CN115982953A - Method and device for evaluating influence of continuous high temperature on power supply capacity of new energy power grid - Google Patents
Method and device for evaluating influence of continuous high temperature on power supply capacity of new energy power grid Download PDFInfo
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Abstract
The invention provides a method, a device, equipment and a storage medium for evaluating the influence of continuous high temperature on the power supply capacity of a new energy power grid, wherein the method comprises the following steps: acquiring historical temperature data of a target area, determining an extreme high-temperature event based on preset defined conditions, and acquiring corresponding historical power grid operation data during the extreme high-temperature event; data mining is carried out based on power grid operation historical data, power grid output and load models under different meteorology are respectively established, output and load curves under a continuous high-temperature scene are generated based on the power grid output and load models, and the output and load curves are subjected to superposition operation to form a net load curve; and calculating a preset evaluation index based on the output and load curve and the net load curve to obtain an evaluation result for evaluating the electric quantity abundance and the peak regulation capacity of the target area under the continuous high-temperature scene. The method can quickly and effectively evaluate the electric quantity abundance and the peak regulation capacity of the power grid under continuous high temperature.
Description
Technical Field
The invention relates to the technical field of power grid evaluation, in particular to a method, a device, equipment and a storage medium for evaluating the influence of continuous high temperature on the power supply capacity of a new energy power grid.
Background
With the increase of new energy permeability and the frequent occurrence of extreme weather, the problem of insufficient power supply abundance of a high-proportion new energy power system in a local time period is increasingly prominent. Compared with a traditional power supply, the wind power, photovoltaic and other new energy power generation are more easily affected by extreme weather such as strong wind and high temperature, and extreme meteorological disasters can cause the output of wind, photovoltaic and other new energy to be reduced sharply and power generation facilities to be damaged, so that the power generation system has the risk of long-time large-area power failure. Therefore, it is necessary to start from the perspective of reliable power supply under extreme weather conditions to develop new energy bearing capacity assessment and improve technical research.
High temperature weather of longer duration is more prevalent in southern regions. The continuous high-temperature event often acts simultaneously along with multiple factors such as increased load, reduced wind power output, insufficient water power output and the like, and the power supply capacity of a high-proportion new energy power grid is easy to be insufficient. However, at present, due to the lack of corresponding research on the output model and the load model of the new energy unit under continuous high temperature, it is difficult to generate an extreme operation scene under a planned power grid. And for the evaluation of the bearing capacity of the new energy of the power grid considering the continuous high-temperature event, a complete flow system does not exist.
Disclosure of Invention
The invention aims to provide a method, a device, equipment and a storage medium for evaluating the influence of continuous high temperature on the power supply capacity of a new energy power grid so as to solve the technical problems, and thus, the power supply capacity of the new energy power grid at the continuous high temperature can be evaluated.
In order to solve the technical problem, the invention provides an evaluation method for the influence of continuous high temperature on the power supply capacity of a new energy power grid, which comprises the following steps:
acquiring historical temperature data of a target area, determining an extreme high-temperature event based on preset defined conditions, and acquiring corresponding historical power grid operation data during the extreme high-temperature event;
performing data mining based on the power grid operation historical data, respectively establishing power grid output and load models under different meteorology, generating output and load curves under a continuous high-temperature scene based on the power grid output and load models, and performing superposition operation on the output and load curves to form a net load curve;
and calculating a preset evaluation index based on the output and load curve and the net load curve to obtain an evaluation result for evaluating the electric quantity abundance and the peak regulation capacity of the target area under the continuous high-temperature scene.
Further, the acquiring of historical temperature data of the target area and determining the extreme high temperature event based on preset defined conditions includes:
acquiring daily highest air temperature historical data of a target area, sequencing the daily highest air temperature historical data from high to low, and determining a temperature threshold value based on a preset percentage quantile;
and based on the daily maximum air temperature time sequence, if the daily maximum air temperature exceeding the continuous preset days is greater than the temperature threshold, determining that the extremely high temperature event occurs.
Further, the performing data mining based on the power grid operation historical data includes:
respectively carrying out normalization processing on a historical load curve and a new energy power generation time sequence curve in the power grid operation historical data by taking the annual maximum load as a load reference value and the installed capacity of each station as a new energy power reference value to obtain a non-extreme meteorological period normalization curve and an extreme meteorological period normalization curve;
corresponding to the extreme weather high monthly degrees, calculating a power grid output daily average curve and a load daily average curve of the monthly non-extreme weather period one by one to obtain a daily average curve corresponding to the monthly degrees;
calculating a power grid output daily average curve and a load daily average curve one by one for all extreme meteorological periods to obtain a corresponding daily average curve during an extreme high-temperature event;
counting non-extreme meteorological time normalization curves based on the extreme meteorological high-monthly degree to obtain the nighttime wind power output mean value of each normalization curve;
and carrying out statistics based on the extreme weather period normalization curves to obtain the daily average value of each normalization curve.
