The improvements generally relate to the field of ice mitigation systems such as de-icing and anti-icing systems, and more particularly to intelligent control thereof to reduce energy consumption.
Some known ice mitigation systems are switched on or off manually, which requires human intervention. In other cases, when the icing condition status cannot readily be determined by human intervention, ice mitigation systems are left active more than actually required, or even sometimes permanently, which is a cause of energy waste. Energy waste is a concern in itself, and is particularly a concern in situations of limited energy resources, such as where the ice mitigation system is battery powered for instance.
There thus remained room for improvement.
A system or method to automatically determine an icing condition status of an environment such as described below can be used in automating the control of an ice mitigation system, for instance, or for other purposes.
In accordance with one aspect, there is provided a method for determining an icing condition status of an environment, the method comprising: receiving a value of a quantity of heat applied to at least a portion of a structure, said structure having a sensor surface exposed to the environment, receiving a temperature measurement of the sensor surface, receiving a wind speed measurement of the environment, receiving an ambient temperature measurement of the environment, determining a temperature projection of the sensor area using the value of the quantity of heat applied, the wind speed measurement, and the ambient temperature measurement, comparing the temperature projection to the temperature measurement of the sensor surface, and generating a signal indicating the icing condition status based on the comparison.
In accordance with another aspect, there is provided an apparatus for determining an icing condition status of an environment, the sensor comprising: a structure having a sensor surface exposed to the environment, a heater positioned to apply a quantity of heat to at least a portion of the structure, a temperature sensor positioned to obtain a temperature measurement of the sensor surface, a controller to receive a wind speed measurement of the environment and an ambient temperature measurement of the environment, a function to determine a heat transfer projection of the sensor area using at least the wind speed measurement, the ambient temperature measurement, and one of the value of a quantity of heat and a target temperature of the sensor surface and a function to compare the heat transfer projection to an associated heat transfer value.
In accordance with another aspect, there is provided a method for determining an icing condition status of an environment, the method comprising: receiving a value of a quantity of heat applied to at least a portion of a structure, said structure having a sensor surface exposed to the environment, receiving a temperature measurement of the sensor surface, receiving a wind speed measurement of the environment, receiving an ambient temperature measurement of the environment, determining a heat transfer projection of the sensor area using at least the wind speed measurement, the ambient temperature measurement, and one of the value of a quantity of heat and a target temperature of the sensor surface; comparing the heat transfer projection to an associated heat transfer value, and generating a signal indicating the icing condition status based on the comparison.
As demonstrated below, the temperature projection can be computed based on the laws of thermodynamics and other measured or predictable parameters. The temperature projection can be compared with the corresponding measured temperature and the likelihood of icing can then be evaluated. If used as an input of or as part of a controller in an ice mitigation system for an anemometer or a windmill, for instance, this method can reduce significantly the amount of energy needed. Moreover, if icing is likely to occur, different actions can be taken such generating a signal indicative of the likelihood of icing. Such a signal can be recorded by a data recording device such as a data logger, for instance.
When icing is likely to occur, actions can be triggered such as activating an ice mitigation system, activating a bearing heating system, storing data in a data recording device such as a data logger, transmitting the signal to a remote location, etc. Henceforth, information on weather conditions with potential risk of icing can be provided and used as desired.
Many further features and combinations thereof concerning the present improvements will appear to those skilled in the art following a reading of the instant disclosure.
In the figures,
In an embodiment shown in
In this embodiment, the shaft forms a structure to which heat is applied and of which an sensor area is exposed to the environment. In this particular embodiment, the shaft is hollow, having a cylindrical wall, and a coiled electrical wire forming a resistor 1 is provided inside the cylindrical wall, placed in contact with an inner face of the cylindrical wall—the outer face being exposed to the environment. Heat is applied to the cylindrical wall by the Joule effect, when a measurable electrical current is circulated through the resistor. The cylindrical wall can be formed of a high electrical conductivity material, such as a metal for instance, to favour uniformity of the temperature of the cylindrical wall. The quantity of heat applied to the cylindrical wall, or heat transfer rate qmeas, can be determined, by measuring the voltage drop and the current flowing into the resistor and multiplying these two values together, for instance. The heated portion can extend to rotor bearings, for instance, to keep them warm and maintain the predictability of the instrument's calibration curve which is likely to be affected by temperature variations, such as from increased friction which can result from temperature decrease.
