专利摘要:
The system (40) for dynamically determining maximum electrical power carrying capacitances comprises: means (44) for storing a grid portion model (54), a thermal equilibrium relationship (56), and ), limiting operating temperatures and conduction parameters; and a receiver (46) of wind speed values measured by anemometer stations (24, 26, 28, 30). It further includes a programmed computer (48) (62, 64, 66, 68) for: applying a wind propagation model (60) from at least one selected station to singular points of the network portion model (54) , for the estimation of a value of wind speed at each singular point; and calculating at least one maximum capacity value at each singular point from the thermal equilibrium relationship (56), each operating limit temperature, each conduction parameter, and meteorological parameters (58), taking into account said estimated wind speed value at each singular point in the thermal equilibrium relationship (56).
公开号:FR3047083A1
申请号:FR1650466
申请日:2016-01-21
公开日:2017-07-28
发明作者:Thierry Buhagiar
申请人:RTE Reseau de Transport dElectricite SA;
IPC主号:
专利说明:

The present invention relates to a system for dynamically determining maximum electrical current carrying capacity relative to a portion of a high-voltage electrical power transmission network. It also relates to a corresponding method and an electrical transmission installation comprising such a system.
It relates more specifically to a system comprising: - storage means of a model of the network portion, this model comprising singular points and at least one conductive line of high voltage electrical current between these singular points, a predetermined thermal equilibrium relationship, a limiting operating temperature of each conductive line and conduction parameters of each conductive line, - a computer, having access to the storage means, programmed to calculate at least a maximum capacity value in each singular point of the network portion model from the predetermined thermal equilibrium relationship, each operating limit temperature, each conduction parameter, and meteorological parameters.
The maximum electrical current carrying capacity of a high-voltage line, sometimes called "ampacity", is the permissible limit value of the intensity of the current carried by this line, expressed in amperes. It is generally postulated that this maximum capacity is a constant whose value is dependent on the operating limit temperature, itself constant and calculated on the basis of assumed constant geometric parameters of the high-voltage line, and meteorological parameters. . The relationship between the maximum electrical power carrying capacity and the operating limit temperature is then expressed in a thermal equilibrium relationship providing an intensity value as a function of a temperature value of the conductor of the high voltage line, meteorological parameters and intrinsic data of the driver. For a static calculation of this maximum capacity, the meteorological parameters are chosen a priori as the most unfavorable possible in the environment of the high-voltage line to ensure that the resultant calculated in this way constitutes a truly relevant limit value the risks of exceeding the operating limit temperature. As a result, the calculated maximum capacity is generally largely suboptimal. Moreover, the meteorological parameters being chosen a priori, the actual risks of exceeding the limit temperature of operation, although limited, are generally not controlled.
Today, it is becoming more and more common to use dynamic determinations of maximum power transmission capabilities of high-voltage power lines, replacing at least a portion of the adverse meteorological parameters with more realistic environmental data. locally, from measurements. This is notably the conclusion made by the document entitled "Dynamic line rating Systems for transmission lines: topical report", published by the U.S. Department of Energy in April 2014.
A parameter identified as particularly important, in particular in the document entitled "Guide for thermal rating calculations of overhead lines", published by the study committee "B2-airlines" of the organization Cigré, WG B2.43, in December 2014 , is the speed of the wind, including its direction and its amplitude. Its impact is very sensitive on the convection cooling of the high voltage lines and therefore on the increase of their actual maximum capacity of electricity transmission. Unfortunately, this is a parameter that is generally considered difficult to measure locally and many solutions for dynamic determination of maximum capacity of airlines try to circumvent it.
A first solution, called CAT-1 and marketed by the company "The Valley Group - a Nexans company" plans to deploy various sensors on a portion of high-voltage electrical power transmission network: - mechanical voltage sensors that come under the form of strain gauges, deployed on each high-voltage line of the portion of the network considered to estimate the arrow (of the English "sag"), as defined in US Patent 5,918,288, and - radiation sensors net, deployed on the towers of the portion of the network considered for measuring environmental data including the impact of wind, as defined in US Patent 5,559,430.
This first solution involves the installation of many sensors and singularly complicates the maximum capacity calculations in the portion of network considered.
A second solution, marketed by the company "Ampacimon" also plans to deploy sensors on a portion of high voltage power transmission network. More specifically, these sensors are deployed on each high-voltage line of the considered network portion to measure the arrow by frequency analysis of vibrations, as taught in the patent application WO 2007/031435 A1. Wind sensors, as taught in the patent application WO 2014/090416 A1, can also be arranged on the high voltage lines.
This second solution also involves the installation of many sensors. Moreover, if one wishes to dispense with wind sensors, it complicates the calculations of maximum capacities in the portion of the network considered since they must then be done in two stages: to exploit the relation of thermal equilibrium predetermined on the basis measured deflection hypotheses, measured electrical current and other known parameters for deriving an indirect estimate of the wind speed on each conductive line of the network portion; and then again exploiting the same predetermined thermal equilibrium relationship based on the indirectly estimated wind speed and other known parameters to derive the maximum capacity of each conductive line of the network portion. The article by Schell et al, titled "Quantifying the limits of weather based dynamic line rating methods" and published on the occasion of Cigré Canada, Conference on Power Systems, Halifax, September 2011, lays out the basis for this calculation in two time that proves complex.
It may thus be desirable to provide a system for dynamically determining maximum electrical current carrying capacity which makes it possible to overcome at least some of the aforementioned problems and constraints.
