WO2019086179A1 - Détermination de géométrie d'enroulement de transformateur - Google Patents

Détermination de géométrie d'enroulement de transformateur Download PDF

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Publication number
WO2019086179A1
WO2019086179A1 PCT/EP2018/076250 EP2018076250W WO2019086179A1 WO 2019086179 A1 WO2019086179 A1 WO 2019086179A1 EP 2018076250 W EP2018076250 W EP 2018076250W WO 2019086179 A1 WO2019086179 A1 WO 2019086179A1
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WO
WIPO (PCT)
Prior art keywords
winding
transformer
geometry
count
determining
Prior art date
Application number
PCT/EP2018/076250
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English (en)
Inventor
Meinhard Paffrath
Yayun Zhou
Harald Ertl
Yiqing Guo
Roland Hofmann
Markus RIEDENBAUER
Original Assignee
Siemens Aktiengesellschaft
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Application filed by Siemens Aktiengesellschaft filed Critical Siemens Aktiengesellschaft
Publication of WO2019086179A1 publication Critical patent/WO2019086179A1/fr

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    • H—ELECTRICITY
    • H01—ELECTRIC ELEMENTS
    • H01F—MAGNETS; INDUCTANCES; TRANSFORMERS; SELECTION OF MATERIALS FOR THEIR MAGNETIC PROPERTIES
    • H01F41/00—Apparatus or processes specially adapted for manufacturing or assembling magnets, inductances or transformers; Apparatus or processes specially adapted for manufacturing materials characterised by their magnetic properties
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F30/00—Computer-aided design [CAD]
    • G06F30/20—Design optimisation, verification or simulation
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F30/00—Computer-aided design [CAD]
    • G06F30/30—Circuit design
    • G06F30/39—Circuit design at the physical level
    • H—ELECTRICITY
    • H01—ELECTRIC ELEMENTS
    • H01F—MAGNETS; INDUCTANCES; TRANSFORMERS; SELECTION OF MATERIALS FOR THEIR MAGNETIC PROPERTIES
    • H01F30/00—Fixed transformers not covered by group H01F19/00
    • H01F30/06—Fixed transformers not covered by group H01F19/00 characterised by the structure

Definitions

  • Transformer Winding Geometry Determination Present invention concerns power transformers. More
  • present invention concerns the determination of a favourable winding geometry for a power transformer.
  • An electric transformer is used for changing the voltage of an alternating electric current (AC) .
  • An input voltage is elevated (step-up) while the corresponding current is reduced or the voltage is lowered (step-down) , causing an increase of current.
  • a transformer typically comprises a primary coil, a secondary coil and a magnetic core, coupling the coils.
  • An alternating input current through the primary coil generates an alternating magnetic field that is conducted by the core to the secondary coil where it induces an alternating output current.
  • a transformer used on a ship, an urban power grid or in mining applications may be considered medium scale and handle power up to several ten MVA (apparent power in Mega volt-ampere) .
  • a large scale transformer may be used for example in a power plant, a steelworks or a high-voltage, direct current (HVDC) electric power transmission system (also called a power super highway or electrical super highway) .
  • An exemplary large scale transformer may conduct a power equivalent of up to 1,300 MVA, be about three storeys high and weigh more than 600 tons. Given the sheer mass and the efforts required for handling such a transformer, even a minute change in one parameter may have a significant impact on safety and costs.
  • Present invention concerns a method and a device for
  • a method for determining a winding geometry for an electrical transformer comprises steps of determining at least one electrical requirement for the transformer; determining at least one physical constraint for transformer dimensions; and determining a winding geometry based on the at least one requirements and at least one constraint.
  • the winding geometry comprises a winding arrangement, a conductor cross section and a count of turns and determination is done following an optimization algorithm with the objective to find a technical solution for given constraints with lowest costs .
  • Geometry determination may be done using an Ant Colony
  • a search space generated by the requirements and constraints may be reduced prior to optimization. By reducing the size of the search space the time required for optimization can be reduced and quality of a found solution may be increased.