The temperature of the sensor surface of the cylindrical wall, which is exposed to the environment can be measured with one or more temperature sensor(s), and will be referred to as Ts_meas. In the embodiment illustrated in
The conditions of the environment will affect the surface temperature Ts_meas of the sensor area. For instance, if the ambient temperature T∞ decreases, while every other parameter remains constant, the surface temperature will decrease as well. In the same way, if the wind speed Umeas increases, the surface temperature Ts_meas will decrease since the convection coefficient will increase and more heat will be removed from the heated surface. If the heat transfer rate q is increased, while all other parameters remain constant, the surface temperature Ts_meas will increase. Given necessary obedience to the laws of physics and given apparatus features, a relationship can be established between the surface temperature Ts_meas, and the outside conditions, namely the measured wind speed Umeas, the ambient temperature T∞ and the measured heat transfer rate qmeas, which can allow to determine a temperature projection of the sensor area. Environment conditions such as precipitation or icing for instance, can cause the measured temperature of the sensor area Ts_meas to differ from the temperature projection. Henceforth, comparing the temperature projection to the measured temperature of the sensor area, which can be done by the controller for instance, can allow to determine an icing condition status. An associated signal can then be generated, such as by the controller for instance. The signal can be in any suitable form such as frequency-based, voltage-based, and/or current-based, for instance.
In one embodiment, the temperature of the sensor area is controlled in order to maintain it constant independently of external conditions. Henceforth, a target temperature can be set.
The theoretical heat transfer rate required a qtheo to keep the surface at a given temperature Ts_meas can be expressed as equation 1.
qtheo=f(T∞,Umeas,Ts_meas) eq. 1
If precipitations are occurring, the heat transfer rate theoretically required qtheo will be lower than the heat transfer rate actually required because water will contribute to extract more heat from the sensor surface. The control of the heat transfer rate can be done by the controller for instance, to ensure that the surface temperature remains constant at a given value by adjusting the heat transfer rate qmeas of the heating element. A difference, which can be referred to as an error, can be obtained by comparing the measured heat transfer rate qmeas to the heat transfer rate theoretically required qtheo to maintain the surface at a given temperature Ts_meas under given meteorological conditions Umeas and T∞. It will be understood by those skilled in the art that this is equivalent to and indirectly involves comparing a temperature projection to the measured temperature of the sensor area, because the actual measured heat transfer rate qmeas is obtained from a measure of the temperature of the sensor area. The reference value (equation 1), the heat transfer rate theoretically required qtheo, is obtained from a previous calibration and stored in the anemometer's controller 5. If the difference is greater than a given threshold, it can indicate that precipitations are occurring. If the ambient temperature T∞ is below the freezing point, it is likely that the precipitations would lead to icing, and a signal indicating icing condition status as a presence of icing or a quantitative indication of a likelihood of icing can then be generated.
The generation of the signal can trigger activation of an icing mitigation system, such as heating of the anemometer rotor and bearings, for instance, to prevent biased wind measurements, as well as any suitable alternate action such as transmitting data, or recording data in a data recording device such as a data logger for instance.
In such an embodiment, the theoretical heat transfer rate can be considered to be a heat transfer projection which is then compared with an associated heat transfer value, the actual measured quantity of heat value, to form a basis for the signal generation.
In another embodiment, the temperature projection Ts_theo can be theoretically modeled using the expression presented in equation 2.