It is therefore proposed a system for dynamically determining maximum electrical current carrying capacity relative to a portion of a high voltage electrical power transmission network, comprising: means for storing a model of the portion of the network; model comprising singular points and at least one conductive line of high voltage electrical current between these singular points, a predetermined thermal equilibrium relation, a limit temperature of operation of each conductive line and conduction parameters of each conductive line, - a computer, having access to the storage means, programmed to calculate at least one maximum capacity value at each singular point of the network portion model from the predetermined thermal equilibrium relationship, of each limit temperature of operation, of each parameter of conduction and meteorological parameters ues, further comprising means for receiving, by the computer, wind speed values measured by a set of airspeed stations deployed around the network portion, the computer being then programmed to: - select at least one airspeed station in the set of airspeed stations, - apply a wind propagation model from the said at least one selected station to the singular points of the network portion model, for the estimation of a wind speed value at each singular point at from the received wind speed values, and - calculating said at least one maximum capacity at each singular point taking into account said estimated wind speed value at each singular point in the predetermined thermal equilibrium relationship.
Thus, thanks to such a system, a direct estimate of the wind speed at several sensitive points of the considered portion of the network is proposed by the clever application of a propagation model that can be done on the basis of a limited number of anemometric sensors. This estimate is then judiciously exploited in the predetermined thermal equilibrium relation to optimize the calculation of the maximum capacities of the network portion. Many wind propagation models are known to those skilled in the art and may be employed. From the simplest to the most sophisticated according to the desired performance, they all present surprising results for the calculation of the maximum electric power transport capacity in at least each singular point of a considered portion of the network. This can be better estimated, on the rise, for a cost in sensors that can be limited.
Optionally, the computer is more precisely programmed to: - determine a main direction of wind from the values of wind speeds received, and - select the airspeed station, said station downwind, located furthest upstream in the direction main wind determined.
Also optionally: the predetermined thermal equilibrium relation is a mathematical equation balancing at least mathematical expressions of Joule and solar energy gains with mathematical expressions of convective losses and electromagnetic radiation, and the calculator is programmed to take into account said estimated wind speed value at each singular point in the mathematical expression of convective loss.
Optionally also, the computer is further programmed to calculate a temperature value in at least one point of the network portion model for which a wind speed value has been estimated, from the predetermined thermal equilibrium relationship. a quantity of electric current carried by the conductive line comprising this point of the grating portion model, conduction parameters of this conductive line and meteorological parameters, taking into account said value of estimated wind speed in the relation predetermined thermal equilibrium.
Optionally also, the computer is programmed to trigger the calculation of said at least one maximum capacity at each singular point provided that predetermined criteria of minimum value of wind speed and coherence, among them, values of wind speeds received are verified.
Also optionally: the predetermined criterion of minimum wind speed value is defined as follows: the wind speed value supplied by the downwind station must be greater in amplitude at a first threshold and each speed value of wind supplied by an airspeed station other than the leeward station must be greater in amplitude at a second threshold, the second threshold being less than the first threshold, the predetermined criterion of consistency, between them, of the wind speed values received is defined as follows: the wind speed values received being vectorial, the angular difference between the different directions of these vector values must remain lower than a third threshold and the difference in amplitude between the different norms of these vector values must remain below a fourth threshold.
It is also proposed to provide an electrical transmission system with dynamic determination of maximum electric power carrying capacity, comprising: a portion of a high-voltage electrical power transmission network comprising local electrical substations and at least one transmission or transmission line; distribution of high-voltage electrical current carried by pylons between these local electrical substations, - a set of airspeed stations deployed around the network portion, and - a dynamic determination system of maximum electric power transport capacities according to the invention .
There is also provided a method for dynamically determining maximum electrical current carrying capacity relative to a portion of a high-voltage electrical power transmission network, comprising the following steps: establishing a model of the portion of the network, this a model comprising singular points and at least one conductive line of high voltage electric current between these singular points, - calculating at least one maximum capacity value at each singular point of the network portion model from a relation of predetermined thermal equilibrium, a limit operating temperature of each conductive line, conduction parameters of each conductive line and meteorological parameters, further comprising the following steps: measurements of values of wind speeds by a set of stations anemometer deployed around the network portion, - selectio n of at least one airspeed station in the set of airspeed stations, - application of a wind propagation model from said at least one selected station to the singular points of the network portion model, for the estimation of a wind speed value at each singular point from the wind speed values received, and - calculating said at least one maximum capacity at each singular point taking into account said estimated wind speed value at each singular point in the predetermined thermal equilibrium relationship.
Optionally: - each conductive line is subjected to a default capacity of electric current transport, - the calculation of said at least one maximum capacity at each singular point is triggered provided that predetermined criteria of minimum value of wind speed and of consistency, between them, measured wind speed values are verified, and each default capacity is replaced by the smallest of the maximum capacities calculated at the singular points forming the ends of each respective conducting line, said optimum capacity, if this optimal capacity is higher than the corresponding default capacity and if the predetermined criteria are checked.
Also optionally: the calculation of said at least one maximum capacity at each singular point is triggered at a time T and established by temporal projection using the wind propagation model for a time T + H where H> 0 between the instants T and T + H, the calculation of the said at least one maximum capacity at each singular point is repeated and established by time projection for the instant T + H, and at the instant T + H, the said at least one maximum capacity value retained at each singular point is the smallest of the corresponding maximum capacity values calculated between the instants T and T + H. The invention will be better understood with the aid of the description which follows, given solely by way of example and with reference to the appended drawings, in which: FIG. 1 schematically represents the general structure of a transmission installation; electrical system with dynamic determination of maximum electric power transport capacities, according to one embodiment of the invention; - FIG. 2 illustrates the successive steps of a method of dynamic determination of maximum power transmission capacities implemented by The installation of FIG. 1. The electrical transmission installation illustrated in FIG. 1 comprises a portion 10 of a high-voltage electrical power transmission network comprising local electrical substations, at least one transmission or distribution line. high voltage electrical power between these posts and pylons to support each lin e transmission or distribution between two stations.
