The present invention is related to a method and system for determining the thermal power line rating (real-time and forecasted) with respect to an overhead electrical power line.
Maximum allowable current rating or ampacity is primarily limited by the need to maintain at least a minimum safety clearance around the sagging suspended/anchored span of electrically conductive cable to prevent arcing. Power line ratings could also be limited by maximum conductor temperature, due to material limitation(s), if reached before the maximum sag.
The maximum allowable constant electrical current rating having to meet the design, security and safety criteria, such as electrical clearance, of a particular power line on which an electrically conductive cable is used is known under the term “ampacity”, as described for instance in “Sag-tension calculation methods for overhead lines”, published in 2007 as CIGRE Technical Brochure No. 324 by Study Committee B2 of the International Council on Large Electric Systems (CIGRE).
Power line rating (i.e. ampacity) can be dynamically estimated using smart sensors. The so-called dynamic line rating is nowadays considered with great interest in everyday operation of power networks all around the world. Forecasted values of ampacity are also used in day-ahead network management as well in several days ahead network market approach, while even very long term approach may be used for planning. Medium- and long-term, i.e. over about four hours, forecasted values are based on forecasted meteorological data whereas real-time and short-time ampacity forecasts are based on real-time and possibly short past analysis of actual conditions acting on the power lines, like time series. Those conditions, including wind speed, wind direction, and ambient temperature for example may be locally measured, computed or inferred from actual observations on or near the field. Most generally, measurements, computations and actual observations may be combined by appropriate stochastic tools to deduce the forecasted power line rating values.
Methods to evaluate the ampacity of a suspended/anchored cable span on the basis of various data are explained for instance in A. Deb, “Power line ampacity system”, published in 2000 by CRC Press, and in technical brochures from international organizations, such as CIGRE Technical Brochures No. 207 (“Thermal behavior of overhead conductors”) and No. 498 (“Guide for application of direct real-time monitoring systems”), respectively published in 2002 and 2012, as well as in abovementioned CIGRE Technical Brochure No. 324. The methods disclosed in these documents use weather data as locally measured or simulated following international recommendations as explained, for example, in CIGRE Technical Brochure No. 299 (“Guide for the selection of weather parameters for bare overhead conductor ratings”), published in 2006 or IEEE Standard 738-2006—IEEE Standard for Calculating the Current-Temperature of bare Overhead Conductors, published in 2007.
The ampacity calculation is also based on the ruling span concept which allows to replace a full multi-span section by one equivalent so-called “ruling span” which is theoretically giving access to all individual span behaviors but many hypotheses lie behind that theory (Kiessling et al, “Overhead power lines”, Springer 2003, page 548).
Thus, all existing models so far usually use the ruling span concept coupled with the state change equation (Kissling et al, ibid., page 546) and thermal equations including meteorological data, conductor data, sagging conditions, etc.
As explained in U.S. Pat. No. 8,184,015, continuous monitoring of electrical power lines, in particular high-voltage overhead lines, is essential to timely detect anomalous conditions which could lead to a power outage. Measurement of the sag of power line spans between successive supports to determine whether the sag is greater than a maximum value has become a mandatory requirement in some countries.
U.S. Pat. No. 8,184,015 discloses a device and method for continuously monitoring the sag on a power line span. This method allows the determination of mechanical dynamic properties of the power lines just by sensing mechanical vibrations in a frequency range from 0 to some tens of Hertz. Indeed, power lines in the field are always subject to movements and vibrations, which may be very small but detectable by their accelerations in both time and frequency domains.
A number of different methods to measure the sag of a suspended/anchored cable span are also known. An example of tentative sag measurement consists in the optical detection of a target clamped on the monitored conductor by a camera fixed to a pylon, as disclosed in U.S. Pat. No. 6,205,867. Other examples of such methods include measurement of the conductor temperature or tension or inclination of conductor in the span. A conductor replica is sometimes attached to the tower to catch an assimilated conductor temperature without Joule effect.
Besides the fact that these methods only allow a partial monitoring of the power line, such methods suffer from other drawbacks: optical techniques are sensitive to reductions of the visibility induced by meteorological conditions while the other measurement methods depend on uncertain models and/or data which may be unavailable and/or uncertain, e.g. wind speeds, topological data, actual conductor characteristics, etc.
