Method of installing and controlling an offshore wind power plant

Abstract

Method of installing the offshore wind power plant, in which a number of installation design variants are modelled to determine performance characteristics. Modelling comprises applying a Monte Carlo method. An installation design is then selected based on the variant with the highest performance characteristics. The offshore wind power plant may be controlled by determining its instability probability characteristics based on modelling using a plurality of known installation design parameters and one or more variable control parameters associated with the wind power plant, wherein modelling comprises applying a Monte Carlo method. The one or more variable control parameters may then be controlled such that the wind power plant is operated below a selected instability probability threshold.

Description

METHOD OF INSTALLING AND CONTROLLINGAN OFFSHORE WIND POWER PLANT

[0001] The present application concerns a method of installing an of fshore wind power plant . As well as a method of controlling an of fshore wind power plant (WPP ) . The present application is particularly relevant to control and installation methods for maintaining grid stability, and methods of improving reliability and optimi zing of fshore wind power plant operations . The present application also concerns a method of dimensioning and controlling an of fshore wind power plant , while considering the statistical variations of the WPP elements that result from manufacturing and installation variations , tolerances and uncertainties .

[0002] Of fshore WPPs are hugely expensive and complex systems . During the process of designing and building a new installation, design choices are made , and component parameters can vary between installations , which ultimately can have a signi ficant bearing on the reliability and operational stability of the wind power plant during use . For example , the wind turbines , cables in the collection grid, trans formers at the of fshore substation, long HVAC transmission cables , onshore trans formers and other components create various electrical system resonance scenarios in the system, such as electrical resonance between components in the electrical control and distribution equipment . This poses a signi ficant challenge in terms of developing a stable system as the interaction of electrical system resonance characteristics can cause part or all of the WPP to become unstable , or lead to the failure of the WPP . Such instability can also includeinteraction with the power transmission system that the WPP is connected to . In addition, manufacturing tolerances of equipment , and particularly cabling, can also impact ultimate performance of the stability of the electrical system . As such, installation decisions , including design and dimensioning decisions , such as component selections , and operating control methodologies have to try to account for both the inherent complexity of the system, as well as the performance variances arising from di f ferences between real-world installations .

[0003] In view of the above , improved electrical system modelling of a WPP, including the electrical control and protection systems , which is able to account for variables such as component tolerances , cable lengths , cable burial depths , temperature , and loading, is an important area of research to provide for more cost ef fective and ef ficient installation and control methods in wind power plant systems . For example , conventional techniques will often use impedance-based stability analysis and apply a worstcase approach to set operating parameters . However, this leads to conservative installation and operating approaches , which limit the si ze or output of the system, cause suboptimal installation, design and control choices to be made , and can become prohibitively expensive or less cost ef ficient . That is , typical ly a larger than necessary stability margin will be adopted in order to avoid a loss of grid stabil ity and compensate for the inaccurate assessment of the risk of grid instability .

[0004] In view of the above there is a need for an improved method of instal ling and controlling the operation of anof fshore wind power plant which better balances the risk of grid instability against system performance .

[0005] According to a first aspect of the present invention, there is provided a method of installing the of fshore wind power plant , comprising : ( a ) modelling a number of installation design variants having di f ferent electrical system characteristics to determine performance characteristics for each installation design, wherein modelling comprises applying a Monte Carlo method; (b ) selecting an installation design based on the variant with the highest performance characteristics , wherein the performance characteristics comprise at least the electrical system stability of the wind power plant .

[0006] In this way, variables influencing electrical system characteristics can be modelled by simulating how the model responds to randomly generated inputs corresponding to statistical variations in electrical parameters for WPP elements . That is , by using the Monte Carlo technique , a large number of random simulations can be used to replicate this variance in inputs and provide for determination of how probable it is for the electrical system within each design to become unstable . Accordingly, a system stability model is generated based on a plurality of parameters associated with the speci fic wind power plant system design using the installation design parameters and associated electrical system characteristics speci fic to that design variant . Simulations may then be run using the computeri zed model of the wind power plant system for a plurality of scenarios where random values are assigned to the random input variables . As such, the risk of each design variable can be characterised in order to select the optimumvariant. For example, the cheapest design variant which achieves a required operating stability may be selected.

[0007] In embodiments, each installation design variant comprises an on-state parameter associated with one or more electrical components of the respective design variant. In this way, the electrical system characteristics of the design variant operating within its normal parameters can be determined for evaluating the stability of the wind power plant. Electrical components encompasses individual components such as resistors but also subassemblies of components into power factor correction modules or synchronous condensers or the like.

