Priority-considered standby resource scheduling method and priority-considered standby resource scheduling system

Abstract

The invention discloses a priority-considered standby resource scheduling method and system, and relates to the technical field of power systems, and the method comprises the steps: inputting at least two standby input evaluation indexes and an initial weight; and calculating the standby level of each standby resource under the unit capacity, taking the initial weight as the current weight, carrying out iteration on the current weight, and when an iteration ending condition is met, outputting a standby resource scheduling scheme. According to the method, the priority sequence factors of different standby resources are calculated based on the weight and the standby level in each round of iteration, the standby resources can be sorted based on the adaptation degree of each standby resource and the scheduling requirement, the standby resources with the high adaptation degree are put into standby preferentially, and in addition, the scheduling efficiency is improved. In addition, the weight is adjusted on the basis of the total cost actually generated by the standby resource scheduling scheme, the calculated priority sequence factor can practically reflect the adaptation degree of the standby resources and the scheduling requirement by correcting the weight, and the reasonability of the scheduling scheme is improved.

Description

Technical Field

[0001] The present invention relates to the technical field of power systems, and in particular to a priority-based backup resource scheduling method and system. Background Art

[0002] The access of new energy sources such as wind and solar power and random loads such as electric vehicles has increased the volatility and uncertainty of the operation of the new power system. Therefore, it is necessary to make full use of the coordinated complementarity of multiple backup resources to improve the flexibility and stability of the operation of the new power system.

[0003] Traditional reserve resource scheduling mainly considers the matching between required power and reserve capacity. However, in new power systems, the types of reserve resources are more diverse, and the properties of different reserve resources are significantly different. For example, the carbon emissions of traditional units and new energy units are quite different. However, the traditional reserve resource scheduling method does not consider the different adaptability of different reserve resources to scheduling needs, nor does it assign different scheduling priorities to different reserve resources. Therefore, it is unable to give full play to the energy structure advantages of multiple reserve resources to improve the quality of reserve resource deployment. Summary of the Invention

[0004] The purpose of the embodiments of the present invention is to provide a priority-based backup resource scheduling method and system, which can improve the adaptability of the backup resource scheduling scheme and the scheduling requirements, thereby improving the quality of backup resource delivery.

[0005] To achieve the above objectives, an embodiment of the present invention further provides a priority-based backup resource scheduling method, comprising:

[0006] Enter at least two backup investment evaluation indicators and the initial weight of the current time segment;

[0007] Calculate the per-unit value of the reserve investment evaluation index of each reserve resource under unit capacity;

[0008] The initial weight is used as the current weight, and the current weight is iterated. When the iteration end condition is met, the backup resource scheduling solution is output; wherein, in each round of iteration:

[0009] Based on the current weight and the per-unit value of the backup input evaluation index, the priority order factor of each backup resource under unit capacity is calculated; according to the priority order indicated by the priority order factor, under the constraint of the backup resource timing model, a backup resource scheduling plan is generated; based on the backup resource scheduling plan and the backup input evaluation index, the total cost is calculated; when the total cost does not meet the iteration end condition, the current weight is updated to perform the next round of iteration; wherein, the total cost is associated with each backup input evaluation index.

[0010] As an improvement to the above solution, the initial weight is the current weight of the last iteration of the previous time segment.

[0011] As an improvement to the above solution, the standby investment evaluation indicators include operating cost, response time and carbon emissions.

[0012] As an improvement to the above scheme, the per-unit value of the standby investment evaluation index is the ratio of the standby investment evaluation index value of each of the standby resources under unit capacity to a predetermined benchmark value; wherein, the benchmark value is the maximum value of the standby investment evaluation index values of each of the standby resources under unit capacity.

[0013] As an improvement to the above solution, the current weight is updated based on the following objective function:

[0014]

[0015] in, The per-unit value represents the total operating cost of the backup resource scheduling scheme; The per-unit value represents the total carbon emissions of the backup resource scheduling scheme; Indicates the per-unit value of the total response time of the backup resource scheduling solution.

[0016] As an improvement to the above solution, the per-unit value of each target parameter is calculated in the following manner, wherein the target parameter is any one of the total operating cost, the total response time, and the total carbon emissions:

[0017] When the current time segment is not the first time segment, the ratio of the target parameter to the target parameter at the end of the iteration of the previous time segment is used as the per-unit value of the target parameter;

[0018] When the current time segment is the first time segment, the ratio of the target parameter to the target parameter of the initial backup resource scheduling scheme is used as the per-unit value of the target parameter; wherein the initial backup resource scheduling scheme is a backup resource scheduling scheme calculated based on the initial weight.