U.S. Pat. No. 5,933,355 discloses a software to evaluate ampacity of a power line. It is based on a thermal model and the ruling span concept.
U.S. Pat. No. 6,205,867 discloses a power line sag monitor based on inclination measurement. It is based on a thermal model and the ruling span concept.
International Publication No. WO 2010/054072 is related to real-time power line rating. It alleges the existence of a sensor about wind speed direction and amplitude but does not disclose how these sensors are constituted. It is based on a thermal model and the ruling span concept.
U.S. Patent Appl. Publ. No. 2014/0180616 is related to power line rating and is using conductor temperature sensor to calibrate IEEE theoretical model, based on actual observations of clearance by LIDAR and conductor temperature spot measurements. It relates to these two values by a linear regression. It is based on IEEE model correction and thus needs all data related to IEEE model, including conductor data, meteorological data and sagging data.
The present invention aims at providing a method to evaluate the ampacity of power lines which is not based on a model like existing ones (based on the ruling span concept, state change equation and thermal equilibrium).
The object of the invention is focused on the way to compute power line rating based on some sensor output, the sag for example, and the knowledge of effective wind speed (defined hereinafter) and ambient temperature (real-time or forecast) without any need of details on conductor data nor on power line data, except very few ones, like conductor diameter. As an example, power line rating obtention in relation with maximum sag (and thus clearance limitations) will not need to measure nor to compute conductor temperature.
First, in this disclosure, the effective wind speed is defined as the wind speed value for the considered span which is representative, for conductor mean temperature along the span, of the mean perpendicular wind speed cooling effect along the entire suspended cable span.
Now, the object of the invention is to solely use the outputs from a sensor giving recurrent access of one key parameter, like the sag, of at least one span of a power line section, coupled with (quasi-)simultaneous information about the effective wind speed acting on the same span and the knowledge of the actual load current flowing into the line. These kinds of sensors allow to gather, during a few months—typically three—one key parameter, the sag for example, versus the current flow (in amperes) at a given effective wind speed with a relative short interval of time, typically around a few minutes. Those outputs appropriately treated as discussed in this disclosure, are enough to determine the ampacity of the line forever, without any need of other data. It may be added that a watchdog of the key parameters, mainly one in fact, the so-called tan(α) as discussed in this disclosure, used to determine the ampacity may be installed in order to regularly, every 6 months for example or on request, check any deviation, which would be due to abnormal line data or sagging changes, from initial values.
Accordingly, in at least one illustrative embodiment, this method comprises the steps of monitoring directly or indirectly (i.e. means through other variable like a camera, a GPS position, ultrasonic measurement, etc.) a variable such as sag, tension, position, temperature, etc., of at least one point of said suspended/anchored cable span over a time interval.
The sag may be measured, for instance, using the method disclosed in above-mentioned U.S. Pat. No. 8,184,015, which is incorporated by reference in the present patent application.
The effective wind speed component may be measured for instance, using the method disclosed in above-mentioned International Publication WO 2014/090416, which is incorporated by reference in the present patent application. If the effective wind speed is not an output of the sensor, it has to be deduced by appropriate measurement or deduced from other data or inputs.
In at least one embodiment, if the sag is an output of the sensor, maximum allowable sag for said suspended/anchored cable span must be known or measured. The “sag reserve” is then the subtraction of the actual sag measured on site from that maximum allowed value.
If other variables are measured, such as tension, temperature, position, their maximum or minimum value must be known in connection with minimum allowable clearance on that span/section. Thus “tension reserve”, “temperature reserve” (or maximum temperature) or “position reserve” could be defined or any other variable representing the same effect on clearance.
In the case maximum conductor temperature is the limit (for material degradation limits) before clearance limitation arises, the system used must be able to properly determine the conductor temperature margin available in order to convert such margin into ampacity, as detailed in this disclosure.
Accordingly, the rate of change of the sag (or the other measured variable) versus the square (or an exponent very close to 2) of the current flow is evaluated. Implicitly, such a rate of change integrates all material, mechanical and meteorological acting parameters. As material (conductor data) and mechanical (geometrical sensitivity of sag change into a section of single or multi-span) parameters are quasi-constant (in the order of a few minutes) for a given real-time sag (or other variable depending on the sensor used), only meteorological parameters are influencing the rate of change of the sag. It can be noticed that ambient temperature and solar radiation, while they impact the sag value itself, do not impact significantly the rate of change of the sag with respect to the square of the current.
