A method and device for determining effective spare capacity considering grid congestion

Abstract

The present application discloses a method and device for determining effective reserve capacity taking into account grid congestion. The method includes: constructing a safety constraint unit combination model that does not consider positive reserve constraints; determining the constraint conditions of the safety constraint unit combination model, and modeling the unit operating costs to generate a target model; the constraint conditions include system constraints, unit constraints, unit group constraints, and network constraints; the system constraints include establishing positive reserve variable constraints for each unit; solving the target model until the target model converges to obtain effective reserve capacity. By changing some variable constraints of the clearing model, the present application can accurately calculate the effective reserve value that each unit can provide, providing further protection for the safe and stable operation of the power grid.

Description

Technical Field

[0001] The present application relates to the technical field of power grid data analysis, and in particular to a method and device for determining effective spare capacity considering power grid congestion. Background Art

[0002] To ensure power system reliability, power dispatching agencies typically reserve a large amount of operating capacity to meet system reserve requirements. However, the actual grid transmission is severely congested, and some units are restricted by blocked sections. If this reserved reserve capacity is called upon, the relevant sections will exceed the limit, making this reserve unavailable. Existing market-clearing models cannot avoid the generation of ineffective reserves. To address this issue, some provinces currently use a method that calculates the actual reserve deduction value based on the unit combination results of the previous iteration of the algorithm and incorporates it into the reserve constraints of the next unit combination. However, this method is cumbersome, difficult, and highly subjective. Furthermore, with regard to zoned reserves, the complex power structure of some provinces in my country makes it difficult to create feasible and effective zones for units. This has led to low market acceptance and difficulty in implementation. Summary of the Invention

[0003] The purpose of this application is to provide a method and device for determining effective spare capacity taking into account grid congestion, so as to achieve optimal resource allocation while ensuring grid reliability and accuracy, and improve resource utilization.

[0004] To achieve the above objectives, the present application provides a method for determining effective reserve capacity taking into account grid congestion, comprising:

[0005] Construct a safety-constrained unit commitment model without considering positive reserve constraints;

[0006] Determining the constraints of the safety-constrained unit commitment model, performing unit operating cost modeling, and generating a target model; the constraints include system constraints, unit constraints, unit group constraints, and network constraints; the system constraints include establishing positive standby variable constraints for each unit;

[0007] The target model is solved until the target model converges to obtain the effective spare capacity.

[0008] Furthermore, the construction of the safety constraint unit commitment model without considering the positive standby constraint includes:

[0009]

[0010] Where N is the total number of units; T is the total number of time periods considered; P i,t represents the output of unit i in period t; C i,t (P i,t ), are the operating cost and startup cost of unit i in period t, respectively, where the unit operating cost C i,t (P i,t ) is a multi-segment linear function related to the output intervals reported by the unit and the corresponding energy prices; M is the network power flow constraint relaxation penalty factor used for market clearing optimization, usually 100 million; are the forward and reverse power flow slack variables of line l respectively; NL is the total number of lines; are the forward and reverse tidal flow relaxation variables of section s respectively; NS is the total number of sections.

[0011] Furthermore, the system constraints also include system load balance constraints, system negative reserve capacity constraints and system spinning reserve constraints; wherein,

[0012] The positive reserve variable constraint of each unit is established as follows:

[0013]

[0014] Where, α i,t represents the start and stop status of unit i in period t, α i,t =0 means the unit is shut down, α i,t =1 means the unit is on; is the maximum output of unit i in period t; PR i,t represents the maximum effective reserve that unit i can provide at time t; is the system positive reserve capacity requirement for period t;

[0015] Establish the load balancing constraint for each time period t:

[0016]

[0017] Where, P i,t represents the output of unit i in period t, T j,t represents the planned power of tie line j in time period t, with input as positive and output as negative, NT as the total number of tie lines, D t is the system load during period t;

[0018] Establish the negative spare capacity constraint of the system:

[0019]

[0020] Where, is the minimum output of unit i in period t; is the system negative reserve capacity requirement for period t;

[0021] Establish the system spinning reserve constraints:

[0022]

[0023]

[0024] Where ΔP i U is the maximum ramp rate of unit i, ΔP i D is the maximum down-slope rate of unit i; are the maximum and minimum outputs of unit i in period t respectively; They are respectively used to increase and decrease the spinning reserve requirement for period t.

