remove the HST problem. A nozzle is perhaps the most important and basic piece of engineering hardware associated with the high-speed flow of oils for cooling the hot spot. The usual configuration for a nozzle is shown in the figure1 .The oil flows through the nozzle from a region of high pressure (usually referred to as the chamber or Tank) to one with low pressure (referred to as the hot spot area). The Tank is usually big enough so that flow velocities in it are negligible. The pressure in the tank is denoted by the symbol pc. Oil flows from the chamber into the converging portion of the nozzle, past the throat, through the diverging portion and then shoots into the hot spot point. The pressure of the HST point is referred to as the “back pressure” and is given the symbol pb. In order to understand the concept and behavior of the fluid pressure, we have to remember only few basic rules: When the flow accelerates, the pressure drops and the pressure rises instantaneously across a shock, and the pressure falls across an expansion wave. However, the temperature distribution behaves qualitatively like the pressure distribution. A. Selecting the sprayer application rate A recommended range of sprayer application rates, in liter/mm2, is calculated on base of the nominal power of transformer and distance of tank body with core surface. From that range, could choose the rate that is compatible with spraying equipment. B. Selecting the field speed A 10% reduction in the oil speed will result in a reasonable heat transfer coefficient; it is shown in figure9. Where speed must be reduced for a short period at the end of cooling period, when get the over 70% of HST cooling or in other situations, (for a 30% of all spraying time) [23], a small reduction in pump speed is preferable to selecting a lower cooling. Reducing the cooling speed causes the nozzle flow rate as well as the travel speed to decrease, although not proportionately. If it is necessary to reduce the speed frequently, calibrate the sprayer for the slower speed. http://www.bepress.com/ijeeps/vol9/iss2/art3

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Mousavi Takami: Hot Spot Cooling in Large Scale Electric Power Transformers

C. Determining the width sprayed by each nozzle The width sprayed by each nozzle on a broadcast spray boom is equal to the distance between the nozzles. If a sprayer has nozzles spaced every 40 inches on the boom, the width sprayed by each nozzle would be 40 inches. If a sprayer has several nozzles that will be used to spray each row, such as sprayers used to apply hot spot location, then the width sprayed by each nozzle is equal to the distance between the rows divided by the number of nozzles used to spray each row. If the sprayer is a band sprayer and the labeled rate applies to the actual area sprayed, the width is equal to the width of the band. If the sprayer is a band sprayer and the labeled rate applies to the total area covered, the width is equal to the spacing between the rows. However, intelligent system based on fuzzy logic can be used; then, the nozzle can rotate with many degrees of freedom. This allows the designer to reduce the number of nozzles for half or less.

a

b

Fig. 1. a-Nozzle b-Schematically cut of power transformer with oil spraying system [23].

D. Determining the nozzle flow rate The nozzle flow rate can be calculated: GPM = GPA x V x W x k And the travel speed is given by: V = D×60 t

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(1) (2)

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International Journal of Emerging Electric Power Systems, Vol. 9 [2008], Iss. 2, Art. 3

V = travel speed (mm/s) E. High viscosity problem for nozzle The high viscosity of the oil prevents the nozzles from forming the equivalent spray patterns, at equivalent temperature and pressure settings. The first and most obvious solution is to increase the working pressure of the system. The drawbacks to this solution are higher cost in the higher pressure rated pumps, motors, and delivery lines to the nozzles. This also increases the safety concerns in the event of ruptured lines in the building. A booster pump on the outlet of this system can be a solution. A second solution is to employ local area pumps. Consequently, the third option to be considered is to use some sort of rotating nozzles, which would spray the oil in a rotating type fashion. III. TEMPERATURE CALCULATION A. Heat transfer conventional equations In most of the heat and mass transfers, the heat equation [17, 18, 19 and 20] can be seen. In this paper, convection and conduction is considered for all the calculations. The following are the assumptions considered for simulation: • Oil and air are initially in steady state. • Oil is a Newtonian and incompressible fluid. • Fluid flow is laminar, unsteady and two-dimensional. Continuity equation: ∂ρ ∂ ∂ + (ρu ) + (ρv) = 0 ∂t ∂x ∂y