Further, the respectively establishing power grid output and load models under different meteorology, generating output and load curves under a continuous high-temperature scene based on the power grid output and load models, and performing superposition operation on the output and load curves to form a net load curve includes:
taking an average daily load curve and a photovoltaic daily power generation curve of a month corresponding to the extreme meteorological period as a load curve and a photovoltaic curve before continuous high temperature in a continuous high-temperature scene;
for the corresponding month degree of the continuous high-temperature scene, taking the daily power generation curve with the minimum mean value of the night wind power generation in all historical data as the wind power curve before continuous high temperature in the continuous high-temperature scene;
for historical samples in a continuous high-temperature period, respectively taking an extreme event a and an extreme event b, wherein the daily peak value increase amplitude and the daily valley value increase amplitude are maximum, and setting an extreme scene load peak valley value based on the average daily load peak and valley value of the months in which the extreme event a and the extreme event b occur; keeping the load curve form and the peak-valley period unchanged, and obtaining a load curve in a continuous high-temperature period by adopting cubic spline interpolation;
taking an extreme event c with the minimum average daily curve peak value for historical samples in the continuous high-temperature period, and using a photovoltaic curve corresponding to the extreme event c in a time period to construct an extreme photovoltaic scene;
for historical samples in the continuous high-temperature period, taking an extreme event d with the minimum average daily curve mean value, and using a wind power curve of a time period corresponding to the extreme event d to construct an extreme wind power scene;
calculating a continuous high temperature period net load curve based on the continuous high temperature period load curve, the extreme photovoltaic scene and the extreme wind power scene;
determining a high temperature duration net charge demand based on the high temperature duration net load curve and the duration of the extreme high temperature event.
Further, the preset evaluation indexes comprise a power shortage index caused by power shortage, a power shortage index caused by peak-up regulation capacity shortage, a new energy power generation loss power index caused by peak-down regulation capacity shortage and an average duration index of resource shortage.
Further, the index of the power shortage caused by power shortage is determined based on the net power demand during the continuous high temperature period, the water and power generating capacity, the installed capacity of the thermal power plant, a preset overhaul discount coefficient, a preset fuel supply discount coefficient and the duration of the extremely high temperature event;
the calculation mode of the power shortage index caused by insufficient upward peak shaving capacity and the new energy power generation loss index caused by insufficient downward peak shaving capacity is as follows: determining a net load peak load value and a net load valley load value according to the net load curve during the continuous high temperature, respectively determining a maximum starting capacity and a minimum starting capacity based on a minimum output coefficient and a backup coefficient, and then carrying out load shedding amount and wind and light discarding amount statistics based on the size relationship among the maximum starting capacity, the minimum starting capacity and the starting capacity of a system available conventional power supply;
the adjustment resource shortage average duration index is determined based on the ratio of the adjustment capacity shortage duration to the adjustment capacity shortage times within the extreme meteorological event duration.
The invention also provides an evaluation device for the influence of continuous high temperature on the power supply capacity of the new energy power grid, which comprises the following steps:
the event definition module is used for acquiring historical temperature data of a target area, determining an extreme high-temperature event based on preset definition conditions, and acquiring corresponding historical power grid operation data during the extreme high-temperature event;
the model construction module is used for carrying out data mining on the basis of the power grid operation historical data, respectively establishing power grid output and load models under different meteorology, generating output and load curves under a continuous high-temperature scene on the basis of the power grid output and load models, and carrying out superposition operation on the output and load curves to form a net load curve;
and the index evaluation module is used for calculating a preset evaluation index based on the output and load curve and the net load curve to obtain an evaluation result for evaluating the electric quantity abundance and the peak regulation capacity of the target area under the continuous high-temperature scene.
The invention also provides terminal equipment which comprises a processor and a memory, wherein the memory is used for storing the computer program, and the processor is used for realizing the evaluation method for the influence of any continuous high temperature on the power supply capacity of the new energy power grid when executing the computer program.
The invention also provides a non-transitory computer-readable storage medium on which a computer program is stored, which, when being executed by a processor, implements any one of the above methods for assessing the influence of sustained high temperatures on the power supply capacity of a new energy grid.
Compared with the prior art, the invention has the following beneficial effects:
the invention provides a method, a device, equipment and a storage medium for evaluating the influence of continuous high temperature on the power supply capacity of a new energy power grid, wherein the method comprises the following steps: acquiring historical temperature data of a target area, determining an extreme high-temperature event based on preset defined conditions, and acquiring corresponding historical power grid operation data during the extreme high-temperature event; performing data mining based on the power grid operation historical data, respectively establishing power grid output and load models under different meteorology, generating output and load curves under a continuous high-temperature scene based on the power grid output and load models, and performing superposition operation on the output and load curves to form a net load curve; and calculating a preset evaluation index based on the output and load curve and the net load curve to obtain an evaluation result for evaluating the electric quantity abundance and the peak regulation capacity of the target area under the continuous high-temperature scene. The method can quickly and effectively evaluate the electric quantity abundance and the peak regulation capacity of the power grid under continuous high temperature.
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FIG. 1 is a schematic flow chart of a method for evaluating the influence of continuous high temperature on the power supply capacity of a new energy power grid, provided by the invention;
FIG. 2 is a second schematic flowchart of the method for evaluating the influence of sustained high temperature on the power supply capability of the new energy grid according to the present invention;
FIG. 3 is a schematic diagram of the load shedding amount and the wind and light abandoning amount provided by the present invention;
FIG. 4 is a schematic view of the load curve of the area before the high temperature is continuously provided by the present invention;
FIG. 5 is a schematic view of the load curve of the area during the continuous high temperature period provided by the present invention;
FIG. 6 is a schematic view of the photovoltaic curve of the area before the sustained high temperature is provided by the present invention;
FIG. 7 is a schematic view of the photovoltaic curve provided by the present invention for the region during a sustained high temperature period;
FIG. 8 is a schematic diagram of a normalized curve of historical wind power in the area on a certain day of 8 months;
FIG. 9 is a schematic view of a wind power curve of the area before the continuous high temperature is provided by the present invention;
FIG. 10 is a schematic view of a wind power curve provided by the present invention in the area during a continuous high temperature period;
FIG. 11 is a graphical illustration of the net load curve for the area during sustained high temperatures provided by the present invention;
FIG. 12 is a graph illustrating the net load curve and maximum and minimum loadable during sustained high temperature conditions provided by the present invention;
fig. 13 is a schematic structural diagram of the device for evaluating the influence of the sustained high temperature on the power supply capacity of the new energy power grid provided by the invention.