The power line thermal rating, if limited by clearance problem, is then deduced by the sole knowledge of the “sag reserve”, or other “variable reserve”, like temperature reserve, tension reserve or position reserve, as well as the sag measurement, and its rate of change with respect to the square of the current, as explained in the detailed description of the invention.
The power line thermal rating limited by maximum conductor temperature (due to material degradation) before clearance limitations appear will need one further step, as explained later in the detailed description of the invention. This invention does not need any conductor temperature measurement but may use it if confidently available.
Accordingly, in at least one embodiment, a maximum allowable current rating for said suspended/anchored span of electrically conductive cable is determined according to the above-mentioned method for this purpose, and a current passing through said power line is limited at or below said maximum allowable current rating. If the power line comprises a plurality of successive suspended/anchored cable spans, a maximum allowable current rating may be calculated for each one of these suspended/anchored cable spans, or for a subset of these suspended/anchored cable spans which has previously been identified as critical1, and the current passing through said power line may then be limited at or below the lowest of these maximum allowable current ratings. 1 A critical span in a multi-span section is a span that may reach the maximum allowable sag on that span before other spans. That may be due to specific conditions like lower perpendicular wind speed due to screening effect or orientation, obstacles (like trees for example) that may grow more quickly compared to other situations along the line, etc. There are possibly several critical spans in one section, each of them being critical in different situations of external weather or local consideration.
The present invention also relates to computer programs and memory carriers containing computer-readable instruction sets for implementing these methods.
The above summary of some example embodiments is not intended to describe each disclosed embodiment or every implementation of the invention. In particular, selected features of any illustrative embodiment within this specification may be incorporated into an additional embodiment unless clearly stated to the contrary.
The invention may be more completely understood in consideration of the following detailed description of embodiments in connection with the accompanying drawings, in which:
Unless stated otherwise, all preceding figures and observation points are given for illustrative purpose only and are based on actual measurements or simulations on a 150 kV line, in a multi-span section, all aluminum alloy conductor AAAC 445: diameter=27.45 mm; m=1230 kg/km. Line parameters are the following: ruling span length=342.31 m, span length under supervision=369 m, emissivity=0.9, absorptivity=0.7.
While the invention is amenable to various modifications and alternative forms, specifics thereof have been shown by way of example in the drawings and will be described in detail hereinafter. It should be understood, however, that the intention is not to limit aspects of the invention to the particular embodiments described. On the contrary, the intention is to cover all modifications, equivalents, and alternatives falling within the scope of the invention.
As to the following defined terms, these definitions shall be applied, unless a different definition is given in the claims or elsewhere in this specification.
All numeric values are herein assumed to be preceded by the term “about”, whether or not explicitly indicated. The term “about” generally refers to a range of numbers that one of skill in the art would consider equivalent to the recited value (i.e. having the same function or result). In many instances, the term “about” may be indicative as including numbers that are rounded to the nearest significant number.
Although some suitable dimension ranges and/or values pertaining to various components, features and/or specifications are disclosed, one of skill in the art, incited by the present disclosure, would understand that desired dimensions, ranges and/or values may deviate from those expressly disclosed.
As used in this specification and in the appended claims, the singular forms “a”, “an”, and “the” include plural referents unless the content clearly dictates otherwise. As used in this specification and in the appended claims, the term “or” is generally employed in its sense including “and/or” unless the content clearly dictates otherwise.
The following detailed description should be read with reference to the drawings in which similar elements in different drawings are numbered the same. The detailed description and the drawings, which are not necessarily to scale, depict illustrative embodiments and are not intended to limit the scope of the invention. The illustrative embodiments depicted are intended only as exemplary. Selected features of any illustrative embodiment may be incorporated into an additional embodiment unless clearly stated to the contrary.
The present invention relates to measuring a power line thermal rating with respect to a suspended/anchored cable span. This consists in providing a maximum allowable current rating, also known as “ampacity”, for such a suspended/anchored cable span or for an electric power line comprising such a suspended/anchored cable span.