(3)

Linear momentum equation in the x direction: ∂(ρu) ∂ ∂ ∂p ∂ ∂u ∂ ∂u + u (ρu) + v (ρu) = − + (μ ) + (μ ) ∂t

∂x

∂y

∂x ∂x

∂x

∂y

∂y

(4)

Linear momentum equation in the y direction: ∂(ρv) ∂ ∂ ∂p ∂ ∂v ∂ ∂v + u (ρv) + v (ρv) = − + (μ ) + (μ ) − g(ρ − ρref ) ∂t ∂x ∂y ∂y ∂x ∂x ∂y ∂y

(5)

Energy equation: ∂(ρCpT) ∂t

+u

∂ ∂ ∂ ∂T ∂ ∂T (ρCpT) + v (ρCpT) = (k ) + (k ) + R(t)q′′′ ∂x ∂y ∂x ∂x ∂y ∂y

(6)

With

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Mousavi Takami: Hot Spot Cooling in Large Scale Electric Power Transformers ⎧ ⎪0 for fluids ⎪⎪ R(t) = ⎨ −4 ⎪ −9 2 ⎪−1.457×10 × t + 0.925×10 × t + 0.1658 ⎩⎪

for the compunentsof the active unit

The heat source function presented by R (t) coefficient, it has been modified here to take account of variation of copper resistivity with temperature, it was found by experimental test. With this representation, the function R becomes time dependent, distributed, heat source. The initial conditions in steady state (do not operate the oil pump) mode and ambient temperature are: At t=0, u=v=o, T0 =Tf =24 o C (7) The boundary conditions considering natural convection, with the transference coefficient h as a function of the wall temperature and radiation are [20]: x = 0, y = y,t = t,u = v = 0 ⇒ −kw ∂Tw = hyl ( T − T f ) + εσ.(( T + 273)4 − (T f + 273)4) ∂x

x=0

x=0

(8) ∂ T T T 4 w = hyr( − T ) + εσ.(( + 273) − (T f + 273)4) x = lx, y = y,t = t,u = v = 0 ⇒ −kw ∂x x = lx f x = lx (9) T ∂ T T 4 w y = 0, x = x, t = t, u = v = 0 ⇒ −kw = h yb ( − T f ) + εσ .(( + 273) − (T f + 273)4 ) ∂y

y=0

y=0

(10)

y = l y , x = x, t = t, u = v = 0 ⇒ −kw ∂Tw = hyt ( T − T f ) + εσ .(( T + 273)4 − (T f + 273)4 ) ∂y y = ly y = ly -8

2 4

(11)

Where: ε=0.2, σ =5.67×10 k/m k . The convective coefficients included in the boundary conditions are determined using the approach proposed by Montsinger [7], which permit to determine the convective heat losses by unit area on the tank wall in terms of the air friction factor f, the barometric pressure Pa, and the wall and surrounding temperatures Tw and Tf, respectively. It is given by: Wc = 2.17. f . pa (Tw −Tf )1.25 (12) Where f = 1 for flat walls. In another way, in accordance with the Newton’s Law, the convective heat transfer on the tank walls is given by: q ′′ = h.(Tw − T f ) (13) So, from (12) and (13), it is obtained that: h ( x , y ) = 2 . 17 .(T w − T f ) 0 .25 (14) At the interface oil-air, the boundary condition is the one used by Ramaswamy and Jue [8]: Published by The Berkeley Electronic Press, 2008

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International Journal of Emerging Electric Power Systems, Vol. 9 [2008], Iss. 2, Art. 3