[0025] Furthermore, determining the unit constraint includes:

[0026] Determine the upper and lower limits of the unit output:

[0027]

[0028] If the unit is shut down, α i,t = 0, then the unit output can be limited to 0 through this constraint; when the unit is turned on, α i,t =1, this constraint is the conventional upper and lower limit constraint of output;

[0029] Determine the unit climbing constraints:

[0030]

[0031]

[0032] Where ΔP i U is the maximum ramp rate of unit i, ΔP i D is the maximum down-slope rate of unit i;

[0033] Determine the minimum continuous start and stop time constraints of the unit:

[0034]

[0035]

[0036] Where, α i,t is the start and stop status of unit i in period t; T U 、T D The minimum continuous start time and minimum continuous stop time of the unit; The state variable α is the continuous start-up time and continuous shutdown time of unit i in period t. i,t (i=1~N, t=1~T) to express:

[0037]

[0038]

[0039] Determine the maximum start and stop times constraint for the unit:

[0040] Define the switching variables for start and stop, and define η i,t Is the unit i switched to the startup state in period t? Define γ i,t Indicates whether unit i switches to shutdown state during period t, η i,t , γ i,t The following conditions are met:

[0041]

[0042]

[0043] The start and stop times limit for the corresponding unit i is:

[0044]

[0045]

[0046] Where, are the maximum number of starts and stops of unit i respectively;

[0047] Among them, η i,t , γ i,t satisfy:

[0048]

[0049] Determine the unit power constraints:

[0050]

[0051] Where T represents the total number of time periods considered; T0 is the length of a time period in the planning cycle. If 96 time periods are considered per day, each time period is 15 minutes, that is, T0 = 0.25 (hours); are the maximum and minimum power of unit i respectively;

[0052] Determine the unit's designated state constraints, including maintenance status, designated start and shutdown, and designated output.

[0053] Furthermore, determining the unit constraint also includes determining the unit operating state and the standby variable coupling constraint, including:

[0054] If the start-stop curve is not considered, the following constraints are established:

[0055]

[0056] If the start-stop curve is considered, the following constraints are established:

[0057]

[0058] Where UD is the duration of the startup process, calculated to the minimum output; DD is the duration of the shutdown process, calculated from the minimum output; β i,t and γ i,t They are 0-1 variables indicating the start and stop of the unit respectively.

[0059] Furthermore, determining the group constraint includes:

[0060] Determine the upper and lower limits of the generator group output:

[0061]

[0062] Where, are the maximum and minimum outputs of group j in time period t;

[0063] Determine the power constraints of the unit group:

[0064]

[0065] Where, T0=96 is the total number of time periods on D day, is the upper limit of power consumption of unit group j on day D.

[0066] Furthermore, determining the network constraint includes:

[0067] Determine the line power flow constraints:

[0068]

[0069] Where, P l max is the power transmission limit of line l; G l-i is the generator output power transfer distribution factor of the node where unit i is located on line l; G l-j is the generator output power transfer distribution factor of the node where the tie line j is located to the line l; K is the number of nodes in the system; G l-k is the generator output power transfer distribution factor of node k on line l; D k,t is the bus load value of node k in period t; are the forward and reverse power flow slack variables of line l respectively;

[0070] Determine the cross-sectional power flow constraints:

[0071]

[0072] Where, P s min 、P s max are the tidal current transmission limits of section s; G s-i G is the generator output power transfer distribution factor of the node where unit i is located on section s; s-j G is the generator output power transfer distribution factor of the node where the tie line j is located on section s; s-k is the generator output power transfer distribution factor of node k to section s; are the forward and reverse tidal flow relaxation variables of section s, respectively;

[0073] Determine the backup network security constraints:

[0074]

[0075]

[0076] Where, Represent the transfer distribution factors above the sensitivity threshold in the forward and reverse directions, respectively.