In this example, the network portion 10 comprises four local electrical stations 12, 14, 16 and 18, each defined by the International Electrotechnical Commission (IEC), as a "part of an electrical network, situated in the same place, mainly comprising the ends of transmission or distribution lines, electrical equipment, buildings, and possibly transformers ". A local electrical station is therefore an element of the electrical power transmission network serving both transmission and distribution of electricity. It makes it possible to raise the electric tension for its high voltage transmission, and to lower it for consumption by users (private or industrial).
It is possible to establish a model of this network portion 10, consisting of singular points and at least one conductive line of high voltage electrical current between these singular points. Since the local electrical substations 12, 14, 16 and 18 are at the ends of power transmission or distribution lines, they constitute singular points of the network portion 10. Other singular points can also be identified. For example, by imposing that each conductive line between two singular points of the model is homogeneous in terms of operating limit temperature, cross-section of cables and / or rectilinear tracing at +/- 10 °, certain pylons of the network portion 10 can also constitute singular points. There is for example illustrated two in Figure 1. A first pylon forming a singular point 20 is thus disposed on a transmission line or distribution between the local electrical stations 12 and 14 and a second pylon forming a singular point 22 is located on a transmission or distribution line between the local substations 14 and 16.
In the particular nonlimiting example of FIG. 1: the local electrical station 12 is electrically connected to the local electrical substations 14 and 18 by transmission or distribution lines carried by pylons; the local electrical station 14 is electrically connected to the local electrical stations 12, 16 and 18 by transmission lines or distribution lines carried by towers; and the local electrical station 16 is electrically connected to the local electrical substations 14 and 18 by transmission lines or distribution lines carried by towers.
The model of the network portion 10 illustrated in FIG. 1 thus comprises six singular points 12, 14, 16, 18, 20, 22 interconnected by seven homogeneous conducting lines L1 (between the singular points 12 and 20), L2 (FIG. between the singular points 20 and 14), L3 (between the singular points 14 and 18), L4 (between the singular points 14 and 22), L5 (between the singular points 22 and 16), L6 (between the singular points 16 and 18) and L7 (between the singular points 18 and 12). Other conductive lines leaving the network portion 10 each further have an end connected to one of the four local electrical stations 12, 14, 16 and 18. This is of course only a simple example not provided for a good illustration of the invention. The electrical transmission installation illustrated in Figure 1 further comprises a set of airspeed stations 24, 26, 28, 30 deployed around the network portion 10 for measuring wind speed values. Each wind speed value measured by any one of the airspeed stations 24, 26, 28, 30 comprises a direction of the wind and a wind amplitude expressed for example in m / s. It is therefore a vector value. These stations can be arranged independently of the different singular points 12, 14, 16, 18, 20 and 22. They have transmission means, for example by radio waves, values they measure.
Finally, the electrical transmission installation illustrated in FIG. 1 comprises a system 40 for dynamically determining the maximum electrical power transport capacities relative to the network portion 10. It concerns the maximum capacities of each of the conductive lines that are in particular at their ends, that is to say at each singular point, and for each conductive line connected to each singular point, the model of the network portion 10 is applied. This system 40, as represented diagrammatically in FIG. 1, is for example installed in one of the local substations, in this case the station 16. It could also be installed independently of the network portion 10. It is implemented in a computing device such as a conventional computer and includes a processing unit 42 associated in a conventional manner with a memory 44 (for example a RAM memory) for storing years of data and computer programs. The processing unit 42 comprises a receiver 46 of the measured values emitted by the airspeed stations 24, 26, 28, 30 and a computer 48, for example a microprocessor, able to process the values provided by the receiver 46.
The memory 44 is partitioned into a first processing data storage area 50 and a second computer program storage area 52. This partition is purely functional, chosen for a clear presentation of the system 40, but does not necessarily reflect the actual organization of the memory 44.
The first storage area 50 firstly comprises data 54 relating to the model, detailed above, of the network portion 10. These data comprise parameters for identifying and characterizing the singular points 12, 14, 16, 18, 20, 22 and homogeneous conductive lines L1, L2, L3, L4, L5, L6, L7, including, in addition to the topological or geographical considerations, a limiting operating temperature and conduction parameters for each conductive line.
The first storage area 50 further includes data 56 relating to a predetermined thermal equilibrium relationship. This relation is for example a mathematical equation balancing at least mathematical expressions of gains by Joule effect and solar energy with mathematical expressions of convective losses and electromagnetic radiation. This may include a relationship from the steady-state IEEE equation, defined in the IEEE standard for calculating the current-temperature relationship of bare overhead conductors, published by IEEE Power Engineering Society under the reference IEEE Std 738 ™ -2006, January 2007. It may also be a relationship stemming from the steady-state Cigré equation, defined in the document entitled "Thermal behavior of overhead conductors" published by the committee. study "B2-airlines" organization Cigré, WG 22.12, in August 2002, or specified in the document "Guide for thermal rating calculations of overhead lines" previously cited. It takes for example the general form:
Pj + Ps = Pc + PR, where Pj is the heat gain by Joule effect, Ps the heat gain by solar energy, Pc the heat loss by convection and PR the thermal loss by electromagnetic radiation. Reference is made to the documents cited above for examples of detailed expressions of each of these gains or losses.