Detailed Description
The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings in the embodiments of the present invention, and it is obvious that the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
Referring to fig. 1, an embodiment of the present invention provides a method for evaluating an influence of a sustained high temperature on a power supply capability of a new energy grid, which may include:
s1, obtaining historical temperature data of a target area, determining an extreme high-temperature event based on preset defining conditions, and obtaining corresponding historical power grid operation data during the extreme high-temperature event;
s2, data mining is carried out based on the power grid operation historical data, power grid output and load models under different meteorology are respectively established, output and load curves under a continuous high-temperature scene are generated based on the power grid output and load models, and the output and load curves are subjected to superposition operation to form a net load curve;
and S3, calculating a preset evaluation index based on the output and load curve and the net load curve, and obtaining an evaluation result for evaluating the electric quantity abundance and the peak regulation capacity of the target area under the continuous high-temperature scene.
In this embodiment of the present invention, further, the obtaining historical data of air temperature of the target area, and determining the extreme high temperature event based on a preset defined condition includes:
acquiring the daily highest air temperature historical data of a target area, sequencing the daily highest air temperature historical data from high to low, and determining a temperature threshold value based on a preset percentage quantile;
and based on the daily maximum air temperature time sequence, if the daily maximum air temperature exceeding the continuous preset days is greater than the temperature threshold, determining that the extremely high temperature event occurs.
In an embodiment of the present invention, further, the performing data mining based on the power grid operation historical data includes:
respectively carrying out normalization processing on a historical load curve and a new energy power generation time sequence curve in the power grid operation historical data by taking the annual maximum load as a load reference value and the installed capacity of each station as a new energy power reference value to obtain a non-extreme meteorological period normalization curve and an extreme meteorological period normalization curve;
corresponding to the extreme weather high monthly degrees, calculating a power grid output daily average curve and a load daily average curve of the monthly non-extreme weather period one by one to obtain a daily average curve corresponding to the monthly degrees;
calculating a power grid output daily average curve and a load daily average curve one by one for all extreme meteorological periods to obtain a corresponding daily average curve during an extreme high-temperature event;
counting non-extreme meteorological time normalization curves based on the extreme meteorological high-monthly degree to obtain the nighttime wind power output mean value of each normalization curve;
and carrying out statistics based on the extreme weather period normalization curves to obtain the daily average value of each normalization curve.
In this embodiment of the present invention, further, the respectively establishing power grid output and load models in different meteorology, generating output and load curves in a continuous high temperature scene based on the power grid output and load models, and performing a superposition operation on the output and load curves to form a net load curve includes:
taking an average daily load curve and a photovoltaic daily power generation curve of a month corresponding to the extreme meteorological period as a load curve and a photovoltaic curve before continuous high temperature in a continuous high-temperature scene;
for the corresponding month degree of the continuous high-temperature scene, taking a daily power generation curve with the minimum mean value of the night wind power generation in all historical data as a wind power curve before continuous high temperature in the continuous high-temperature scene;
for historical samples in a continuous high-temperature period, respectively taking an extreme event a and an extreme event b, wherein the daily peak value increase amplitude and the daily valley value increase amplitude are maximum, and setting an extreme scene load peak valley value based on the average daily load peak and valley value of the months in which the extreme event a and the extreme event b occur; keeping the load curve form and the peak-valley time period unchanged, and obtaining a load curve in a continuous high-temperature period by adopting cubic spline interpolation;
taking an extreme event c with the minimum average daily curve peak value for historical samples in the continuous high-temperature period, and using a photovoltaic curve corresponding to the extreme event c in a time period to construct an extreme photovoltaic scene;
for historical samples in the continuous high-temperature period, taking an extreme event d with the minimum average daily curve mean value, and using a wind power curve corresponding to the extreme event d in a time period to construct an extreme wind power scene;
calculating a net load curve during continuous high temperature based on the load curve during continuous high temperature, the extreme photovoltaic scene and the extreme wind power scene;
determining a high temperature duration net charge demand based on the high temperature duration net load curve and the duration of the extreme high temperature event.
In the embodiment of the present invention, further, the preset evaluation indexes include an insufficient power supply index caused by insufficient power, an insufficient power supply index caused by insufficient peak shaving capacity, an electric quantity index of new energy power generation loss caused by insufficient peak shaving capacity, and an average duration index of insufficient regulated resources.
In the embodiment of the present invention, further, the index of the power shortage amount caused by power shortage is determined based on the net power demand during the sustained high temperature, the water and power generation amount, the thermal power installed capacity, a preset overhaul discount coefficient, a preset fuel supply discount coefficient and the duration of the extreme high temperature event;
the calculation mode of the power shortage index caused by insufficient up peak regulation capacity and the new energy power generation loss index caused by insufficient down peak regulation capacity is as follows: determining a net load peak load value and a net load valley load value according to the net load curve during the continuous high temperature, respectively determining a maximum starting capacity and a minimum starting capacity based on a minimum output coefficient and a backup coefficient, and then carrying out load shedding amount and wind and light discarding amount statistics based on the size relationship among the maximum starting capacity, the minimum starting capacity and the starting capacity of a system available conventional power supply;
the adjustment resource shortage average duration index is determined based on the ratio of the adjustment capacity shortage duration to the adjustment capacity shortage times within the extreme meteorological event duration.
Based on the above scheme, in order to better understand the method for evaluating the influence of the continuous high temperature on the power supply capacity of the new energy power grid provided by the embodiment of the invention, the following detailed description is provided:
the calculation method for evaluating the influence of the continuous high-temperature extreme weather on the power supply capacity of the high-proportion new energy power grid in the embodiment of the invention can be mainly divided into the following three links, namely sample acquisition and modeling of the continuous high-temperature extreme weather, generation of a power grid operation scene and measurement and calculation of the power supply capacity of the power grid in the scene, and the overall thought framework is shown in FIG. 2.