  • search space reduction at least one of a strand height, a strand width, a count of axial parallel conductors and a count of radially parallel conductors may be limited in their range. Simple and reliable restrictions may be applied to restrict these variables. The more variables are restricted, the more effectively the search space may be minimized.
  • the winding type may comprise a disc winding wherein at least one of a count of discs and a count of turns per disc is limited in its range.
  • the winding type may comprise a layer winding wherein at least one of a count of layers and a count of turns per layer is limited in its range.
  • Disc type windings and layer windings may be mixed in the same transformer.
  • the conductor may be of the
  • continuously transposed conductors type wherein a count of radially parallel conductors is limited in its range.
  • a method for determining a winding geometry for an electrical transformer comprises steps of: determining a range for a count of layers for each winding of layer type; determining geometry candidates, each candidate having a different combination of a winding height, a winding width and a count of layers for each of the windings; and finding an optimized winding geometry using a method described herein.
  • a device comprises a processing unit, wherein the processing unit is adapted to execute a method disclosed herein.
  • the method may especially be carried out, completely or in part, on a computer system. To this end, the method may be
  • Fig. 1 shows an exemplary transformer
  • Fig. 2 shows an exemplary winding geometry on a core of a transformer
  • Fig. 3 shows a graphic representation 300 of an exemplary strand dimension constraint
  • Fig. 4 shows a system and a method for winding geometry
  • Fig. 5 shows strand layout and dimensions for a flat
  • Fig. 6 shows conductor layout and dimensions for a
  • CTC continuously transposed conductor
  • Fig. 7 shows a block diagram of a method for determining a winding geometry for a transformer
  • Fig. 8 shows a schematic diagram of a method for optimizing a winding geometry.
  • Figure 1 shows a schematic view of an exemplary transformer 100. Depicted are a side view 105, a perspective view 110 and a top view 115.
  • the transformer 100 comprises a core 120 which in the given arrangement possesses an m-shape with three limbs 125 and a yoke 125. In other embodiments the core 105 may also have a different shape.
  • the iron core 105 forms the central element of the
  • transformer 100 and usually comprises metal sheets with thicknesses of ca. 0.35 mm or less.
  • the individual sheets are then preferred to be assembled into the core 105 manually, for example using the "step-lap" technique. This may lead to a good flux distribution at joints, resulting in low losses and reduced no-load noise.
  • the transformer 100 furthermore comprises windings 135 on the limbs 125.
  • a primary winding 135 and a secondary winding 135 are disposed coaxially on the same limb 125, wherein one of the windings 135 lies radially inside the other winding 135.
  • One winding 135 may be of disc type while another winding 135 on the same limb 125 may be of the layer type. More than two windings 135 may be disposed with radial offsets.
  • Figure 1 shows only the items of concern in
  • a real world transformer 100 would typically comprise other elements that are not shown, for example a container for the core 120 and the windings 135, oil to fill the container, an external tank for oil supply, leads and cleats as well as a bushing, measuring equipment or a tap-changer.
  • Accessories may comprise a cooling system which may comprise a fan, a pump or a valve. More common features comprise a foundation, attachment points for lashing and the like.
  • Each winding 135 comprises one or more turns of a conductor 150 having one or several strands 155 and is subject to a continuously high electrical or mechanical load.
  • the windings 135 may be implemented in one of several different
  • the conductor 150 may be wound to a disc wherein several turns of the conductor 150 may be primarily displaced radially. Several such discs may be comprised by one winding 135. Turns of the conductor 150 may lie radially adjacent or be separated by another item like another
  • Discs may lie axially adjacent or be separated similarly .
  • the conductor 150 may be wound such that several of its turns lie primarily displaced in an axial direction so that the turns form a hollow cylinder.
  • Several coaxial hollow cylinders may be comprised by a winding 135.
  • the conductor 150 may have a continuous slope over one turn or extend chiefly in a plane perpendicular to the winding axis and change its axial position only once or a few times per turn.
  • the conductor 150 may comprise one or more strands 155 which are preferred to be nominally of oblong cross section .
  • a flat conductor 150 may comprise one or more strands that follow a fixed arrangement as the conductor 150 is wound around the limb 125 and its winding axis.
