Assessment Methods and Devices for the Impact of Sustained High Temperatures on the Power Supply Capacity of New Energy Grids

Abstract

This invention provides a method, apparatus, equipment, and storage medium for assessing the impact of sustained high temperatures on the power supply capacity of renewable energy power grids. The method includes: acquiring historical temperature data of a target region, identifying extreme high-temperature events based on preset definition conditions, and acquiring corresponding historical power grid operation data during extreme high-temperature events; performing data mining based on the historical power grid operation data to establish power grid output and load models under different meteorological conditions; generating output and load curves under sustained high-temperature scenarios based on the power grid output and load models; and superimposing the output and load curves to form a net load curve; calculating preset evaluation indicators based on the output and load curves and the net load curve to obtain an evaluation result for assessing the power adequacy and peak-shaving capacity of the target region under sustained high-temperature scenarios. This invention can quickly and effectively assess the power adequacy and peak-shaving capacity of the power grid under sustained high temperatures.

Description

Technical Field

[0001] This invention relates to the field of power grid assessment technology, and in particular to an assessment method, apparatus, equipment and storage medium for assessing the impact of continuous high temperatures on the power supply capacity of new energy power grids. Background Technology

[0002] With the increasing penetration of new energy sources and the frequent occurrence of extreme weather events, the problem of insufficient power supply sufficiency in high-proportion new energy power systems during certain periods is becoming increasingly prominent. Compared with traditional power sources, wind power, photovoltaic power, and other new energy power generation are more susceptible to the impact of extreme weather events such as strong winds and high temperatures. Extreme weather disasters can lead to a sharp reduction in the output of wind and solar power and damage to power generation facilities, posing a risk of prolonged and large-scale power outages. Therefore, it is necessary to conduct research on the assessment and improvement technologies of new energy carrying capacity from the perspective of reliable power supply under extreme weather conditions.

[0003] Prolonged periods of high temperatures are more frequent in southern regions. These events are often accompanied by multiple factors, including increased load, reduced wind power output, and insufficient hydropower output, which can easily lead to insufficient power supply capacity in grids with a high proportion of renewable energy sources. However, currently, due to a lack of research on the output and load models of renewable energy units under prolonged high temperatures, it is difficult to generate extreme operating scenarios for the planned power grid. Furthermore, there is no complete process system for assessing the renewable energy carrying capacity of the power grid considering prolonged high-temperature events. Summary of the Invention

[0004] The present invention aims to provide a method, apparatus, equipment and storage medium for assessing the impact of sustained high temperature on the power supply capacity of new energy power grids, so as to solve the above-mentioned technical problems and thereby enable the assessment of the power supply capacity of new energy power grids under sustained high temperature.

[0005] To address the aforementioned technical problems, this invention provides a method for assessing the impact of sustained high temperatures on the power supply capacity of new energy power grids, comprising:

[0006] Acquire historical temperature data for the target region, identify extreme high-temperature events based on preset definition conditions, and acquire historical power grid operation data corresponding to the extreme high-temperature events.

[0007] Data mining is performed based on the historical power grid operation data to establish power grid output and load models under different weather conditions. Based on the power grid output and load models, output and load curves under the continuous high temperature scenario are generated, and the output and load curves are superimposed to form the net load curve.

[0008] Based on the output and load curves and the net load curve, preset evaluation indicators are calculated to obtain evaluation results for assessing the power sufficiency and peak-shaving capacity of the target region under continuous high-temperature scenarios.

[0009] Furthermore, the acquisition of historical temperature data for the target area and the determination of extreme high-temperature events based on preset definition conditions include:

[0010] Obtain historical data of daily maximum temperature in the target area, sort the historical data of daily maximum temperature from high to low, and determine the temperature threshold based on the preset percentage quantile.

[0011] Based on the time series of daily maximum temperatures, if the daily maximum temperature exceeds the temperature threshold for more than a preset number of consecutive days, it is determined that an extreme high temperature event has occurred.

[0012] Furthermore, the data mining based on the historical power grid operation data includes:

[0013] Using the annual maximum load as the load benchmark and the installed capacity of each power station as the new energy power benchmark, the historical load curve and the new energy power generation time series curve in the power grid operation history data are normalized to obtain the normalized curves for non-extreme weather periods and the normalized curves for extreme weather periods.

[0014] For each month with a high incidence of extreme weather, the daily average power output curve and the daily average load curve for the non-extreme weather period of that month are calculated one by one to obtain the daily average curve for the corresponding month.

[0015] For each of the extreme weather periods, the daily average power output curve and the daily average load curve of the power grid are calculated to obtain the corresponding daily average curve during the extreme high temperature event.

[0016] Based on the normalized curves of non-extreme weather periods in the months with high incidence of extreme weather, the average nighttime wind power output of each normalized curve was obtained.

[0017] Based on the normalized curves of the extreme weather periods, the daily average values ​​of each normalized curve were obtained.

[0018] Furthermore, the process of establishing power grid output and load models under different meteorological conditions, generating output and load curves for a sustained high-temperature scenario based on these models, and superimposing these output and load curves to form a net load curve includes:

[0019] The average daily load curve and photovoltaic daily power generation curve of the corresponding month during the extreme weather period are used as the load curve and photovoltaic curve before the sustained high temperature in the sustained high temperature scenario.

[0020] For the month corresponding to the occurrence of the sustained high temperature scenario, the daily power generation curve with the smallest nighttime wind power generation average among all historical data is taken as the wind power curve before the sustained high temperature scenario.

[0021] For historical samples during periods of sustained high temperatures, extreme events a and b with the largest daily peak and trough increases were selected respectively. The peak and trough values ​​of the extreme scenarios were set based on the average daily load peak and trough values ​​of the months in which extreme events a and b occurred. The load curve shape and peak and trough periods were kept unchanged, and the load curve during the sustained high temperatures was obtained by cubic spline interpolation.