The calculation process for the influence of continuous high-temperature weather on the power supply capacity of the power grid mainly comprises the following three steps:
1. historical meteorological data are collected and analyzed, period range definition of extreme high-temperature events is definitely given by combining with the operation condition of a power grid, and the method is distinguished from the concept in the meteorology.
2. The method for generating the extreme scene comprises the following steps: according to the event definition, historical period power grid operation data meeting the conditions are screened out, data mining is carried out on the basis of new energy output and load data, and wind power, photovoltaic and load models under different meteorological conditions are established. And generating and screening wind-light-load curves under extreme scenes on the basis, and further superposing to form a net load curve.
3. The method for evaluating the bearing capacity of the planned power grid for the extreme meteorological event comprises the following steps: and screening out evaluation indexes of different layers, carrying out power shortage and upward/downward peak regulation capability evaluation and index calculation based on the extreme scene net load curve generated in the last step, and comprehensively evaluating the power supply capability of the power grid.
The following describes an implementation process of the embodiment of the present invention specifically:
1. definition of continuous high-temperature extreme weather and historical sample screening treatment:
1. definition of continuous high temperature extreme weather:
for a given region, daily maximum temperature history data is obtained for at least 5 years or more. Sorting the temperature data from top to bottom, taking the top 10% quantile point as a high temperature threshold value T M，G . Searching the time sequence of the maximum temperature of the day, if the maximum temperature of the day is more than T for more than 5 consecutive days M，G Then, a "sustained high temperature" extreme weather event is defined. And collecting corresponding power records of the wind power plant and the photovoltaic power station and power grid load historical records during the screened duration period of the extreme high temperature event to form an initial data sample.
2. Data preprocessing:
(1) First of all with annual maximum load P max The wind power and photovoltaic power generation power time series curve and the load curve are normalized by taking the load reference value and the installed capacity of each station as the photovoltaic and wind power reference value to obtain a non-extreme meteorological period normalization curve S i (t) extreme weather period normalization curve H i (t)，(t＝1，2，...，n)：
(2) Calculating average photovoltaic, wind power and load daily curves of the month in the non-extreme meteorological period one by one for the extreme meteorological high monthly degree to obtain a daily average curve P of i months i (t)：
Wherein S is ij And (t) is a photovoltaic, wind power and load daily curve of i, month and j days.
(3) Calculating average photovoltaic, wind power and load daily curves one by one in all historical extreme meteorological periods to obtain a daily average curve P in an event a period a (t)：
Wherein H aj And (t) is a photovoltaic, wind power and load daily curve of the j th day during the extreme meteorological event a.
Therefore, the load peak and valley change rate of the continuous high-temperature event a relative to the normal condition can be calculated as follows:
wherein, P imax 、P imin Average load peak-to-valley value, P, for month i of the first day of occurrence of event a amax 、P amin The average daily load peak, trough during sustained high temperature event a.
(3) History data S of normal condition for the above-mentioned month ij (t) carrying out statistics, and calculating the night wind power output mean value of the i-month and j-day normalization curve:
since the data sampling interval is 15min, t = 77-96, and t = 1-20 respectively correspond to 7-12 hours at night and 12-5 hours at morning.
(5) Historical data H for extreme weather periods i (t) performing statistics, and calculating the daily average value of each curve:
2. generating a power grid operation scene and simulating a net load power sequence under continuous high-temperature extreme weather:
1) Before the continuous high temperature:
load and photovoltaic scene generation: average daily load curve P of corresponding month for continuous high-temperature extreme scene Li (t) photovoltaic daily power generation curve P Si (t) as load, photovoltaic curve, in extreme scenes, up to a high temperature.
Generating a wind power scene: for the corresponding month i of the extreme scene, taking the average value P of the wind power generation at night in all historical data avij Minimum daily power generation curve P Wi And (t) taking the curve as a wind power curve before continuous high temperature in an extreme scene.
2) And (3) lasting for a high-temperature period:
load scene generation: for historical samples in the continuous high-temperature period, the daily peak value increase amplitude is respectively taken
The increasing amplitude of the daily trough value>
The largest extreme events a, b. Setting the load peak-valley values of the jth day of the extreme scene as follows:
wherein m and n are the continuous days of the events a and b respectively;
for the month of occurrence of event a, bThe peak and the trough of the daily load are averaged. Keeping the load curve form and the peak-valley time section unchanged, and obtaining the load curve P in the occurrence period of the continuous high-temperature event by adopting cubic spline interpolation load (t)。
Photovoltaic scene generation: taking the average daily curve P of historical samples in the continuous high-temperature period c (t) extreme event c with minimum peak value, with which time interval the photovoltaic curve is used to construct an extreme photovoltaic scene P ph (t)。
Generating a wind power scene: taking an average daily curve P of historical samples during continuous high temperature d (t) extreme event d with minimum mean value, and using the time interval wind power curve to construct extreme wind power scene P wind (t)。
3) Calculating a net load curve P during a sustained high temperature event pl (t)：
P pl (t)＝P load (t)-P ph (t)-P wind (t) (9)
4) Calculating net electrical energy demand W during sustained high temperature load ：
Where T is the duration of the extreme high temperature event in units of h.