  • Several strands 155 that are entwined in a predetermined way to form a conductor 150 are called Continuously Transposed Conductors (CTC) .
  • CTC Continuously Transposed Conductors
  • windings 135 are preferred to be manufactured with high precision, in one piece and from a material with narrow tolerance dimensions.
  • the finished windings 135 may be pressed, dried under constant pressure, impregnated with oil, measured exactly, and geometrically adjusted if required.
  • Figure 2 shows a winding geometry 200 on a core 120 of a transformer 100.
  • the core 120 forms one or more windows 205 of height 210 into which at least one winding 135 may be installed.
  • a windings' 135 height 215 should be smaller than the window height 210.
  • An advantageous winding geometry 200 may make good use of an available space. It is proposed to determine an optimized winding geometry 200 on the basis of available electrical and/or mechanical specifications or constraints. Further constraints may be determined on the basis of cost and manufacturing relevant requirements. The specifications and constraints, as well as possible additional variables, form a search space in which an optimal combination is determined. It is proposed to conduct an automated search with an
  • a winding geometry 200 is sought that optimizes the winding's 135 height 215 into the window height 210.
  • a predetermined yoke distance 220 between the winding 135 and the yoke must be kept . Since the optimization variables contain integer variables, a black-box MINLP (mixed-integer-non-linear-programming) solver is suggested for solving the optimization problem. According to test results, this can lead to automatically generated valid winding geometry within seconds, while a corresponding manual process might take hours even by an experienced design engineer. A generated winding geometry may fulfil given cost and manufacturing requirements and even have a higher quality than a geometry initially proposed by a design engineer. Possible variables include:
  • n Disc n TurriPerDisc (integer)
  • n Layer n Layer , n TurriPerLayer (integer) Possible winding constraints include:
  • n Total ⁇ - Di ⁇ sc il TurnPerDisc
  • Dimensions of the strand 155 may cover certain combinations of width (w) vs. height (h) .
  • Figure 3 shows a graphic
  • a horizontal direction shows a strand width and a vertical direction a strand height.
  • a polygon 305 outlines combinations of height and width of a strand 155 that are considered sensible or feasible.
  • An optimal combination 310 is as yet to be
  • An object of the optimization could then be:
  • the conductor may generally come flat or as CTC.
  • a flat conductor may comprise more than one strand but an
  • a CTC conductor always comprises more than one strand and an arrangement of the strands is varied over the turns of a winding 135. In this, different variation schemes may apply.
  • the following two figures give definitions for characteristically geometric measurements.
  • Figure 4 shows a system 400 for determining a winding
  • the system 400 comprises a data interface 405, a processing system 410 and an optional reference database 415. Using the data interface 405, definitions and constraints for a transformer 100 may be entered or selected.
  • the processing system 410 is adapted to determine a winding geometry 200 for the transformer 100 according to the teachings herein.
  • the reference database 415 is adapted to hold reference data of known transformers 100 and/or winding geometries 200.
  • the processing system 410 may especially comprise a programmable microcomputer or
  • microcontroller that is adapted to execute a computer program product that processes a method that is described herein.
  • Advantages or features of the processing system 410 may apply for the method and vice versa.
  • the processing system 410 is preferred to be adapted to carry out a method 420 for determining the winding geometry 200.
  • the method 420 is also shown in figure 4 in schematic form.
  • the method 420 may come as a computer program product and may be stored on a computer readable medium.
  • definition data for a transformer 100 for which a winding geometry 200 is to be determined may be entered or selected.
  • the processing system 410 may be initialized. Data on a known transformer 100 or a known winding geometry may be retrieved from the database 415.
  • geometry 200 of a transformer 100 is evaluated. An objective function and constraints are
  • a penalty function is calculated to evaluate a winding design 200.
  • a penalty function value is calculated to evaluate the generated winding design.
  • the penalty function value of step 430 will guide the solver 440 in generating a new winding design.
  • These steps are iterated until the generated winding design fulfils all requirements and a minimum of the objective function is reached.
  • An optimized transformer geometry may be output in a step 445. It is preferred that optimization in step 440 is done using a MINLP solver. Such solvers are commercially available and may run on standard computer systems.