∂u 1 ∂σ i ∂T =− ∂y μ ∂T ∂x

(15) Where τ is the thermal process time constant (TC); Δt is the time difference; ρ is the density and μ is the dynamic viscosity. B. AC power electromagnetic fields To derive the equation system (magnetic field) solves, start with Ampère’s law, (16) ∇ × H = J + ∂ D = σ e E + σ eV × B + J e + ∂ D ∂t

∂t

Now assume time-harmonic fields and use the definitions of the potentials, B = ∇ × A , E = −∇ V − ∂∂At , and combine them with the constitutive relationships B = μ 0 ( H + M ) and D

= ε 0 E + P to rewrite Ampère’s law as 2 − 1 ( j ωσ e − ω ε 0 ) A + ∇ × ( μ ∇ × A − M ) − σ eV × (∇ × A) + (σ e + j ωε 0 )∇ V = J (17) 0

In the 2D in-plane case, there are no variations in the z-direction, and the electric field is parallel to the z-axis. Therefore, you can write ∇ V as −ΔV/L where ΔV is the potential difference over the distance L. Now simplify these equations to ⎡− M ⎤ y⎥ − ∇.(μ −1∇Az − ⎢⎢ ) + σ eV .∇Az + ( jωσ e − ω 2ε 0 ) Az = σ e ∇V + Jϕe + jωPϕ ⎥ 0 L ⎢⎣ M x ⎥⎦

(18)

The Ants algorithm using finite element mode performs this transformation to avoid singularities on the symmetry axis. The relevant interface condition is: n2×(H1-H2)=Jφ The natural boundary condition fulfills this equation if the surface current vanishes. We can transform the Neumann condition of this PDE into:

[

]

⎡−M ⎤ ⎡−M ⎤ − n.[(μ0−1∇Az − ⎢ y ⎥)1 − (μ0−1∇Az − ⎢ y ⎥)2 = −n × (μ0−1∇× A − M )1 − (μ0−1∇× A − M )2 = −n × (H1 − H2 ) = 0 (19) M x ⎣ ⎦ ⎣ Mx ⎦

C. Solution procedure The Ants algorithm has been used for the solution of these set equations. A set of m artificial ants construct solutions from elements of a finite set of available solution components C = { c ij } , i = 1,..., n , j = 1,..., D i . A solution construction starts with an empty partial solution S p = φ . Then, at each construction step, the current partial solution S p is extended by adding a feasible solution component from the set of feasible neighbors N ( s p ) ⊆ C . The process of constructing solutions can be regarded as a path on the construction graph GC (V, E). The allowed paths in GC are implicitly defined by the solution construction mechanism that defines the

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Mousavi Takami: Hot Spot Cooling in Large Scale Electric Power Transformers

set N ( s p ) with respect to a partial solution S p . The best known rule is the one of ant system (AS) : p(cij s p ) =

τ ijα .ηijβ

∑p

τ ilα .ηilβ

, ∀cij ∈ N ( s p ),

(20)

cij ∈N ( s )

Where τ ij andη ij are the pheromone value and the heuristic value associated with the component c ij respectively. Furthermore, α and β are positive real nodes in solution matrix whose values determine the relative importance of pheromone versus heuristic information. Solution components cij are the edges of the graph, and the pheromone update for τ ij , that is, for the pheromone associated to the edge joining parameters i

and j , is performed as follows: τ ij

m

← (1 − ρ ).τ ij + ∑ τ ijk k =1

Where ρ ∈ ( 0 , 1] is the evaporation rate, m is the number of ants, and Δτ ijk is the quantity of pheromone laid on edge ( i , j ) by the k -th ant: 1