3. Analyzing the influence of continuous high-temperature weather on the power supply capacity of the power grid:
the influence of continuous high-temperature weather on the power supply capacity of the power grid is evaluated by adopting the following four indexes:
(1) Power shortage due to insufficient power: LEL EI ；
(2) Insufficient power supply due to insufficient up-peak regulation capacity: LEL DI ；
(3) The power loss of the new energy caused by insufficient down-peak regulation capacity is as follows: LER DI ；
(4) Flexibly adjusting the average duration of resource shortage: t is SI ；
The analytical calculation method of the above-mentioned index is proposed as follows:
(1) And (3) insufficient electric quantity evaluation and index calculation:
calculate W as follows loss ：
W loss ＝W load -P wat ×T-P heat ×C heat ×C re ×T (11)
Wherein, W load Net charge demand during extreme high temperature events; p is wat The water and electricity can generate electricity; p is heat The installed thermal power capacity; c re Discounting coefficients for overhaul; c heat A fuel offer discount coefficient; and T is the duration of the extremely high temperature event. If W loss If less than zero, no power is sufficient, and LEL is taken EI =0; if W loss If it is greater than zero, then take LEL EI ＝W loss 。
(2) Evaluation and index calculation of insufficient peak-shaving capacity in upward/downward direction:
from net load curve P pl (t) determination of the payload peak load value P plmax The valley value P pl min Respectively determining the maximum boot capacity P according to the following formula op max Minimum boot capacity P op min ：
Wherein, C min Is the minimum output coefficient; c sp Is a spare coefficient.
1) If P op min ≤P op max And the system can use the starting capacity P of the conventional power supply norm ≥P op min And then the problem of insufficient peak regulation capability does not exist. Wherein, the system can use the starting capacity P of the conventional power supply norm Can be calculated using the following formula:
P norm ＝P wat +P heat ×C heat ×C re (13)
2) If P op min ≤P op max And the system can use the starting capacity P of the conventional power supply norm ＜P op min Calculating the maximum loadable P according to the consideration of the normal power supply full start a max And minimum loadable P n min ：
Wherein, P op Is the actual boot capacity of the system, here P op ＝P norm ；C min Is the minimum output coefficient; c sp Is a spare coefficient. The part of the net load curve that exceeds the maximum loadable load is the load shedding amount caused by insufficient peak-shaving capacity. The part which is less than the minimum loadable part is the wind and light abandoning quantity caused by insufficient down-peak regulation capability. As shown in fig. 3.
3) If P op min ＞P op max And the system can use the starting capacity P of the conventional power supply norm ≥P op min According to the minimum boot capacity P op min Starting up the computer and calculating the minimum loadable P a min The part of the net load curve lower than the net load curve is the wind curtailment quantity caused by insufficient down-peak regulation capacity.
4) If P op min ＞P op max And the system can use the starting capacity P of the conventional power supply norm ＜P op min Calculating the maximum loadable P according to the consideration of the normal power supply full start a max And minimum loadable P a min . The part of the net load curve that exceeds the maximum loadable load is the load shedding amount caused by insufficient peak-shaving capacity. The part which is less than the minimum loadable part is the wind and light abandoning quantity caused by insufficient down-peak regulation capability.
Within the duration time T of the extreme meteorological event, the load shedding quantities obtained above are summed, and the power supply shortage quantity caused by insufficient peak shaving capacity can be obtained: LEL DI . Summing the obtained abandoned wind and abandoned light quantities to obtain the new energy power generation loss electric quantity caused by insufficient down-peak regulation capacity: LER DI 。
(3) And in the duration time T of the extreme meteorological event, summing the obtained out-of-range (insufficient regulation capacity) duration time, and dividing by the out-of-range times to obtain the average duration time of the flexible regulation resource insufficiency: t is SI 。
The following examples are given by way of illustration:
the process of generating and evaluating extreme weather event scenes is described below with an example of an extreme scene of continuous high temperature in 2025 months in a certain area.
(1) Generating a power grid operation scene and simulating a net load power sequence in continuous high-temperature extreme weather:
1) Load scene generation:
calculating the mean value of the normalized total load curve of all the non-continuous high-temperature periods in 8 months in 2018-2021 in the area by using the formula (3), and multiplying the mean value by the maximum load 8650MW of the planned high-temperature scheme in 2025 to obtain a curve shown in FIG. 4, wherein the curve is used for a load scene before continuous high temperature;
for historical samples in the continuous high temperature period, the daily peak increasing amplitude is taken respectively
The increasing amplitude of the daily trough value>
The largest extreme events a, b. Wherein the event a duration is 21 days and the event b duration is 11 days. The peak value of the load 11 days before the event a is taken as the peak value of the extreme load scene, and the valley value of the event b is taken as the valley value. Keeping the load curve form and the peak-valley time period unchanged, and obtaining the load curve during the occurrence period of the continuous high-temperature event by adopting cubic spline interpolation, as shown in FIG. 5;
2) Photovoltaic scene generation:
calculating the mean value of the normalized total photovoltaic curves of all the non-continuous high-temperature periods in 8 months in 2018-2021 in the region by using the formula (3), and multiplying the mean value by the programmed installed capacity 28000MW in 2025 to obtain the curve shown in the figure 6, wherein the curve is used for photovoltaic scenes before continuous high temperature;
averaging daily curves P for all samples during sustained high temperature using equation (4) c (t) wherein P c (t) peak value was minimum 0.55 and duration of the event was 13 days. Using the time-interval photovoltaic curve to construct a photovoltaic scene during an extreme event, as shown in fig. 7;
3) Generating a wind power scene:
calendar of 8 months and j daysSteer wind power normalization curve S 8j (t) is shown in FIG. 8.
The wind power output at night time in FIG. 8 is averaged by equation (6) to obtain P av8j =0.41. Similarly, the nighttime mean of the 8-month-daily wind power curve is calculated. Get P av8j Minimum daily power generation curve P W8 (t) and multiplying by the 2025 year wind power planning total installation 25100MW in the region as a wind power curve before continuous high temperature in an extreme scene, as shown in FIG. 9.
