CN111950764B - Wind power prediction correction method for power grid under extreme weather conditions - Google Patents
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Abstract
The invention discloses a wind power prediction correction method for an extreme weather condition power grid, which comprises the steps of starting a correction flow through extreme weather information contained in conventional weather prediction, identifying and optimizing correction numerical weather prediction based on extreme weather events, judging the type of the extreme weather, if the wind is strong wind, performing unidirectional deviation correction of wind speed prediction, fitting an actual power characteristic curve to optimize a wind resource-power conversion model, if the wind is cold or damp, directly fitting the actual power characteristic curve to optimize the wind resource-power conversion model, correcting the wind power prediction of the extreme weather condition power grid by combining environment protection setting and self-grid connection setting, and finally outputting correction results; the wind power prediction correction method for the power grid under the extreme weather conditions can continuously improve the wind power prediction level, and bring wind power prediction results into the support of the daily power balance arrangement better.
Description
Technical Field
The invention relates to the field of wind power prediction, in particular to a wind power prediction correction method for a power grid under extreme weather conditions.
Background
Along with the continuous building of wind power plants and the annual increase of the installed capacity of wind power, the reliable operation of wind power generation sets is more important, so that the economic benefit of the wind power plants can be determined, and the whole safe and stable operation of a power grid can be related. The wind turbine generator is installed outdoors, extreme weather is a main cause for disturbing the normal operation of the wind turbine generator, and serious weather disasters even cause faults.
Wind power prediction is researched and practiced for many years, the prediction accuracy is obviously improved, and the wind power prediction is gradually incorporated into a daily scheduling plan of a power system. The power prediction model widely adopted in the wind power industry at present is to calculate wind resources according to numerical weather forecast in principle, so as to calculate predicted power, and the influence of extreme weather on the running of the wind turbine generator is not considered. The existing research mainly aims at improving the power prediction accuracy under the general condition, and the research on the power prediction deviation caused by special events such as extreme weather is relatively less. The unplanned power change caused by the protective shutdown of the wind turbine generator under extreme weather can bring serious impact to the daily power balance and standby leaving of the provincial power grid, and the execution of a dispatching plan is affected. Therefore, aiming at the provincial power grid with special meteorological environment and higher occurrence probability of extreme weather, it is necessary to estimate the influence of the extreme weather on the running of the wind turbine generator, correct the power prediction result and formulate corresponding scheduling countermeasures so as to ensure the safe consumption of wind power and the reliable running of the power grid.
Disclosure of Invention
In order to solve the defects in the prior art, the invention provides the wind power prediction correction method for the power grid under the extreme weather condition, which is based on a shutdown protection mechanism of a unit and an extreme weather power prediction deviation cause, provides a wind power prediction power correction strategy and a scheduling countermeasure proposal for a special provincial power grid in a meteorological environment, and provides support for continuously improving the wind power prediction level and bringing a wind power prediction result into the daily power balance arrangement better.
In order to achieve the above object, the present invention adopts the following technical scheme:
a wind power prediction correction method for a power grid under extreme weather conditions specifically comprises the following steps:
1) Starting a correction flow through extreme weather information contained in the conventional weather forecast;
2) Identifying an optimized revised numerical weather forecast based on the extreme weather event;
3) Judging the extreme weather type, if the extreme weather type is strong wind, performing unidirectional deviation correction on wind speed prediction, fitting an actual power characteristic curve to optimize a wind resource-power conversion model, and if the extreme weather type is cold, directly fitting the actual power characteristic curve to optimize the wind resource-power conversion model;
4) And correcting the wind power prediction of the power grid under the extreme weather condition by combining the environment protection setting and the self-grid connection setting, and finally outputting a correction result.
Further, the optimizing and correcting numerical weather forecast based on the extreme weather event identification specifically comprises the following steps:
predicting the future extreme weather and the influence of the future extreme weather on the predicted power of the wind turbine based on the temperature and humidity numerical weather forecast elements of the wind turbine;
collecting historical cases of extreme weather, establishing an extreme weather historical database, identifying future extreme weather events by adopting an identified event identification method, and correcting weather index predicted values;
searching similar events in an extreme weather history database according to three basic characteristic quantities of the extreme weather prediction duration, the weather element index change direction and the weather element index change amplitude;
and correcting the predicted weather index based on the actual change process of the weather index in the similar event.