Each span 2 has a sag S which will increase with the average temperature Tc of the cable, since thermal dilatation increases the length of the cable between successive pylons 3. Increasing sag of a suspended/anchored cable span always decreases the clearance C of the cable with respect to the ground or any aboveground obstacles, such as trees or buildings, as schematically shown on
It is also required to maintain conductor temperature below a critical maximum value to avoid conductor (and accessories) degradation.
There are various methods for measuring this sag S which are available to the skilled person. For example, in abovementioned U.S. Pat. No. 8,184,015 a method was disclosed for measuring this sag S by analyzing motion sensed by the autonomous device 4.
Sag S may be drawn versus time or current or many other variables.
A generic curve is the sag versus the square of the current, or with an exponent thereof very close to 2. Different curves may be obtained depending on the effective wind speed, ambient temperature and sun radiation, as shown on
Sun radiation effect as well as ambient temperature effect are basically a vertical shift (for a given effective wind speed), with a typical error less than 5% on ampacity calculated for a maximum sag corresponding to 75° C. if sag vs. I2 is considered, as shown on
The apparent linear relationship between the sag and the square of the current is not valid stricto sensu. In fact the resistivity of the conductor is slightly increasing with increased current flow, as this is changing conductor temperature. Radiated heat loss also increases with increasing current flow, as this is changing conductor temperature. Another effect is that geometrical stiffness of sag change with sag itself. Last but not least, expansion of conductor with temperature is not fully linear, especially for HTLS3 and ACSR4 conductors and at the “knee-point”5, but there are workarounds in those cases as detailed further in this document. But these effects are very limited, there are compensations as some effects are slightly increasing the sag rate of change while others are slightly decreasing it and all in one, the global effect is extremely limited in terms of ampacity evaluation. 3 HTLS=high temperature low sag conductor4 ACSR=aluminium conductor steel reinforced5 The knee point is related to different dilatation coefficients into some conductors, when they are bi-material (like aluminium-steel in ACSR or aluminium-composite core in HTLS). The sag versus conductor temperature curve is then showing such a knee at a specific conductor temperature, which doesn't evolve significantly over a time span of a few days under normal conditions. Beyond that conductor temperature, the sag rate of change (vs. conductor temperature) is lower.
The method used here is based on actual line behavior instead of being based on models and (sometimes uncertain) data. It is thus valid for any case of multi-span section constitution, including the presence of (very) unequal span length within a line section, (much) unlevelled spans, etc.
Thus, around a given sag (or other variable measured) value, the rate of change of the sag (or other variable measured) w.r.t. the square of the current load flow, depends almost solely on the effective wind speed. Knowing that rate of change of the sag with respect to the current squared allows to calculate the ampacity as described hereinafter.
We first need some months of observations after sensor installation to establish the full cited “rate of change” curve, as different events with different effective wind speeds and different load currents must be observed. A permanent watchdog of these slopes may be settled in order to detect any anomalous change(s) in these data due to abnormal situations (slipping in clamps, broken wires, tower movement, presence of snow, ice, etc.).
An event is defined by a quadruplet:
We will only detail here the case of sag being the “measured variable by the sensor”. The adaptation to any other variable of interest may be easily deduced. For example, the inverse of tension in the conductor or the conductor temperature may be used instead of sag if tension is a direct output from the sensor. The corresponding limits for ampacity (minimum tension or maximum conductor temperature) will then be used later on, instead of sag reserve. Nevertheless some of these outputs, like conductor tension, would need extra data and modeling which may not be the case if sag is an output from the sensor. In particular, the sensor described in U.S. Pat. No. 8,184,015 does not need any external data to calculate the sag.
The method consists of three main successive stages:
Data storage is preferably limited to night observations, as the sun radiation effect is then cancelled, but daytime observations could also be used if sun radiation may be quantified reasonably and all dots corrected to cancel sun radiation effect on sag. The relationship between sag and ambient temperature may be obtained without any conductor nor section data, by catching observation points (sag, ambient temperature) as detailed on
More specifically
Linear fit parameters in this case are according to: f=a.x+b, where f is the sag, x the ambient temperature, a=0.053 [m/K] and b=9.98 [m]; a=tan(α1) as discussed in the disclosure. That fit is also an image of the in-the-field observed state change equation (like detailed in Kiessling et al, ibid., chapter 14, page 546-553).