Averaging daily curves P for each sustained high temperature event sample using equation (4) c (t) reuse of equation (7) for the curve P c (t) averaging P avh . The minimum extreme event was taken, which lasted 11 days, and P avh =0.19. The wind power normalization curve during the event is multiplied by the 25100MW of the 2025 year wind power planning total installation in the region, and the wind power normalization curve is used as a wind power curve during the continuous high temperature period in the extreme scene, and is shown in FIG. 10.
4) Net load curve:
a net load curve lasting for 12 days can be generated according to the load, the photovoltaic and the wind power scenes, as shown in fig. 11;
the net electricity demand of the area during the continuous high temperature period can be calculated by the formula (10):
W load ＝17681591.04MW·h。
(2) Analyzing the influence of continuous high-temperature weather on the power supply capacity of the power grid:
and analyzing the power supply capacity based on the net load curve. Generated energy P of water and electricity wat =18280MW, thermal power installed capacity P heat =75285MW, overhaul discount coefficient C re =0.9, fuel supply discount coefficient C heat =0.85 and duration of the extreme high temperature event T =264h, and a power shortage electricity abandonment expected value W can be calculated by equation (11) loss = 2348887.56 < 0. Can know that the LEL does not exist under the condition of insufficient electric quantity in the scene EI ＝0。
Peak load value P is obtained from net load curve pl max =76167.38MW, valley charge value P pl min =41450.03MW. Taking a spare coefficient C sp =1.1, minimum coefficient of contribution C min =0.5, the maximum boot capacity P is calculated according to equation (12) op max =82900.06MW, minimum boot-up capacity P op min =83784.12MW, known as P op min ＞P op max 。
Starting capacity P of conventional unit norm =75873.03MW, so there is P norm ＜P op min . Taking P out of consideration when the power supply is fully started up op ＝P norm =75873.03MW. The maximum loadable P is calculated from equation (14) a max =68975.48MW, minimum loadable P a min ＝37936.51MW。
The net load curve and the maximum and minimum loadable case are shown in fig. 12, and can be calculated as follows:
insufficient power supply due to insufficient up-peak regulation capacity: LEL DI ＝106347.68MW·h；
The situation that the upward peak regulation capacity is insufficient exists, the average duration time of resource shortage is flexibly adjusted: t is SI ＝3.10h；
The situation that the downward peak regulation capacity is insufficient does not exist, and the power loss of the new energy source caused by the insufficient downward peak regulation capacity is as follows: LER DI ＝0。
Compared with the prior art, the embodiment of the invention provides a calculation method for evaluating the influence of continuous high-temperature extreme weather on the power supply capacity of a high-proportion new energy power grid, and fills the blank of a power supply capacity evaluation process system of the power grid at the continuous high temperature. The method provides a definition method of continuous high-temperature extreme weather and a corresponding screening and preprocessing method of power grid operation historical data according to the power grid operation characteristics. By adopting a data-driven modeling thought, a new energy unit output characteristic model and a load model modeling method under continuous high-temperature extreme weather are provided for planning the generation of extreme scenes under a power grid; the method for evaluating the power supply capacity and quickly calculating the indexes can quickly and effectively evaluate the power abundance and the up/down peak regulation capacity of the power grid in the continuous high-temperature extreme weather scene.
It should be noted that the key points of the embodiment of the present invention mainly include:
(1) Providing a calculation flow of power grid power supply capacity evaluation in continuous high-temperature extreme weather, and providing a continuous high-temperature extreme weather judgment and source-load historical sample pretreatment method which influences the power supply capacity of the high-proportion new energy power grid; (2) Providing a calculation process for evaluating the power supply capacity of the power grid under continuous high-temperature extreme weather, and providing a new energy power and load modeling and scene generation method under the extreme high-temperature condition; (3) A power grid power supply capacity index calculation method based on analysis of a net load curve and net electric quantity is provided.
It should be noted that, for simplicity of description, the above method or flow embodiment is described as a series of acts, but those skilled in the art should understand that the embodiment of the present invention is not limited by the described acts, as some steps can be performed in other orders or simultaneously according to the embodiment of the present invention. Further, those skilled in the art will appreciate that the embodiments described in the specification are exemplary embodiments and that no single embodiment is necessarily required by the inventive embodiments.
Referring to fig. 13, an embodiment of the present invention further provides an apparatus for evaluating an influence of a sustained high temperature on a power supply capability of a new energy grid, including:
the event definition module 1 is used for acquiring historical temperature data of a target area, determining an extreme high-temperature event based on preset definition conditions, and acquiring corresponding historical power grid operation data during the extreme high-temperature event;
the model construction module 2 is used for performing data mining based on the power grid operation historical data, respectively establishing power grid output and load models under different meteorology, generating output and load curves under a continuous high-temperature scene based on the power grid output and load models, and performing superposition operation on the output and load curves to form a net load curve;
and the index evaluation module 3 is used for calculating a preset evaluation index based on the output and load curve and the net load curve, and obtaining an evaluation result for evaluating the electric quantity abundance and the peak regulation capacity of the target area under the continuous high-temperature scene.
It can be understood that the above apparatus item embodiments correspond to the method item embodiments of the present invention, and the apparatus for evaluating an influence of a sustained high temperature on a power supply capability of a new energy power grid provided by the embodiments of the present invention can implement the method for evaluating an influence of a sustained high temperature on a power supply capability of a new energy power grid provided by any one of the method item embodiments of the present invention.
The invention also provides a non-transitory computer-readable storage medium on which a computer program is stored, which, when being executed by a processor, implements any one of the above methods for assessing the influence of sustained high temperatures on the power supply capacity of a new energy grid.