[0008] In embodiments, the installation design variants include one or more of the following design variables: component selections, component combinations, component characteristics, cable burial depths, cable gauges, material selections, configuration options, transformer characteristics, filter characteristics, and operating condition characteristics. In this way, analysis can be carried out accounting for component variables, operational variables, location variables to obtain a more complete picture of the electrical system characteristics for each specific design variant.

[0009] In embodiments, the step of selecting an installation design comprises selecting a variant with the highest performance score based on one or more performance characteristics .

[0010] In embodiments, the calculated highest performance score includes weighting the one or more performance characteristics. In embodiments, the one or moreperformance characteristics include cost characteristics. In embodiments, the cost characteristics include installation costs and costs resulting from power outages. Power outages may result from interruption to operations caused by instability of the WPP.

[0011] In embodiments, the step of modelling a number of installation design variants comprises performing a plurality of simulations for each design variant. In this way, each design variant can be modelled to determine the probability of instability over a number of simulations based on a number of design choices associated with the particular variant to determine the performance characteristics for different combinations of elements forming an electrical system.

[0012] In embodiments, the plurality of simulations comprises one or more random parameter selections.

[0013] In embodiments, the method further comprises the step of installing the offshore wind power plant according to the selected variant with the highest performance characteristics .

[0014] In embodiments, the performance characteristics comprise at least the harmonic stability of the design variant. In this way, the harmonic stability associated with each design variant can be analysed, and thus the probability that a particular design variant causes an instability can be determined.

[0015] According to a second aspect, there is provided a method of controlling an offshore wind power plant, comprising: (a) determining electrical system instabilityprobability characteristics for the of fshore wind power plant based on modelling using a plurality of known installation design parameters having electrical system characteristics and one or more variable control parameters associated with the wind power plant , wherein modelling comprises applying a Monte Carlo method; (b ) setting an instability probability threshold; and ( c ) controlling the one or more variable control parameters associated with the wind power plant such that the wind power plant is operated below the instability probability threshold .

[0016] In this way, the Monte Carlo technique is used to determine how probable it is for the system to become unstable . As such, control parameters which can influence the stability of the electrical system during operation of the wind power plant can be adj usted such that the required operating stability is maintained .

[0017] In embodiments , the step of determining instability probability characteristics comprises modelling a plurality of simulations using random parameter selections .

[0018] According to a third aspect , there is provided a non-transient computer readable medium comprising instructions which, when executed by a processor or processors , perform the method according to the above .

[0019] According to a fourth aspect , there is provided a computer software product comprising instructions which, when executed by a processor or processors , perform the method according to any of the above .

[0020] According to a fi fth aspect , there is provided a method of designing an of fshore wind power plant ,comprising : ( a ) modelling a number of wind power plant design variants having di f ferent electrical system characteristics to determine performance characteristics for each wind power plant design, wherein modelling comprises applying a Monte Carlo method; (b ) selecting the wind power plant design based on the variant with the highest performance characteristics , wherein the performance characteristics comprise at least the electrical system stability of the wind power plant .

[0021] According to a sixth aspect , there is provided a method of dimensioning an offshore wind power plant , comprising : ( a ) modelling a number of wind power plant design variants having di f ferent electrical system characteristics to determine performance characteristics for each wind power plant design, wherein modelling comprises applying a Monte Carlo method; (b ) selecting the wind power plant design based on the variant with the highest performance characteristics , wherein the performance characteristics comprise at least the electrical system stability of the wind power plant .

[0022] An illustrative embodiment of the present invention will now be described with reference to the accompanying drawings in which :Figure 1 shows an output from a Monte Carlo simulation for the selection of a wind turbine power plant variant ;Figure 2 shows a histogram of the Monte Carlo simulation showing probability mapped against di stance to instability;Figure 3 shows a schematic illustration of cost plotted against stability for selecting an optimised performance in an illustrative example ; andFigure 4 shows a flow diagram of a method of determining the electrical stabi lity of a wind power plant in an illustrative example .

[0023] Embodiments of the present invention are based on using Monte Carlo simulations to model the stability of the wind power plant . In one aspect , the wind power plant may then be controlled based on control thresholds determined using the simulations . In another aspect , a wind power plant may be installed based on design decisions determined using the output of the simulations .

[0024] An of fshore wind power plant includes the wind turbines themselves as well as associated components up to point of interconnection on land . In arrangements , this may include the power collection and transmission asset equipment such as , wind turbines , cables , trans formers , STATCOMs , active and reactive power balancing equipment , and energy storage and conversion equipment connected behind the meter .