[0022] For historical samples during periods of sustained high temperatures, the extreme event c with the smallest average daily curve peak value is selected, and the photovoltaic curve corresponding to the period of extreme event c is used to construct extreme photovoltaic scenarios.

[0023] For historical samples during periods of sustained high temperatures, the extreme event d with the smallest average daily curve mean is selected, and the wind power curve corresponding to the time period of extreme event d is used to construct extreme wind power scenarios.

[0024] The net load curve during the sustained high temperature period is calculated based on the load curve during the extreme photovoltaic scenario and the extreme wind power scenario.

[0025] The net electricity demand during the sustained high temperature period is determined based on the net load curve during the sustained high temperature period and the duration of the extreme high temperature event.

[0026] Furthermore, the preset evaluation indicators include power shortage indicators caused by insufficient power supply, power shortage indicators caused by insufficient upward peak regulation capacity, power loss indicators of new energy power generation caused by insufficient downward peak regulation capacity, and average duration indicators of insufficient regulation resources.

[0027] Furthermore, the power shortage index caused by insufficient power is determined based on the net power demand during the sustained high temperature period, the hydropower generation capacity, the thermal power installed capacity, the preset maintenance discount coefficient, the preset fuel supply discount coefficient, and the duration of the extreme high temperature event.

[0028] The calculation methods for the power shortage index caused by insufficient upward peak regulation capacity and the power loss index of new energy power generation caused by insufficient downward peak regulation capacity are as follows: the net load peak load value and valley load value are determined according to the net load curve during the continuous high temperature period, and the maximum operating capacity and minimum operating capacity are determined based on the minimum output coefficient and the backup coefficient, respectively. Then, the load shedding amount and wind and solar curtailment amount are statistically obtained based on the relationship between the maximum operating capacity, the minimum operating capacity and the operating capacity of the available conventional power source in the system.

[0029] The average duration of insufficient regulation resources is determined based on the ratio of the duration of insufficient regulation capacity to the number of times regulation capacity is insufficient during the duration of an extreme weather event.

[0030] This invention also provides an assessment device for the impact of sustained high temperatures on the power supply capacity of new energy power grids, comprising:

[0031] The event definition module is used to acquire historical temperature data of the target area, determine extreme high temperature events based on preset definition conditions, and acquire historical power grid operation data corresponding to the extreme high temperature events.

[0032] The model building module is used to perform data mining based on the historical data of the power grid operation, establish power grid output and load models under different weather conditions, generate output and load curves under the continuous high temperature scenario based on the power grid output and load models, and perform superposition calculation on the output and load curves to form a net load curve.

[0033] The indicator evaluation module is used to calculate preset evaluation indicators based on the output and load curves and the net load curve, and obtain evaluation results for evaluating the power sufficiency and peak-shaving capacity of the target area under continuous high temperature scenarios.

[0034] The present invention also provides a terminal device, including a processor and a memory storing a computer program, wherein the processor executes the computer program to implement the assessment method for the impact of continuous high temperature on the power supply capacity of the new energy grid as described in any one of the claims.

[0035] The present invention also provides a non-transitory computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the assessment method for the impact of continuous high temperature on the power supply capacity of the new energy grid as described in any one of the claims.

[0036] Compared with the prior art, the present invention has the following beneficial effects:

[0037] This invention provides a method, apparatus, equipment, and storage medium for assessing the impact of sustained high temperatures on the power supply capacity of renewable energy power grids. The method includes: acquiring historical temperature data of a target region, identifying extreme high-temperature events based on preset definition conditions, and acquiring corresponding historical power grid operation data during extreme high-temperature events; performing data mining based on the historical power grid operation data to establish power grid output and load models under different meteorological conditions; generating output and load curves under sustained high-temperature scenarios based on the power grid output and load models; and performing superposition calculations on the output and load curves to form a net load curve; calculating preset evaluation indicators based on the output and load curves and the net load curve to obtain an evaluation result for assessing the power adequacy and peak-shaving capacity of the target region under sustained high-temperature scenarios. This invention can quickly and effectively assess the power adequacy and peak-shaving capacity of the power grid under sustained high temperatures. Attached Figure Description

[0038] Figure 1 This is one of the flowcharts illustrating the assessment method for the impact of sustained high temperatures on the power supply capacity of new energy power grids provided by this invention.

[0039] Figure 2 This is the second flowchart of the assessment method for the impact of continuous high temperature on the power supply capacity of new energy power grids provided by the present invention;

[0040] Figure 3 This is a schematic diagram of the load shedding and wind / solar curtailment provided by the present invention;

[0041] Figure 4 This is a schematic diagram of the load curve of the region before sustained high temperatures, provided by the present invention.

[0042] Figure 5 This is a schematic diagram of the load curve for the region during a period of sustained high temperatures, provided by the present invention.

[0043] Figure 6 This is a schematic diagram of the photovoltaic curve of the region before the sustained high temperature provided by the present invention;

[0044] Figure 7 This is a schematic diagram of the photovoltaic curve in this region during a period of sustained high temperatures, provided by the present invention.

[0045] Figure 8 This is a schematic diagram of the normalized historical wind power curve for a certain day in August provided by the present invention;

[0046] Figure 9 This is a schematic diagram of the wind power curve in the region before the sustained high temperature provided by the present invention;

[0047] Figure 10 This is a schematic diagram of wind power curves in the region during a period of sustained high temperatures, provided by the present invention.

[0048] Figure 11 This is a schematic diagram of the net load curve for the region during a period of sustained high temperatures, provided by the present invention.