[0019] As an improvement to the above solution, the total operating cost is calculated as follows:

[0020]

[0021] Among them, F 1,t represents the total operating cost of the backup resource scheduling scheme for time segment t; μ i,t represents the operating cost coefficient of the i-th backup resource being put into standby at time segment t; represents the average power of the i-th backup resource in the t-time period; ΔT trepresents the duration of the t-th time segment; M represents the total number of standby resources put into standby during the t-th time segment;

[0022] The total carbon emissions are calculated as follows:

[0023] F 2,t =μ i,t F 1,t

[0024] Among them, F 2,t represents the total carbon emissions of the backup resource scheduling scheme in time segment t; μ i,t represents the carbon emission coefficient of the i-th backup resource in time segment t; F 1,t represents the total operating cost of the backup resource scheduling scheme in time segment t;

[0025] The total response time is calculated as follows:

[0026] F 3,t =max(K i,t T i,t ),i∈[1,M]

[0027] Among them, F 3,t represents the total response time of the backup resource scheduling scheme in the time segment t; max() represents the maximum value function; K i,t Indicates the standby flag, K i,t =1 means it is put into standby mode, K i,t =0 means exit standby; T i,t It represents the response time of the i-th backup resource being put into backup in time segment t; M represents the total number of backup resources put into backup in time segment t.

[0028] As an improvement to the above solution, when the backup resource is a load-side backup resource, the corresponding backup resource timing model is as follows:

[0029]

[0030] in, It represents the load increase of the load-side backup resources in the time period t; It indicates the load reduction of the load-side backup resources in the time period t; P represents the maximum value of the load that can be transferred in the time segment t; TL,t It represents the load amount that needs to be transferred in time segment t; N represents the total number of time segments for backup resource scheduling.

[0031] As an improvement to the above solution, when the backup resource is a storage-side backup resource, the corresponding backup resource timing model is as follows:

[0032]

[0033] in, represents the charging power of the backup resource on the energy storage side in time segment t; Indicates the rated charging power of the backup resource on the energy storage side; represents the discharge power of the backup resource on the energy storage side in time segment t; Indicates the rated discharge power of the backup resource on the energy storage side; S t represents the amount of energy storage side backup resources in time segment t; S t-1 Indicates the amount of energy storage side backup resources in the t-1 time segment; Indicates the charging status of the backup resources on the energy storage side in the time segment t; Indicates the charging efficiency of the backup resources on the energy storage side; Indicates the discharge status of the energy storage side backup resources in the time segment t; Indicates the discharge efficiency of the backup resources on the energy storage side; S min Indicates the lower limit of the backup resource power on the energy storage side; S max Indicates the upper limit of the backup resource power on the energy storage side.

[0034] To achieve the above objectives, an embodiment of the present invention further provides a priority-based backup resource scheduling system:

[0035] A data input module is used to input at least two backup investment evaluation indicators and the initial weight of the current time segment;

[0036] The reserve level calculation module is used to calculate the per-unit value of the reserve input evaluation index of each reserve resource under unit capacity;

[0037] The backup resource scheduling solution calculation module is configured to use the initial weight as the current weight, iterate the current weight, and output the backup resource scheduling solution when the iteration end condition is met; wherein, in each round of iteration:

[0038] Based on the current weight and the per-unit value of the backup input evaluation index, the priority order factor of each backup resource under unit capacity is calculated; according to the priority order indicated by the priority order factor, under the constraint of the backup resource timing model, a backup resource scheduling plan is generated; based on the backup resource scheduling plan and the backup input evaluation index, the total cost is calculated; when the total cost does not meet the iteration end condition, the current weight is updated to perform the next round of iteration; wherein, the total cost is associated with each backup input evaluation index.

[0039] Compared with the prior art, the priority-based backup resource scheduling method and system provided in an embodiment of the present invention inputs at least two backup investment evaluation indicators and the initial weight of the current time segment; calculates the per-unit value of the backup investment evaluation indicator of each backup resource under unit capacity; uses the initial weight as the current weight, iterates the current weight, and outputs a backup resource scheduling plan when the iteration end condition is met; wherein, in each round of iteration: based on the current weight and the per-unit value of the backup investment evaluation indicator, calculates the priority order factor of each backup resource under unit capacity; according to the priority order indicated by the priority order factor, generates a backup resource scheduling plan under the constraints of the backup resource timing model; calculates the total cost based on the backup resource scheduling plan and the backup investment evaluation indicator; when the total cost does not meet the iteration end condition, updates the current weight for the next round of iteration; wherein, the total cost is associated with each backup investment evaluation indicator. Compared with the existing technology, the embodiment of the present invention calculates the priority order factors of different backup resources based on weights and backup levels in each round of iteration, and can sort the backup resources based on the adaptability of each backup resource to the scheduling requirements, and give priority to the backup resources with high adaptability. Furthermore, the embodiment of the present invention also adjusts the weights based on the total cost actually generated by the backup resource scheduling scheme. By correcting the weights, the calculated priority order factors can effectively reflect the adaptability of the backup resources to the scheduling requirements, thereby improving the rationality of the scheduling scheme. BRIEF DESCRIPTION OF THE DRAWINGS

[0040] Figure 1 This is a flow chart of a priority-based backup resource scheduling method provided by one embodiment of the present invention;

[0041] Figure 2 is a flowchart of a priority-based backup resource scheduling method provided by another embodiment of the present invention;

[0042] Figure 3 This is a schematic diagram of a priority-based backup resource scheduling system provided by an embodiment of the present invention. DETAILED DESCRIPTION

[0043] The following will clearly and completely describe the technical solutions in the embodiments of the present invention in conjunction with the accompanying drawings. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. All other embodiments obtained by ordinary technicians in this field based on the embodiments of the present invention without making any creative efforts shall fall within the scope of protection of the present invention.