Thus a cubic (or quasi linear) fit on the lower bound actually provides the sought sag-conductor temperature relationship (at least valid on ambient temperature range, the only one used in this invention). This, in turn, gives the correction factor needed to adjust the sag value to an identical pre-set reference ambient temperature. The reference temperature may be chosen e.g. as the median of the ambient temperature (for example 10° C.) dataset to minimize the mean absolute error, and hence the approximation error. This allows to shift from the initial quadruplet cited above to a triplet (adjusted sag, current flow, effective wind speed), thus reducing the size of the data base.
The triplets so obtained are preferably grouped by ranges of effective wind speeds. These ranges are chosen using small interval for low effective wind speeds as ampacity is more sensitive for low wind speed ranges, e.g. 0 to 0.5; 0.5 to 1; 1 to 1.5; 1.5 to 2; 2 to 3; 3 to 5; 5 to 7; etc. (Unit: m/s).
Stage 2
More specifically
The linear fit in this case is: f=a.x+b where f is the adjusted span sag, x the current-squared, and the parameter ‘a’ found is actually the value of tan(α2) [m/A2] sought after for that class of wind speeds.
In
In
Most generally a couple of month's records are enough. In particular, satisfactory values for tan(α2) were obtained on the tested sample period considering three consecutive months featuring events of current exceeding a third of the seasonal rating for 1.5% of the time on average. Only night time samples were considered.
The scattering of data around the linear fit (limited to about +/−10 cm) comprises transients and measurement errors in addition to the class width itself. All these linear fits cross the ordinates axis near the same value which is obviously the unloaded sag at the chosen reference ambient temperature, with no incident radiation from sun.
The angular coefficient of the straight line fit is the rate of change of the sag (vs the square of the current flow), for a wind speed value taken as the middle of the effective wind speed class range. The lower the wind speed the higher the rate of change.
Such rate of change versus effective wind speed may be stored in a database until enough dots are available to generate a curve fit of the rate of change versus the effective wind speed (as shown on
The rate of change, as shown on
We validate the concept here below by adding some theoretical considerations.
A typical rate of change, given by tan(α), versus the effective wind speed is drawn on
The measured tan(α) curve versus the effective wind speed is then deduced by least square fit. IEEE analysis based on long term empirical observations has in fact fixed the exponent of the wind speed (in the wind cooling effect term) to 0.52 for “low wind speeds” (IEEE Standard 738-2006—IEEE Standard for Calculating the Current-Temperature of Bare Overhead Conductors. IEEE Power Engineering Society. 2006, page 8, equation 3a), and 0.6 at “high wind speeds”.
The non-linear fit of the curve may be done using that exponent following equation (1) with c=0.52. The fit may also be evaluated with “c” as an unknown but in a range of value close to 0.52 (range typically close to 0.4 to 0.7):
where a and b are positive coefficients, “a” typically ranging from 10−6 to 5×10−6; “b” typically ranging from 0.10 to about 0.17. Other ranges may easily be found if v is expressed in other units than in m/s.
Those points are the tan(α2) values obtained in stage 2 for each class of effective wind speeds. The parameters found here are the following: a=2.349×10−6 and b=0.159, and c=0.52 (c has been set beforehand).
Stage 3
Ampacity can then be easily calculated from any real-time measurement: let us consider one measurement featuring a couple (sag, current) for a known effective wind speed. As represented on
A right-angled triangle can then be drawn as shown in
In more detail
This is valid for any sun radiation, any ambient temperature (with no need to know their values) as the rate of change of the sag is almost not depending on these values.
Using actual sag reserve (DF), actual current flow (I) in the line and, for the actual effective wind speed, tan(α), the actual ampacity of the line is:
of course using a consistent system of units, for example with current and ampacity in amperes, sag and sag reserve in meters. tan(α2) may be replaced by α2 as α is very small (order of amplitude 10−6 m/A2).