[0077] Furthermore, the unit operation cost modeling includes:

[0078] Determine the unit output:

[0079]

[0080]

[0081] Where, M is the total number of sections in the unit quotation, P i,t,m is the winning bid power of unit i in the mth output interval during period t, are the upper and lower bounds of the mth output interval declared by unit i;

[0082] Determine the unit operating costs:

[0083]

[0084] Where, M is the total number of sections in the unit quotation, C i,t,m is the energy price corresponding to the mth output segment declared by unit i in period t;

[0085] Determine the unit startup cost:

[0086]

[0087] Where, is the single startup cost of unit i.

[0088] Furthermore, solving the target model until the target model converges to obtain the effective spare capacity includes:

[0089] When the target model output does not converge, the positive reserve demand is reduced according to the preset conditions and the target model solution process is returned until the target model converges and the effective reserve capacity is obtained.

[0090] The present application also provides a device for determining effective reserve capacity taking into account grid congestion, comprising:

[0091] A model building unit, used for building a safety constraint unit commitment model without considering positive reserve constraints;

[0092] a constraint construction unit, configured to determine the constraint conditions of the safety constraint unit commitment model, perform unit operation cost modeling, and generate a target model; the constraint conditions include system constraints, unit constraints, unit group constraints, and network constraints; the system constraints include establishing positive standby variable constraints for each unit;

[0093] The solving unit is used to solve the target model until the target model converges to obtain the effective spare capacity.

[0094] Compared with the prior art, the beneficial effects of this application are:

[0095] 1) This application can accurately calculate the effective reserve value that each unit can provide, providing further guarantee for the safe and stable operation of the power grid.

[0096] 2) This application does not add any new 0-1 variables, which has little impact on computational efficiency. Therefore, this method is easy to promote and has engineering practice value for large-scale systems.

[0097] 3) This application only modifies some variable constraints, with minor changes to the existing clearing framework and high technical compatibility. BRIEF DESCRIPTION OF THE DRAWINGS

[0098] In order to more clearly illustrate the technical solution of the present application, the following is a brief introduction to the drawings required for use in the implementation. Obviously, the drawings described below are only some implementation methods of the present application. For ordinary technicians in this field, other drawings can be obtained based on these drawings without any creative work.

[0099] Figure 1 This is a flowchart of a method for determining effective spare capacity considering grid congestion provided by an embodiment of the present application;

[0100] Figure 2 This is a schematic diagram of line capacity allocation provided by an embodiment of the present application;

[0101] Figure 3 This is a flowchart of the sub-steps of step S30 provided in one embodiment of the present application;

[0102] Figure 4 This is a structural diagram of a device for determining effective spare capacity taking into account grid congestion, provided in a certain embodiment of the present application. DETAILED DESCRIPTION

[0103] The following will be combined with the drawings in the embodiments of this application to clearly and completely describe the technical solutions in the embodiments of this application. Obviously, the embodiments described are only part of the embodiments of this application, not all of the embodiments. Based on the embodiments in this application, all other embodiments obtained by ordinary technicians in this field without making creative efforts are within the scope of protection of this application.

[0104] It should be understood that the step numbers used herein are only for convenience of description and are not intended to limit the order in which the steps are to be executed.

[0105] It should be understood that the terms used in this specification are only for the purpose of describing specific embodiments and are not intended to limit this application. As used in this specification and the appended claims, the singular forms "a", "an", and "the" are intended to include the plural forms unless the context clearly indicates otherwise.

[0106] The terms “include” and “comprising” indicate the presence of described features, integers, steps, operations, elements and / or components, but do not preclude the presence or addition of one or more other features, integers, steps, operations, elements, components and / or groups thereof.

[0107] The term "and / or" refers to and includes any and all possible combinations of one or more of the associated listed items.

[0108] See also Figure 1 , a certain embodiment of the present application provides a method for determining effective spare capacity considering grid congestion. Figure 1 As shown, the method for determining effective reserve capacity considering grid congestion includes steps S10 to S30. The specific steps are as follows:

[0109] S10. Construct a safety constraint unit commitment model without considering positive reserve constraints;

[0110] S20, determining the constraints of the safety-constrained unit combination model, performing unit operating cost modeling, and generating a target model; the constraints include system constraints, unit constraints, unit group constraints, and network constraints; the system constraints include establishing positive standby variable constraints for each unit;

[0111] S30: Solve the target model until the target model converges to obtain effective spare capacity.