[0049] Figure 12 This invention provides a net load curve and a schematic diagram of the maximum and minimum load capacity during sustained high temperatures.

[0050] Figure 13 This is a schematic diagram of the structure of the assessment device for the impact of continuous high temperature on the power supply capacity of new energy power grids provided by the present invention. Detailed Implementation

[0051] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0052] Please see Figure 1 This invention provides a method for assessing the impact of sustained high temperatures on the power supply capacity of new energy power grids, which may include the following steps:

[0053] S1. Obtain historical temperature data for the target area, identify extreme high-temperature events based on preset definition conditions, and obtain historical power grid operation data corresponding to the extreme high-temperature events.

[0054] S2. Based on the historical data of the power grid operation, data mining is performed to establish power grid output and load models under different weather conditions. Based on the power grid output and load models, output and load curves under the continuous high temperature scenario are generated, and the output and load curves are superimposed to form a net load curve.

[0055] S3. Based on the output and load curves and the net load curve, calculate the preset evaluation indicators to obtain the evaluation results used to assess the power sufficiency and peak-shaving capacity of the target area under continuous high temperature scenarios.

[0056] In this embodiment of the invention, the step of acquiring historical temperature data of the target area and determining extreme high-temperature events based on preset definition conditions further includes:

[0057] Obtain historical data of daily maximum temperature in the target area, sort the historical data of daily maximum temperature from high to low, and determine the temperature threshold based on the preset percentage quantile.

[0058] Based on the time series of daily maximum temperatures, if the daily maximum temperature exceeds the temperature threshold for more than a preset number of consecutive days, it is determined that an extreme high temperature event has occurred.

[0059] In this embodiment of the invention, the data mining based on the historical power grid operation data further includes:

[0060] Using the annual maximum load as the load benchmark and the installed capacity of each power station as the new energy power benchmark, the historical load curve and the new energy power generation time series curve in the power grid operation history data are normalized to obtain the normalized curves for non-extreme weather periods and the normalized curves for extreme weather periods.

[0061] For each month with a high incidence of extreme weather, the daily average power output curve and the daily average load curve for the non-extreme weather period of that month are calculated one by one to obtain the daily average curve for the corresponding month.

[0062] For each of the extreme weather periods, the daily average power output curve and the daily average load curve of the power grid are calculated to obtain the corresponding daily average curve during the extreme high temperature event.

[0063] Based on the normalized curves of non-extreme weather periods in the months with high incidence of extreme weather, the average nighttime wind power output of each normalized curve was obtained.

[0064] Based on the normalized curves of the extreme weather periods, the daily average values ​​of each normalized curve were obtained.

[0065] In this embodiment of the invention, the step of establishing power grid output and load models under different meteorological conditions, generating output and load curves under a sustained high-temperature scenario based on the power grid output and load models, and performing superposition calculations on the output and load curves to form a net load curve includes:

[0066] The average daily load curve and photovoltaic daily power generation curve of the corresponding month during the extreme weather period are used as the load curve and photovoltaic curve before the sustained high temperature in the sustained high temperature scenario.

[0067] For the month corresponding to the occurrence of the sustained high temperature scenario, the daily power generation curve with the smallest nighttime wind power generation average among all historical data is taken as the wind power curve before the sustained high temperature scenario.

[0068] For historical samples during periods of sustained high temperatures, extreme events a and b with the largest daily peak and trough increases were selected respectively. The peak and trough values ​​of the extreme scenarios were set based on the average daily load peak and trough values ​​of the months in which extreme events a and b occurred. The load curve shape and peak and trough periods were kept unchanged, and the load curve during the sustained high temperatures was obtained by cubic spline interpolation.

[0069] For historical samples during periods of sustained high temperatures, the extreme event c with the smallest average daily curve peak value is selected, and the photovoltaic curve corresponding to the period of extreme event c is used to construct extreme photovoltaic scenarios.

[0070] For historical samples during periods of sustained high temperatures, the extreme event d with the smallest average daily curve mean is selected, and the wind power curve corresponding to the time period of extreme event d is used to construct extreme wind power scenarios.

[0071] The net load curve during the sustained high temperature period is calculated based on the load curve during the extreme photovoltaic scenario and the extreme wind power scenario.

[0072] The net electricity demand during the sustained high temperature period is determined based on the net load curve during the sustained high temperature period and the duration of the extreme high temperature event.

[0073] In this embodiment of the invention, the preset evaluation indicators further include power shortage indicators caused by insufficient power supply, power shortage indicators caused by insufficient upward peak regulation capacity, power loss indicators of new energy power generation caused by insufficient downward peak regulation capacity, and average duration indicators of insufficient regulation resources.

[0074] In this embodiment of the invention, the power shortage index caused by insufficient power is further determined based on the net power demand during the continuous high temperature period, the hydropower generation capacity, the thermal power installed capacity, the preset maintenance discount coefficient, the preset fuel supply discount coefficient, and the duration of the extreme high temperature event.

[0075] The calculation methods for the power shortage index caused by insufficient upward peak regulation capacity and the power loss index of new energy power generation caused by insufficient downward peak regulation capacity are as follows: the net load peak load value and valley load value are determined according to the net load curve during the continuous high temperature period, and the maximum operating capacity and minimum operating capacity are determined based on the minimum output coefficient and the backup coefficient, respectively. Then, the load shedding amount and wind and solar curtailment amount are statistically obtained based on the relationship between the maximum operating capacity, the minimum operating capacity and the operating capacity of the available conventional power source in the system.

[0076] The average duration of insufficient regulation resources is determined based on the ratio of the duration of insufficient regulation capacity to the number of times regulation capacity is insufficient during the duration of an extreme weather event.

