CN111950764A - Extreme weather condition power grid wind power prediction correction method - Google Patents
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Abstract
The invention discloses a method for predicting and correcting wind power of an extreme weather condition power grid, which comprises the steps of starting a correction process through extreme weather information contained in conventional weather forecast, identifying, optimizing and correcting numerical weather forecast based on extreme weather events, judging extreme weather types, fitting an actual power characteristic curve to optimize a wind resource-power conversion model after correcting unidirectional deviation of wind speed prediction if the weather is strong wind, directly fitting the actual power characteristic curve to optimize the wind resource-power conversion model if the weather is cold tide, correcting the wind power prediction of the extreme weather condition power grid by combining environmental protection setting and self-grid-connection setting, and finally outputting a correction result; the method for predicting and correcting the wind power of the power grid under the extreme weather conditions can continuously improve the wind power prediction level and better bring the wind power prediction result into the day-ahead power balance arrangement for providing support.
Description
Technical Field
The invention relates to the field of wind power prediction, in particular to a method for predicting and correcting wind power of a power grid under extreme weather conditions.
Background
With the continuous construction of wind power plants and the annual increase of installed capacity of wind power, the reliable operation of wind generation sets becomes more important, the economic benefit of the wind power plants can be determined, and the overall safe and stable operation of a power grid can be also related. The wind turbine generator is arranged outdoors, extreme weather is a main reason for interfering normal operation of the wind turbine generator, and serious meteorological disasters even cause faults.
Through years of research and practice, the wind power prediction accuracy is obviously improved, and the wind power prediction is gradually incorporated into a day-ahead scheduling plan of a power system. A power prediction model widely adopted in the wind power industry at present calculates wind resources according to numerical weather forecast in principle, and then calculates predicted power, and influence of extreme weather on operation of a wind turbine generator is not considered. The existing research mainly aims at improving the power prediction accuracy under the general condition, and relatively few power prediction deviation researches caused by special events such as extreme weather are carried out. The change of the unplanned power caused by the protective shutdown of the wind turbine generator in extreme weather brings serious impact to the day-ahead power balance and reserve reservation of the provincial power grid, and the execution of a dispatching plan is influenced. Therefore, for a provincial power grid with special meteorological environment and high extreme weather occurrence probability, the influence of the extreme weather on the operation of the wind turbine generator needs to be estimated, the power prediction result is corrected, and a corresponding scheduling strategy is formulated to guarantee the safe consumption of wind power and the reliable operation of the power grid.
Disclosure of Invention
In order to solve the defects in the prior art, the invention provides a wind power prediction correction method for an extreme weather condition power grid, which is based on a unit shutdown protection mechanism and an extreme weather power prediction deviation cause, provides a wind power prediction power correction strategy and a scheduling strategy suggestion for a special provincial power grid in a meteorological environment, and provides support for continuously improving the wind power prediction level and bringing the wind power prediction result into the day-ahead power balance arrangement.
In order to achieve the above purpose, the invention adopts the following technical scheme:
a method for predicting and correcting wind power of a power grid under extreme weather conditions specifically comprises the following steps:
1) starting a correction process through extreme weather information contained in the conventional weather forecast;
2) identifying, optimizing and correcting a numerical weather forecast based on the extreme weather event;
3) judging the extreme weather type, if the extreme weather type is strong wind, fitting an actual power characteristic curve to optimize a wind resource-power conversion model after correcting the wind speed prediction unidirectional deviation, and if the extreme weather type is cold tide, directly fitting the actual power characteristic curve to optimize the wind resource-power conversion model;
4) and correcting the power grid wind power prediction under the extreme weather condition by combining the environmental protection setting and the self-grid-connection setting, and finally outputting a correction result.
Further, the identifying, optimizing and correcting numerical weather forecast based on the extreme weather event specifically includes:
forecasting future extreme weather and influence of the future extreme weather on the forecasting power of the wind turbine generator based on the numerical weather forecast factors of the temperature and the humidity of the operation of the wind turbine generator;
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 a weather index predicted value;
searching for similar events in an extreme weather historical database according to three basic characteristic quantities, namely the extreme weather prediction duration, the weather element index change direction and the weather element index change amplitude;
the predicted weather indicator is corrected based on the actual course of change of the weather indicator in a similar event.