  • a MINLP solver is generally adapted to find an optimal solution in a given search space. The search space is determined by a number of design
  • Quality of a solution may be determined using a penalty function that combines the value of an objective function and corresponding constraints. In present case, quality may be indicative of how well a winding geometry fills an available winding space.
  • An MINLP solver generally starts at a solution and tries to improve it in the search space. If the solution cannot be improved any further, it may be output. Several such runs may be required to find a globally optimized solution. Depending on the application, in a MINLP solver it is generally known how far a determined solution is away from a theoretically achievable optimal solution (“gap”) .
  • optimization may terminate (a) if an optimal solution is found, (b) a predetermined search time has been used up or (c) the search space has been
  • the output may comprise one or more geometric designs from which a user may then chose.
  • the method 420 may evaluate thousands proposed designs within a matter of seconds.
  • the method 420 may reduce the design time for a transformer 100 and enable a user to concentrate on his main engineering tasks (electrical design / costs) and not to take care of geometrical details.
  • the method may also explore solutions which are sometimes neglected by design engineers, leading to novel and better transformer designs.
  • present method 420 may also provide to a user the option to work interactively with the system 400: when the processing system 410 delivers a geometry design, the user may change a parameter search area, remove or add a new constraint, and run the optimization method 420 again. The processing system 420 may then determine a new geometry design according to the modification very fast. In this way, the user can continuously improve the design of the
  • the next two figures 5 and 6 show geometric dimensions of a conductor 150 in a winding 135 of a transformer 100.
  • Symbols used in these figures comprise: number of axial parallel strands NAPS
  • Figure 5 shows dimensions of a flat conductor 150.
  • a conductor 150 with generally rectangular cross section may be used.
  • the conductor 150 may comprise two strands 155 that are stacked in a radial direction with respect to a winding axis for windings 135.
  • the conductor 150 may comprise two strands 155 that are stacked in an axial direction with respect to a winding axis for windings 135.
  • a fourth option 520 (QUAD) , four strands 155 are combined in both radial and axial direction.
  • the dimension polygon 305 of a flat conductor is generally drawn based on empiric values.
  • Conductor 150 height, width and cross section can be determined thus:
  • a cable may comprise several isolated conductors 150 running in parallel.
  • a cross section of the cable comprises the cross sections of all its conductors 150.
  • Figure 6 shows exemplary dimensions of a CTC conductor 150 in a first option 605 and a second option 610.
  • the number of axial parallel strands is preferred to be fixed, while the number of radial parallel strands may be an optimization variable.
  • the strand dimension polygon 305 of a CTC conductor 150 is generally drawn based on empiric values. Strand height, width and cross section can be determined thus:
  • a CC A NA PS * N RPS * [D HC * D wc - (D CRC ) 2 * (4 - ⁇ ) ⁇
  • the height of a winding 135 may be calculated differently for layer and disc windings 135. For a layer winding 135 the height may be determined thus:
  • N S (N T + 1) * N APC - 1;
  • Symbols comprise (cf . Fig. 6) : nominal height of the winding D WH width of the winding DRW
  • the height may be determined
  • Symbols comprise: axial height of conductor 150 after pressing D HC
  • an optimized winding geometry 200 may be determined by an optimization method as described above or performing an exhaustive search.
  • a search space may be very large so that processing may take a very long time even on a high performance computer system.
  • Step 0 reduce upper limit for the height of the strand:
  • Step 2 reduce range for number of axially parallel
  • Step 3 reduce upper limit for number of radially parallel conductors (only for CTC)
  • Step 4 reduce range for number of radially parallel
  • Step 0 reduce upper limit for the height of the strand 150
  • Step 1 reduce range for number of axially parallel
  • Step 2 reduce upper limit for number of radially parallel strands (only for CTC)
  • Step 3 reduce range for number of radially parallel
  • the number of radially parallel conductors may be limited to the maximum number of radially parallel conductors.