Δτ ijk = {0Lk

otherwise,

if ant k used edge (i, j ) in its tour , where Lk is the tour length of

the k-th ant. When constructing the solutions, the ants in AS traverse the construction graph and make a probabilistic decision at each vertex. The transition probability p ( cij s p ) of the k-th ant moving from i parameter to parameter j is given by (20). , where dij is the length of component cij (i.e., of edge (i,j)). In this work, a transformer model was adapted using the FEM analysis software Matlab and on flow chart1 algorithm. The solution has been successfully converged around 765 iterations. Verification has been performed by simulation in Femlab (Comsol 3.a version) software results [7]. The FEM analysis was carried out on different industrial transformers to estimate the winding eddy current and hysteresis losses. Circulating current losses in continuously transposed conductors (CTC) or properly transposed windings is small and their contribution to the eddy current loss was considered negligible. η ij =

1

d ij

IV. RESULTS AND DISCUSSION

A. Experimental data The experimental data are the result of test on the 230/63/0.4KV transformer, 230/63/20KV Sari substation in Iran. For a one-month period, in July 2006, the

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International Journal of Emerging Electric Power Systems, Vol. 9 [2008], Iss. 2, Art. 3

temperatures of the oil, three windings, and ambient have been measured in every days (Fig. 2). start Initilize:τij(1)= τ0 Ti(1)=T0 nij costbest T1k T2k

Re initilize T1best T2best t≤ number of iteration

Print costbest T1best True

K++

END

Number of ants=n = number of potential stations of the line

k≤ number of Ants True Have all the customers been allocated?

False Allocated new customer, update

Can the station is the

T1k

False Activate new station update T2k(t)

Compute costbest False Costk(t)< Costbest True Set, Costbest = Costk(t) T1best=T1k(t) T2best=T2k(t)

Update pheromone trails T1best using T2best

t++ Pheromones are updated using the global solution

Flow chart1: Ant algorithm flowchart

It is obvious in figure 2 that the low voltage winding has the highest temperature. This is due to this fact that it carries the highest current magnitudes. In addition, for unknown data used the IEEE loading guide published in 1995, 250 MVA power transformer given data. It is illustrated in Table I.

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Mousavi Takami: Hot Spot Cooling in Large Scale Electric Power Transformers

B. Magnetic field solution Fig 4b shows the magnetic field solution of transformer. The leakage flux in the windings flows axially up through the coils and then bends radially across the windings. Fig 4b shown the component of the leakage flux has its greatest concentration at the interface between the two windings and then decreases progressing away from the gap between the windings. The inner LV winding typically has a higher attraction of the leakage flux due to the high permeance of the core. The leakage flux in the HV winding is divided between the core, the Table I: Transformer data from IEEE guide 1995[7] core clamps and other structural parts [8, Description Value 17 and 18]. In the upper end of the No Load (W) 78,100 windings, the conductors are exposed to an inclined magnetic field with two 411,78 Pdc losses (W) 6 components, an axial component and a Eddy losse (W)s 41,200 radial component. The eddy current loss Nominal Voltage 118 kv 230kv is the contribution of these two Pdc at HST location 467 527 components [23, 24]. Eddy current losses at HST

TABLE II. Calculated COEFFICIENTS c and n S/So

C

n

100%

9.1

0.41

30%

1.65

20% 10%

p.u. height to winding HST

309(0. 65pu) 1

157(0. 3pu) 1

Temperature Rise ºC

Rated top oil rise

38.3

Rated top duct oil rise

38.8

0.61

Rated hot spot rise

58.6

50.8

0.495

0.685

Rated average winding rise

41.7

39.7

0.83

0.66

Rated bottom oil rise

16

Initial top oil

38.3

Initial top oil duct

38.3

Initial average winding

33.2

Initial bottom oil Initial hot spot

28 38.3

Transformer components weights (kg) Mass of core and oil 172,20 assembly 0 Mass of tank 39,700 Mass of oil

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International Journal of Emerging Electric Power Systems, Vol. 9 [2008], Iss. 2, Art. 3

variation of temperature in TR. (july) 66 temperature in oc

64

therid w inding temp.

62 60

low voltage w inding temp

58

high voltage w inding temp

56 54 52

oil temp.