[0077] Based on the above scheme, and to facilitate a better understanding of the assessment method for the impact of continuous high temperatures on the power supply capacity of new energy power grids provided in the embodiments of the present invention, the following detailed description is provided:

[0078] The calculation method for assessing the impact of sustained high-temperature extreme weather on the power supply capacity of a high-proportion renewable energy grid in this invention embodiment can be mainly divided into the following three steps: sample acquisition and modeling of sustained high-temperature extreme weather, generation of grid operation scenarios, and calculation of grid power supply capacity under these scenarios. The overall framework is as follows: Figure 2 As shown.

[0079] The calculation process for the impact of sustained high temperatures on the power grid's supply capacity mainly involves the following three steps:

[0080] 1. First, collect and analyze historical meteorological data, and combine it with the power grid operation to clearly define the time range of extreme high temperature events, distinguishing it from the concept in meteorology.

[0081] 2. The method for generating extreme scenarios is as follows: Based on the above event definitions, select historical power grid operation data that meet the conditions, perform data mining based on new energy output and load data, and establish wind power, photovoltaic, and load models under different meteorological conditions. On this basis, generate and select wind-solar-load curves under extreme scenarios, and further superimpose them to form a net load curve.

[0082] 3. The method for assessing the carrying capacity of the power grid for extreme weather events is as follows: different levels of evaluation indicators are selected, and the power shortage and upward / downward peak shaving capacity are assessed and indicators are calculated based on the net load curve of extreme scenarios generated in the previous step, so as to comprehensively assess the power supply capacity of the power grid.

[0083] The implementation process of the embodiments of the present invention will be described in detail below:

[0084] I. Definition and historical sample screening of persistent high-temperature extreme weather:

[0085] 1. Definition of persistent high-temperature extreme weather:

[0086] For a given region, obtain at least 5 years of historical daily maximum temperature data. Sort this temperature data from highest to lowest, and take the top 10% quantiles as the high-temperature threshold T. M，G Search for daily maximum temperature time series; if the daily maximum temperature is greater than T for more than 5 consecutive days... M，G If the extreme high temperature event is defined as a "sustained high temperature" extreme weather event, then power records from wind farms and photovoltaic power plants, as well as historical grid load records, will be collected during the selected period to form an initial data sample.

[0087] 2. Data preprocessing:

[0088] (1) First, take the annual maximum load P max Using the load benchmark and the installed capacity of each power station as the benchmark for photovoltaic and wind power, the time series curves of wind power and photovoltaic power generation and the load curve are normalized to obtain the normalized curve S for non-extreme weather periods. i (t), Normalized curve H during extreme weather periods i (t), (t=1, 2,..., n):

[0089]

[0090] (2) For the months with the highest incidence of extreme weather, calculate the daily average curves of photovoltaic power, wind power, and load during the non-extreme weather period of each month to obtain the daily average curve P for month i. i (t):

[0091]

[0092] Among them, Sij (t) represents the daily curves of photovoltaic power, wind power, and load on day j of month i.

[0093] (3) Calculate the average daily curves of photovoltaic power, wind power, and load for each of the historical extreme weather periods to obtain the daily average curve P for event a. a (t):

[0094]

[0095] Among them, H aj (t) represents the daily curves of photovoltaic power, wind power, and load on day j during extreme weather event a.

[0096] Therefore, the rate of change of the load peak and trough values ​​relative to normal conditions during the sustained high-temperature event a can be calculated as follows:

[0097]

[0098]

[0099] Among them, P imax P imin Let P be the average peak and trough values ​​of the load in month i, where the first day of event a occurs. amax P amin The average daily load peak and trough values ​​during the sustained high-temperature event a.

[0100] (3) Historical data S under normal conditions for the above months ij (t) Perform statistical analysis to calculate the average nighttime wind power output of the normalized curve for day j in month i:

[0101]

[0102] Since the data sampling interval is 15 minutes, t = 77 to 96, and 1 to 20 correspond to 7-12 at night and 12-5 at dawn, respectively.

[0103] (5) Historical data H for extreme weather periods i (t) Perform statistical analysis and calculate the daily average value of each curve:

[0104]

[0105] II. Generation of power grid operation scenarios and simulation of net load power sequence under continuous high temperature extreme weather:

[0106] 1) Before the sustained high temperatures:

[0107] Load and photovoltaic scenario generation: The average daily load curve P corresponding to the month in which the continuous high temperature extreme scenario occurs. Li (t), Photovoltaic daily power generation curve P Si(t) represents the load and photovoltaic curve before sustained high temperatures in extreme scenarios.

[0108] Wind power scenario generation: For the month i corresponding to the occurrence of the extreme scenario, take the average nighttime wind power generation P from all its historical data. avij Minimum daily power generation curve P Wi (t) represents the wind power curve before sustained high temperatures in extreme scenarios.

[0109] 2) During periods of sustained high temperatures:

[0110] Load scenario generation: For historical samples during periods of sustained high temperatures, the daily peak growth rate is taken respectively. Daily trough value growth rate The most extreme events are a and b. The peak and trough load values ​​for day j in the extreme scenario are set as follows:

[0111]

[0112] Where m and n are the number of days that events a and b last, respectively; Let P be the average daily peak and trough values ​​of the months in which events a and b occur. Maintaining the shape of the load curve and the peak and trough periods unchanged, cubic spline interpolation is used to derive the load curve P during the sustained high-temperature event. load (t).

[0113] Photovoltaic scene generation: For historical samples during periods of sustained high temperatures, the average daily curve P is taken. c (t) The extreme event c with the minimum peak value, and the photovoltaic curve during this period is used to construct the extreme photovoltaic scenario P. ph (t).