[0025] The Monte Carlo simulations , according to an embodiment of the invention, allow variables to be modelled by simulating how the model responds to randomly generated inputs . That is , it is typically di f ficult to derive the probability distribution function analytically for a complicated system . By using the Monte Carlo technique , a large number of random simulations can be used to replicate this variance and provide for determination of how probable it is for the system to become unstable .

[0026] In particular, a grid stability model is generated based on a plurality of parameters associated with the wind power plant system . These parameters may include known installation design parameters , such as component performance and resonance characteristics , as well as one or more variable control parameters . Of the installation design parameters , those that are known to have a variance , for example associated with component tolerances , a plurality of random input variables is added to the model to account for that uncertainty . Simulations are then run using the computeri zed model of the wind power plant system for a plurality of scenarios where random values are assigned to the random input variables . Where present , scenarios are also run for the variable control parameters to determine how the stability response varies with adj ustment of these parameters .

[0027] Based on the above it will be appreciated that the design variants may include electrical parameters related to design variables . As an example , for each electrical component or subassembly of components , a particular tolerance is speci fied or otherwise known . Additionally, these tolerances can be further af fected by environmental factors such as cable length or burial depth, wind speed variance etc . The modelling of design variants , including di f ferent combinations of electrical system components , can thereby take into account the respective tolerances of those components and the environmental factors as random inputs into the Monte Carlo simulations , so that random combinations of the above variables can be plotted to assess their impact on the overall stability of the electrical system .

[0028] The outputs of the simulations are then aggregated, and the aggregated results are assessed to evaluate the probability distribution of the stability indices . This provides for an assessment of the risk of the system being unstable .

[0029] As mentioned above , in one aspect , the wind power plant may be controlled based on a control threshold determined using the simulations . In this respect , in one embodiment , the method comprises first determining instability probability characteristics for the of fshore wind power plant based on the above modelling for the plurality of parameters associated with the wind power plant . An instability probability threshold is then set and mapped to the simulation results to determine an acceptable range for each relevant control parameter that still maintains operations below the set instability probability . For example , a probability of instability may be set to a predetermined maximum threshold .

[0030] Once the one or more thresholds have been set , the one or more variable control parameters may be controlled such that the wind power plant is operated below the instability probability threshold .

[0031] As mentioned above , in another aspect , a new wind power plant may be installed based on design decisions determined using the output of the simulations . In this respect , in one embodiment , the method comprises modelling a number of installation design variants to determine performance characteristics using the Monte Carlo method . Each design variant may include di f ferences , for example , in terms of the electrical components chosen, as well asdesign choices such as cable burial depths or lengths and the arrangement of operating units . Figure 1 shows an illustrative example output from a Monte Carlo simulation for a particular wind power plant variant and Figure 2 shows a histogram of the Monte Carlo simulation showing probability mapped against distance to instability .

[0032] The performance characteristics for each model can then be compared to determine the optimum variant and the wind power plant may then be installed according to the selected variant . For example , a threshold probability of instability 1 may be set as a required minimum . The optimum variant may be selected as the design variant which has the highest distance to instability relative to cost .

[0033] In this connection, Figure 3 shows a schematic illustration of cost 2 plotted against reliability 3 for selecting an optimised performance in an illustrative example . Line 4 shows the cost of a power loss outage and line 7 shows the system installation cost . Line 5 shows the total cost change , which indicates that a highest performance is where the total cost is minimised by balancing the cost of a power loss outage against the installation costs . In practice , it will be understood that the selection of an optimised performance reliability level may be achieved by weighting installation costs and instability factors in a calculation algorithm to identi fy an optimal design variant .

[0034] Wind turbine power plants , and other renewable energy sources , are particularly susceptible to electrical system instability due to their complexity and variations in their operating conditions . For example , harmonics canbe established between inductive and capacitive components . This is distinct from the reliability of a particular plant or turbine , where an analysis can be carried out to determine the ef fect of a component failing or an operating parameter being exceeded . Instead, electrical system instability arises when the components operating within their normal parameters cause an unwanted ef fect on power delivery which can impact supply and protection systems further down the electrical system chain .

[0035] An example of the type of instability faced by a wind power plant is harmonic instability . It is therefore beneficial to analyse the ef fect of design choices on the harmonic stability of the wind power plant .

[0036] In some embodiments , the highest level of electrical system stability may be selected, however in other embodiments weighting may be applied to select the lowest cost design variant which provides an acceptable level of stability . That is to say that a high level of stability may be useful for robustness of the wind power plant , however it may come with an increased complexity, higher maintenance requirements and a greater cost . As such, priorities for the installation may be balanced based on requirements .