[0044] See also Figure 1, is a flowchart of a priority-based backup resource scheduling method provided by an embodiment of the present invention, including steps S1 to S3:

[0045] S1. Input at least two backup input evaluation indicators and the initial weight of the current time segment;

[0046] S2. Calculate the per-unit value of the reserve investment evaluation index of each reserve resource under unit capacity;

[0047] S3. Using the initial weight as the current weight, iterating the current weight, and outputting a backup resource scheduling solution when an iteration end condition is met; wherein, in each round of iteration:

[0048] Based on the current weight and the per-unit value of the backup input evaluation index, the priority order factor of each backup resource under unit capacity is calculated; according to the priority order indicated by the priority order factor, under the constraint of the backup resource timing model, a backup resource scheduling plan is generated; based on the backup resource scheduling plan and the backup input evaluation index, the total cost is calculated; when the total cost does not meet the iteration end condition, the current weight is updated to perform the next round of iteration; wherein, the total cost is associated with each backup input evaluation index.

[0049] It is worth noting that in actual applications, the time that needs to be scheduled can be divided into several time segments, and the priority-based backup resource scheduling method described in the embodiment of the present invention can be executed in each time segment. The time segments can be divided into equal lengths or not, and the length of each time segment can be 1 hour, 15 minutes, or other lengths. The way of dividing the time segments is not limited here.

[0050] Exemplarily, in step S1, the standby investment evaluation index may include operating costs, response time, and carbon emissions, wherein operating costs refer to the costs of maintenance, upkeep, energy consumption, etc. required for standby resources during idleness and use, and response time refers to the time required for standby resources to be actually put into use after receiving a scheduling instruction. Furthermore, the number of initial weights is the same as the number of standby investment evaluation indicators, that is, in step S1, an initial weight is assigned to each standby investment evaluation indicator, wherein the weights of different standby investment evaluation indicators can also constitute a weight ratio. Therefore, in some embodiments, the input of step S1 can also be an initial weight ratio, which is not limited here.

[0051] Furthermore, in step S2, the per-unit value of the standby input evaluation index of each standby resource under unit capacity is calculated to distinguish the standby levels of different standby resources. For example, in step S2, the operating cost, response time and carbon emissions of the thermal power unit under unit capacity are calculated, wherein the above values are expressed in per-unit value. It is worth noting that, due to the differences in the capacities of different standby resources, in order to eliminate the interference of capacity factors, in an embodiment of the present invention, the per-unit value of the standby input evaluation index of each standby resource under "unit capacity" is calculated to achieve an accurate assessment of the standby levels of different standby resources; further, in an embodiment of the present invention, by calculating the per-unit value, the dimensional differences of different standby input evaluation indicators can be bridged, thereby achieving optimal scheduling of standby resources under multiple indicators.

[0052] Furthermore, in step S3, based on the backup capacity required by the backup resources in the current time period, the backup resources are optimized and scheduled according to the priority order indicated by the priority order factor and the timing constraint model of the backup resources. Here, referring to formula (1), it is a calculation formula for the backup capacity provided by an embodiment of the present invention:

[0053]

[0054] in, Indicates the power consumption required for the time period t; It represents the planned power supply of the power grid in time period t; Indicates the planned dispatched power supply of renewable energy (wind turbines and photovoltaic generators, etc.) in time period t; It represents the spare capacity required for the time segment t.

[0055] In step S3, for ease of understanding, the scheduling optimization strategy provided by the embodiment of the present invention may be understood as a "double-layer optimization strategy" including an inner optimization strategy and an outer optimization strategy.

[0056] Among them, in the inner layer, based on the current weight and the per-unit value of the backup investment evaluation index, the priority order factors of different backup resources are calculated, wherein the priority order factors are used to indicate the priority order of different backup resources being put into standby, and the backup resources with higher priority orders are put into use first. Furthermore, each backup resource is subject to the constraints of the corresponding backup resource timing model when it is put into use. For example, for the backup resources on the energy storage side, its charging and discharging power will be constrained by the charging and discharging rated power. Then, in the inner layer, after calculating the priority order factors, a backup resource scheduling plan is also generated based on the priority order factors and the backup resource timing model, wherein the backup resource scheduling plan includes the backup resources put into standby and their output power.

[0057] For example, the calculation formula of the priority order factor is shown in formula (2):

[0058]

[0059] Among them, ω i,j represents the priority order factor of the i-th backup resource in the j-th iteration; j represents the weight of the running cost in the jth iteration; j represents the weight of carbon emissions in the jth iteration; ρ j Represents the weight of the response time in the jth iteration; represents the per-unit operating cost of the ith backup resource under unit capacity; represents the per-unit carbon emission value of the i-th backup resource under unit capacity; It represents the per-unit value of the response time of the i-th backup resource under unit capacity.