Further, the fitting of the actual power characteristic curve to optimize the wind resource-power conversion model specifically includes:
and (3) obtaining an actual power characteristic curve of the wind turbine generator set through fitting, filtering abnormal operation state points by using the 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 diagram is drawn according to the operation data.
Further, the abnormal operation state point comprises an electricity limiting point and a fault point.
Further, the combination of the environmental protection setting to correct the prediction of the wind power of the power grid under the extreme weather condition specifically comprises:
the wind turbine generator sets respectively correspond to different action time, and multi-gear automatic shutdown/recovery protection fixed values are set corresponding to extreme operation environments;
meanwhile, the wind turbine generator is also provided with a manual recovery mode, and after the environmental condition is recovered and the running requirement is met, the wind turbine generator prompts a wind power plant operator to start a fan in a manual mode to be connected with the grid for power generation;
and correcting the extreme weather power prediction result aiming at different wind power plants and wind power plants of different models by combining the numerical weather forecast and the specific setting of the wind power plant environment protection.
Further, the specific setting of environmental protection includes an extreme weather condition protection fixed value, an action time and a recovery mode.
The invention achieves the following beneficial effects:
the large-scale access of new energy such as wind power and the like can bring various influences on each link of power system scheduling. For areas with special meteorological environments, the influence of extreme weather on wind power output needs to be considered particularly. The method is based on the wind power prediction all-link prediction error cause, and provides a targeted error correction strategy and scheduling strategy suggestions for different prediction links. Practical cases show that the method is beneficial to improving the wind power prediction level and bringing the wind power prediction result into the day-ahead power balance arrangement better.
Drawings
FIG. 1 is the basic characteristic quantity of the extreme weather event in example 1;
FIG. 2 is a diagram for screening an abnormal operation state point in example 1;
FIG. 3 is a logic block diagram of the correction method of the present invention;
FIG. 4 is a graph of the wind farm power correction results during the low temperature shutdown process of example 2;
fig. 5 is a diagram of the results of the entire network predicted power correction during the low-temperature shutdown in example 2.
Detailed Description
The invention is further described below with reference to the accompanying drawings. The following examples are only for illustrating the technical solutions of the present invention more clearly, and the protection scope of the present invention is not limited thereby.
The wind power short-term power prediction pointer predicts the power of one to three days in the future. The prediction principle mainly comprises three links of numerical weather forecast generation, a wind resource-power conversion model and prediction result correction: firstly, inputting a downscale numerical weather forecast provided by a meteorological data company into a wind resource-power conversion model, calculating theoretical prediction power of a wind power plant, and then correcting according to actual production operation conditions of the wind power plant to obtain a final power prediction result.
Errors are generated in all links of wind power prediction, and accuracy of prediction results is affected. In order to reduce the negative influence of extreme weather on the scheduling plan making and execution, correction strategies and strategy suggestions need to be provided respectively aiming at the errors of three links of wind power prediction under the extreme weather condition.
Numerical Weather Prediction (NWP) refers to a method of performing numerical calculation by a large-scale computer under certain initial value and edge value conditions according to the actual conditions of the atmosphere, solving a fluid mechanics and thermodynamics equation set describing the weather evolution process, and predicting the atmospheric motion state and the weather phenomenon in a certain time period. The larger the spatial scale is, the higher the accuracy of weather forecast is, but the wind power prediction using a wind power plant as a unit needs small-scale meteorological element information, so that space downscaling work needs to be carried out, that is, the 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 can increase the error of numerical weather forecasts.
A power prediction manufacturer establishes a wind resource-power conversion model mainly based on a theoretical power characteristic curve of a wind turbine generator. Due to individual difference 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, and power prediction errors are caused.
At present, the short-term power prediction system of the domestic mainstream wind power does not consider a protective shutdown mechanism of the wind turbine generator under the extreme weather condition, so that even if the future extreme weather is accurately predicted by numerical weather forecast, the power loss caused by the protective shutdown of the wind turbine generator cannot be counted in the power prediction result. The specific setting of the environmental protection of the wind turbine generator is related to the power change process of the wind power plant in the extreme weather event.