[0037] According to the foregoing, the Monte Carlo method discussed herein is used to determine the ef fect of each design variant operating within its on-state or intended parameters as af fected by installation and control conditions . As such, the electrical system stability of the wind power plant when the plant is operating as intended can be modelled, rather than merely thereliability of component parts or the likelihood of mechanical damage during operation of the wind power plant.

[0038] Figure 4 shows a flow diagram of a method for determining the electrical stability of a wind power plant design according to an illustrative example. For instance, the method may be implemented as a computer simulation using software. In the first step 4.1, a plurality of elements of the wind power plant design are identified. As such, electrical components and connectors forming the electrical system of the proposed wind power plant may be defined within the simulation. In step 4.2, the range of variation of electrical characteristics of those elements is defined. In step 4.3, the range of variation based on environmental factors associated with a planned installation of the wind power plant design are defined. In step 4.4, a plurality of Monte Carlo simulations are run based on the defined electrical characteristics and ranges of variation. In the final step 4.5, the estimated electrical stability of the wind power plant design is determined based on the plurality of Monte Carlo simulations. As such, the methodology allows the probability of instability to be assessed, taking into account electrical parameters and their variations, based on element types, tolerances and environmental factors. As such, different designs of wind power plant can be evaluated using the simulation, thereby allowing prospective wind power plant designs to be dimensioned using modeling before installation. Equally, operational control parameters can be also modeled within the simulation to determine the control methodologies that subsequently applied once the design is installed. Thisthereby allows design and control choices to be tested before implementation in situ.

[0039] It will be understood that the embodiments illustrated above show applications of the invention only for the purposes of illustration. In practice the invention may be applied to many different configurations, the detailed embodiments being straightforward for those skilled in the art to implement.

[0040] In this respect, whilst the above examples focus on the installation and control of a wind power plant, it will be understood that the disclosure is also relevant to a method of dimensioning and controlling an offshore wind power plant (WPP) , while considering the statistical variations of the WPP elements that result from manufacturing and installation variations, tolerances and uncertainties. As such, methods may be provided for securing grid stability considering the dimensioning of wind power plant elements and the corresponding statistical variations of their characteristic electrical component parameters. For example, a method of determining the stability of an electrical system may be provided.

[0041] Furthermore, it will also be understood that whilst the focus of the above examples is offshore wind farms, the methods and systems disclosed herein are also applicable to other systems, such as electrical systems on land (e.g. power transmission and power distribution systems) , as well as other electrical and control systems (e.g. power plants, industrial plants, and combinations thereof) .

Claims

CLAIMS1. A method of installing an offshore wind power plant, comprising :(a) modelling a number of installation design variants having different electrical system characteristics to determine performance characteristics for each installation design, wherein modelling comprises applying a Monte Carlo method;(b) selecting an installation design based on the variant with the highest performance characteristics; wherein the performance characteristics comprise at least the electrical system stability of the wind power plant .

2. A method according to claim 1, wherein each installation design variant comprises an on-state parameter associated with one or more electrical components of the respective design variant.

3. A method according to claim 1 or 2, wherein the installation design variants include one or more of the following design variables: component selections, component combinations, component characteristics, cable burial depths, cable gauges, material selections, configuration options, transformer characteristics, filter characteristics, and operating condition characteristics.

4. A method according to claim 1 to 3, wherein the step of selecting an installation design comprises selecting avariant with the highest performance score based on one or more performance characteristics .5 . A method according to claim 4 , wherein the calculated highest performance score includes weighting the one or more performance characteristics .6 . A method according to any preceding claim, wherein the step of modelling a number of installation design variants comprises performing a plurality of simulations for each design variant .7 . A method according to claim 6 , wherein the plurality of simulations comprises one or more random parameter selections .8 . A method according to any preceding claim, further comprising the step of installing the of fshore wind power plant according to the selected variant with the highest performance characteristics .9 . A method according to any preceding claim, wherein the performance characteristics comprise at least the harmonic stability of the design variant .10 . A method of controlling an of fshore wind power plant , comprising :( a ) determining electrical system instability probability characteristics for the of fshore wind power plant based on modelling using a plurality of known installation design parameters having electrical system characteristics and one or more variable control parametersassociated with the wind power plant , wherein modelling comprises applying a Monte Carlo method;(b ) setting an instability probability threshold; and( c ) controlling the one or more variable control parameters associated with the wind power plant such that the wind power plant is operated below the instability probability threshold .11 . A method according to claim 10 , wherein the step of determining instability probability characteristics comprises modelling a plurality of simulations using random parameter selections .12 . A non-transient computer readable medium comprising instructions which, when executed by a processor or processors , perform the method according to any preceding claim .13 . A computer software product comprising instructions which, when executed by a processor or processors , perform the method according to any of claim 1 to 11 .

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