[0114] Wind power scenario generation: For historical samples during periods of sustained high temperatures, the average daily curve P is taken. d The extreme event d with the smallest mean (t) is used to construct the extreme wind power scenario P using the wind power curve during that period. wind (t).

[0115] 3) Calculate the net load curve P during the sustained high-temperature event. pl (t):

[0116] P pl (t)=P load (t)-P ph (t)-P wind (t) (9)

[0117] 4) Calculate the net electricity demand W during the period of sustained high temperature. load :

[0118]

[0119] Where T represents the duration of the extreme high-temperature event, measured in hours (h).

[0120] III. Analysis of the impact of sustained high temperatures on power grid supply capacity:

[0121] The following four indicators will be used to assess the impact of sustained high temperatures on the power grid's supply capacity:

[0122] (1) Power shortage caused by insufficient power: LEL EI ;

[0123] (2) Power shortage caused by insufficient upward peak regulation capability: LEL DI ;

[0124] (3) Electricity loss from renewable energy generation due to insufficient downward peak-shaving capacity: LER DI ;

[0125] (4) Flexible adjustment of the average duration of resource shortage: T SI ;

[0126] The following presents the analytical calculation method for the above indicators:

[0127] (1) Insufficient power assessment and index calculation:

[0128] Calculate W using the following formula loss :

[0129] W loss =W load -P wat ×TP heat ×C heat ×C re ×T (11)

[0130] Among them, W load Net electricity demand during extreme heat events; P wat P represents the amount of electricity that can be generated by hydropower. heat For thermal power installed capacity; C re C is the maintenance discount factor. heat is the fuel supply discount factor; T is the duration of the extreme high-temperature event. If W loss If the value is less than zero, then there is no insufficient power; take LEL. EI =0; if W loss If it is greater than zero, then take LEL. EI =W loss .

[0131] (2) Assessment and index calculation of insufficient upward / downward peak shaving capacity:

[0132] From the net load curve P pl (t) Determine the net peak load value P plmaxValley value P pl min The maximum power-on capacity P is determined according to the following formula. op max Minimum power-on capacity P op min :

[0133]

[0134] Among them, C min C is the minimum output coefficient. sp This is a reserve coefficient.

[0135] 1) If P op min ≤P op max And the system can be powered on using a conventional power supply with a capacity of P. norm ≥P op min Therefore, there is no problem with insufficient peak-shaving capacity. The system can utilize the conventional power supply's on-time capacity P. norm The following formula can be used to calculate:

[0136] P norm =P wat +P heat ×C heat ×C re (13)

[0137] 2) If P op min ≤P op max And the system can be powered on using a conventional power supply with a capacity of P. norm <P op min If we assume that the power supply is fully operational under normal conditions, we can calculate its maximum load capacity P. a max and minimum load capacity P n min :

[0138]

[0139] Among them, P op P represents the actual system startup capacity. op =P norm C min C is the minimum output coefficient. sp This is the reserve factor. The portion of the net load curve exceeding the maximum load capacity represents the load shedding caused by insufficient upward peak-shaving capacity. The portion below the minimum load capacity represents the wind and solar power curtailment caused by insufficient downward peak-shaving capacity. For example... Figure 3 As shown.

[0140] 3) If P op min >P op max And the system can be powered on using a conventional power supply with a capacity of P. norm ≥P op min Then, according to the minimum startup capacity P op min Power on the machine and calculate its minimum load capacity P. a minThe portion of the net load curve below it represents the amount of wind and solar power curtailment caused by insufficient downward peak-shaving capacity.

[0141] 4) If P op min >P op max And the system can be powered on using a conventional power supply with a capacity of P. norm <P op min If we assume that the power supply is fully operational under normal conditions, we can calculate its maximum load capacity P. a max and minimum load capacity P a min The portion of the net load curve exceeding the maximum load capacity represents the load shedding caused by insufficient upward peak-shaving capacity. The portion below the minimum load capacity represents the wind and solar power curtailment caused by insufficient downward peak-shaving capacity.

[0142] Summing the above-obtained load shedding amounts over the duration T of the extreme weather event yields the power shortage caused by insufficient upward peak shaving capacity: LEL DI Summing up the above-mentioned wind and solar curtailment amounts yields the electricity loss from renewable energy generation caused by insufficient downshaving capacity: LER DI .

[0143] (3) Within the duration T of the extreme weather event, sum the above-obtained out-of-bounds (insufficient regulation capacity) durations and divide by the number of out-of-bounds occurrences to obtain the average duration of insufficient flexible regulation resources: T SI .

[0144] The following specific examples illustrate this:

[0145] The following example, using a sustained high-temperature extreme scenario in a certain region in August 2025, illustrates the generation and assessment process of extreme weather event scenarios.

[0146] (1) Generation of power grid operation scenarios and simulation of net load power sequence under continuous high temperature extreme weather:

[0147] 1) Load scenario generation:

[0148] Using equation (3), the normalized total load curve mean for all non-sustained high-temperature periods in the region from 2018 to August 2021 was calculated. Multiplied by the maximum load of the planned high-temperature scheme in 2025, 8650MW, the following result was obtained: Figure 4 The curve shown is used for load scenarios before sustained high temperatures.

[0149] For historical samples during periods of sustained high temperatures, the daily peak growth rate was taken respectively. Daily trough value growth rate The two most extreme events are a and b. Event a lasts for 21 days, and event b lasts for 11 days. The peak load 11 days before event a is taken as the peak value of the extreme load scenario, and the trough value of event b is taken as the trough value. Preserving the shape of the load curve and the peak-to-trough periods, cubic spline interpolation is used to derive the load curve during the sustained high-temperature event, as shown below. Figure 5 As shown;

[0150] 2) Photovoltaic scene generation:

[0151] Using equation (3), the normalized total photovoltaic curve mean for all non-sustained high-temperature periods in the region from 2018 to August 2021 was calculated, and multiplied by the planned installed capacity of 28,000 MW in 2025, to obtain the following result. Figure 6 The curve shown is used for photovoltaic scenarios before sustained high temperatures.