[0112] In order to ensure the reliability of the power system, the power dispatching agency usually reserves a large startup capacity to meet the system's backup needs; however, the actual power grid transmission is severely congested, and some units are limited by blocked sections. If the reserved backup capacity is called, it will cause the relevant sections to exceed the limit, and this part of the backup cannot actually be provided. There are currently two means to solve this problem: the first is to build a zoned backup, divide the units into zones, and consider the backup that can be provided by the units in the zone separately. The second is to go through multiple iterations, and in each iteration, the invalid backup value generated in the previous calculation is added to the current backup demand. However, these methods are often prone to large errors. Therefore, in order to effectively calculate the system's backup demand, this embodiment provides a method for determining effective backup capacity considering grid congestion.

[0113] To help understand, first explain the physical meaning of unit reserve limitation. Figure 2 , Figure 2 A schematic diagram of line capacity allocation in a certain scenario is provided, such as Figure 2 As shown, node 4 and node 3 have loads of 200 and 300 respectively. The sensitivity matrix is ​​as follows, where the row labels on the left side of the matrix represent the line numbers, and node 3 is a balancing machine:

[0114]

[0115] Furthermore, the unit output is shown in Table 1 below:

[0116] Table 1 Unit output distribution

[0117] unit power Backup under normal logic Node 2's unit G1 211 59 Node 3 is located in unit G2 272 28 Node 4 is located in unit G3 17 183

[0118] The line flow conditions are shown in Table 2 below:

[0119] Table 2 Line flow distribution

[0120] line trend 32 14.6666666666667 21 242.666666666667 31 257.333333333333 42 17

[0121] According to the table above, under normal reserve calculation logic, the effective reserve capacity of unit G3 is 200-17 = 183 MW. However, due to the influence of line 42, unit G3 will reach the limit of line 42 once its power reaches 150 MW. Therefore, considering only the impact of line 42 on unit G3, the maximum effective reserve capacity of unit G3 should be 150-17 = 123 MW. However, line 32 also limits the effective reserve capacity of unit G3. After considering the impact of line 32, the maximum effective reserve capacity of unit G3 should be (14.66667 + 15) / 0.6666667 = 44.5 MW. Therefore, the maximum effective reserve capacity of unit G3 is 44.5 MW.

[0122] Furthermore, when executing step S10, it is first necessary to construct a safety constraint unit commitment model without considering the positive standby constraint, and the result is as follows:

[0123]

[0124] Where N is the total number of units; T is the total number of time periods considered; P i,t represents the output of unit i in period t; C i,t (P i,t ), are the operating cost and startup cost of unit i in period t, respectively, where the unit operating cost C i,t (P i,t ) is a multi-segment linear function related to the output intervals reported by the unit and the corresponding energy prices; M is the network power flow constraint relaxation penalty factor used for market clearing optimization, usually 100 million; are the forward and reverse power flow slack variables of line l respectively; NL is the total number of lines; are the forward and reverse tidal flow relaxation variables of section s respectively; NS is the total number of sections.

[0125] After the model is established, the next step is to determine the constraints of the safety constraint unit combination model, model the unit operation costs, and generate the target model;

[0126] The constraints include system constraints, unit constraints, unit group constraints and network constraints; the system constraints include establishing positive standby variable constraints for each unit.

[0127] In a specific embodiment, the content of each constraint is described in detail:

[0128] 1) System constraints:

[0129] 1.1) System load balancing constraints.

[0130] Establish the load balancing constraint for each time period t:

[0131]

[0132] Where, P i,t represents the output of unit i in period t, T j,t represents the planned power of tie line j in time period t, with input as positive and output as negative, NT as the total number of tie lines, D t is the system load during period t.

[0133] 1.2) System positive spare capacity constraint.

[0134] On the premise of ensuring system power balance, in order to prevent system load forecast deviations and system supply and demand imbalance fluctuations caused by various actual operation accidents, the entire system generally needs to have a certain amount of spare capacity, that is, it is necessary to ensure that the total daily startup capacity meets the system's minimum spare capacity.