Ts_theo=f(T∞,Umeas,qmeas) eq. 2
In this embodiment, the quantity of heat applied to the sensor area qmeas can be constant for instance, rather than being varied to maintain the temperature of the sensor area constant. If precipitations are occurring, the measured surface temperature Ts_meas will be lower than the temperature projection Ts_theo because water will contribute to extract additional heat from the heated zone. The temperature projection for the measured wind velocity Umeas and ambient temperature T∞ is obtained from a previous calibration and stored in the anemometer's controller 5 for instance. The temperature projection can be directly compared to the measured surface temperature to determine a difference, or error, therebetween. If the difference is greater than a given threshold, it can indicate that precipitations are occurring. If the ambient temperature T∞ is below the freezing point, it is likely that the precipitations would lead to icing, and a signal indicating icing condition status as a presence of icing or a quantitative indication of a likelihood of icing can then be generated.
In such an embodiment, the temperature projection can be considered to be a heat transfer projection which is then compared with an associated heat transfer value, the actual measured temperature of the sensor area, to form a basis for the signal generation.
The total heat transfer rate from the sensor area can be express by equation 3, the usual convective heat transfer equation also known as Newton's law of cooling, where q is the heat transfer rate,
q=
The average convection coefficient can be approximated by a function, for example but not limited to, a second order polynomial equation, such as the one presented in equation 4, where coefficients a, b and c are obtained empirically through calibration. An analytical expression or one obtained through numerical simulations or a look-up table could also be used to describe the average convection coefficient.
In one embodiment, the heat transfer rate theoretically needed qtheo to keep the surface of a heated volume at a given temperature is obtained using equation 5, which is derived from equations 3 and 4. The heat transfer rate theoretically needed qtheo can be calculated according to, but not limited to, equation 5 or an equivalent expression.
qtheo=(a·Umeas2+b·Umeas+c)As(Ts_meas−T∞) eq. 5
The heat transfer rate qmeas is measured at any given time and compared with the heat transfer rate theoretically needed qtheo.
In another embodiment, the temperature projection Ts_theo can be calculated based on equation 6, which is derived from equations 3 and 4, and directly compared to the measured temperature of the sensor area.
In still another embodiment, the surface area of the sensor surface to which the heat is being generated is modified so that the exposed surface area As can be changed. This embodiment requires to obtain a measurement of the surface area of the sensor area As_meas contrary to the embodiments described above where the surface area of the sensor area can be treated as a constant. This can be achieved by changing the surface area of a flexible polymer membrane for instance. The theoretical area needed As_theo is calculated according to the surface temperature Ts_meas, the measured heat transfer rate from the volume qmeas, the measured flow velocity Umeas and the ambient temperature T∞, using equation 7, which is derived from equations 3 and 4. The theoretical needed area As_theo can be calculated according to, but not limited to, equation 7 or an equivalent expression.
The surface area of the heated zones As_meas is measured at any given time and compared with the theoretical area needed As_theo. If the theoretical area As_theo is larger than that of the measured area As_meas, it is a sign of precipitations.
In such an embodiment, the surface area required can be considered to be a heat transfer projection which is then compared with an associated heat transfer value—the actual measured surface area of the sensor area, to form a basis for the signal generation.
In the embodiment shown in
An other alternate embodiment is shown in
A still other alternate embodiment is shown in
It will be understood that ice mitigation systems which can be triggered upon an indication of an icing condition status can be de-icing, anti-icing, can be battery powered, grid powered, can be vibratory, heat based, etc. Ice mitigation systems can be used on wind powered devices such as windmills and anemometers, but can also be used on other structures such as on ocean-based platforms, ships, buildings, etc.
As can be seen therefore, the examples described above and illustrated are intended to be exemplary only. The scope is indicated by the appended claims.