Further, the fitting of the actual power characteristic curve optimizes the wind resource-power conversion model, specifically:
and (3) fitting to obtain an actual power characteristic curve of the wind turbine generator, filtering abnormal operation state points by using a wind speed-power scatter diagram, and optimizing a wind resource-power conversion model by using the actual power characteristic curve.
Further, the wind speed-power scatter plot is drawn from operational data.
Further, the abnormal operation state points include a limit point and a fault point.
Furthermore, the method corrects the prediction of the wind power of the power grid under the extreme weather condition by combining with the environment protection setting, and specifically comprises the following steps:
the wind turbine generator sets respectively correspond to different action time, and a multi-gear automatic shutdown/recovery protection fixed value is set corresponding to an extreme running environment;
meanwhile, a manual recovery mode is further arranged on the wind turbine generator, and after the environmental condition of the wind turbine generator recovers to meet the operation requirement, wind farm operators are prompted to start a fan to grid in a manual mode for power generation;
and the method is combined with the specific settings of numerical weather forecast and environmental protection of the wind turbine, and the extreme weather power prediction results are corrected for different wind power plants and different types of wind turbine.
Further, the specific environmental protection settings include an extreme weather condition protection fixed value, an action time and a recovery mode.
The invention has the beneficial effects that:
the large-scale access of new energy such as wind power can bring multiple aspects to each link of power system dispatching. For special areas of meteorological environment, the influence of extreme weather on wind power output is particularly required to be considered. The method is based on wind power prediction all-link prediction error causes, and provides targeted error correction strategies and scheduling countermeasure suggestions for different prediction links. Practical cases show that the method is beneficial to improving the wind power prediction level and better incorporating wind power prediction results into the daily power balance arrangement.
Drawings
FIG. 1 is an extreme weather event base characteristic amount of example 1;
FIG. 2 is an abnormal operation status point screening chart of example 1;
FIG. 3 is a logic block diagram of a correction method of the present invention;
FIG. 4 is a graph of the power correction results of the low temperature shutdown process of example 2;
fig. 5 is a graph of the whole-network predicted power correction result for the low-temperature shutdown process of example 2.
Detailed Description
The invention is further described below with reference to the accompanying drawings. The following examples are only for more clearly illustrating the technical aspects of the present invention, and are not intended to limit the scope of the present invention.
Wind power short-term power prediction pointer predicts power for one to three days in the future. The method mainly comprises three links of numerical weather forecast generation, wind resource-power conversion model and prediction result correction in the prediction principle: firstly, inputting a downscaling numerical weather forecast provided by a meteorological data company into a wind resource-power conversion model, calculating theoretical predicted power of a wind power plant, and then correcting according to actual production and operation conditions of the wind power plant to obtain a final power prediction result.
Errors can be generated in all links of wind power prediction, and accuracy of prediction results is affected. In order to reduce negative influence of extreme weather on scheduling planning and execution, correction strategies and countermeasure suggestions are respectively provided for errors of three links of wind power prediction under extreme weather conditions.
Numerical weather forecast (numerical weather prediction, NWP) refers to a method for predicting the atmospheric motion state and weather phenomenon in a certain period of time in the future by solving a hydrodynamic and thermodynamic equation set describing the weather evolution process through a large-scale computer under a certain initial value and edge value condition according to the actual condition of the atmosphere. The larger the space scale is, the higher the accuracy of weather forecast is, but the wind power forecast by taking a wind farm as a unit needs small-scale meteorological element information, so that space downscaling work needs to be carried out, namely, large-scale and low-resolution weather forecast information is converted into small-scale and high-resolution small-area ground climate change. The spatial downscaling process increases the error of the numerical weather forecast.
The power prediction manufacturer mainly establishes a wind resource-power conversion model based on a theoretical power characteristic curve of the wind turbine generator. Due to individual differences and fault aging of the wind turbine generator, a certain difference may exist between an actual power characteristic curve and a factory theoretical power characteristic curve, so that a power prediction error is caused.