50 1 3

5 7 9 11 13 15 17 19 21 23 Hours

Variations of ambient temprature 40

Temp. (oc)

35 30 25 20 15 10 5 0 1

3

5

7

9

11 13 15 17 19 21 23 25 27 29 31 33 Hours

Fig.2. Variation of temperature in transformer and ambient for three winding 250MVA, 230/63/0.4KV transformer on July 2006 in Sari 230/63/20KV substation – Iran

TABLE III. Temperatures comparison Calculation and simulation method

HST

MATLAB cal.

126

COMSOL cal.

120

Tset in site

124

Using of oil spraying (MATLAB) cal.

91

Fig.3: Uncovered transformer

We have coded a program by PDE operator in MATLAB software environment based on Ant algorithm, as a MATLAB M-file. The assessment was done in the steady state mode. It equals the second part of the equation (5) to zero and solve it. Behaviours of oil and temperatures have obtained and calculated, with and http://www.bepress.com/ijeeps/vol9/iss2/art3

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Mousavi Takami: Hot Spot Cooling in Large Scale Electric Power Transformers

without oil spraying system. Moreover, in order to obtain of flow pattern, transformer oil flow has modelled. The velocity and temperature distributions have been simulated by COMSOL software. For the maximum internal temperature above the surrounding oil, was found T (0, 0) - Toil=25°C. The surface temperature rise in the top of oil is approximately T (top)-T (oil) =17.8 °C and bottom oil is T (bottom) –T (oil) =12.2 °C This modelling shows that the hottest spot point is located in 91% of the core and winding altitude from the bottom. This is shown in figure 5. For HST removing, oil sprayed to its area (in 91% height of core) after HST identification using calculation method. Until reach to desired temperature value, Spraying can continuous. Results shown that winding and oil temperature in this area due to spraying decreased. For the maximum internal temperature was found that above the surrounding oil we have T (0, 0)-Toil= -35.8°C. The results of this section has verified by COMSOL simulation, this shown in figure 11.

a. b. Fig. 4 a- Transformer essential parts b-Transformer field solution in FEM environment

For sake of simplicity and importance of top oil temperature, higher than of 90% in height, temperature and velocity are considered in this simulation. Using figure 11 empirical oil velocity has obtained, it is: v=9.78e-3(exp(exp(24.89)T3.87 )-6.89e-1) ms-1, this formula can cover the velocity curve of figure 11. Optimum oil speed in circulation is 0.08 m/s; it is shown in figure 12. With increasing of oil velocity, top oil temperature decrease and oil density and Published by The Berkeley Electronic Press, 2008

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International Journal of Emerging Electric Power Systems, Vol. 9 [2008], Iss. 2, Art. 3

viscosity will increase. It means with increasing of velocity, cooling will mitigate and TOT and consequently HST will decrease. However, it can seem to make problem in the power transformer due to oil spraying in electric and magnetic field cases. Along with performing of oil spraying, non-homogeneous field might occur. It may be lead to voltages break down in insulation, therefore need to assessments and calculation of fields and their effects on insulation behaviour [21, 22]. It is our future work, although our initial investigation shown a healthy work of transformer on oil spraying mode.

C. Simulation of nozzle in shooting of oil Flow of sprayed oil, which is passing through the oil in the tank, is calculated using MATLAB environment; these are illustrated in figures 7 and 8. It is shown that oil pressure form nozzle to the HST point will decrease, but it has not created too much disturbance, therefore the produced turbulence is negligible. In figures 7 and 8, the colours red, yellow, light blue and dark blue shown a flow rate from high to low ranges. A load of computations shows that the contribution of variation of Re and Nu numbers are very limited, therefore for sake of complicity the laminar flow has been chosen. Heat transfer coefficient has been constant in 150 in last sections, now for effect of heat transfer coefficient (HTC) on heat dissipation and removing, a simplified approach is used: (21) h (G ) = C .G n Coefficients C and n depend on the geometry and are evaluated from measured HTC using a least square method. The values of the coefficients in equation (21) are calculated to C and n that are shown in table 2. The experiments were made on an ON-cooled disc winding with oil guiding elements and radial cooling ducts. The cross section of the investigated winding is natural convective cooling (ON) and forced directed cooling (OD), and the winding equipped with a number of PT100 sensors in order to measure local temperatures.

