PRODUCTION DURING REDUCED NOISE OPERATION

Technical field

The invention relates to a method for controlling a wind park including a plurality of wind turbines, particularly in order to optimise the power production of the wind park during operation under noise restriction requirements. Background to the invention

In order to leverage economies of scale and reduce the cost of electricity generation, wind turbines are typically grouped into wind turbine arrays, also known as wind 'farms', 'parks' or 'power plants'. Modern wind parks may comprise over a hundred individual wind turbines in the same location, albeit extended over an area of many square miles, and providing generation capacity often in the order of hundreds of megawatts (MW).

The process of selecting an appropriate site for a wind park involves many considerations such as local wind characteristics, land topology, accessibility and proximity to local power demand, to name but a few factors. Of these, the proximity of the wind farm to residential areas is a significant issue that affects the planning stages of wind park development. On the one hand, it is desirable to locate a wind park near to where the power is required because this simplifies the power transmission arrangements. However, this goal is in tension with the need to limit the impact of the wind park on populated areas, due to the noise generated by the wind park.

In order to limit the impact of noise on the surrounding area of a wind park, it is known to operate a wind park under a 'reduced noise regime' in which the power output of the wind turbines is curtailed during certain conditions in order to control noise generation. For example, power generation may be cut back during high winds, or during night time hours which reduces the noise impact on nearby residents. As examples of patenting activity in this space, US 6, 688, 841 , B1 describes a method of operating a wind park according to which the rotary speed of selected wind turbines closest to an immission point is reduced if the noise level at the immission point is above a predetermined threshold.

l EP 2 216 549 A2 describes a similar approach in which a wind turbine is operated in a 'noise control mode' if the wind turbine controller receives a signal, which may be driven by time of day, for example, which notifies the controller that the noise control mode is required. Both of these examples, however, reply on simply reducing the power output of wind turbines in order to have a corresponding reduction from the generated noise. This means that there is a reduction in generation efficiency, which may be prolonged in some circumstances which can have a significant downward pressure on the yield of the wind park.

It is against this background, that the invention has been devised, in order to optimise the generation of power during the periods in which the wind park is being operated in a reduced noise regime. Summary of the invention

According to one aspect, the invention provides a method of operating a wind power plant comprising a plurality of wind turbines, the method comprising: identifying operation of the wind power plant in a reduced noise regime; determining that at least one of the wind turbines in the wind power plant is non-operational; and increasing the power output of one or more wind turbines in response to the determination.

The invention extends to and therefore embraces a wind power plant control system for controlling the operation of a plurality of wind turbines, wherein the controller is configured to: identify when the power plant is in a reduced noise regime; determine that at least one of the wind turbines in the wind power plant is non-operational, and increase the power output of one or more of the wind turbines based on the results of the determination.

In other aspect, the invention can be expressed as a computer program product downloadable from a communication network and/or stored on a machine readable medium, comprising program code instructions for implementing a method as defined above, and also as a machine readable medium having stored on such a computer program product.

Beneficially, the invention permits increased power production when it is recognised that one of the other wind turbines in the wind power plant has been stopped, for example due to component failure, accidental disconnection from the grid, or for routine maintenance. This means that one or more of the remaining operational wind turbines are able to take advantage of the extra noise allowance realised by the stopping of the inactive wind turbine in order to reduce their power reserve without exceeding the noise limits imposed on the wind power plant. The increased power production from the affected turbines represents added power production from the power plant as a whole, thereby increasing power generation efficiency.

In one embodiment, the method may include determining power plant noise output data at one or more noise receptor points, and determining, based on the noise output data, the noise contribution made by at least some of the wind turbines. This embodiment represents an 'active' approach whereby a noise model that indicates the noise contribution of each of the wind turbines is generated dynamically based on noise measurements at a receptor point. Alternatively, the noise contribution of each of the wind turbines could be predetermined and stored in a suitable data structure such as a matrix or lookup table. In such a case, a separate data structure/matrix could be stored including the noise mode settings to be used for the wind turbines when on or the wind turbines has become inactive. In this embodiment, therefore, no noise measurements need to be made; it is only required that it is recognised that one of the wind turbines has become inactive.