[0135] Specifically, the positive reserve variable constraint of each unit is established:

[0136]

[0137] Where, α i,t represents the start and stop status of unit i in period t, α i,t =0 means the unit is shut down, α i,t =1 means the unit is on; is the maximum output of unit i in period t; PR i,t represents the maximum effective reserve that unit i can provide at time t; is the system positive spare capacity requirement for period t.

[0138] 1.3) System negative spare capacity constraint.

[0139] Establish system negative reserve capacity constraints:

[0140]

[0141] Where, is the minimum output of unit i in period t; is the system negative spare capacity requirement during period t.

[0142] 1.4) System spinning reserve constraints.

[0143] The sum of the upward and downward adjustment capabilities of the unit output in each period must meet the upward and downward adjustment requirements of the rotating standby in actual operation.

[0144] Specifically, the system spinning reserve constraint is established:

[0145]

[0146]

[0147] Where ΔP i U is the maximum ramp rate of unit i, ΔP i D is the maximum down-slope rate of unit i; are the maximum and minimum outputs of unit i in period t respectively; They are respectively used to increase and decrease the spinning reserve requirement for period t.

[0148] 2) Unit constraints:

[0149] 2.1) Upper and lower limits of unit output.

[0150] The unit output should be within its maximum / minimum technical output range, and its constraints can be described as:

[0151]

[0152] If the unit is shut down, α i,t = 0, then the unit output can be limited to 0 through this constraint; when the unit is turned on, α i,t =1, this constraint is the conventional upper and lower limit constraint of output.

[0153] 2.2) Unit climbing constraints.

[0154] When the unit is climbing up or down a slope, it must meet the climbing rate requirements. The climbing constraint can be described as:

[0155]

[0156]

[0157] Where ΔP i U is the maximum ramp rate of unit i, ΔP i D is the maximum ramp-down rate of unit i.

[0158] It should be noted that the unit output limit is determined by several factors:

[0159] When the unit is in normal operation, the unit's output range is ΔP i U , ΔP i D Decide;

[0160] When the unit is in the start-up state, the unit's output range is determined by the unit's allowable start-up rate (here )Decide;

[0161] When the unit is at shutdown, the unit's output range is determined by the unit's allowable shutdown rate (here )Decide.

[0162] 2.3) Minimum continuous start and stop time constraints of the unit.

[0163] Due to the physical properties of thermal power units and actual operating needs, thermal power units are required to meet minimum continuous start-up / shutdown time.

[0164] Specifically, determine the minimum continuous start and stop time constraint of the unit:

[0165]

[0166]

[0167] Where, α i,t is the start and stop status of unit i in period t; T U 、T D The minimum continuous start time and minimum continuous stop time of the unit; The state variable α is the continuous start-up time and continuous shutdown time of unit i in period t. i,t (i=1~N, t=1~T) to express:

[0168]

[0169]

[0170] 2.4) Constraints on the maximum number of starts and stops of the unit.

[0171] Define the switching variables for start and stop, and define η i,t Is the unit i switched to the startup state in period t? Define γ i,t Indicates whether unit i switches to shutdown state during period t, η i,t , γ i,t The following conditions are met:

[0172]

[0173]

[0174] The start and stop times limit for the corresponding unit i is:

[0175]

[0176]

[0177] Where η i max , γ i max are the maximum number of starts and stops of unit i respectively;

[0178] Among them, η i,t , γ i,t satisfy:

[0179]

[0180] 2.5) Unit power constraints.

[0181] Specifically, the unit power constraint can be described as:

[0182]

[0183] Where T represents the total number of time periods considered; T0 is the length of a time period in the planning cycle. If 96 time periods are considered per day, each time period is 15 minutes, that is, T0 = 0.25 (hours); Q i max , Q i min are the maximum and minimum power of unit i respectively;

[0184] 2.6) Determine the unit's designated state constraints, including maintenance status, designated start and shutdown, and designated output.

[0185] 2.7) Coupling constraints between unit operating status and standby variables.

[0186] When the unit is shut down, no backup can be provided, so PR i,t There should be a coupling relationship with the operating status of the unit, that is:

[0187]

[0188] In addition, PR i,t The upper limit constraint should be less than the maximum output and actual output of the unit, that is, it should meet the following constraints:

[0189]

[0190] The above formulas can be combined into one to obtain:

[0191]

[0192] If the start-stop curve is not considered, then according to the formula Establish constraints.