The current short-term power prediction system of the main current wind power in China does not consider the protective shutdown mechanism of the wind turbine generator under the extreme weather condition, so that even if the numerical weather forecast accurately predicts the future extreme weather, the power prediction result cannot account for the power loss caused by the protective shutdown of the wind turbine generator. The specific setting of the environmental protection of the wind turbine generator relates to the power change process of the wind farm in extreme weather events.
Example 1
As shown in FIG. 3, the wind power prediction correction method for the power grid under the extreme weather condition specifically comprises the following steps:
step S1, starting a correction flow through extreme weather information contained in conventional weather forecast;
s2, predicting the future extreme weather and the influence of the future extreme weather on the predicted power of the wind turbine based on the temperature and humidity numerical weather forecast elements of the wind turbine running;
(besides the wind speed, wind direction and air pressure which are directly related to wind resources, numerical weather forecast elements such as temperature, humidity and the like are introduced to forecast the future extreme weather and the influence of the future extreme weather on the forecast power of the wind turbine generator set) collecting historical cases of the extreme weather, establishing an extreme weather historical database, identifying the future extreme weather event by adopting an identified event identification method, and correcting the weather index forecast value;
searching similar events in an extreme weather history database according to three basic characteristic quantities (shown in figure 1) of the duration of extreme weather prediction, the change direction of the weather element index and the change amplitude of the weather element index;
correcting the predicted weather index based on the actual change process of the weather index in the similar event;
step S3, judging the extreme weather type, if the wind is strong, fitting an actual power characteristic curve optimized wind resource-power conversion model after carrying out unidirectional deviation correction on wind speed prediction, and if the wind is cold, directly fitting the actual power characteristic curve optimized wind resource-power conversion model, wherein the fitting of the actual power characteristic curve optimized wind resource-power conversion model is specifically as follows:
fitting to obtain an actual power characteristic curve of the wind turbine generator, filtering abnormal operation state points (such as limit points, fault points and the like) by a wind speed-power scatter diagram (drawn according to operation data), and optimizing a wind resource-power conversion model by adopting the actual power characteristic curve;
s4, correcting the wind power prediction of the power grid under the extreme weather condition by combining the environment protection setting and the self-grid-connected setting, and finally outputting a correction result, wherein the wind power prediction of the power grid under the extreme weather condition is corrected by combining the environment protection setting, and the method specifically comprises the following steps:
the wind turbine generator sets respectively correspond to different action time, and a multi-gear automatic shutdown/recovery protection fixed value is set corresponding to an extreme running environment;
meanwhile, a manual recovery mode is further arranged on the wind turbine generator, and after the environmental condition of the wind turbine generator recovers to meet the operation requirement, wind farm operators are prompted to start a fan to grid in a manual mode for power generation;
and the method is combined with the specific settings of numerical weather forecast and environmental protection of the wind turbine, and the extreme weather power prediction results are corrected for different wind power plants and different types of wind turbine. And the specific environmental protection settings include extreme weather condition protection fixed values, action time and recovery modes.
Example 2
By adopting the method in the embodiment 1, aiming at the low-temperature shutdown event of the Jibei power grid in the month 1 in 2019, based on numerical weather forecast data and wind power plant power prediction data, and combining the statistics rule of the low-temperature shutdown event of the Jibei power grid in the past, the original power prediction curve reported by the wind power plant is corrected in links, and the whole-network power prediction correction result is further calculated.
The correction result of the predicted power curve of the wind power plant 24 hours before and after the low-temperature shutdown is shown in fig. 4. Before the cooling time is 21:30 at night, the wind farm inorganic unit is stopped, and the predicted power is optimized, corrected and predicted mainly through a wind resource-power conversion model link; from 21:30, judging that the full-farm power gradually falls by combining the low-temperature protection setting of the machine set and the historical low-temperature shutdown data of the wind farm, and keeping unchanged after the full-farm power is estimated to fall to 30MW (15% of installed capacity) at 0; before 12 pm in the next day, the predicted temperature of the all-day wind power plant is still maintained below-25 ℃, the power generation recovery requirement is not met, and the power of the whole plant is judged to be kept unchanged by 30 MW.