[0060] For example, the priority order factor can also be calculated using formula (3):

[0061]

[0062] Among them, ψ j Represents the priority order factor vector at the j-th iteration, including the priority order factors of each backup resource at the j-th iteration; It represents the per-unit operating cost of the nth backup resource under unit capacity; represents the per-unit carbon emission value of the nth backup resource under unit capacity; represents the per-unit value of the response time of the nth backup resource under unit capacity; j represents the weight of the running cost in the jth iteration; j represents the weight of carbon emissions in the jth iteration; ρ j represents the weight of response time in the jth iteration; n represents the total number of backup resources.

[0063] It is understandable that when it is necessary to distinguish the priority order factors, weights and standby investment evaluation indicators of different time segments, a superscript or subscript representing the time segment may be added to each parameter.

[0064] Furthermore, in the outer layer, the weights (ratios) are optimized. Specifically, the total cost is calculated based on the backup resource scheduling plan generated by this round of iteration. For example, when the backup investment evaluation indicators are operating cost, response time, and carbon emissions, the corresponding total cost is the sum of the total operating cost, total response time, and total carbon emissions generated by the backup resource scheduling plan. Furthermore, based on the total cost, it is determined whether the iteration end condition is met. If the iteration end condition is not met, the weights are updated (the weight ratios are corrected) and a new round of iteration is performed.

[0065] Exemplarily, the condition for ending the iteration may be that the total cost is minimized. Furthermore, in practical applications, in order to reduce the amount of calculation and improve scheduling efficiency, in each time segment, the condition for ending the iteration may also be the number of iterations, and the backup resource scheduling scheme with the minimum total cost generated during the iteration process is used as the optimal backup resource scheduling scheme for the current time segment. Exemplarily, in some embodiments, the total cost corresponding to the final backup resource scheduling scheme of the previous time segment may also be compared. When the total cost of the backup resource scheduling scheme generated by the current time segment is smaller than that of the previous time segment (a threshold value may also be set for the difference to further limit the condition for ending the iteration), it is considered that the "total cost is minimum" at this time, and the iteration is ended.

[0066] Furthermore, at the end of the iteration, the backup resource scheduling scheme generated in the current iteration round is used as the final backup resource scheduling scheme for the current time segment, and the weight (ratio) of the current round is used as the optimal weight (ratio) of the current time segment.

[0067] For ease of understanding, the following explains the above-mentioned "double-layer optimization strategy" with reference to the accompanying drawings. Figure 2 , is a flowchart of a priority-based backup resource scheduling method provided by another embodiment of the present invention, wherein the above-mentioned "two-level optimization strategy" is executed by a multi-objective time-series backup two-level optimization model. Figure 2 It can be seen that in an embodiment of the present invention, the timing constraint model of each backup resource, the backup investment evaluation index and the initial weight (which is also the current weight of the first round of iteration) are input into the multi-objective timing standby two-layer optimization model, wherein the multi-objective timing standby two-layer optimization model will perform inner-layer optimization and outer-layer optimization on the backup resource scheduling plan. In the inner-layer optimization, it is necessary to calculate the priority order factor of each backup resource under unit capacity. In the outer-layer optimization, it is necessary to search for the optimal weight (ratio) of the current timing segment. By iteratively executing the inner-layer optimization and the outer-layer optimization on each timing segment, the optimal backup resource scheduling plan for each timing segment can be obtained.

[0068] Compared with the existing technology, the embodiment of the present invention calculates the priority order factors of different backup resources based on weights and backup levels in each round of iteration, and can sort the backup resources based on the adaptability of each backup resource to the scheduling requirements, and give priority to the backup resources with high adaptability. Furthermore, the embodiment of the present invention also adjusts the weights based on the total cost actually generated by the backup resource scheduling scheme. By correcting the weights, the calculated priority order factors can effectively reflect the adaptability of the backup resources to the scheduling requirements, thereby improving the rationality of the scheduling scheme.

[0069] As an optional implementation manner, the initial weight is the current weight of the last iteration of the previous time segment.

[0070] It is worth noting that, to a certain extent, the unit output has continuity in time. For example, since the weather generally does not change suddenly in a short period of time, when the time period is short, the photovoltaic output of adjacent time periods may not change much. Furthermore, the electricity load also has a certain degree of continuity, that is, the electricity demand of adjacent time periods may not change much. Therefore, in an embodiment of the present invention, by using the current weight of the last round of iteration of the previous time period (that is, the optimal weight of the previous time period) as the initial weight of the current time period, the amount of calculation can be reduced and the efficiency of backup resource scheduling can be improved.

[0071] Exemplarily, in some embodiments, when the electricity demand of the current time segment has not changed compared with the previous time segment, and the backup capacity of the backup resources is sufficient, the backup resource scheduling scheme of the previous time segment can be directly used for the current time segment, thereby making full use of the timing change characteristics to improve scheduling efficiency.

[0072] As an optional implementation manner, the standby investment evaluation index includes operating cost, response time and carbon emissions.