In one embodiment, the identification of the one or more non-operational wind turbines is performed following the measurement of the wind park noise output.

Further advantageous and/or optional features are defined in the appended claims.

Brief description of the drawings

So that it may be more fully understood, the invention will now be described by way of example only to the following drawings, in which:

Figure 1 is a schematic view of a wind power plant incorporating a controller in accordance with an embodiment of the invention;

Figure 2 is a block diagram of a power plant controller of the power plant in Figure 1 ;

Figure 3 is a flow chart representing a control process implemented by the controller of Figure 2; Figure 4 is a block diagram of a power plant controller in accordance with an alternative embodiment of the invention; and

Figure 5 is a flow chart representing a control process implemented by the controller of Figure 4.

Detailed description of embodiments of the invention

With reference to Fig. 1 , a wind power plant 100 is located near to a residential area 200. It should be noted that Fig. 1 is schematic and as such the relative distance that the residential area 200 is spaced from the power plant 200 is not to scale and so does not reflect a realistic separation. Typically, established practice based on legal regulations governing the planning of wind power plants is to locate such power plants at an appropriate distance, usually in the order of a few hundred metres, from residential areas. However, even at such distances, the impact of the noise generated by the power plant must be considered carefully and actions put into place to ensure that the noise impact is within acceptable limits.

The power plant 100 comprises a plurality of wind turbine generators, which are labelled consecutively from 101 to 110. As such, the embodiment in Fig.1 is shown as including ten wind turbine generators, although it will be appreciated that this is just an example and, as such, a power plant could include one or more turbines, and typically more than ten.

The wind turbine generators (hereinafter, simply 'wind turbines') form part of an industrial control system and, as such, are connected together by a communications network 1 12. The communications network 112 enables each of the wind turbines 101-1 10 to communicate bi- directionally with a power plant controller 120. Such a communications network is conventional in wind power plants featuring modern utility-scale wind turbines so a detailed explanation will not be given here. However, it should be understood that the network 112 enables the wind turbines 101-1 10 to feed operational data to the power plant controller 120, and enables the power plant controller 120 to transmit control commands and other data to each of the wind turbines 101-1 10, either on a basis of general broadcast transmissions (same data for all wind turbines) or directed transmissions (commands/data tailored to specific wind turbines).

In the embodiment of Fig. 1 , the network 1 12 is depicted as lines, which suggests a cable- based infrastructure. Although a cable-based infrastructure is acceptable, it should be noted that this is not to be considered limiting and, as such, the network 120 may be embodied as a wireless system. Typically, communications protocols for such control systems are standardised by equipment vendors, examples of which are governed by IEC 60870-5-101 or 104, IEC 61850 and DNP3. However, alternative protocols such as TCP/IP may also be used.

At this point, it should be mentioned that Fig.1 does not illustrate the power generation network of the power plant 100 for purposes of clarity since such details are not essential to gaining an understanding of the invention, although the presence of such a power generation network, or 'internal grid', is implied.

During operation, the wind turbines generate noise, also referred to as sound pressure level. Broadly, the noise is generated by different sources and includes: blade noise, resulting from the movement of the blades through the air; mechanical noise from rotating and power components such as the generator and converter system; and infrasound.

The noise emitted by the wind turbines emanates in all directions, but is shown here for illustrative purposes by the arrows labelled 'N' which are directed towards a noise receptor 130. The noise receptor 130 is positioned adjacent to the residential area 200 so that it is able to make an accurate measurement of the noise level at the residential area 200.