[0152] Using equation (4), calculate the average daily curve P for all samples during periods of sustained high temperatures. c (t), where P c The peak value of (t) is minimum 0.55, and the event lasts for 13 days. The photovoltaic curve for this period is used to construct a photovoltaic scenario during an extreme event, such as... Figure 7 As shown;

[0153] 3) Wind power scene generation:

[0154] Historical wind power normalized curve S on August j 8j (t) such as Figure 8 As shown.

[0155] Using equation (6) for Figure 8 The average wind power output during the midnight and nighttime periods can be used to obtain P. av8j =0.41. Similarly, calculate the nighttime average of the daily wind power curves for August. Take P... av8j Minimum daily power generation curve P W8 (t), multiplied by the region's planned total installed wind power capacity of 25,100 MW by 2025, to obtain the wind power curve before the sustained high temperatures in the extreme scenario, such as Figure 9 As shown.

[0156] Using equation (4), the average daily curve P is calculated for each sample of a sustained high-temperature event. c (t), and then using equation (7) for the above curve P c (t) Find the mean P avh Take the extreme event with the smallest mean, which lasts for 11 days, and its P... avh =0.19. Multiply the normalized wind power curve during this event by the region's planned total installed wind power capacity of 25,100 MW by 2025 to obtain the wind power curve during periods of sustained high temperatures in extreme scenarios, such as... Figure 10 As shown.

[0157] 4) Net load curve:

[0158] A net load curve for 12 consecutive days can be generated from the above load, photovoltaic, and wind power scenarios, such as... Figure 11 As shown;

[0159] The net electricity demand during the period of sustained high temperatures in this region can be calculated using equation (10):

[0160] W load =17,681,591.04 MW·h.

[0161] (2) Analysis of the impact of sustained high temperatures on the power grid's supply capacity:

[0162] Power supply capacity analysis is performed based on the above net load curve. The hydropower generating capacity P is taken as an example. wat =18280MW, thermal power installed capacity P heat =75285MW, maintenance discount factor C re =0.9, fuel supply discount factor C heat =0.85, the duration of the extreme high temperature event is T=264h, and the expected value of the power abandonment due to insufficient power can be calculated from equation (11). loss =-2348887.56<0. Therefore, there is no insufficient battery in this scenario, LEL EI =0.

[0163] The peak load value P can be obtained from the net load curve. pl max =76167.38MW, valley load value P pl min =41450.03MW. Take the reserve factor C. sp =1.1, minimum output coefficient C min =0.5, and the maximum operating capacity P is calculated according to formula (12). op max =82900.06MW, minimum operating capacity P op min =83784.12MW, therefore P exists. op min >P op max .

[0164] Conventional unit operating capacity P norm =75873.03MW, therefore P norm <P op min Assuming the power supply is fully on as usual, i.e., taking P... op =P norm =75873.03MW. Its maximum load capacity P is calculated using equation (14). a max =68975.48MW, minimum load capacity P a min =37936.51MW.

[0165] Net load curve and maximum and minimum load conditions are as follows Figure 12 As shown, it can be calculated that:

[0166] Power shortage caused by insufficient upward peak regulation capability: LEL DI =106347.68MW·h;

[0167] There is insufficient upward peak shaving capacity; the average duration of resource shortage should be flexibly adjusted: T SI =3.10h;

[0168] There is no issue of insufficient downshaving capacity. The amount of electricity lost by renewable energy generation due to insufficient downshaving capacity is: LER DI =0.

[0169] Compared with existing technologies, this invention proposes a calculation method for assessing the impact of sustained high-temperature extreme weather on the power supply capacity of a high-proportion renewable energy power grid, filling a gap in the power supply capacity assessment process under sustained high temperatures. Based on the characteristics of power grid operation, this invention proposes a method for defining sustained high-temperature extreme weather and a corresponding method for screening and preprocessing historical power grid operation data. Adopting a data-driven modeling approach, it proposes a modeling method for the output characteristics and load of renewable energy units under sustained high-temperature extreme weather, used for generating extreme scenarios in the planning power grid. It also proposes a method for power supply capacity assessment and rapid calculation of indicators, which can quickly and effectively assess the power adequacy and upward / downward peak-shaving capabilities of the power grid under sustained high-temperature extreme weather scenarios.

[0170] It should be noted that the key points of the embodiments of the present invention mainly include:

[0171] (1) A calculation process for assessing the power supply capacity of the power grid under continuous high temperature extreme weather is proposed, and a method for determining the continuous high temperature extreme weather and preprocessing the source-load historical samples that affect the power supply capacity of the high proportion of new energy power grid is proposed; (2) A calculation process for assessing the power supply capacity of the power grid under continuous high temperature extreme weather is proposed, and a method for modeling and generating scenarios of new energy power and load under extreme high temperature conditions is proposed; (3) A method for calculating the power supply capacity index of the power grid based on the analytical net load curve and net power is proposed.

[0172] It should be noted that, for the sake of simplicity, the above methods or process embodiments are all described as a series of actions. However, those skilled in the art should understand that the embodiments of the present invention are not limited to the described order of actions, because according to the embodiments of the present invention, some steps can be performed in other orders or simultaneously. Furthermore, those skilled in the art should also understand that the embodiments described in the specification are all optional embodiments, and the actions involved are not necessarily essential to the embodiments of the present invention.