The first storage area 50 furthermore includes data 58 relating to general meteorological parameters relating to the geographical area in which the network portion 10 is located. These parameters may be chosen a priori as the most unfavorable possible in the environment of the network. network portion 10. They may include zoning, statistical calculations, regular measurements, etc. They include, for example, room temperature and sunshine values which are function of the place and the season. Note that some of the data 58 may alternatively be replaced or updated dynamically by values supplied to the computer 48 via the receiver 46. In particular, outside temperature values at different points of the network portion 10 may be dynamically provided. to the calculator 48 for a better treatment performed by the latter by taking them into account in the predetermined thermal equilibrium relationship 56.
The first storage area 50 finally includes data 60 relating to a wind propagation model. Many more or less sophisticated propagation models are known. For example, it may be a proportional linear projection model in which the propagation speed is arbitrarily equal to the amplitude of the wind speed, whereas the direction of propagation, considered to be plane, is the same. the wind. Such a model, particularly simple, is far from perfect, but it is already likely to provide good results for a dynamic estimate of the maximum capacities mentioned above. It makes it possible to construct a history of the wind speed values for each point of the model 54 of the network portion 10, and in particular for each singular point. Such a history is progressively enriched according to the measurements taken by the air-pressure stations 24, 26, 28, 30.
The second storage area 52 as illustrated in FIG. 1 functionally comprises four computer programs or four functions of the same computer program 62, 64, 66, 68. It will be noted that the computer programs 62, 64, 66, 68 are presented as distinct, but this distinction is purely functional. They could as well be grouped according to all possible combinations into one or more software. Their functions could also be at least partly micro programmed or micro wired in dedicated integrated circuits. Thus, in a variant, the computing device implementing the processing unit 42 and its memory 44 could be replaced by an electronic device composed solely of digital circuits (without a computer program) for carrying out the same actions.
The first computer program 62 includes instruction lines for the execution of a selection of an air-pressure station, called a downwind station, among the stations 24, 26, 28, 30 available, from speed values. wind measured and transmitted to the microprocessor 48 through the receiver 46. A non-limiting example of operation of this first program will be detailed with reference to Figure 2. Alternatively and according to the complexity of the model 60 wind spread retained, such a program could select several airspeed stations from those available.
The second computer program 64 includes instruction lines for applying the wind propagation model 60 from the lee station to the singular points 12, 14, 16, 18, 20, 22 of the serving model 54. network 10, for estimating successive values of wind speeds at each singular point from successive values of wind speeds measured by the lee station. A nonlimiting example of operation of this second program will be detailed with reference to FIG.
The third computer program 66 includes instruction lines for performing the calculation of at least one maximum electrical power carrying capacity value at each singular point 12, 14, 16, 18, 20 and 22 of the model. 54 of network portion 10 from: - the predetermined thermal equilibrium relationship 56, - each operating limit temperature and each network conduction parameter recorded with the model 54 data of the network portion 10, - general meteorological parameters 58, and - any meteorological parameters dynamically supplied to the computer 48, such as measured external temperatures, taking into account, in the predetermined thermal equilibrium relation 56, the estimated wind speed values in all the singular points 12, 14, 16, 18, 20, 22 by executing the second program 64.
More specifically and in accordance with the teaching of the document "Guide for thermal rating calculations of overhead lines" previously cited, the values of wind speeds can be taken into account in the mathematical expression of convection loss Pc of the expression Pj + Ps = Pc + PR.
In the example of FIG. 1, two maximum capacitance values can be calculated at singular point 12, one for the conductive line L1, the other for the conductive line L7. Three maximum capacitance values can be calculated at singular point 14, one for the conductive line L2, another for the conductive line L3, the last for the conductive line L4. Two maximum capacitance values can be calculated at singular point 16, one for the conductive line L5, the other for the conductive line L6. Three maximum capacitance values can be calculated at singular point 18, one for the conductive line L6, another for the conductive line L3, the last for the conductive line L7. Two maximum capacitance values can be calculated at singular point 20, one for the conductive line L1, the other for the conductive line L2. Two maximum capacitance values can be calculated at the singular point 22, one for the conductive line L4, the other for the conductive line L5.
The fourth computer program 68 includes instruction lines for the optional execution of the calculation of a real temperature value at each singular point 12, 14, 16, 18, 20 and 22 of the model 54 of the network portion. From: - the same predetermined thermal equilibrium relationship 56, - a quantity of electric current actually carried by each conductive line and each recorded network conduction parameter with the data of the network portion model 54 - general meteorological parameters 58, and - possible meteorological parameters dynamically supplied to the computer 48, such as measured external temperatures, taking into account, in the predetermined thermal equilibrium relation 56, the values of estimated wind speeds in all the singular points 12, 14, 16, 18, 20, 22 by executing the second program 64.
A method for dynamically determining maximum electrical power carrying capacity in the network portion 10, implemented by executing the computer programs 62, 64, 66, 68 with the aid of the microprocessor 48, will now be detailed in FIG. reference to Figure 2.
During a prior stage 100 for preparing the system 40, the portion of network 10 in which this dynamic determination of maximum capacity is intended to apply is defined by its perimeter, the local electrical substations it contains and the lines transmission or distribution between these stations. The set of airspeed stations deployed around the defined portion of network 10 is furthermore selected.
Advantageously, but without constraint or obligation, such a portion of network 10 has one or more of the following characteristics: its geographical perimeter is not too wide, so that it has homogeneous geographic characteristics in terms of relief (it must remain relatively flat) and obstacles (they must be as few as possible), - it constitutes an "electric pocket": this means that it constitutes an autonomous zone answering homogeneous local electrotechnical rules in terms of supply, transmission and supply of electricity, - it is powered by a significant wind farm generating demands for transport capacity which increase with the strength of the wind: it is then all the interest of the invention to be able to dynamically estimate upward the maximum transport capacity of the network portion 10 as a function of the wind speed.