  • NoRadialParallelStrand > 30 THEN NoRadialParallelConductor ⁇ MaxNoRadialParallelConductor END
  • the optimization process may follow a deterministic or white box approach that guarantees global optimality and quick convergence and requires the given formulation of the
  • Figure 7 shows a block diagram of a method 700 for
  • Short circuit impedance of a transformer 100 determines the regulation (voltage drop across the transformer 100) under load conditions. By ensuring predetermined impedance, a short circuit current and a resulting force on the core 120 or a strand 150 may be limited.
  • the short circuit impedance of a transformer 100 is generally a design goal and may be
  • the short circuit impedance may be expressed in percent of rated impedance, which is equal to a percent value of a short circuit value, or in Watts related to primary or secondary side of the transformer 100.
  • jX depends on geometry, amp-turns, base power and frequency of the transformer 100.
  • Short circuit reactance of a transformer 100 may be
  • a high value of stray reactance in design may result in one or more of the following:
  • the proposed method 700 uses a first block 705 in which a winding geometry 200 for the transformer 100 is determined and a second block 710 in which the transformer 100 itself is designed.
  • the second block 710 may use one or several known approaches to determine transformer characteristics excluding the winding geometry 200.
  • the first block 705 determines the number of layers used on the transformer 100 in a step 715.
  • the count of layers corresponds to how many strands 155 may lie in parallel in a radial direction as part of one conductor 150.
  • the determination is based on a planned target window height 210 (cf . Figure 2) . As the number of layers may be dependent on other parameters, several different window heights 210 may be determined that may be treated as candidates.
  • the second block 710 determines at least some characteristic values of the transformer's 100 geometry on the basis of the candidate window heights 210 and a
  • each dataset has a winding height 215, a winding width and a count of layers.
  • a step 725 the above described optimization process for the winding geometry 200 using mixed integer nonlinear programming is performed once for each of the datasets. As will be shown below, optimization may be done iteratively over the windings 135, effectively reducing the number of required optimization runs. For each winding 135 not only one but several optimizations may be run. Optimization yields one optimized winding geometry which may then be used.
  • the second block 710 may perform a fine concept optimization, that is, other parameters of the transformer 100 may be adapted to the chosen winding geometry 200.
  • Method 700 is special over other methods in that it firstly decouples the problem of determining a transformer 100 design into a winding geometry optimization 705 and a design generation 710, and secondly in the novel approach to reduce the number of optimizations required in step 720.
  • optimization in step 725 may work iteratively.
  • the iterative approach may be further
  • FIG. 8 shows a schematic diagram of a method 800 for winding geometry optimization.
  • Method 800 may be an
  • step 725 of method 700 The method 800 will be explained with reference to sample datasets that may have been provided by step 720. Each dataset is represented as one line in a table 1:
  • Table 1 In a first step 805, table 1 is sorted according to the number of layers in each of the windings 135 in descending direction. After sorting, the winding 135 with the biggest change range of number of layers comes first. In present case, three windings Wl, W2 and W3 are used. However, the second winding W2 will be a disc type so that the
  • the winding 135—145 with the highest change range (here: W3) defines groups where its number (or count) of layers is unique.
  • a first group comprises variants 1, 3 and 5 and a second group comprises variants 2, 4 and 6.
  • number of layers for winding W3 will be 1, 2 or 3.
  • For each group one optimization will be run. If the difference between target heights is small, the second optimization is expected to take much less time than the first one, since the solution achieve of the first
  • optimization is used as the initial achieve of the second optimization.
  • the optimized number of layers for W3 in the first group is 1 (variant 1) and the optimized number of layers in the second group is 2 (variant 4) .
  • the next winding here: Wl
  • optimization is run on variants 1 and 4. The process repeats until all layer type windings 135 are optimized. In present example only four optimization runs are required for
  • step 805 layer winding indices are sorted in descending order according to the change range of variable ("NoLayer" (number of layers) .
  • target value groups are built as described above. For each group, an optimization is run in a step 815. In a step 820 it can be determined if an optimum has been found. Should this not be the case, the target windings of the next optimized winding may be set to -1, effectively excluding this winding from optimization.
  • the variant index of the found optimum may be taken as target values of next optimized winding.
  • another group may be built from the found optima and another
  • optimization may be run on that group.