Incidentally, the maximum error on ampacity determination can be easily deduced from the formula (2) where variables are considered independent (we neglect the error on the current flow and replace tan(α) by α):
ΔA/A=½(Δα/α+relative error on sag) (3)
Where the relative error on α term may be expressed versus effective wind speed using formula (1):
As an example, if we may get an error on sag due to the sensor sensitivity at about 2%, then an error of 5% on ampacity would be linked to a 8% error on the rate of change α (using formula 3) or an admissible relative error on wind speed near 1 m/s of about 18% (using formula 4).
Special Case
Consider the case where ampacity is determined first by maximum conductor temperature instead of maximum sag, in particular for High Temperature Low Sag (HTLS) conductors.
Sometimes, as for HTLS conductors, the ampacity is not necessarily coupled with maximum sag anymore (which has nevertheless to be checked as detailed later on) but with maximum allowable conductor temperature, which will need further considerations as detailed below.
The following embodiment is based on available sag values by the sensor. In the case of tension measurement sensor, sag may be deduced from tension and the method detailed below is unchanged. In the case of conductor temperature sensor, the procedure may be simplified as β factor (detailed in the procedure below) is obtained straightforward and some steps of the procedure may be skipped.
In this case, two other conductor data are needed: the conductor AC ohmic resistance per unit length R0 at a given reference temperature T0, and k, the temperature coefficient of electrical resistance.
The rate of change λ.β (defined on
Conductor temperature rate of change=λ.β+2.λ.β2.k.I2 (5)
λ.β being the initial value of the rate of change in the linear part (β is evaluated as detailed later and is dependent of the effective wind speed), where “k” is the temperature coefficient of electrical resistance (typically 0.0036 to 0.004/° C. for aluminum wires), λ is a correction factor linked to the reference temperature T0 (very often 20° C.) for AC ohmic conductor resistance (given by formula 7).
In other words, conductor temperature versus the square of the current may be written as follows:
Tc−Tc0=Δ.β.I2+λ.Δ2.k.(I2)2 (6)
Tc0 being the initial conductor temperature at no electrical load.
λ=(1+k(Tc0−T0)) (7)
The approximations (5) and (6) are valid until about 150° C. (
Dotted curves are IEEE-computed. Solid curves are an approximation using α1 and α2. Tc0 is computed by using formula (6) of the disclosure. ACCR conductor (Hawk 477) is with the same line parameters as in the base case. Knee point is defined at 100° C. Maximum allowed conductor temperature is set at 120° C.; Ta=25° C.; Psun=0 W/m2; effective wind speeds equal 0.5, 2, 5 m/s respectively.
Typical conductor temperature increases (over initial value) are shown on
If a conductor replica is used, Tc0 is known without any other needs. If not, following procedure may be applied to catch it.
During night time, the initial conductor temperature at no load (Tc0) is the ambient temperature Ta (if we neglect albedo). During sunny days, a correction must be applied depending on sun radiation and wind speed. If no information is available about actual sun radiation, theoretical value may be used as it will give a conservative value for ampacity based on maximum conductor temperature. The corresponding initial conductor temperature at no load is thus calculated as follows:
Tc0=Ta+(β.αs.Sun.d)/R0 (8)
where “Sun”, given in W/m2, is the sun radiation at the location. If unknown, theoretical maximum value can be calculated using formula detailed in IEEE Standard 738-2006 for calculating the current-temperature of bare overhead conductors, published in 2006, page 9, formulae 8 and 9. If albedo needs to be included, it has to be inserted here; Ta is the ambient temperature (° C.); d is the conductor external diameter (m); αs is the conductor absorptivity (take 0.9 as recommended by CIGRE Technical Brochure No. 299, page 22—“Guide for selection of weather parameters for bare overhead conductor ratings”, published in 2006); R0 is the AC conductor ohmic resistance per unit length (Ω/m) at the frequency of the network (50 or 60 Hz). It is given at a reference temperature T0 (most generally T0=20° C.) and β is the main part of the initial conductor temperature rate of change detailed below. It depends on the effective wind speed.
Conductor temperature rate of change w.r.t. the square of the current (formula 5) is not affected by the knee-point. In fact it is guided by the heating up of the aluminum layer. The initial rate of change λ.β shown on
Using formula (1) for tan(α2), λ can be expressed in an analytical way, only depending on effective wind speed, for this procedure.