It should be noted that the above-described device embodiments are merely illustrative, where the units described as separate parts may or may not be physically separate, and the parts displayed as units may or may not be physical units, may be located in one place, or may be distributed on multiple network units. Some or all of the modules may be selected according to actual needs to achieve the purpose of the solution of the present embodiment. In addition, in the drawings of the embodiment of the apparatus provided by the present invention, the connection relationship between the modules indicates that there is a communication connection between them, and may be specifically implemented as one or more communication buses or signal lines. One of ordinary skill in the art can understand and implement without inventive effort.
It can be clearly understood by those skilled in the art that, for convenience and brevity, the specific working process of the apparatus described above may refer to the corresponding process in the foregoing method embodiment, and is not described herein again.
The terminal device may be a desktop computer, a notebook, a palm computer, a cloud server, or other computing devices. The terminal device may include, but is not limited to, a processor, a memory.
The Processor may be a Central Processing Unit (CPU), other general purpose Processor, a Digital Signal Processor (DSP), an Application Specific Integrated Circuit (ASIC), an off-the-shelf Programmable Gate Array (FPGA) or other Programmable logic device, discrete Gate or transistor logic, discrete hardware components, etc. The general-purpose processor may be a microprocessor or the processor may be any conventional processor or the like, said processor being the control center of said terminal device, and various interfaces and lines are used to connect the various parts of the whole terminal device.
The memory may be used to store the computer program, and the processor may implement various functions of the terminal device by executing or executing the computer program stored in the memory and calling data stored in the memory. The memory may mainly include a storage program area and a storage data area, wherein the storage program area may store an operating system, an application program required for at least one function, and the like; the storage data area may store data created according to the use of the mobile phone, and the like. In addition, the memory may include high speed random access memory, and may also include non-volatile memory, such as a hard disk, a memory, a plug-in hard disk, a Smart Media Card (SMC), a Secure Digital (SD) Card, a Flash memory Card (Flash Card), at least one magnetic disk storage device, a Flash memory device, or other volatile solid state storage device.
The storage medium is a computer-readable storage medium, in which the computer program is stored, which computer program, when being executed by a processor, is adapted to carry out the steps of the above-mentioned respective method embodiments. Wherein the computer program comprises computer program code, which may be in the form of source code, object code, an executable file or some intermediate form, etc. The computer-readable medium may include: any entity or device capable of carrying the computer program code, recording medium, usb disk, removable hard disk, magnetic disk, optical disk, computer Memory, read-Only Memory (ROM), random Access Memory (RAM), electrical carrier wave signals, telecommunications signals, software distribution medium, and the like. It should be noted that the computer readable medium may contain content that is subject to appropriate increase or decrease as required by legislation and patent practice in jurisdictions, for example, in some jurisdictions, computer readable media does not include electrical carrier signals and telecommunications signals as is required by legislation and patent practice.
While the foregoing is directed to the preferred embodiment of the present invention, it will be understood by those skilled in the art that various changes and modifications may be made without departing from the spirit and scope of the invention.
Claims (10)
1. A method for evaluating influence of continuous high temperature on power supply capacity of a new energy power grid is characterized by comprising the following steps:
acquiring historical temperature data of a target area, determining an extreme high-temperature event based on preset defined conditions, and acquiring corresponding historical power grid operation data during the extreme high-temperature event;
performing data mining based on the power grid operation historical data, respectively establishing power grid output and load models under different meteorology, generating output and load curves under a continuous high-temperature scene based on the power grid output and load models, and performing superposition operation on the output and load curves to form a net load curve;
and calculating a preset evaluation index based on the output and load curve and the net load curve, and obtaining an evaluation result for evaluating the electric quantity abundance and the peak regulation capacity of the target area under the continuous high-temperature scene.
2. The method for evaluating the influence of the continuous high temperature on the power supply capacity of the new energy power grid according to claim 1, wherein the step of obtaining historical temperature data of the target area and determining the extreme high temperature event based on preset defined conditions comprises the following steps:
acquiring daily highest air temperature historical data of a target area, sequencing the daily highest air temperature historical data from high to low, and determining a temperature threshold value based on a preset percentage quantile;
and based on the daily maximum air temperature time sequence, if the daily maximum air temperature exceeding the continuous preset days is greater than the temperature threshold, determining that the extremely high temperature event occurs.
3. The method for evaluating the influence of the continuous high temperature on the power supply capacity of the new energy power grid according to claim 1, wherein the data mining based on the power grid operation historical data comprises the following steps:
respectively carrying out normalization processing on a historical load curve and a new energy power generation time sequence curve in the power grid operation historical data by taking the annual maximum load as a load reference value and the installed capacity of each station as a new energy power reference value to obtain a non-extreme meteorological period normalization curve and an extreme meteorological period normalization curve;
corresponding to the extreme weather high monthly degrees, calculating a power grid output daily average curve and a load daily average curve of the monthly non-extreme weather period one by one to obtain a daily average curve corresponding to the monthly degrees;
calculating a power grid output daily average curve and a load daily average curve one by one for all extreme meteorological periods to obtain a corresponding daily average curve during an extreme high-temperature event;
counting non-extreme meteorological time normalization curves based on the extreme meteorological high-monthly degree to obtain the nighttime wind power output mean value of each normalization curve;
and carrying out statistics based on the extreme weather period normalization curves to obtain the daily average value of each normalization curve.