[0173] Please see Figure 13 This invention also provides an assessment device for the impact of sustained high temperatures on the power supply capacity of new energy power grids, comprising:

[0174] Event definition module 1 is used to acquire historical temperature data of the target area, determine extreme high temperature events based on preset definition conditions, and acquire historical power grid operation data corresponding to the extreme high temperature events.

[0175] Model building module 2 is used to perform data mining based on the historical data of the power grid operation, establish power grid output and load models under different weather conditions, generate output and load curves under the continuous high temperature scenario based on the power grid output and load models, and perform superposition calculation on the output and load curves to form a net load curve.

[0176] The indicator evaluation module 3 is used to calculate the preset evaluation indicators based on the output and load curves and the net load curve, and obtain the evaluation results for evaluating the power sufficiency and peak-shaving capacity of the target area under continuous high temperature scenarios.

[0177] It is understood that the above-described device embodiments correspond to the method embodiments of the present invention. The device for assessing the impact of continuous high temperature on the power supply capacity of the new energy power grid provided by the embodiments of the present invention can realize the assessment method for assessing the impact of continuous high temperature on the power supply capacity of the new energy power grid provided by any one of the method embodiments of the present invention.

[0178] The present invention also provides a non-transitory computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the assessment method for the impact of continuous high temperature on the power supply capacity of the new energy grid as described in any one of the claims.

[0179] It should be noted that the device embodiments described above are merely illustrative. The units described as separate components may or may not be physically separate, and the components shown as units may or may not be physical units; that is, they may be located in one place or distributed across multiple network units. Some or all of the modules can be selected to achieve the purpose of this embodiment according to actual needs. Furthermore, in the accompanying drawings of the device embodiments provided by this invention, the connection relationships between modules indicate that they have communication connections, which can be specifically implemented as one or more communication buses or signal lines. Those skilled in the art can understand and implement this without any creative effort.

[0180] Those skilled in the art will clearly understand that, for convenience and brevity, the specific working process of the device described above can be referred to the corresponding process in the foregoing method embodiments, and will not be repeated here.

[0181] The terminal device can be a desktop computer, laptop, handheld computer, or cloud server, etc. The terminal device may include, but is not limited to, a processor and a memory.

[0182] The processor can be a Central Processing Unit (CPU), or other general-purpose processors, digital signal processors (DSPs), application-specific integrated circuits (ASICs), field-programmable gate arrays (FPGAs), or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. A general-purpose processor can be a microprocessor or any conventional processor. The processor is the control center of the terminal device, connecting all parts of the terminal device via various interfaces and lines.

[0183] The memory can be used to store the computer program. The processor implements various functions of the terminal device by running or executing the computer program stored in the memory and calling data stored in the memory. The memory may mainly include a program storage area and a data storage area. The program storage area may store the operating system, at least one application program required for a function, etc.; the data storage area may store data created based on the use of the mobile phone, etc. In addition, the memory may include high-speed random access memory, and may also include non-volatile memory, such as hard disk, RAM, plug-in hard disk, smart media card (SMC), secure digital (SD) card, flash card, at least one disk storage device, flash memory device, or other volatile solid-state storage device.

[0184] The storage medium is a computer-readable storage medium, and the computer program is stored in the computer-readable storage medium. When executed by a processor, the computer program can implement the steps of the various method embodiments described above. The computer program includes computer program code, which can be in the form of source code, object code, executable file, or some intermediate form. The computer-readable medium can include: any entity or device capable of carrying the computer program code, recording media, USB flash drive, portable hard drive, magnetic disk, optical disk, computer memory, read-only memory (ROM), random access memory (RAM), electrical carrier signals, telecommunication signals, and software distribution media, etc. It should be noted that the content included in the computer-readable medium can be appropriately added or removed according to the requirements of legislation and patent practice in the jurisdiction. For example, in some jurisdictions, according to legislation and patent practice, the computer-readable medium does not include electrical carrier signals and telecommunication signals.

[0185] The above description represents the preferred embodiments of the present invention. It should be noted that those skilled in the art can make various improvements and modifications without departing from the principles of the present invention, and these improvements and modifications are also considered to be within the scope of protection of the present invention.

Claims

1. A method for assessing the impact of sustained high temperatures on the power supply capacity of new energy power grids, characterized in that, include: Acquire historical temperature data for the target region, identify extreme high-temperature events based on preset definition conditions, and acquire historical power grid operation data corresponding to the extreme high-temperature events. Data mining is performed based on the historical power grid operation data to establish power grid output and load models under different weather conditions. Based on the power grid output and load models, output and load curves under the continuous high temperature scenario are generated, and the output and load curves are superimposed to form the net load curve. Based on the output and load curves and the net load curve, preset evaluation indicators are calculated to obtain evaluation results for assessing the power sufficiency and peak-shaving capacity of the target region under continuous high-temperature scenarios. The process involves establishing power grid output and load models under different meteorological conditions, generating output and load curves for a sustained high-temperature scenario based on these models, and then superimposing these output and load curves to form a net load curve. The average daily load curve and photovoltaic daily power generation curve of the corresponding month during the extreme weather period are used as the load curve and photovoltaic curve before the sustained high temperature in the sustained high temperature scenario. For the month corresponding to the occurrence of the sustained high temperature scenario, the daily power generation curve with the smallest nighttime wind power generation average among all historical data is taken as the wind power curve before the sustained high temperature scenario. For historical samples during periods of sustained high temperatures, extreme events a and b with the largest daily peak and trough increases were selected respectively. The peak and trough values ​​of the extreme scenarios were set based on the average daily load peak and trough values ​​of the months in which extreme events a and b occurred. The load curve shape and peak and trough periods were kept unchanged, and the load curve during the sustained high temperatures was obtained by cubic spline interpolation. For historical samples during periods of sustained high temperatures, the extreme event c with the smallest average daily curve peak value is selected, and the photovoltaic curve corresponding to the period of extreme event c is used to construct extreme photovoltaic scenarios. For historical samples during periods of sustained high temperatures, the extreme event d with the smallest average daily curve mean is selected, and the wind power curve corresponding to the time period of extreme event d is used to construct extreme wind power scenarios. The net load curve during the sustained high temperature period is calculated based on the load curve during the extreme photovoltaic scenario and the extreme wind power scenario. The net electricity demand during the sustained high temperature period is determined based on the net load curve during the sustained high temperature period and the duration of the extreme high temperature event.