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Mousavi Takami: Hot Spot Cooling in Large Scale Electric Power Transformers

130

125

Temprature in oc

125 120

120

115 110

115

105 100 1

110

0.5 radius of core and winding in pu.

0.6

0

0

0.2

0.8

1

0.4 Height of core and winding in pu.

105

Fig. 5. Evaluation of temperature profile with OFAF evaluation of temperature profile with ONAN and oil spraying to %91 of core height 90

temprature in oc

100

80

80

70

60

60

40 50 20 1

40 1 0.5

radius of core and winding in per unit

0.5 0

0

30

per unit of core and winding height

Fig. 6. Temperature profile with OFAF and oil spraying

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flow diameter in verticall direction in decimeter

International Journal of Emerging Electric Power Systems, Vol. 9 [2008], Iss. 2, Art. 3

3 2 1 0 -1 -2 -3 2

10

flow diameter in horizental 0 direction in decimeter -2

5 0

distance between nozzle and winding in decimeter

diameter of oil flow from nozzle center

Fig . 7. Flow pattern that emission from nozzle to HST

2 1 0 -1 -2 2 0

diameter of oil flow -2 from center

1

2

3

4

5

6

7

8

9

distancce from nozzle to core and winding in decimeter

Fig. 8. Flow pattern in slice form by 30-degree rotation form nozzle

Variations of heat transfer coefficients with heat flux density in four different kind of nozzle cross section are shown in figure 9. It is assumed that S0=282mm2 and oil velocity due to pumping and nozzle action is 1 m/s. Nozzle cross section effected on heat flux density, these variation are illustrated in figure 10. It means that with higher cross sections, winding heat removing is

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Mousavi Takami: Hot Spot Cooling in Large Scale Electric Power Transformers

more efficient. In Table II the values of the coefficients C and n, stated in equation (14), for all four oil entrance cross sections are given. 140 S/So=100%

Heat transfer cofficent(w/k.m2)

120

100 S/So=30%

80

60

S/So=20%

40

20

0

S/So=10% 0

50

100

150

200

250

300

350

400

q(w/m2)

temperature diffrerence between oil and winding(Twinding-Toil)

Fig. 9. Heat transfer coefficient versus heat flux density on much cross section of nozzle 45

40

S/So=15%

S/So=40%

35

S/So=70%

30 S/So=100%

25

20

15

10 50

100

150

200

250

300

350

400

heat flux density(w/m2)

Fig. 10. Difference of temperature versus heat flux density in much nozzle cross-section

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International Journal of Emerging Electric Power Systems, Vol. 9 [2008], Iss. 2, Art. 3

(a)

(b)

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Mousavi Takami: Hot Spot Cooling in Large Scale Electric Power Transformers

(c)

(d)

Fig. 11. Temperature rise (b, d) and oil velocity (a, c) profiles with ONAF, (simulation in COMSOL Software)

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International Journal of Emerging Electric Power Systems, Vol. 9 [2008], Iss. 2, Art. 3

4

10

3

BOT,TOT,Viscosty,Density

10

2

10

1

10

0

10

BOTc=100*(BOT-39)/39 TOTc=100*(TOT-43)/43 Viscosityc=100*(Density-735)/735 Viscosityc=100*(Viscosity-0.0001)/0.0001

-1

10

-2

10

0

0.05

0.1

0.15

0.2 0.25 Velocity(m/s)

0.3

0.35

0.4

4

10

3

10

Viscosity&Density

2

10

1

10

0

10

-1

10

Densityc=100*(Density-735)/735 Viscosityc=100*(Viscosity-0.0001)/0.0001

-2

10

40

60

80

100

120 140 160 Temprature(0C)

180

200

220

240

Fig. 12. Viscosity, density, TOT and BOT (bottom oil temperature) versus velocity, resulted in COMSOL software.