[0073] It is understandable that, in some embodiments, the standby input evaluation index may also include only any two of the above indicators. For example, the standby input evaluation index only includes response time and carbon emissions. Furthermore, in some embodiments, other indicators may also be included, such as mean failure time, etc., which are not limited here.

[0074] As one of the optional implementation methods, the standby investment evaluation index per unit value is the ratio of the standby investment evaluation index value of each of the standby resources under unit capacity to a predetermined benchmark value; wherein, the benchmark value is the maximum value of the standby investment evaluation index values of each of the standby resources under unit capacity.

[0075] For example, the calculation formula of the per unit operating cost is shown in formula (4):

[0076]

[0077] in, represents the per-unit operating cost of the ith backup resource under unit capacity; represents the operating cost of the i-th backup resource under unit capacity; max{} represents the maximum value function; n represents the total number of backup resources.

[0078] For example, the calculation formula of the per-unit value of the response time is shown in formula (5):

[0079]

[0080] in, represents the per-unit carbon emission value of the i-th backup resource under unit capacity; represents the carbon emissions of the i-th backup resource under unit capacity; max{} represents the maximum value function; n represents the total number of backup resources.

[0081] For example, the calculation formula of the per unit value of carbon emissions is shown in formula (6):

[0082]

[0083] in, represents the per-unit value of the response time of the ith backup resource under unit capacity; represents the response time of the i-th backup resource under unit capacity; max{} represents the maximum value function; n represents the total number of backup resources.

[0084] Furthermore, in some implementations, the benchmark value may also be the sum of the standby investment evaluation index values of all standby resources. Then, referring to equations (7) to (9), they are respectively the calculation formulas for the per-unit value of the operating cost, the per-unit value of the response time, and the per-unit value of the carbon emissions provided in another embodiment of the present invention:

[0085]

[0086] in, represents the per-unit operating cost of the ith backup resource under unit capacity; represents the operating cost of the i-th backup resource under unit capacity; n represents the total number of backup resources.

[0087]

[0088] in, represents the per-unit carbon emission value of the i-th backup resource under unit capacity; represents the carbon emissions of the i-th backup resource under unit capacity; n represents the total number of backup resources.

[0089]

[0090] in, represents the per-unit value of the response time of the ith backup resource under unit capacity; represents the response time of the i-th backup resource under unit capacity; n represents the total number of backup resources.

[0091] It is worth noting that the per-unit value of the above-mentioned standby input evaluation index is used to evaluate the standby level of different standby resources. Furthermore, in each round of iteration, the priority order factor is calculated based on the per-unit value of the standby input evaluation index and the current weight, wherein the calculation formula of the priority order factor can be found in formula (2) and formula (3). Furthermore, when determining the standby resource scheduling scheme based on the priority order factor, it is also necessary to meet the constraints of the standby resource timing model. For example, in a new power system, it may include traditional unit standby resources (such as thermal power generating units, hydropower generating units and gas turbines, etc.), new energy standby resources (such as wind power generating units and photovoltaic power generation, etc.), grid interconnection standby resources, load side standby resources and energy storage side standby resources, then it is necessary to construct corresponding standby resource timing constraint models for different standby resources.

[0092] For example, when the backup resource is a traditional unit backup resource, the corresponding backup resource timing model is shown in formula (10):

[0093]

[0094] Among them, α M,t represents the coefficient, and α M,t >1;P M,g,t represents the power output of the traditional unit in the time segment t, where M∈[G,Hy,Gas], G represents thermal power generation, Hy represents hydropower generation, Gas represents gas turbine power generation, and g represents power output; P M,R,t It represents the reserve output of the traditional unit in the time segment t, and R represents the reserve output; Indicates the minimum power of a conventional unit; Indicates the maximum power of the traditional unit; ΔP M,H Indicates the ramping constraint of traditional units.

[0095] It is understandable that when the traditional unit backup resources are selected to be put into standby, the backup output P needs to be determined according to the backup resource timing model. M,R,t .

[0096] For example, when the backup resource is a new energy backup resource, the corresponding backup resource timing model is shown in formula (11):

[0097]

[0098] Among them, P Y,t P represents the planned dispatched power supply of new energy in time period t; R,t Indicates the reserve output of new energy in time period t; It represents the predicted output of new energy in time segment t.

[0099] Furthermore, since the output of wind and solar energy is uncertain, for example, the output of wind power generation is affected by environmental factors such as wind speed, while the output of photovoltaic power generation is affected by environmental factors such as light intensity, the output of wind and solar energy is characterized by probability density distribution. For example, the embodiment of the present invention takes the probability density calculated by Gaussian distribution parameters as an example to give a probability density and predicted output The model is as follows:

[0100]

[0101] in, express The density function of μ t represents the population mean of the time series segment t; σ represents the population standard deviation; It represents the predicted output of new energy in time segment t.

[0102] It is understandable that when new energy backup resources are selected for backup, the backup output P needs to be determined based on the backup resource timing model. R,t .