[0193] It should be noted that the operating stages of electricity spot markets vary across regions. Some power markets have not yet considered the start-stop curves for units, while others have already considered them. A unit's start-stop curve refers to the specific output curve that a unit must follow to start from a shutdown state and reach a specified output. This output curve is consistent with the unit's physical operating characteristics. If backup modeling for the start-stop curve is considered, the following constraints are established:

[0194]

[0195] Where UD is the duration of the startup process, calculated to the minimum output; DD is the duration of the shutdown process, calculated from the minimum output; β i,t and γ i,t They are 0-1 variables indicating the start and stop of the unit respectively.

[0196] 3) Group constraints:

[0197] 3.1) Upper and lower limits of the unit group output.

[0198] The output of the generator group should be within its maximum / minimum output range, so the upper and lower limits of the generator group output are determined as follows:

[0199]

[0200] Where, are the maximum and minimum outputs of group j in time period t.

[0201] 3.2) Power constraints of the unit group.

[0202] For a group of generators that are partially restricted by primary energy supply constraints, their winning bid in the day-ahead electricity market should meet the upper limit of the generator group's power consumption. Specifically, the generator group power consumption constraint is determined as:

[0203]

[0204] Where, T0=96 is the total number of time periods on D day, is the upper limit of power consumption of unit group j on day D.

[0205] 4) Network constraints:

[0206] 4.1) Determine line power flow constraints:

[0207]

[0208] Where, P l max is the power transmission limit of line l; G l-i is the generator output power transfer distribution factor of the node where unit i is located on line l; G l-jis the generator output power transfer distribution factor of the node where the tie line j is located to the line l; K is the number of nodes in the system; G l-k is the generator output power transfer distribution factor of node k on line l; D k,t is the bus load value of node k in period t; are the forward and reverse power flow slack variables of line l, respectively.

[0209] 4.2) Determine cross-section flow constraints:

[0210]

[0211] Where, P s min 、P s max are the tidal current transmission limits of section s; G s-i G is the generator output power transfer distribution factor of the node where unit i is located on section s; s-j G is the generator output power transfer distribution factor of the node where the tie line j is located on section s; s-k is the generator output power transfer distribution factor of node k to section s; are the forward and reverse tidal flow relaxation variables of section s, respectively.

[0212] 4.3) Determine backup network security constraints:

[0213] When considering the backup network security constraints, the forward-sensitive units and the reverse-sensitive units are added separately, that is, the constraints are established using the following formula:

[0214]

[0215]

[0216] Where, Represent the transfer distribution factors above the sensitivity threshold in the forward and reverse directions, respectively.

[0217] It should be noted that when considering the backup network security constraints in the above equation, the backup variables associated with the forward and reverse limits of the section only increase the forward or reverse flow of the current section. Therefore, in this case, it is not necessary to add the original network security constraints.

[0218] Preferably, when creating a new backup network security constraint, it is necessary to screen and note whether the corresponding sensitivity is above the sensitivity threshold, which is usually between 0.1 and 0.2. To streamline processing, the penalty factor here only adds the corresponding forward and reverse limit penalty factors.

[0219] After the above constraints are established, in a specific embodiment, it is also necessary to model the unit operating costs, including:

[0220] Determine the unit output:

[0221]

[0222]

[0223] Where, M is the total number of sections in the unit quotation, P i,t,m is the winning bid power of unit i in the mth output interval during period t, They are the upper and lower bounds of the mth output range declared by unit i.

[0224] Determine the unit operating costs:

[0225]

[0226] Where, M is the total number of sections in the unit quotation, C i,t,m The energy price corresponding to the mth output segment declared by unit i in period t.

[0227] Determine the unit startup cost:

[0228]

[0229] Where, is the single startup cost of unit i.

[0230] S30: Solve the target model until the target model converges to obtain effective spare capacity.

[0231] See also Figure 3 When the target model output does not converge during step S30, the positive reserve demand is reduced according to preset conditions and the target model solution process is returned to the target model solution process until the target model converges and the effective reserve capacity is obtained. The preset conditions in this embodiment can be set based on actual conditions to determine the magnitude of each reduction in the positive reserve demand, and are not limited herein.