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Mousavi Takami: Hot Spot Cooling in Large Scale Electric Power Transformers

V. CONCLUSION The main objective of this study is to find the temperature distribution and hot spot temperature value and location by which it is possible to determine the life of the transformer and to remove or mitigate its side effects by oil spraying system. With increase of ambient temperature or loading level, the temperature will increase, which creates hot spot. In order to solve this problem, considering effect of the magnetic field, authors propose using of oil spraying devices, which can spray the oil to the hot spot locations. Oil spraying system can instantaneously accelerate the cooling rate for removing of hot spot. By changing, the geometric parameters of the spraying apparatus and the physical parameters of the oil one can substantially vary the cooling rate in any temperature range. The other way is installation a number of oil-spraying nozzles in which would be automatically activated when the temperature exceed HST. Further, the nozzles could be adjusted to move at any angle until it can spray oil to hot spot point or area. See figure 1 and 6. Validation has been performed by test, these results shown in table III. In this method, the solution has been convergence with maximum 765 iterations; of course it can be reduced to lower by choosing a best initiation data. The control system can be designed using genetic algorithm, neural networks, fuzzy logic or other capable algorithms, that could be chosen for spraying applications. Worth to mention that all spraying equipment including nozzles will be done located inside tank. NOMENCLATURE R(t) Cp f g h K l p Pa q// t T Tf u,v x, y, z

Time variation of heat generated. Specific heat at constant pressure. Friction factor. Acceleration due to gravity. Heat transfer coefficient. Thermal conductivity . Length. Pressure. Barometric pressure. Heat flux at walls. Time. Temperature. Surrounding temperature. Velocity components. Cartesian coordinates.

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International Journal of Emerging Electric Power Systems, Vol. 9 [2008], Iss. 2, Art. 3

ΔV The potential difference over the distance L The electric polarization Pφ Az The magnetic potential z component Vloop The loop potential Jφe The external current density H Electric field B Density of electric field M Magnetic field Kn A constant for conversion of units GPM Nozzle flow rate (liter/s) GPA Sprayer application rate (litre/mm2), W Width sprayed by each nozzle (mm). D Distance (mm) S Search space in ant colony optimization f Objective function T Pheromone trail parameters Greek Symbols α Relaxation parameter. Relaxation parameter for pressure. αp Δt Time difference. Ε Emissivity. ρ Density. μ Dynamic viscosity. σ Stefan-Boltzmann coefficient . σe Electrical conductivity in electric formulae. σi Surface tension . Subscripts i In the position i. t At the time t. u For the u velocity component. v For the v velocity component . w At the tank wall. x In the x direction. xi In the x direction at the bottom. In the direction x at the top. xt y In the direction y. Superscripts t At the time t.

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Mousavi Takami: Hot Spot Cooling in Large Scale Electric Power Transformers