Example 1
As shown in fig. 3, a method for predicting and correcting wind power of a power grid under extreme weather conditions specifically includes the following steps:
step S1, starting a correction process through extreme weather information contained in the conventional weather forecast;
step S2, forecasting future extreme weather and influence of the future extreme weather on the forecasting power of the wind turbine generator based on the numerical weather forecast factors of the temperature and the humidity of the wind turbine generator;
(except for wind speed, wind direction and air pressure directly related to wind resources, numerical weather forecast elements such as temperature and humidity should be introduced to forecast future extreme weather and influence of the future extreme weather on forecast power of a wind turbine generator) collector end weather historical cases, an extreme weather historical database is established, future extreme weather events are identified by adopting an identified event identification method, and weather index forecast values are corrected;
searching similar events in an extreme weather historical database according to three basic characteristic quantities (shown in figure 1) of the extreme weather prediction duration, the weather element index change direction and the weather element index change amplitude;
correcting the predicted weather index based on the actual change process of the weather index in the similar event;
step S3, extreme weather types are judged, if the weather is strong wind, wind speed prediction unidirectional deviation correction is carried out, an actual power characteristic curve is fitted to optimize a wind resource-power conversion model, if the weather is cold tide, the actual power characteristic curve is directly fitted to optimize the wind resource-power conversion model, wherein the fitting of the actual power characteristic curve to optimize the wind resource-power conversion model specifically comprises the following steps:
fitting to obtain an actual power characteristic curve of the wind turbine generator, filtering abnormal operation state points (power limiting points, fault points and the like, as shown in figure 2) 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;
step S4, correcting the extreme weather condition power grid wind power prediction by combining the environment protection setting and the self-grid-connection setting, and finally outputting a correction result, wherein the extreme weather condition power grid wind power prediction 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 multi-gear automatic shutdown/recovery protection fixed values are set corresponding to extreme operation environments;
meanwhile, the wind turbine generator is also provided with a manual recovery mode, and after the environmental condition is recovered and the running requirement is met, the wind turbine generator prompts a wind power plant operator to start a fan in a manual mode to be connected with the grid for power generation;
and correcting the extreme weather power prediction result aiming at different wind power plants and wind power plants of different models by combining the numerical weather forecast and the specific setting of the wind power plant environment protection. And the specific setting of environmental protection comprises an extreme weather condition protection fixed value, action time and a recovery mode.
Example 2
By adopting the method in the embodiment 1, aiming at the low-temperature shutdown event of the north power grid in 1 month in 2019, the original power prediction curve reported by the wind power plant is corrected in different links based on numerical weather forecast data and wind power plant power prediction data and in combination with the statistical law of the low-temperature shutdown event of the north power grid in the past year, and the whole grid power prediction correction result is further calculated.
The result of correcting the predicted power curve of the wind farm 24 hours before and after the low-temperature shutdown is shown in fig. 4. At night 21:30 before cooling, the wind power plant inorganic unit stops, and predicted power is optimized and corrected mainly through a wind resource-power conversion model link; 30, judging that the power of the whole field gradually falls by combining the low-temperature protection setting of the unit and the historical low-temperature shutdown data of the wind power plant, and keeping the power unchanged after the power is estimated to fall to 30MW (15% installed capacity) at 0; and before 12 noon in the next day, the predicted temperature of the wind power plant is still maintained below-25 ℃ throughout the day, the power generation recovery requirement is not met, and the power of the whole plant is judged to be kept unchanged at 30 MW.
Based on the specific data conditions of different wind power plants, the predicted power reported by all wind power plants in the north grid in the low-temperature shutdown event is corrected according to the steps, and the corrected predicted power curve of the whole grid is obtained by adding the corrected predicted power curves of the whole grid and is shown in fig. 5. The different correction ring internode boundary nodes are respectively the moment when the predicted air temperature of the wind farm in North Ji is firstly reduced to a unit low-temperature protection fixed value (18: 45 in the first day) and the moment when the predicted air temperature of the shut-down wind farm is firstly increased to the recovery operation temperature (10: 30 in the second day).