[0103] For example, when the backup resource is a grid interconnection backup resource, the corresponding backup resource timing model is shown in formula (13):

[0104]

[0105] Among them, P grid,t represents the amount of electricity purchased from the power grid during time period t; Indicates the upper limit of the power grid's power purchase volume in time period t.

[0106] It is understandable that when the grid interconnection backup resource is selected to be put into backup, it is necessary to determine P according to the backup resource timing model. grid,t .

[0107] As an optional implementation manner, when the backup resource is a load-side backup resource, the corresponding backup resource timing model is shown as follows:

[0108]

[0109] in, It represents the load increase of the load-side backup resources in the time period t; It indicates the load reduction of the load-side backup resources in the time period t; P represents the maximum value of the load that can be transferred in the time segment t; TL,t It represents the load amount that needs to be transferred in time segment t; N represents the total number of time segments for backup resource scheduling.

[0110] It is understandable that when the load side backup resource is selected to be put into standby, it is necessary to determine the time series model of the backup resource. or

[0111] As an optional implementation manner, when the backup resource is a storage-side backup resource, the corresponding backup resource timing model is shown as follows:

[0112]

[0113] in, represents the charging power of the backup resource on the energy storage side in time segment t; Indicates the rated charging power of the backup resource on the energy storage side; represents the discharge power of the backup resource on the energy storage side in time segment t; Indicates the rated discharge power of the backup resource on the energy storage side; S t represents the amount of energy storage side backup resources in time segment t; S t-1 Indicates the amount of energy storage side backup resources in the t-1 time segment; Indicates the charging status of the backup resources on the energy storage side in the time segment t; Indicates the charging efficiency of the backup resources on the energy storage side; Indicates the discharge status of the energy storage side backup resources in the time segment t; Indicates the discharge efficiency of the backup resources on the energy storage side; S min Indicates the lower limit of the backup resource power on the energy storage side; S max Indicates the upper limit of the backup resource power on the energy storage side.

[0114] In formula (15), Indicates charging. Indicates no charging. Indicates discharge, Indicates no discharge.

[0115] It is understandable that when the energy storage side backup resource is selected for backup, it is necessary to determine the backup resource timing model. or

[0116] Furthermore, in each round of iteration, the corresponding total cost needs to be calculated based on the current backup resource scheduling plan, wherein the total cost is associated with all backup investment evaluation indicators.

[0117] As an optional implementation manner, the current weight is updated based on the following objective function:

[0118]

[0119] in, The per-unit value represents the total operating cost of the backup resource scheduling scheme; The per-unit value represents the total carbon emissions of the backup resource scheduling scheme; Indicates the per-unit value of the total response time of the backup resource scheduling solution.

[0120] Among them, in formula (16), Indicates the total cost.

[0121] As one optional implementation method, the total operating cost is calculated as follows:

[0122]

[0123] Among them, F 1,t represents the total operating cost of the backup resource scheduling scheme for time segment t; η i,t represents the operating cost coefficient of the i-th backup resource being put into standby at time segment t; represents the average power of the i-th backup resource put into standby during the t-time period, r represents the backup resource, which is used to distinguish it from the operation plan; ΔT t represents the duration of the t-th time segment; M represents the total number of standby resources put into standby during the t-th time segment;

[0124] The total carbon emissions are calculated as follows:

[0125] F 2,t =μ i,t F 1,t (18)

[0126] Among them, F 2,t represents the total carbon emissions of the backup resource scheduling scheme in time segment t; μ i,t represents the carbon emission coefficient of the i-th backup resource in time segment t; F 1,t represents the total operating cost of the backup resource scheduling scheme in time segment t;

[0127] The total response time is calculated as follows:

[0128] F 3,t =max(K i,t T i,t ),i∈[1,M](19)

[0129] Among them, F 3,t represents the total response time of the backup resource scheduling scheme in the time segment t; max() represents the maximum value function; K i,t Indicates the standby flag, K i,t =1 means it is put into standby mode, K i,t =0 means exit standby; T i,tIt represents the response time of the i-th backup resource being put into backup in time segment t; M represents the total number of backup resources put into backup in time segment t.

[0130] It is worth noting that in order to reduce the response time of the standby resources, in actual applications, all standby resources will be put into use at the same time. Therefore, in formula (19), the maximum response time of the standby resources put into use is taken as the total response time.

[0131] As an optional implementation manner, the per-unit value of each target parameter is calculated in the following manner, wherein the target parameter is any one of the total operating cost, the total response time, and the total carbon emissions:

[0132] When the current time segment is not the first time segment, the ratio of the target parameter to the target parameter at the end of the iteration of the previous time segment is used as the per-unit value of the target parameter;

[0133] When the current time segment is the first time segment, the ratio of the target parameter to the target parameter of the initial backup resource scheduling scheme is used as the per-unit value of the target parameter; wherein the initial backup resource scheduling scheme is a backup resource scheduling scheme calculated based on the initial weight.