During a subsequent modeling step 102 of the previously defined network portion 10, the model 54 of this network portion 10 is established and stored in memory 44 from a map of local electrical substations and transmission lines. or distribution it contains. This step 102 can be executed automatically using a computer program (not shown) specifically implemented in the system 40. It is mainly to determine the singular points of the model 54: these include all local electrical substations and some pylons at the ends of homogeneous sections of high-voltage lines in terms of straight lines (eg +/- 10% angular deviation), cable cross-sections and temperature limits Operating. For example, the model 54 illustrated in FIG. 1 is obtained by the singular points 12, 14, 16, 18, 20, 22 and the homogeneous conductive lines L1, L2, L3, L4, L5, L6, L7.
During a parameterization step 104, which can take place before, during or after the steps 100 and 102, at least a minimum wind speed value Vmin, an AVmax value of maximum variation of wind speeds between airspeed stations and a value A0max of maximum angular variation of wind directions between airspeed stations are predetermined. The value Vmin makes it possible to define a minimum wind speed value below which it is not considered useful to execute the computer programs 66 and 68, or even the computer program 64, thus imposing a first predetermined criterion. conditioning the triggering of the calculation of the maximum capacities of electric current transport in each singular point. The values AVmax and A0max make it possible to define maximum values of variations of the measurements between airspeed stations beyond which it is not considered useful to execute the computer programs 66 and 68, or even the computer program 64, imposing thus a second predetermined criterion of coherence of these measurements between them conditioning the triggering of the calculation of the maximum capacities of electrical current transport at each singular point. These criteria make it possible to make the most of the process of FIG. 2, knowing that it provides effective results when the wind speed measurements provided by the different airspeed stations are coherent with one another and when the wind measured exceeds a certain value to be determined. specifically according to each context in which the invention is implemented.
Then, during a measurement step 106, each airspeed station 24, 26, 28, 30 locally measures a succession of wind speed values. Each measured value is vector and transmitted to the receiver 46 of the system 40.
In a step 108, the microprocessor 48 of the system 40 triggers the execution of the first computer program 62. In this step, it determines a main direction of wind from the last values of wind speeds received. This can be done in a manner known per se by a mean angular calculation of the wind directions measured by the various airspeed stations 24, 26, 28, 30. From this value of the main direction of the wind, the microprocessor 48 determines the station leeward anemometer, that is to say, among the stations 24, 26, 28, 30, which is located the most upstream in the main direction of wind determined. Step 108 is followed by a test 110 during which the criteria for triggering the calculation of the maximum power carrying capacity at each singular point of the network portion 10 are verified. The first criterion, relating to the value Vmin, is divided for example into two criteria relating to thresholds Vmin [1] and Vmin [2] according to which the wind speed value supplied by the leeward station must be greater in amplitude. to Vmin [1] and each wind speed value provided by an airspeed station other than the downwind station must be greater in amplitude than Vmin [2], with Vmin [2] <Vmin [1]. For example, Vmin [1] = 5 m / s and Vmin [2] = 2 m / s can be chosen. The second criterion, of coherence, imposes that the angular difference between the different directions of the measured vector values remains lower than A0max and the difference in amplitude between the different standards of the measured vector values remains lower AVmax. For example, a difference of 10% around average values may be tolerated.
When these criteria are verified, the method proceeds to a next step 112. Otherwise, it returns to step 106 for a new series of measurements.
During the step 112, a time initialization is triggered by the microprocessor 48. It is established a first instant T from which it is decided to start the dynamic calculation of the maximum capacities by time projection using the model 60 of wind propagation for a second instant T + H, where H> 0, from which these calculated maximum capacities can, if necessary, be applied to the network portion 10. Considering Dmax the maximum distance between the leeward station and the singular point farthest from the network portion 10, and in view of Vmin [1] which is the minimum speed measured at the output of step 110, so that one is sure of being able to estimate the wind speed at each singular point of the grating portion 10 by time projection at time T + H, it is preferable to ensure that H> Dmax / Vmin [1]. Thus, H = 90 min is sufficient for a maximum distance of 27 km.
In addition, during this same step 112, a time index t incrementable in steps of At between T and T + H is initialized at t = T. For H = 90 mn, one can for example choose At = 6 mn.
In addition, each conductive line being subjected to a default capacity of electrical current transport for example determined according to the known techniques of the prior art, it can be associated with a default operational capacity at each of the singular points of the network portion. 10 for each of the conductive lines to which it is connected.
Finally, for each singular point and each conductive line to which it is connected, a maximum capacity value C is initialized at infinity (+ "). Step 112 is followed by a loop of steps 114, 116, 118, 120, 122, 124, 126, 128, 130 which is executed for at least each of the singular points of the model 54 of the network portion 10 and for each of the conductive lines to which it is connected.
Thus, for a singular point considered and for a considered conductive line to which it is connected, during the step 114, carried out by executing the second computer program 64, the wind propagation model is applied to at least one value Wind speed measured by leeward wind station during a period ending at time t for time projection, if possible considering measured velocities and distance from lee station and the singular point considered, a wind speed value at the singular point considered at time T + H.
Then, during a test step 116, the first triggering criterion for calculating the maximum electrical current carrying capacity at the singular point in question and for the conducting line considered can again be verified on the basis of the value of wind speed determined in step 114. For example, it must be greater in amplitude at Vmin [1].
If this is not the case, the method proceeds to a next step 118 during which the maximum capacity at the singular point considered at time t is set to its operational value by default. Then it goes to a step 120 of incrementing t to t + At before returning to step 114.