In conclusion, after error correction of each predicted link, the total network power prediction error is obviously reduced compared with that before correction.
The above description is only a preferred embodiment of the present invention, and it should be noted that, for those skilled in the art, several modifications and variations can be made without departing from the technical principle of the present invention, and these modifications and variations should also be regarded as the protection scope of the present invention.
Claims (7)
1. A method for predicting and correcting wind power of a power grid under extreme weather conditions is characterized by comprising the following steps:
1) starting a correction process through extreme weather information contained in the conventional weather forecast;
2) identifying, optimizing and correcting a numerical weather forecast based on the extreme weather event;
3) judging the extreme weather type, if the extreme weather type is strong wind, fitting an actual power characteristic curve to optimize a wind resource-power conversion model after correcting the wind speed prediction unidirectional deviation, and if the extreme weather type is cold tide, directly fitting the actual power characteristic curve to optimize the wind resource-power conversion model;
4) and correcting the power grid wind power prediction under the extreme weather condition by combining the environmental protection setting and the self-grid-connection setting, and finally outputting a correction result.
2. The extreme weather condition power grid wind power prediction correction method according to claim 1, characterized in that the numerical weather forecast is identified, optimized and corrected based on extreme weather events, specifically:
forecasting future extreme weather and influence of the future extreme weather on the forecasting power of the wind turbine generator based on the numerical weather forecast factors of the temperature and the humidity of the operation of the wind turbine generator;
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 a weather index predicted value;
searching for similar events in an extreme weather historical database according to three basic characteristic quantities, namely the extreme weather prediction duration, the weather element index change direction and the weather element index change amplitude;
the predicted weather indicator is corrected based on the actual course of change of the weather indicator in a similar event.
3. The method for predicting and correcting the wind power of the power grid under the extreme weather condition as recited in claim 1, wherein the fitting of the actual power characteristic curve optimizes a wind resource-power conversion model, and specifically comprises:
and (3) obtaining an actual power characteristic curve of the wind turbine generator set through fitting, filtering abnormal operation state points by using the wind speed-power scatter diagram, and optimizing a wind resource-power conversion model by using the actual power characteristic curve.
4. The extreme weather condition power grid wind power prediction correction method as claimed in claim 3, wherein the wind speed-power scatter diagram is drawn according to operation data.
5. The extreme weather condition grid wind power prediction correction method of claim 3, characterized in that the abnormal operation state points comprise a power limiting point and a fault point.
6. The extreme weather condition power grid wind power prediction correction method according to claim 1, characterized in that the extreme weather condition power grid wind power prediction is corrected in combination with environmental protection settings, specifically:
the wind turbine generator sets respectively correspond to different action time, and multi-gear automatic shutdown/recovery protection fixed values are set corresponding to extreme operation environments;
meanwhile, the wind turbine generator is also provided with a manual recovery mode, and after the environmental condition is recovered and the running requirement is met, the wind turbine generator prompts a wind power plant operator to start a fan in a manual mode to be connected with the grid for power generation;
and correcting the extreme weather power prediction result aiming at different wind power plants and wind power plants of different models by combining the numerical weather forecast and the specific setting of the wind power plant environment protection.
7. The extreme weather condition power grid wind power prediction correction method as claimed in claim 6, wherein the specific environment protection settings comprise an extreme weather condition protection fixed value, an action time and a recovery mode.
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| CN112801352A (en) * | 2021-01-15 | 2021-05-14 | 上海电力大学 | Power prediction method for cooperative control in offshore wind farm |
| CN112801429A (en) * | 2021-04-12 | 2021-05-14 | 湖南防灾科技有限公司 | Micro-terrain wind power calculation method, device and system |
| NL2033883A (en) * | 2022-12-30 | 2023-02-10 | State Grid Gansu Electric Power Co | A Wind Power Forecasting Method, System and Medium for Extremely Windy Weather |
| CN118036347A (en) * | 2024-04-11 | 2024-05-14 | 国电南瑞科技股份有限公司 | Wind power generation full-flow error tracing method and system suitable for extreme weather |
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