[0134] For example, if the current time segment is not the first time segment, the per-unit value of the total operating cost is calculated. When the total operating cost of the standby resource in the previous time segment is used as the benchmark value; if the current time segment is the first time segment, the total operating cost of the standby resource scheduling scheme (initial standby resource scheduling scheme) calculated with the initial weight is used as the benchmark value to calculate the per-unit value of the total operating cost.

[0135] For example, if the current time segment is not the first time segment, the per unit value of the total carbon emissions is calculated. When the current time segment is the first time segment, the total carbon emissions of the backup resource scheduling scheme (initial backup resource scheduling scheme) calculated with the initial weights are used as the benchmark value to calculate the per-unit value of the total carbon emissions.

[0136] For example, if the current time segment is not the first time segment, the per-unit value of the total response time is calculated. When the total response time of the backup resource in the previous time segment is used as the benchmark value; if the current time segment is the first time segment, the total response time of the backup resource scheduling scheme (initial backup resource scheduling scheme) calculated with the initial weight is used as the benchmark value to calculate the per-unit value of the total response time.

[0137] It is worth noting that, by using per-unit values to calculate the total cost, the embodiment of the present invention can bridge the dimensional differences of different backup investment evaluation indicators and achieve optimal scheduling of backup resources under multiple indicators.

[0138] See also Figure 3 The embodiment of the present invention further provides a priority-based backup resource scheduling system 10, comprising:

[0139] The data input module 11 is used to input at least two backup investment evaluation indicators and the initial weight of the current time segment;

[0140] The reserve level calculation module 12 is used to calculate the per-unit value of the reserve input evaluation index of each reserve resource under unit capacity;

[0141] The backup resource scheduling solution calculation module 13 is configured to use the initial weight as the current weight, iterate the current weight, and output the backup resource scheduling solution when the iteration end condition is met; wherein, in each round of iteration:

[0142] Based on the current weight and the per-unit value of the backup input evaluation index, the priority order factor of each backup resource under unit capacity is calculated; according to the priority order indicated by the priority order factor, under the constraint of the backup resource timing model, a backup resource scheduling plan is generated; based on the backup resource scheduling plan and the backup input evaluation index, the total cost is calculated; when the total cost does not meet the iteration end condition, the current weight is updated to perform the next round of iteration; wherein, the total cost is associated with each backup input evaluation index.

[0143] The priority-based backup resource scheduling device provided in an embodiment of the present invention can implement all process steps of the priority-based backup resource scheduling method described in the above embodiment. The functions of each module and unit in the device and the technical effects achieved are respectively the same as the functions and technical effects achieved by the priority-based backup resource scheduling method described in the above embodiment. The specific implementation method will not be repeated here.

[0144] Compared with the prior art, the priority-based backup resource scheduling method and system provided in an embodiment of the present invention inputs at least two backup investment evaluation indicators and the initial weight of the current time segment; calculates the per-unit value of the backup investment evaluation indicator of each backup resource under unit capacity; uses the initial weight as the current weight, iterates the current weight, and outputs a backup resource scheduling plan when the iteration end condition is met; wherein, in each round of iteration: based on the current weight and the per-unit value of the backup investment evaluation indicator, calculates the priority order factor of each backup resource under unit capacity; according to the priority order indicated by the priority order factor, generates a backup resource scheduling plan under the constraints of the backup resource timing model; calculates the total cost based on the backup resource scheduling plan and the backup investment evaluation indicator; when the total cost does not meet the iteration end condition, updates the current weight for the next round of iteration; wherein, the total cost is associated with each backup investment evaluation indicator. Compared with the existing technology, the embodiment of the present invention calculates the priority order factors of different backup resources based on weights and backup levels in each round of iteration, and can sort the backup resources based on the adaptability of each backup resource to the scheduling requirements, and give priority to the backup resources with high adaptability. Furthermore, the embodiment of the present invention also adjusts the weights based on the total cost actually generated by the backup resource scheduling scheme. By correcting the weights, the calculated priority order factors can effectively reflect the adaptability of the backup resources to the scheduling requirements, thereby improving the rationality of the scheduling scheme.

[0145] The above is a preferred embodiment of the present invention. It should be pointed out that for ordinary technicians in this technical field, several improvements and modifications can be made without departing from the principles of the present invention. These improvements and modifications are also considered to be within the scope of protection of the present invention.

Claims

1. A priority-based backup resource scheduling method, characterized in that: include: Enter at least two backup investment evaluation indicators and the initial weight of the current time segment; Calculate the per-unit value of the reserve investment evaluation index of each reserve resource under unit capacity; The initial weight is used as the current weight, and the current weight is iterated. When the iteration end condition is met, the backup resource scheduling solution is output; wherein, in each round of iteration: Based on the current weight and the per-unit value of the backup input evaluation index, the priority order factor of each backup resource under unit capacity is calculated; according to the priority order indicated by the priority order factor, under the constraint of the backup resource timing model, a backup resource scheduling plan is generated; based on the backup resource scheduling plan and the backup input evaluation index, the total cost is calculated; when the total cost does not meet the iteration end condition, the current weight is updated to perform the next round of iteration; wherein, the total cost is associated with each backup input evaluation index.