If the value of wind speed determined in step 114 satisfies the criterion of step 116, the method proceeds to a step 122 of dynamically calculating the maximum electrical current carrying capacity at the singular point considered for the conducting line considered. by executing the third computer program 66 taking into account the wind speed value determined in step 114 in the predetermined thermal equilibrium relation 56 and also taking into account the properties of the conductive line under consideration. It can then be deduced a maximum capacity value calculated at time t for the moment T + H.
Then the process eventually passes to an optional step 124 of dynamic calculation of a real temperature value at the singular point considered for the conductive line considered by execution of the fourth computer program 68 taking into account the same parameters as in step previous and the amount of electric current actually transported. This optional step can, for example, be used to validate the relevance of the dynamic calculation of the maximum capacities by comparing the estimated actual temperature values with actual temperature measurements taken by sensors. In a more general manner, this calculation step can be carried out at any point of the network portion 10 provided with a temperature sensor or any other means of evaluating a cable temperature (directly or indirectly). indirectly by measuring the deflection, the mechanical tension or the vibratory frequency of the cable, for example).
During a next test step 126, the maximum capacity dynamically calculated in step 122 is compared with the default operational capacity of the singular point considered for the conductive line under consideration. If the dynamically calculated value is less than or equal to the default operational capacity, the latter is selected as the value calculated in step 122, then the process returns to step 120 as long as the time index t is less than T + H.
If the dynamically calculated value is greater than the default operational capacity or if the time T + H has been reached in step 126, the process proceeds to a next step 128. In this step 128, the maximum capacity calculated dynamically in step 122 is compared with the value C. If it is greater, C remains unchanged, otherwise C is replaced by this maximum capacity calculated at time t for the moment T + H in step 122.
Then, a test step 130 is performed on the time index t. If the latter is less than T + H, the process returns to step 120.
Otherwise, it goes to a final step 132 during which the last value of C is retained as the maximum electrical transport capacity at time T + H at the singular point considered for the conductive line considered. This is, taking into account step 128, the smallest dynamically calculated maximum capacity value that has passed the test of step 126. Moreover, once the loop of steps 114 to 130 has been executed for minus each of the singular points of the model 54 of the network portion 10, the maximum capacities calculated may possibly be revised downwards as follows: for each conductive line, the maximum capacities dynamically calculated for the moment T + H at its two ends are compared and it is the minor value which is finally retained at the two singular points concerned for the conducting line considered. Thus, each default capacity is replaced by the smallest of the maximum capacities calculated at the singular points forming the ends of each respective conductive line, said optimum capacity, if this optimal capacity is higher than the corresponding default capacity and if the predetermined criteria previously indicated are checked.
It then belongs to an operator of the network portion 10 to apply all or part of the optimal capacity values from the time t + H so as to respond to requests from electricity suppliers or consumers.
Following step 132, the process returns to step 106 for a new series of measurements.
It is clear that a system for dynamically determining maximum electric current carrying capacities such as that described above makes it possible to simply and cleverly take wind speed measurements into account in order to obtain a more favorable estimate of these maximum capacities. Since the cooling effect of the wind is accompanied by a growing electricity generation capacity when the portion of the network concerned is connected to a wind farm, it is in this context that the invention presents its best results. .
Note also that the invention is not limited to the embodiment described above.
In particular, the topology of the portion of the network considered may be quite arbitrary, that of Figure 1 having been chosen for illustrative purposes only for its simplicity.
Furthermore, the airspeed stations 24, 26, 28, 30 have been illustrated as arranged independently of the network portion 10, but they could also be installed in at least a portion of the local electrical substations, especially those located at the periphery of the portion. network (which is the case of the four positions illustrated in Figure 1).
Moreover, also, the linear projection wind propagation model 60 taken as an advantageous example could be replaced by any other known model, the adaptation of the invention to a known propagation model other than that presented above being within the range of the skilled person.
Furthermore, the method detailed with reference to FIG. 2 may be declined according to a large number of variants that it is impossible to list exhaustively, only the following general steps necessarily having to be implemented: - establishment of a model of the network portion, this model consisting of singular points and at least one high-voltage electrical current conducting line between these singular points, measurements of values of wind speeds by a set of airspeed stations deployed around the network portion, - selecting at least one airspeed station in the set of airspeed stations, - applying a wind propagation model from said at least one selected station to the singular points of the network portion model, for estimating a wind speed value at each singular point from the speed values received, and - calculating at least one maximum capacity value at each singular point of the network portion model from a predetermined thermal equilibrium relationship, a limiting operating temperature of each conductive line , conduction parameters of each conductive line and meteorological parameters, taking into account said estimated wind speed value at each singular point in the predetermined thermal equilibrium relationship.
It will be noted in particular that the maximum capacity calculations can be executed for other points of the network portion model than the singular points, in particular along at least part of the conductive lines.
It will be apparent more generally to those skilled in the art that various modifications may be made to the embodiment described above, in the light of the teaching just disclosed. In the following claims, the terms used are not to be construed as limiting the claims to the embodiment set forth in this description, but must be interpreted to include all the equivalents that the claims are intended to cover by reason of their formulation and whose prediction is within the reach of those skilled in the art by applying his general knowledge to the implementation of the teaching that has just been disclosed to him.