In order to limit the noise generated by the wind turbines 101-1 10, they are operable in a Noise Reduced Operation (NRO) regime. The NRO regime may be triggered when one or more of a set of predetermined conditions are satisfied. For example, the wind turbines may be commanded into the NRO regime during certain times in a twenty-four hour period in which it is desired to generate less noise. Alternatively, the NRO regime may be entered when the controller 120 detects via the receptor 130 that the noise level is above a predetermined threshold, for example when wind speed exceeds predetermined limit, or when wind direction is aligned in a predetermined direction, or a combination of these non- limiting factors.

Operation of a wind turbine in a NRO regime is a known technique, which may involve derating the wind turbine, in effect operating it in accordance with a more restrictive power curve. Thus, the power output of the wind turbine will be reduced via known approaches, for example by reducing rotor speed or modulating generated power, for example. The NRO regime may include a plurality of NRO mode settings, each offering increasingly restrictive operating regimes in terms of power generation and noise emission. The power plant controller 120 functions to optimise the power production of the power plant 100 to ensure that maximum power production is realised during operation in an NRO regime whilst the generated noise remains below the required level. In a general sense, the controller 120 is operable to increase the power production, and therefore also noise generation, from wind turbines in the power plant, when it has been recognised that one or more of the wind turbines has become inactive or non-operational. In one embodiment, the controller 120 is operable to monitor the total noise generated at the receptor point, to recognise that one or more of the wind turbines is non-operational, or inactive, and to increase the power output of one or more of the remaining operational turbines in order to compensate for the underutilised production margin. In doing so, this approach exploits the individual noise contributions of the non-operational turbines and allocates a noise allowance to one or more of the other wind turbines that are therefore able to increase their power production accordingly. Thus, this approach makes use of the under-utilisation of power production in the power plant that becomes available up by the inactivity of one or more wind turbines. The increase in power production may be performed by gradual uprating of the wind turbine control parameters, or alternatively by switching to less restrictive NRO mode settings. In the above passage, the terms 'non-operational' and 'inactive' are used in the sense that in such conditions the noise contribution of the relevant wind turbine is minimal, so this will include a static wind turbine and also one which is idling, without generating power.

An embodiment illustrating the above approach will now be described with reference to Figures 2 and 3.

Figure 2 illustrates the controller 120 in more detail. It should be appreciated at this point that the functional blocks illustrated in Figure 2 illustrate a specific functionality of the power plant controller 120 which is not intended to represent the entire functionality of the controller 120. In practice, however, the controller 120 would carry out many other functions, but as these functions are not directly relevant to the invention they are not depicted nor described here so as not to obscure understanding of the invention. Furthermore, it should be understood that as the functional blocks in Figure 2 represent functionality, they may be implemented on hardware, software or firmware, either within the same processing environment or on a distributed processing architecture. That is to say, the functional architecture illustrated in Figure 2 is not intended to limit the invention to a specific hardware or software architecture, platform or processing environment. As explained above, the controller 120 is operable to adapt the NRO mode settings of selected ones of the operational wind turbines in the wind power plant 100 in dependence on identifying one or more wind turbines that are non-operational. It achieves this by first monitoring the noise produced by the power plant at the receptor 130 and producing a noise model. The noise model can thereafter be analysed in order to determine the contributions that each operational wind turbine makes to the overall noise level of the power plant 100, and suitable control commands can be issued to uprate production of one or more of the operational wind turbines. Therefore, the power reserves of one or more of the operation turbines can be used to utilise more effectively the allowable noise generation of the power plant 100 and therefore to optimise power production.

In overview, the controller 120 includes a noise modelling unit 140, a turbine status database 142, a noise mode controller 144 and an operational controller 146. The controller 120 is shown as receiving two data inputs. The first data input is noise data 148 from the receptor 130 and the second input is wind turbine status data 150 received by the network 120 that indicates the operational status of the wind turbines. The noise data 148 is input into the noise modelling unit 140, whilst the status data 150 is input into the turbine status database 142.