Filing Document | Filing Date | Country | Kind |
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PCT/CA2013/050380 | 5/17/2013 | WO | 00 |
Publishing Document | Publishing Date | Country | Kind |
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WO2013/177695 | 12/5/2013 | WO | A |
Number | Name | Date | Kind |
---|---|---|---|
4342539 | Potter | Aug 1982 | A |
4631959 | Motycka | Dec 1986 | A |
4967056 | Iwasa | Oct 1990 | A |
6237861 | Northrop et al. | May 2001 | B1 |
6452542 | Bachinski | Sep 2002 | B1 |
6612810 | Olsen et al. | Sep 2003 | B1 |
6651515 | Bernard | Nov 2003 | B2 |
6890152 | Thisted | May 2005 | B1 |
7086834 | LeMieux | Aug 2006 | B2 |
7104502 | Otto | Sep 2006 | B2 |
7182575 | Grabau | Feb 2007 | B2 |
7487673 | Ormel et al. | Feb 2009 | B2 |
7637715 | Battisti | Dec 2009 | B2 |
7674036 | Severson | Mar 2010 | B2 |
7708524 | Sundermann et al. | May 2010 | B2 |
7802961 | Grabau | Sep 2010 | B2 |
7880320 | Cook | Feb 2011 | B2 |
7922449 | Scholte-Wassink | Apr 2011 | B2 |
7926763 | Froman | Apr 2011 | B2 |
8038398 | Nanukuttan et al. | Oct 2011 | B2 |
8039980 | Mizoue et al. | Oct 2011 | B2 |
8050887 | Ahmann | Nov 2011 | B2 |
8806934 | Goedel | Aug 2014 | B2 |
20020122001 | Bachinski | Sep 2002 | A1 |
20030005779 | Bernard | Jan 2003 | A1 |
20040041408 | Casazza | Mar 2004 | A1 |
20050218268 | Otto et al. | Oct 2005 | A1 |
20080151963 | Sandnas | Jun 2008 | A1 |
20090110539 | Uphues | Apr 2009 | A1 |
20090142192 | LeClair et al. | Jun 2009 | A1 |
20090154522 | Kulczyk | Jun 2009 | A1 |
20090246019 | Volanthen et al. | Oct 2009 | A1 |
20100004863 | Ladow et al. | Jan 2010 | A1 |
20100034652 | Battisti | Feb 2010 | A1 |
20100119370 | Myhr | May 2010 | A1 |
20100149785 | Dubuc et al. | Jun 2010 | A1 |
20100189560 | Haraguchi | Jul 2010 | A1 |
20100260603 | Dawson et al. | Oct 2010 | A1 |
20100329841 | O'Neil | Dec 2010 | A1 |
20110148112 | Ormel et al. | Jun 2011 | A1 |
20110182732 | Baba | Jul 2011 | A1 |
20110280723 | Libergren | Nov 2011 | A1 |
20110282595 | Severson | Nov 2011 | A1 |
20120285261 | Goedel | Nov 2012 | A1 |
20130163636 | Parsons | Jun 2013 | A1 |
20130341464 | Stothers | Dec 2013 | A1 |
Number | Date | Country |
---|---|---|
1245721 | Nov 1988 | CA |
2535885 | Mar 2005 | CA |
2647682 | Oct 2006 | CA |
102374137 | Jul 2013 | CN |
202006015047 | Dec 2006 | DE |
202006015047 | Dec 2006 | DE |
102003032387 | Jan 2008 | DE |
200970198 | Nov 2010 | DK |
0407641 | Dec 1993 | EP |
1422137 | May 2004 | EP |
2788600 | Jul 2000 | FR |
1049109 | Nov 1963 | GB |
2293522 | Mar 1996 | GB |
Entry |
---|
Bégin-Drolet, André et al., “Commissioning of a new ice-free anemometer: 2011 Field tests at WEICan”, Measurement Institute of Measurement and Control, vol. 45, Issue 8, May 2012, London, pp. 2029-2040. |
Homola et al., “Ice Sensors for Wind Turbines”, Cold Regions Science and Technology, Nov. 2006, vol. 46, Issue 2, Abstract Only. |
Number | Date | Country | |
---|---|---|---|
20150110149 A1 | Apr 2015 | US |
Number | Date | Country | |
---|---|---|---|
61653553 | May 2012 | US |