权利要求:
Claims (10)
[1" id="c-fr-0001]
A system (40) for dynamically determining maximum electrical power carrying capacity relative to a portion (10) of a high voltage electrical power transmission network, comprising: means (44) for storing a model (54). ) of the grating portion, this pattern (54) having singular points (12, 14, 16, 18, 20, 22) and at least one conductive line (L1, L2, L3, L4, L5, L6, L7) high voltage electrical current between these singular points, a predetermined thermal equilibrium relation (56), a limit operating temperature of each conductive line and conduction parameters of each conductive line, a calculator (48) , having access to the programmed storage means (44) (62, 64, 66, 68) for calculating at least one maximum capacity value at each singular point (12, 14, 16, 18, 20, 22) of the model ( 54) of the network portion from the predetermined thermal equilibrium relationship ( 56), each operating limit temperature, each conduction parameter and meteorological parameters (58), characterized in that it further comprises means (46) for receiving, by the computer (48), values of wind speeds measured by a plurality of airspeed stations deployed around the network portion, and in that the computer (48) is programmed to: select at least one airspeed station from the plurality of airspeed stations, apply a model (60 ) of wind propagation from said at least one selected station to the singular points (12, 14, 16, 18, 20, 22) of the network portion model (54), for estimating a speed value of wind at each singular point from the values of wind speeds received, and calculate said at least one maximum capacity at each singular point taking into account said value of estimated wind speed at each singular point bind in the predetermined thermal equilibrium relationship (56).
[2" id="c-fr-0002]
A system (40) for dynamically determining maximum power carrying capacity according to claim 1, wherein the calculator (48) is more precisely programmed (62) to: determine a main direction of wind from the velocity values of wind received, and select the airspeed station, said station downwind, located furthest upstream in the main direction of wind determined.
[3" id="c-fr-0003]
A system (40) for dynamically determining maximum power carrying capacity according to claim 1 or 2, wherein: the predetermined thermal equilibrium relationship (56) is a mathematical equation balancing at least mathematical expressions of gains by Joule effect and solar energy with mathematical expressions of convective losses and electromagnetic radiation, and the calculator (48) is programmed (66, 68) to take into account said estimated wind speed value at each singular point in the mathematical expression of convective loss.
[4" id="c-fr-0004]
4. System (40) for dynamically determining maximum electric current carrying capacities according to any one of claims 1 to 3, wherein the computer (48) is further programmed (68) to calculate a temperature value in at minus one point of the network portion model (54) for which a wind speed value has been estimated, from the predetermined thermal equilibrium relationship (56), of a quantity of electric current carried by the conductive line comprising this point of the grating pattern (54), the conduction parameters of this conductive line and the meteorological parameters (58), taking into account said estimated wind speed value in the predetermined thermal equilibrium relationship (56). ).
[5" id="c-fr-0005]
A system (40) for dynamically determining maximum power carrying capacity according to any one of claims 1 to 4, wherein the calculator (48) is programmed to trigger the calculation of said at least one maximum capacity in each singular point provided that predetermined criteria of minimum value of wind speed and coherence, among them, values of wind speeds received are verified.
[6" id="c-fr-0006]
The system (40) for dynamically determining maximum electrical power carrying capacities according to claim 5, wherein: the predetermined criterion of minimum value of wind speed is defined as follows: the value of wind speed supplied by the leeward station must be greater in amplitude than a first threshold and each wind speed value provided by an airspeed station other than the leeward station must be greater in amplitude at a second threshold, the second threshold being lower than the first threshold; threshold, the predetermined criterion of coherence, between them, values of wind speeds received is defined as follows: the values of wind speeds received being vector, the angular difference between the different directions of these vector values must remain lower at a third threshold and the difference in amplitude between the different standards of these vector values must lower than a fourth threshold.
[7" id="c-fr-0007]
Electrical transmission installation with dynamic determination of maximum electrical power carrying capacity, comprising: a portion (10) of high voltage electrical power transmission network having local electrical substations (12, 14, 16, 18) and at least one high voltage power transmission or distribution line carried by pylons (20, 22) between these local electrical substations, a set of airspeed stations (24, 26, 28, 30) deployed around the portion of network (10), and a system (40) for dynamically determining maximum power carrying capacities according to any one of claims 1 to 6.
[8" id="c-fr-0008]
A method for dynamically determining maximum electrical current carrying capacity relative to a portion (10) of a high voltage electrical power transmission network, comprising the steps of: establishing (102) a model (54) of the network portion (10), this model (54) having singular points (12, 14, 16, 18, 20, 22) and at least one conductive line (L1, L2, L3, L4, L5, L6, L7) high voltage electrical current between these singular points, - calculation (114, 116, 118, 120, 122, 124, 126, 128, 130, 132) of at least one maximum capacity value at each singular point (12, 14, 16, 18, 20, 22) of the grid portion pattern (54) from a predetermined thermal equilibrium relationship (56), an operating limit temperature of each conductive line (L1 , L2, L3, L4, L5, L6, L7), of conduction parameters of each conductive line (L1, L2, L3, L4, L5, L6, L7) and of metric parameters. orologies (58), characterized in that it further comprises the following steps: measurements (106) of values of wind speeds by a set of airspeed stations (24, 26, 28, 30) deployed around the network portion (10), selecting (108) at least one airspeed station in the set of airspeed stations (24, 26, 28, 30), applying (114) a wind propagation model (60) from said airspeed least one selected station to the singular points (12, 14, 16, 18, 20, 22) of the network portion model (54) (10) for estimating a wind speed value at each singular point from the values of wind speeds received, and - calculation (114, 116, 118, 120, 122, 124, 126, 128, 130, 132) of said at least one maximum capacity at each singular point taking into account said estimated wind speed value at each singular point in the predetermined thermal equilibrium relationship (56).
[9" id="c-fr-0009]
The method of dynamically determining maximum electrical current carrying capacities according to claim 8, wherein: each conductive line (L1, L2, L3, L4, L5, L6, L7) is subjected to a default capacity for transporting power. electric current, - the calculation (114, 116, 118, 120, 122, 124, 126, 128, 130, 132) of said at least one maximum capacity at each singular point is triggered (112) provided that (110) predetermined criteria of minimum value of wind speed and consistency, between them, values of measured wind speeds are verified, and each default capacity is replaced (128, 132) by the smallest of the maximum capacities calculated at the singular points forming the ends of each respective conductive line, said optimum capacity, if this optimum capacity is higher than the corresponding default capacity and if the predetermined criteria are checked.