Based on specific data conditions of different wind power stations, the predicted power reported by all wind power stations of the power grid in the north of the Ji in the low-temperature shutdown event is corrected according to the steps, and the sum is added to obtain a full-network predicted power correction curve as shown in fig. 5. The boundary nodes among different correction links are respectively the moment when the predicted air temperature of the North wind power plant falls to the set low-temperature protection fixed value for the first time (first day 18:45) and the moment when the predicted air temperature of the shutdown wind power plant rises to the recovery operation temperature for the first time (next day 10:30).
In conclusion, after the errors of all links are predicted and corrected, the prediction error of the whole network power is obviously reduced compared with that before correction.
The foregoing is merely a preferred embodiment of the present invention, and it should be noted that modifications and variations could be made by those skilled in the art without departing from the technical principles of the present invention, and such modifications and variations should also be regarded as being within the scope of the invention.
Claims (6)
1. The wind power prediction correction method for the power grid under the extreme weather condition is characterized by comprising the following steps of:
1) Starting a correction flow through extreme weather information contained in the conventional weather forecast;
2) Identifying an optimized revised numerical weather forecast based on the extreme weather event;
3) Judging the extreme weather type, if the extreme weather type is strong wind, performing unidirectional deviation correction on wind speed prediction, fitting an actual power characteristic curve to optimize a wind resource-power conversion model, and if the extreme weather type is cold, directly fitting the actual power characteristic curve to optimize the wind resource-power conversion model;
4) Correcting the wind power prediction of the power grid under the extreme weather condition by combining the environment protection setting and the self-grid connection setting, and finally outputting a correction result;
the method is characterized in that the wind power prediction of the polar weather condition power grid is corrected by combining with environmental protection, and specifically comprises the following steps:
the wind turbine generator sets respectively correspond to different action time, and a multi-gear automatic shutdown/recovery protection fixed value is set corresponding to an extreme running environment;
meanwhile, a manual recovery mode is further arranged on the wind turbine generator, and after the environmental condition of the wind turbine generator recovers to meet the operation requirement, wind farm operators are prompted to start a fan to grid in a manual mode for power generation;
and the method is combined with the specific settings of numerical weather forecast and environmental protection of the wind turbine, and the extreme weather power prediction results are corrected for different wind power plants and different types of wind turbine.
2. The method for predicting and correcting wind power of an extreme weather condition power grid according to claim 1, wherein the method for optimizing and correcting numerical weather forecast based on extreme weather event identification is specifically as follows:
predicting the future extreme weather and the influence of the future extreme weather on the predicted power of the wind turbine based on the temperature and humidity numerical weather forecast elements of the wind turbine;
collecting historical cases of extreme weather, establishing an extreme weather historical database, identifying future extreme weather events by adopting an identified event identification method, and correcting weather index predicted values;
searching similar events in an extreme weather history database according to three basic characteristic quantities of the extreme weather prediction duration, the weather element index change direction and the weather element index change amplitude;
and correcting the predicted weather index based on the actual change process of the weather index in the similar event.
3. The method for predicting and correcting wind power of a power grid under extreme weather conditions according to claim 1, wherein the fitting of the actual power characteristic curve optimizes a wind resource-power conversion model, specifically:
and (3) fitting to obtain an actual power characteristic curve of the wind turbine generator, filtering abnormal operation state points by using a wind speed-power scatter diagram, and optimizing a wind resource-power conversion model by using the actual power characteristic curve.
4. A method of grid wind power prediction correction under extreme weather conditions as claimed in claim 3, wherein the wind speed-power scatter plot is drawn from operational data.
5. A method of grid wind power prediction correction under extreme weather conditions as claimed in claim 3, wherein said abnormal operating condition points include electrical limit points and fault points.
6. The method for predicting and correcting wind power of power grid under extreme weather conditions according to claim 1, wherein,
the environment protection specific settings comprise an extreme weather condition protection fixed value, action time and a recovery mode.
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| NL2033883B1 (en) * | 2022-12-30 | 2023-09-07 | State Grid Gansu Electric Power Co | A Wind Power Forecasting Method, System and Medium for Extremely Windy Weather |
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