The role of the noise modelling unit 140 is to derive a noise model from the noise data 148. Whereas the noise data 148 provides a measurement of the total noise level (in dB, or alternatively, in db(A)) that is detected by the receptor 130 at that particular location, the noise model indicates the contribution of each of the turbine to the total noise output. Thus, in one embodiment, the model may be considered to be a respective dB amount in respect of each wind turbine.

In creating the noise model, the noise modelling unit 140 is configured to take account of which wind turbines in the power plant 100 are in fact non-operational and, therefore, do not contribute to the total or 'cumulative' noise level that is detectable at the receptor 130. The noise modelling unit 140 is therefore operable to determine a modified noise model that factors in the non-operational wind turbines.

In more detail, the noise modelling unit 140 includes a modeller 152 which receives the noise data 148 from the receptor 130. The modeller 152 may be a piece a software implemented algorithm that creates a noise model 154 from the noise data 148. The algorithm is operable to take account of the relative influence that each wind turbine has on the cumulative sound level at the measuring location of the receptor 130, based on certain factors, such as distance to the receptor 130, topology, vegetation levels and so on.

The noise model 154 is then acted on by a model modifier 156 which is responsible for modifying the noise model 154 to take into account the operating status of the wind turbines 101-110. For this purpose, the model modifier 156 is configured to query the turbine status database 142 to identify which of the wind turbines 101-110 in the power plant 100 are not operating and to modify the model 154 so that the contribution of each wind turbine to the total noise output is accurately reflected. Based on the noise model 154 and the data from the turbine status database 142, the model modifier 156 determines a modified noise model 158.

The noise mode controller 144 is responsible for interpreting the modified noise model 158 and directing or modifying the operation of the wind turbines 101-110. In general terms, the noise mode controller 144 is operable to determine if the wind power plant 100 is operating in a reduced noise regime and to command the wind turbines accordingly via the operational controller 146. The noise mode controller 144 checks the total noise output of the wind turbine and determines if the total noise output is below a prevailing noise limit. If so, the noise mode controller 144 is operable to take advantage of the opportunity to modify the power output of the power plant by commanding one or more of the wind turbines into a less restrictive noise mode such that their power output, and therefore also their noise output, is increased. This may be run as an iterative process in which the noise mode controller 144 checks repeatedly the noise data 148 and continues to optimise the noise modes of the wind turbines 101-1 10 until the total noise output of the power plant meets, or is sufficiently near to, the prevailing noise limit imposed on the power plant 100.

An embodiment illustrating how the noise mode controller 144 may achieve this is shown in the process 300 of Fig. 3. The process 300 is initiated at step 302, and, at step 304, the noise mode controller 144 makes a check whether the wind power plant 100 is in a reduced noise operational regime. If the wind power plant 100 is not in a reduced noise regime, the process 300 terminates at step 306. Initiation of the process 300 may occur again after a predetermined time interval. It is currently envisaged that the process may repeat on an internal in the order of one hour or whenever it is detected that one of the wind turbines has become inactive or non- operational. However, if a reduced noise regime is in force, then the process 300 proceeds to step 308 in which it measures noise at the receptor 130 via noise data 148. Once the noise level has been measured, the process 300 proceeds to decision step 310 in which the measured noise level is compared against the prevailing noise limit.

If the measured noise level is sufficiently close to the prevailing noise limit, that is to say, within a predetermined margin of the noise limit, the process will terminate at step 312. However, if the noise mode controller 144 determines that there is a sufficient margin between the measured total noise level and the noise limit, the process 300 moves on to a sequence of steps in which it modifies the NRO modes of selected turbines. Note, here, that a sufficient margin indicates that there is a useful power reserve to exploit.

At step 314, the noise mode controller 144 queries the modified noise model 158 and selects one of the wind turbines 101-1 10 for modification of its NRO mode. Here, it is envisaged that the noise mode controller 144 will identify the wind turbine that makes the lowest contribution to the total noise level of the power plant 100. However, in principle, any one of the wind turbines could be selected.