The starting point of the conductor temperature curve, at zero current flow, is designated Tc0, close to ambient but not identical during sunny days, as detailed here above by formula (8).
Computation of Ampacity Based on Maximum Conductor Temperature
Knowing the maximum available conductor temperature, Tmax, fixed by conductor manufacturer with an acceptable margin, or fixed by the law, or by power line owner, the ampacity linked to that value is then easily obtained, as shown on
with k in ° C.−1, β in ° C./A2, temperatures in ° C., ampacity in amperes.
A redundant security information may be obtained in the case of patent U.S. Pat. No. 8,184,015, with an independent sag alert.
(End of Special Case).
In particular
In particular
The maximum allowable current rating Imax may be calculated for at least each critical suspended/anchored cable span 2 of the power line 1. The lowest value of that set of maximum allowable current ratings Imax for these individual suspended/anchored cable spans 2, points out the most constrained link in the power line 1. That value is therefore the maximum allowable current rating for the entire power line 1, which will be used to limit the electric current supplied through the power line 1.
The long term forecasted ampacity may be calculated with the same method, once the rate of change versus the effective wind speed has been obtained for the power line. In that case, forecasted effective speed is needed over the time period needed. The way to produce such forecasted effective wind speed and other needed meteorological data is not included in this disclosure.
The remote data processing unit 5 may be a conventional programmable computer running a computer program implementing these methods.
This computer program may be in the form of a set of instructions stored in a memory carrier. In the present context, “memory carrier” should be understood as meaning any physical medium capable of containing data readable by a reading device for at least a certain period of time. Examples of such memory carriers are magnetic tapes and discs, optical discs (read-only as well as recordable or re-writable), logical circuit memories, such as read-only memory chips, random-access memory chips and flash memory chips, and even more exotic data storage media, such as chemical, biochemical or mechanical memories.
Although in the illustrated embodiment the data processing unit 5 is remote from the autonomous device 4, it could also be completely or partially integrated into one such autonomous device 4, so that at least some of the computing steps of these methods are carried out within the autonomous device 4 itself.
Those skilled in the art will recognize that the present invention may be manifested in a variety of forms other than the specific embodiments described and contemplated herein. Accordingly, departure in form and detail may be made without departing from the scope of the present invention as described in the appended claims.
Number | Name | Date | Kind |
---|---|---|---|
5933355 | Deb | Aug 1999 | A |
6205867 | Hayes et al. | Mar 2001 | B1 |
8184015 | Lilien et al. | May 2012 | B2 |
8744790 | Lancaster | Jun 2014 | B2 |
9158036 | Liu | Oct 2015 | B2 |
20090138229 | Engelhardt | May 2009 | A1 |
20090243876 | Lilien | Oct 2009 | A1 |
20100114392 | Lancaster | May 2010 | A1 |
20140180616 | Aaserude | Jun 2014 | A1 |
Number | Date | Country |
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WO 2010054072 | May 2010 | WO |
WO 2014090416 | Jun 2014 | WO |
Entry |
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Tapani Seppa et al./CIGRE; Guide for Selection of Weather Parameters for Bare Overhead Conductor Ratings; Brochure No. 299; Aug. 2006; 55 pages. |
R. Stephen et al./CIGRE; Thermal Behaviour of Overhead Conductors; Brochure No. 207; Aug. 2002; 46 pages. |
D. Douglas et al./CIGRE); SAG-Tension Calculation Methods for Overhead Lines; Brochure No. 324; Jun. 2007; 90 pages. |
R. Stephen et al./CIGRE; Guide for Application of Direct Real-Time Monitoring Systems; Brochure No. 498; Jun. 2012; 79 pages. |
Anjan K. Deb; Powerline Ampacity System; published by CRC Press LLC in 2000; Boca Raton, FL; entire publication. |
IEEE Power Engineering Society; IEEE Standard for Calculating the Current-Temperature of Bare Overhead Conductors; IEEE Std 738-2006; 2007; 69 pages. |
F. Kiessling et al.; Overhead Power Lines; published by Springer-Verlag Berlin Heidelberg in 2003; New York; cover, first pages of book, and pp. 546-553. |
Number | Date | Country | |
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20160178681 A1 | Jun 2016 | US |