2. The priority-based backup resource scheduling method according to claim 1, wherein: The initial weight is the current weight of the last iteration of the previous time segment.

3. The priority-based backup resource scheduling method according to claim 1, wherein: The standby investment evaluation indicators include operating cost, response time and carbon emissions.

4. The priority-based backup resource scheduling method according to claim 1, wherein: The per-unit value of the standby investment evaluation index is the ratio of the standby investment evaluation index value of each of the standby resources under unit capacity to a predetermined reference value; wherein the reference value is the maximum value of the standby investment evaluation index values of each of the standby resources under unit capacity.

5. The priority-based backup resource scheduling method according to claim 3, wherein: The current weights are updated based on the following objective function: in, The per-unit value represents the total operating cost of the backup resource scheduling scheme; The per-unit value represents the total carbon emissions of the backup resource scheduling scheme; Indicates the per-unit value of the total response time of the backup resource scheduling solution.

6. The priority-based backup resource scheduling method according to claim 5, wherein: The per-unit value of each target parameter is calculated in the following manner, wherein the target parameter is any one of the total operating cost, the total response time, and the total carbon emissions: When the current time segment is not the first time segment, the ratio of the target parameter to the target parameter at the end of the iteration of the previous time segment is used as the per-unit value of the target parameter; When the current time segment is the first time segment, the ratio of the target parameter to the target parameter of the initial backup resource scheduling scheme is used as the per-unit value of the target parameter; wherein the initial backup resource scheduling scheme is a backup resource scheduling scheme calculated based on the initial weight.

7. The priority-based backup resource scheduling method according to claim 5, wherein: The total operating cost is calculated as follows: Among them, F 1,t represents the total operating cost of the backup resource scheduling scheme for time segment t; η i,t represents the operating cost coefficient of the i-th backup resource being put into standby at time segment t; represents the average power of the i-th backup resource in the t-time period; ΔT t represents the duration of the t-th time segment; M represents the total number of standby resources put into standby during the t-th time segment; The total carbon emissions are calculated as follows: F 2,t =μ i,t F 1,t Among them, F 2,t represents the total carbon emissions of the backup resource scheduling scheme in time segment t; μ i,t represents the carbon emission coefficient of the i-th backup resource in time segment t; F 1,t represents the total operating cost of the backup resource scheduling scheme in time segment t; The total response time is calculated as follows: F 3,t =max(K i,t T i,t ),i∈[1,M] Among them, F 3,t represents the total response time of the backup resource scheduling scheme in the time segment t; max() represents the maximum value function; K i,t Indicates the standby flag, K i,t =1 means it is put into standby mode, K i,t =0 means exit standby; T i,t It represents the response time of the i-th backup resource being put into backup in time segment t; M represents the total number of backup resources put into backup in time segment t.

8. The priority-based backup resource scheduling method according to claim 1, wherein when the backup resource is a load-side backup resource, the corresponding backup resource timing model is as follows: in, It represents the load increase of the load-side backup resources in the time period t; It indicates the load reduction of the load-side backup resources in the time period t; P represents the maximum value of the load that can be transferred in the time segment t; TL,t It represents the load amount that needs to be transferred in time segment t; N represents the total number of time segments for backup resource scheduling.

9. The priority-based backup resource scheduling method according to claim 1, wherein when the backup resource is a storage-side backup resource, the corresponding backup resource timing model is as follows: in, represents the charging power of the backup resource on the energy storage side in time segment t; Indicates the rated charging power of the backup resource on the energy storage side; represents the discharge power of the backup resource on the energy storage side in time segment t; Indicates the rated discharge power of the backup resource on the energy storage side; S t represents the amount of energy storage side backup resources in time segment t; S t-1 Indicates the amount of energy storage side backup resources in the t-1 time segment; Indicates the charging status of the backup resources on the energy storage side in the time segment t; Indicates the charging efficiency of the backup resources on the energy storage side; Indicates the discharge status of the energy storage side backup resources in the time segment t; Indicates the discharge efficiency of the backup resources on the energy storage side; S min Indicates the lower limit of the backup resource power on the energy storage side; S max Indicates the upper limit of the backup resource power on the energy storage side.

10. A priority-based backup resource scheduling system, characterized in that: include: A data input module is used to input at least two backup investment evaluation indicators and the initial weight of the current time segment; The reserve level calculation module is used to calculate the per-unit value of the reserve input evaluation index of each reserve resource under unit capacity; The backup resource scheduling solution calculation module is configured to use the initial weight as the current weight, iterate the current weight, and output the backup resource scheduling solution when the iteration end condition is met; wherein, in each round of iteration: Based on the current weight and the per-unit value of the backup input evaluation index, the priority order factor of each backup resource under unit capacity is calculated; according to the priority order indicated by the priority order factor, under the constraint of the backup resource timing model, a backup resource scheduling plan is generated; based on the backup resource scheduling plan and the backup input evaluation index, the total cost is calculated; when the total cost does not meet the iteration end condition, the current weight is updated to perform the next round of iteration; wherein, the total cost is associated with each backup input evaluation index.

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