  • a step 835 it may be determined if the target value groups have all been processed. If this is not the case, method 800 may proceed with step 815. Otherwise, in a step 840 the optimized winding index is deleted from the sorted indices. In a step 845 it may be determined if the sorted indices have reached an end. In this case optimizations for disc type and regulation windings may be performed in a step 850.
  • method 800 may proceed with step 810.
  • the proposed methods 700, 800 may be used to generate a winding geometry 200 design that fulfils a predetermined short-circuit impedance requirement.
  • the methods 700, 800 take all the winding geometry of a transformer system into consideration. Comparing with another method that optimizes the winding geometry separately and checks the impedance later for further adaption, the proposed methods 700, 800 are straightforward and may deliver a global optimum.
  • Present invention optimizes the winding geometries 200 sequentially.
  • Each optimization contains only the design parameters of one winding 135, therefore the dimension of optimization is reduced, making it require less resource and reducing the risk of the optimization getting stuck on a local minimum.
  • optimization for successive runs may be sped up considerably. If a difference between target heights of a winding 135 is small, the second

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Abstract

La présente invention concerne un procédé (420) et un système destinés à déterminer une géométrie (200) d'enroulement (135) pour un transformateur (100) électrique, le transformateur (100) ayant un enroulement (135) comprenant plusieurs spires d'un conducteur (150) et un noyau (120) avec une fenêtre (205) de noyau (120) destinée à recevoir l'enroulement (135). Les étapes d'un procédé (420) destiné à déterminer une géométrie (200) d'enroulement (135) pour ledit transformateur (100) consistent à déterminer au moins une exigence électrique pour le transformateur (100) ; à déterminer au moins une contrainte physique pour les dimensions du transformateur (100) ; et à déterminer une géométrie (200) d'enroulement (135) sur la base de l'exigence ou des exigences et de la contrainte ou des contraintes. Dans cela, la géométrie (200) d'enroulement (135) comprend un agencement d'enroulement (135), une section transversale de conducteur (150) et un nombre de spires et la détermination est faite suivant un algorithme d'optimisation avec l'objectif de minimiser une distance entre une hauteur de l'enroulement (135) et une hauteur de la fenêtre (205) de noyau (120).
PCT/EP2018/076250 2017-10-30 2018-09-27 Détermination de géométrie d'enroulement de transformateur WO2019086179A1 (fr)

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Citations (6)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US20070027883A1 (en) * 2005-07-29 2007-02-01 Cox David N Automated method and tool for documenting a transformer design
CN102708262B (zh) * 2012-06-07 2014-07-23 蒋雪峰 一种综合节能与减噪的电力变压器多目标优化设计方法
US20150302969A1 (en) * 2014-04-22 2015-10-22 Transformers, LLC Transformer with Improved Power Handling Capacity
US20160104567A1 (en) * 2014-10-10 2016-04-14 Cooper Technologies Company Optimized electromagnetic transformer component design and methods including improved conductivity composite conductor material
CN103729554B (zh) * 2013-12-20 2017-03-29 中原工学院 双绕组连续式线圈电力变压器电磁方案二阶段规划方法
US20170176959A1 (en) * 2015-12-22 2017-06-22 Invensys Systems, Inc. Process optimization by grouping mixed integer nonlinear programming constraints

Patent Citations (6)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US20070027883A1 (en) * 2005-07-29 2007-02-01 Cox David N Automated method and tool for documenting a transformer design
CN102708262B (zh) * 2012-06-07 2014-07-23 蒋雪峰 一种综合节能与减噪的电力变压器多目标优化设计方法
CN103729554B (zh) * 2013-12-20 2017-03-29 中原工学院 双绕组连续式线圈电力变压器电磁方案二阶段规划方法
US20150302969A1 (en) * 2014-04-22 2015-10-22 Transformers, LLC Transformer with Improved Power Handling Capacity
US20160104567A1 (en) * 2014-10-10 2016-04-14 Cooper Technologies Company Optimized electromagnetic transformer component design and methods including improved conductivity composite conductor material
US20170176959A1 (en) * 2015-12-22 2017-06-22 Invensys Systems, Inc. Process optimization by grouping mixed integer nonlinear programming constraints

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