[10" id="c-fr-0010]
The method for dynamically determining maximum electrical current carrying capacities according to claim 9, wherein: calculating (114, 116, 118, 120, 122, 124, 126, 128, 130, 132) said at least one a maximum capacity at each singular point is triggered (112) at a time T and established by time projection (114) using the wind propagation model (60) for a time T + H where H> 0, - between the instants T and T + H, the calculation (114, 116, 118, 120, 122, 124, 126, 128, 130, 132) of the said at least one maximum capacity at each singular point is repeated and established by time projection for the instant T + H, and at time T + H, said at least one maximum capacity value retained at each singular point is the smallest of the corresponding maximum capacity values calculated between the instants T and T + H.
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同族专利:
公开号 | 公开日
TN2018000236A1|2020-01-16|
EP3406014B8|2020-01-08|
EP3406014A1|2018-11-28|
CN108701994B|2021-07-30|
MA43672B1|2020-01-31|
US20190033350A1|2019-01-31|
US10935580B2|2021-03-02|
MA43672A|2019-11-27|
CA3010670A1|2017-07-27|
AU2017209972A1|2018-08-02|
FR3047083B1|2018-02-09|
CN108701994A|2018-10-23|
AU2017209972B2|2020-07-02|
WO2017125683A1|2017-07-27|
EP3406014B1|2019-11-27|
引用文献:
公开号 | 申请日 | 公开日 | 申请人 | 专利标题
US20140180616A1|2012-12-06|2014-06-26|Mwh|Systems and methods for calculating power transmission line capacity|
US20140163884A1|2012-12-10|2014-06-12|Universite De Liege|Method and system for the determination of wind speeds and incident radiation parameters of overhead power lines|
WO2016102443A1|2014-12-22|2016-06-30|Ampacimon Sa|Method and system for determining the thermal power line rating|CN107732972A|2017-11-14|2018-02-23|广西电网有限责任公司电力科学研究院|A kind of area power grid wind-powered electricity generation receives capability assessment method|
CN108471137A|2018-04-17|2018-08-31|国电南京自动化股份有限公司|Wind speed power probability mapping method in a kind of wind power prediction|US5559430A|1994-07-27|1996-09-24|Seppa; Tapani O.|Net radiation sensor|
US5918288A|1997-03-11|1999-06-29|Seppa; Tapani O|Transmission line load cell protection system|
US8184015B2|2005-09-16|2012-05-22|Université de Liège|Device, system and method for real-time monitoring of overhead power lines|
EP2599182A1|2010-07-29|2013-06-05|Spirae Inc.|Dynamic distributed power grid control system|
US9647454B2|2011-08-31|2017-05-09|Aclara Technologies Llc|Methods and apparatus for determining conditions of power lines|
US9562925B2|2012-02-14|2017-02-07|Tollgrade Communications, Inc.|Power line management system|FR3080199B1|2018-04-13|2020-04-17|Rte Reseau De Transport D'electricite|METHOD AND DEVICE FOR MEASURING AN EFFECTIVE WIND SPEED IN THE VICINITY OF AN OBJECT|
FR3083380B1|2018-07-02|2021-07-09|Association Pour La Rech Et Le Developpement Des Methodes Et Processus Industriels Armines|AIRLINE AMPACITY BASED ON FORECAST|
法律状态:
2017-01-17| PLFP| Fee payment|Year of fee payment: 2 |
2017-07-28| PLSC| Publication of the preliminary search report|Effective date: 20170728 |
2018-01-12| PLFP| Fee payment|Year of fee payment: 3 |
2020-01-23| PLFP| Fee payment|Year of fee payment: 5 |
2021-10-08| ST| Notification of lapse|Effective date: 20210905 |
优先权:
申请号 | 申请日 | 专利标题
FR1650466|2016-01-21|
FR1650466A|FR3047083B1|2016-01-21|2016-01-21|SYSTEM AND METHOD FOR DYNAMICALLY DETERMINING MAXIMUM ELECTRICAL CURRENT TRANSPORT CAPABILITIES|FR1650466A| FR3047083B1|2016-01-21|2016-01-21|SYSTEM AND METHOD FOR DYNAMICALLY DETERMINING MAXIMUM ELECTRICAL CURRENT TRANSPORT CAPABILITIES|
AU2017209972A| AU2017209972B2|2016-01-21|2017-01-19|System and method for dynamically determining maximum electric current carrying capacities|
US16/069,936| US10935580B2|2016-01-21|2017-01-19|System and method for dynamically determining maximum electric current carrying capacities|
EP17706544.8A| EP3406014B8|2016-01-21|2017-01-19|System and method for dynamically determining maximum electric current carrying capacities|
CN201780007423.8A| CN108701994B|2016-01-21|2017-01-19|System and method for dynamically determining maximum capacity for current transmission|
TNP/2018/000236A| TN2018000236A1|2016-01-21|2017-01-19|SYSTEM AND METHOD FOR DYNAMIC DETERMINATION OF MAXIMUM ELECTRIC CURRENT TRANSMISSION CAPACITIES|
PCT/FR2017/050109| WO2017125683A1|2016-01-21|2017-01-19|System and method for dynamically determining maximum electric current carrying capacities|
CA3010670A| CA3010670A1|2016-01-21|2017-01-19|System and method for dynamically determining maximum electric current carrying capacities|
MA43672A| MA43672B1|2016-01-21|2017-01-19|System and method for dynamically determining maximum electric current carrying capacities|
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