At step 316, the noise mode controller 144 increases the NRO mode setting on the selected wind turbine. For instance, in a wind turbine that has five NRO mode settings, where Ό' is the normal operational mode and where through to '5' represent increasingly restrictive NRO mode settings, the node mode controller 144 could change "NRO mode 5" to "NRO mode 4". This would have the effect of increasing the power output of the wind turbine, and also therefore of the power plant 100 as a whole, whilst also causing an increase in noise generation.

Once the NRO mode setting for the selected wind turbine has been changed, the process 300 then moves on to decision step 318 in which the noise mode controller 144 checks the total noise level at the receptor point 130. At this point, it should be noted that a 'wait' period could be implemented in order to provide time for the NRO mode setting change to take effect and for the new noise level to stabilise. If it is determined that the noise has increased to a level at which it is sufficiently close to the prevailing noise limit, then it can be considered that the power output and noise generation has been optimised for the power plant 100 operating under a reduced noise regime, and so the process 300 will terminate at step 320. Alternatively, if the noise level is still sufficiently below the prevailing noise limit, this means that there is a further opportunity to increase the power output of the wind farm, thereby exploiting its power reserve, whilst remaining within the noise limit. Therefore, the process 300 moves to decision step 322 in which the noise mode controller 144 checks the NRO mode setting for the selected wind turbine. In the example described above, the NRO mode setting was increased from "NRO mode 5" to "NRO mode 4". Therefore, there are still three less restrictive NRO mode settings that can be used to increase the noise output and associated power output of the selected wind turbine. So, in this example, the process will move back to step 316 in which the noise mode controller 144 will increment the NRO mode setting of the selected wind turbine, that is, the selected wind turbine will be transitioned to "NRO mode 3". This sequence of steps (316-318-322) will repeat for the selected wind turbine until the wind turbine is in a normal operational mode, and not under reduced noise operation. As such, if the NRO mode setting has been increased to such a level that the wind turbine is now in a normal operational mode, the process 300 will proceed back to step 314 at which the noise mode controller 144 will select another wind turbine from the modified noise model 158 in order to optimise is noise and power output. It will be noted that by performing the steps 314 through to 322, the process works through the wind turbines from the lowest noise contributor to optimise the power output from the wind power plant 100, whilst keeping the generated noise below the prevailing noise limit.

It will be appreciated that variations or modifications may be made to the specific embodiments described above without departing from the inventive concept, as defined by the claims.

In the above embodiment, the noise modeller calculates, from a total noise value measured at the receptor 130, a noise model that includes a noise output value for each of the wind turbines. As an alternative to this, it is envisaged that the modelling approach could be more sophisticated, such that the modeller could, in addition to determining the overall noise contribution by each wind turbine, provide a noise profile of each wind turbine, for example in the frequency domain, which data could then be used to fine tune the operation of each individual turbine. For instance, parameters like rotor speed, pitch, generator torque could be varied to influence the frequency content of the noise generated by the WTG so as to reduce the impact at the immission point whilst maximising output power. Furthermore, the controller 120 could also take into account environmental factors, such as sounds transmissibility through the air under certain whether conditions, in order to optimise the power output of the selected wind turbines with even greater effectiveness. In the above embodiment, only once receptor point 130 has been mentioned for simplicity. However, it should be appreciated that the system could include multiple receptor points, which would certainly be the case if the residential area 200 was widespread, or if there were more than one residential area that were spaced apart, for example. In such a case, the modeller would require a more sophisticated algorithm to determine the sound contribution of each wind turbine to the total cumulative sound level at each of the receptors.

The embodiment described with reference to Figures 2 and 3 represents an 'active' process in which a noise model is determined dynamically based on the sound level measured at the receptor point 130. In an alternative embodiment, a 'passive' approach to achieving similar production efficiency advantages does not require noise to be measured at the receptor points in order to switch the wind turbines into different noise reduction modes following recognition that one or more of those wind turbines has become inactive. To this end, reference will now be made to Figures 4 and 5. Note that this embodiment is similar to that of Figure 2 so, where appropriate, the same or similar reference numerals are used to refer to the same or similar features.