4. The method according to claim 3, wherein the method for evaluating the influence of the sustained high temperature on the power supply capacity of the new energy power grid comprises the steps of respectively establishing power grid output and load models under different meteorology, generating output and load curves under a sustained high temperature scene based on the power grid output and load models, and performing superposition operation on the output and load curves to form a net load curve, and comprises the following steps:
taking an average daily load curve and a photovoltaic daily power generation curve of a month corresponding to the extreme meteorological period as a load curve and a photovoltaic curve before continuous high temperature in a continuous high-temperature scene;
for the corresponding month degree of the continuous high-temperature scene, taking the daily power generation curve with the minimum mean value of the night wind power generation in all historical data as the wind power curve before continuous high temperature in the continuous high-temperature scene;
for historical samples in a continuous high-temperature period, respectively taking an extreme event a and an extreme event b, wherein the daily peak value increase amplitude and the daily valley value increase amplitude are maximum, and setting an extreme scene load peak valley value based on the average daily load peak and valley value of the months in which the extreme event a and the extreme event b occur; keeping the load curve form and the peak-valley time period unchanged, and obtaining a load curve in a continuous high-temperature period by adopting cubic spline interpolation;
taking an extreme event c with the minimum average daily curve peak value for historical samples in the continuous high-temperature period, and using a photovoltaic curve corresponding to the extreme event c in a time period to construct an extreme photovoltaic scene;
for historical samples in the continuous high-temperature period, taking an extreme event d with the minimum average daily curve mean value, and using a wind power curve of a time period corresponding to the extreme event d to construct an extreme wind power scene;
calculating a continuous high temperature period net load curve based on the continuous high temperature period load curve, the extreme photovoltaic scene and the extreme wind power scene;
determining a high temperature duration net charge demand based on the high temperature duration net load curve and the duration of the extreme high temperature event.
5. The method for evaluating the influence of the sustained high temperature on the power supply capacity of the new energy power grid according to claim 4, wherein the preset evaluation indexes comprise an insufficient power supply capacity index caused by insufficient power, an insufficient power supply capacity index caused by insufficient peak-up regulation capacity, a new energy power generation loss capacity index caused by insufficient peak-down regulation capacity and an average duration index of insufficient regulation resources.
6. The method for evaluating the influence of the sustained high temperature on the power supply capacity of the new energy power grid according to claim 5, wherein the index of the power shortage caused by the power shortage is determined based on the net power demand during the sustained high temperature, the water power generation amount, the thermal power installation capacity, a preset overhaul discount coefficient, a preset fuel supply discount coefficient and the duration of the extreme high temperature event;
the calculation mode of the power shortage index caused by insufficient up peak regulation capacity and the new energy power generation loss index caused by insufficient down peak regulation capacity is as follows: determining a net load peak load value and a net load valley load value according to the net load curve during the continuous high temperature, respectively determining a maximum starting capacity and a minimum starting capacity based on a minimum output coefficient and a backup coefficient, and then carrying out load shedding amount and wind and light discarding amount statistics based on the size relationship among the maximum starting capacity, the minimum starting capacity and the starting capacity of a system available conventional power supply;
and the average duration index of insufficient adjusting resources is determined based on the ratio of the duration of insufficient adjusting capacity to the number of times of insufficient adjusting capacity within the duration of the extreme meteorological event.
7. An evaluation device for influence of continuous high temperature on power supply capacity of a new energy power grid is characterized by comprising:
the event definition module is used for acquiring historical temperature data of a target area, determining an extreme high-temperature event based on preset definition conditions, and acquiring corresponding historical power grid operation data during the extreme high-temperature event;
the model construction module is used for carrying out data mining on the basis of the power grid operation historical data, respectively establishing power grid output and load models under different meteorology, generating output and load curves under a continuous high-temperature scene on the basis of the power grid output and load models, and carrying out superposition operation on the output and load curves to form a net load curve;
and the index evaluation module is used for calculating a preset evaluation index based on the output and load curve and the net load curve, and obtaining an evaluation result for evaluating the electric quantity abundance and the peak regulation capacity of the target area under the continuous high-temperature scene.
8. The device for evaluating the influence of the continuous high temperature on the power supply capacity of the new energy power grid according to claim 7, wherein the step of obtaining historical temperature data of the target area and determining the extreme high temperature event based on preset defined conditions comprises the following steps:
acquiring the daily highest air temperature historical data of a target area, sequencing the daily highest air temperature historical data from high to low, and determining a temperature threshold value based on a preset percentage quantile;
and based on the daily maximum air temperature time sequence, if the daily maximum air temperature exceeding the continuous preset days is greater than the temperature threshold, determining that the extremely high temperature event occurs.
9. Terminal device comprising a processor and a memory storing a computer program, characterized in that the processor, when executing the computer program, implements the method for assessing the impact of sustained high temperatures on the power supply capacity of a new energy grid according to any one of claims 1 to 6.
10. A non-transitory computer-readable storage medium, on which a computer program is stored, wherein the computer program, when executed by a processor, implements the method for assessing the impact of sustained high temperatures on the power supply capability of a new energy grid according to any one of claims 1 to 6.
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| CN116796926A (en) * | 2023-06-30 | 2023-09-22 | 国家电网有限公司华东分部 | Low-voltage side new energy resource aggregation capacity assessment method and device, medium and equipment |
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| CN116796926A (en) * | 2023-06-30 | 2023-09-22 | 国家电网有限公司华东分部 | Low-voltage side new energy resource aggregation capacity assessment method and device, medium and equipment |
| CN116796926B (en) * | 2023-06-30 | 2024-03-15 | 国家电网有限公司华东分部 | Low-voltage side new energy resource aggregation capacity assessment method and device, medium and equipment |
| CN116629457A (en) * | 2023-07-24 | 2023-08-22 | 国网浙江省电力有限公司经济技术研究院 | Long-period energy storage optimal configuration method and device for sustainable airless scene |
| CN116629457B (en) * | 2023-07-24 | 2023-10-20 | 国网浙江省电力有限公司经济技术研究院 | Long-period energy storage optimal configuration method and device for sustainable airless scene |
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