VI. REFERENCES 1. Kourosh mousavi Takami, A FFT technique for discrimination between faults and magnetizing inrush currents in power transformers, KAHROBA scientific magazine specialized in power electric engineering, 2002, Mazandaran, Iran 2. T. C. B. N. Assunçlo, et. al, Transformer Top-Oil Temperature Modeling and Simulation, transactions on engineering, computing and technology volume 15 October 2006 ISSN 1305-5313 3. Ed G. teNyenhuis, et. al, Calculation of Core Hot-Spot Temperature in Power and Distribution Transformers, IEEE transactions on power delivery, October 2002 T. V, Vol.17, NO. 4,. 4. Oommen, R. A. Ronnau, R. S. Girgis, New mechanism of moderate hydrogen generation in oil-filled transformers, in Proc.CIGRE Conf., Aug.–Sept. 1998, Paris, France, Paper 12-206. 5. Hydrogen generation for some oil-immersed cores of large power transformers, in Proc. DOBLE Conf., Mar.–Apr. 1998. 6. K. Eckholz, et. al, new development in transformer cooling calculations. 7. IEEE Loading Guide for Mineral Oil Immersed Transformer, 1995, C57.91, pp. 18–19, 46–53. 8. FEMLAB V2.3, Electromagnetics Module. Comsol, 2002. 9. A. Elmoudi, M. Lehtonen, Eddy losses calculation in transformer windings using FEM, The 44th International Scientific Conference of Riga Technical University, Riga, Latvia, October 9-11, 2003, Series 4, Vol. 10, pp. 46-51. 10. K. Haymer and R. Belmans, Numerical Modelling and Design of Electric Machines and Devices, WIT-Press, 1999. 11. M. David and Others, Finite Element Method Magnetic FEMM. 12. A. Konard, Inegrodifferential Finite Element Formulation of TwoDimensional Steady-State Skin Effect Problems, IEEE Trans. on Magnetics, vol. MAG-18, no.1, Jan 1982, pp.284-292. 13. J. Weiss and Z. J. Csendes, A One Step Finite Element Method for Multiconductor. 14. Skin Effect Problems, IEEE Trans. on Power Apparatus and Systems, vol. PAS-101, no.10, Oct. 1982, pp.3796-3800. 15. A. Konard, et. Al, New Finite Element Techniques for Skin Effect Problems, IEEE Trans. on Magnetics, vol. MAG-18, no.2, Mar. 1982, pp.450-455. 16. Lates L. V., Electromagnetic calculation of Transformers and Reactors: Moscow ENERGY, 1981 (In Russian), p.313. 17. D. Pavlik, et. al, Calculation and reduction of stray and eddy losses in core form transformers using a highly accurate finite element modelling technique, IEEE Trans Power Delivery, vol. 8, no. 1 Jan. 1993, pp.239-245.

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18. Kourosh Mousavi Takami, Evaluation of oil in over 20 year’s old oil immersed power transformer, Mazandaran University, May 2001. 19. Kourosh Mousavi Takami, Advanced Transformer Monitoring & Diagnostic Systems and thermal assessment with robust software's, research presentation, Water and power University, March 2007, Tehran, Iran 20. Kourosh Mousavi Takami, Hot Spot identification and find a best thermal model for large scale power transformers, April 2006, KTH University, Stockholm, Sweden. 21. M. K. Pradhan and T. S. Ramu, Prediction of Hottest Spot Temperature (HST) in Power and Station Transformers, IEEE Transaction on power delivery,vol.18, NO.4,October2003 22. Kourosh Mousavi Takami, et. al, Thermal and hot spot evaluations on oil immersed power Transformers by FEMLAB and MATLAB software’s, IEEE Conference, Int. Conf. on Thermal, Mechanical and Multiphysics Simulation and Experiments in Micro-Electronics and Micro-Systems, EuroSimE 2007, London, 17 April 2007, pp 529-534. 23. Kourosh Mousavi Takami, Jafar Mahmoudi, Evaluation of Large Power Transformer Losses for green house gas and final cost reductions, 3rd IGEC conference, Sweden, June 18, 2007. 24. Kourosh Mousavi Takami, Jafar Mahmoudi, A novel device (oil spraying system) for local cooling of hot spot and high temperature areas in power transformers, 3rd IGEC conference, Sweden, June 19, 2007. 25. Kourosh Mousavi Takami, Jafar Mahmoudi, Thermal evaluation and energy saving with loss reduction in core and winding of power transformers, 3rd IGEC conference, Sweden, June 19, 2007.

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