In the embodiment of Figure 4, the controller 120 includes, in overview, a noise mode database 404, a noise mode selector module 406, a turbine status database 442, a noise mode controller 444 and an operational controller 446.

The controller 120 is shown as receiving a single data input, namely the wind turbine status data 150 that is received by the network 120 and indicates the operational status of the wind turbines. The wind turbine status data 150 is used to update the turbine status database 442 which keeps an accurate record of the operational status of each wind turbine.

The noise mode database 404 is a memory area in which information is stored about the most appropriate noise modes for the wind turbines under certain operating conditions. For the purposes of this discussion, a simplified scenario will be considered, but it should be appreciated that more complex scenarios are envisaged.

The noise mode database 404 can be considered to hold a series of matrices that list information on the noise mode for each of the wind turbines in the power plant depending on the operational regime of the power plant. For example the first matrix will list the noise mode for each wind turbine when each wind turbine is in an operational status. It will be appreciated that the noise modes for the wind turbines will vary depending on the relative position of each wind turbine to a residential area; wind turbines closer to a residential will have a more restrictive noise mode than wind turbines that are further away from residential areas. The noise modes can therefore be considered to provide an indication as to the noise contribution made by the wind turbines to the total noise level that will be experienced at an associated measurement point. Such information is determined through measurement offline using a receptor point near to the residential area.

Each of the other matrices will include comparable information regarding the noise modes of the wind turbines, but the noise modes in any given one of the matrices are modified to take account of the additional noise margin that is available when a respective one of the wind turbines is in a non-operational status. So, for a power plant with ten wind turbines, there will be ten matrices, each of which list the noise modes for the nine remaining wind turbines when one of the wind turbines is in a non-operational status.

The noise mode selector 406 is responsible for checking the turbine status database 442 and then selecting the most appropriate noise mode matrix from the noise mode database 404 which should be used by the noise mode controller 444.

As in the Figure 2 embodiment, the noise mode controller 444 is responsible for interpreting the noise mode information it obtains from the noise mode database 404 and directing or modifying the operation of the wind turbines 101-110.

A process is shown in Figure 5 corresponds to the functional block diagram of Figure 4.

The process 500 begins at step 502 which may be on a periodical basis, or the process 500 may be called when an internal monitoring routine configured to identify that one of the wind turbines has transitioned into an in active or non-operational state.

At step 504 the noise mode selector 406 checks the turbine status database 442 to determine which of the wind turbines has become inactive. It then selects, at step 506, the most appropriate noise mode matrix from the noise mode database 404 based on which wind turbine is now inactive. It will be appreciated that the process described here is simplified for the purposes of this discussion such that the noise mode selector 406 selects the most appropriate noise mode matrix based simply on which wind turbine has become inactive. It is envisaged, however, that further matrices could be configured to take into account over variables that may affect noise, such as time of day, ambient weather conditions (e.g. wind speed and fog, background noise levels). Overall, however, it should be noted that the noise mode matrix that is selected will contain information that will cause the noise mode of at least one of the wind turbines to be changed into a less restrictive mode in order to take advantage of the increased noise generation margin that will have been created by the inactive status of one of the wind turbines.

At step 508, the noise mode controller 444 refers to data from the noise mode database 404, implements the new noise mode settings for the wind turbines as directed by the selected noise mode matrix, and then commands the wind turbines accordingly via the operational controller 446.

In the embodiment just described, the noise modes for the wind turbines are contained within respective matrixes; each one including a set of different noise mode settings for the wind turbines of the power plant when a particular one of the wind turbines has become non- operational. Further matrices may be included to build in responses to different conditions, such as changes in the ambient weather conditions or background noise levels, for example. It will be noted that in these examples the data contained in the matrices is determined by testing before the wind power plant is commissioned. However, it should be appreciated that the same solution could be achieved algorithmically.