2. The method for assessing the impact of sustained high temperatures on the power supply capacity of new energy power grids according to claim 1, characterized in that, The acquisition of historical temperature data for the target area, and the determination of extreme high-temperature events based on preset definition conditions, includes: Obtain historical data of daily maximum temperature in the target area, sort the historical data of daily maximum temperature from high to low, and determine the temperature threshold based on the preset percentage quantile. Based on the time series of daily maximum temperatures, if the daily maximum temperature exceeds the temperature threshold for more than a preset number of consecutive days, it is determined that an extreme high temperature event has occurred.

3. The method for assessing the impact of sustained high temperatures on the power supply capacity of new energy power grids according to claim 1, characterized in that, The data mining based on the historical power grid operation data includes: Using the annual maximum load as the load benchmark and the installed capacity of each power station as the new energy power benchmark, the historical load curve and the new energy power generation time series curve in the power grid operation history data are normalized to obtain the normalized curves for non-extreme weather periods and the normalized curves for extreme weather periods. For each month with a high incidence of extreme weather, the daily average power output curve and the daily average load curve for the non-extreme weather period of that month are calculated one by one to obtain the daily average curve for the corresponding month. For each of the extreme weather periods, the daily average power output curve and the daily average load curve of the power grid are calculated to obtain the corresponding daily average curve during the extreme high temperature event. Based on the normalized curves of non-extreme weather periods in the months with high incidence of extreme weather, the average nighttime wind power output of each normalized curve was obtained. Based on the normalized curves of the extreme weather periods, the daily average values ​​of each normalized curve were obtained.

4. The method for assessing the impact of sustained high temperatures on the power supply capacity of new energy power grids according to claim 1, characterized in that, The preset evaluation indicators include the power shortage index caused by insufficient power supply, the power shortage index caused by insufficient upward peak regulation capacity, the power loss index of new energy power generation caused by insufficient downward peak regulation capacity, and the average duration index of insufficient regulation resources.

5. The method for assessing the impact of sustained high temperatures on the power supply capacity of new energy power grids according to claim 4, characterized in that, The power shortage index caused by insufficient power is determined based on the net power demand during the sustained high temperature period, the hydropower generation capacity, the thermal power installed capacity, the preset maintenance discount coefficient, the preset fuel supply discount coefficient, and the duration of the extreme high temperature event. The calculation methods for the power shortage index caused by insufficient upward peak regulation capacity and the power loss index of new energy power generation caused by insufficient downward peak regulation capacity are as follows: the net load peak load value and valley load value are determined according to the net load curve during the continuous high temperature period, and the maximum operating capacity and minimum operating capacity are determined based on the minimum output coefficient and the backup coefficient, respectively. Then, the load shedding amount and wind and solar curtailment amount are statistically obtained based on the relationship between the maximum operating capacity, the minimum operating capacity and the operating capacity of the available conventional power source in the system. The average duration of insufficient regulation resources is determined based on the ratio of the duration of insufficient regulation capacity to the number of times regulation capacity is insufficient during the duration of an extreme weather event.

6. An assessment device for the impact of continuous high temperatures on the power supply capacity of new energy power grids, characterized in that, The assessment method for the impact of sustained high temperatures on the power supply capacity of new energy power grids, as described in any one of claims 1 to 5, is adopted; the assessment device includes: The event definition module is used to acquire historical temperature data of the target area, determine extreme high temperature events based on preset definition conditions, and acquire historical power grid operation data corresponding to the extreme high temperature events. The model building module is used to perform data mining based on the historical data of the power grid operation, establish power grid output and load models under different weather conditions, generate output and load curves under the continuous high temperature scenario based on the power grid output and load models, and perform superposition calculation on the output and load curves to form a net load curve. The indicator evaluation module is used to calculate preset evaluation indicators based on the output and load curves and the net load curve, and obtain evaluation results for evaluating the power sufficiency and peak-shaving capacity of the target area under continuous high temperature scenarios.

7. The assessment device for the impact of continuous high temperature on the power supply capacity of new energy power grids according to claim 6, characterized in that, The acquisition of historical temperature data for the target area, and the determination of extreme high-temperature events based on preset definition conditions, includes: Obtain historical data of daily maximum temperature in the target area, sort the historical data of daily maximum temperature from high to low, and determine the temperature threshold based on the preset percentage quantile. Based on the time series of daily maximum temperatures, if the daily maximum temperature exceeds the temperature threshold for more than a preset number of consecutive days, it is determined that an extreme high temperature event has occurred.

8. A terminal device, comprising a processor and a memory storing a computer program, characterized in that, When the processor executes the computer program, it implements the assessment method for the impact of continuous high temperature on the power supply capacity of the new energy grid as described in any one of claims 1 to 5.

9. A non-transitory computer-readable storage medium having a computer program stored thereon, characterized in that, When executed by a processor, the computer program implements the assessment method for the impact of sustained high temperatures on the power supply capacity of new energy power grids as described in any one of claims 1 to 5.

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