[0232] In summary, the method for determining effective reserve capacity taking into account grid congestion, provided in the embodiments of the present application, can be used as a means of calculating effective reserve capacity for large-scale power grids with severe congestion. This method can accurately calculate the effective reserve value that each unit can provide, providing further assurance for the safe and stable operation of the power grid. Furthermore, since no new 0-1 variables are added to the calculation process, the impact on computational efficiency is minimal, making it valuable for engineering practice in large-scale systems. Furthermore, this method only modifies some variable constraints, making minimal changes to the existing clearing framework and resulting in high technical compatibility.

[0233] See also Figure 4 In one embodiment of the present application, a device for determining effective spare capacity taking into account grid congestion is provided, comprising:

[0234] Model building unit 01, used to build a safety constraint unit commitment model without considering positive reserve constraints;

[0235] The constraint construction unit 02 is used to determine the constraint conditions of the safety constraint unit commitment model, perform unit operation cost modeling, and generate a target model; the constraint conditions include system constraints, unit constraints, unit group constraints, and network constraints; the system constraints include establishing positive standby variable constraints for each unit;

[0236] The solving unit 03 is used to solve the target model until the target model converges to obtain the effective spare capacity.

[0237] It can be understood that the device provided in this embodiment is used to execute the effective spare capacity determination method considering grid congestion as described in any of the above embodiments and achieve the same technical effect, which will not be further described here.

[0238] In the several embodiments provided in this application, it should be understood that the disclosed systems, devices and methods can be implemented in other ways. For example, the device embodiments described above are only schematic. For example, the division of the units is only a logical function division. In actual applications, there may be other division methods when implementing them. For example, multiple units or page components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the mutual coupling or direct coupling or communication connection shown or discussed can be through some interfaces, indirect coupling or communication connection of devices or units, which can be electrical, mechanical or other forms.

[0239] 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 these units may be selected to achieve the purpose of this embodiment according to actual needs.

[0240] In addition, the functional units in the various embodiments of the present application may be integrated into a single processing unit, or each unit may exist physically separately, or two or more units may be integrated into a single unit. The aforementioned integrated units may be implemented in the form of hardware or in the form of hardware plus software functional units.

[0241] The above-mentioned integrated unit implemented in the form of a software functional unit can be stored in a computer-readable storage medium. The above-mentioned software functional unit is stored in a storage medium and includes a number of instructions for causing a computer device (which can be a personal computer, server, or network device, etc.) or a processor to perform some steps of the method described in each embodiment of the present application. The aforementioned storage medium includes: a USB flash drive, a mobile hard disk, a read-only memory (ROM), a random access memory (RAM), a magnetic disk or an optical disk, and other media that can store program code.

[0242] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present application, rather than to limit them. Although the present application has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that they can still modify the technical solutions described in the aforementioned embodiments, or make equivalent replacements for some of the technical features therein. However, these modifications or replacements do not deviate the essence of the corresponding technical solutions from the spirit and scope of the technical solutions of the embodiments of the present application.

Claims

1. A method for determining effective reserve capacity considering grid congestion, characterized in that: include: Construct a safety-constrained unit commitment model without considering positive reserve constraints; Determining the constraints of the safety-constrained unit commitment model, performing unit operating cost modeling, and generating a target model; the constraints include system constraints, unit constraints, unit group constraints, and network constraints; the system constraints include establishing positive standby variable constraints for each unit; The unit constraints also include determining the unit operating state and the coupling constraints of the standby variables, including: If the start-stop curve is not considered, the following constraints are established: Where, α i,t represents the start and stop status of unit i in period t, α i,t =0 means the unit is shut down, α i,t =1 means the unit is on; is the maximum output of unit i in period t; PR i,t represents the maximum effective reserve that unit i can provide at time t; P i,t represents the output of unit i in period t; If the start-stop curve is considered, the following constraints are established: Where UD is the duration of the startup process, calculated to the minimum output; DD is the duration of the shutdown process, calculated from the minimum output; β i,t 0-1 variable indicating the start of the unit, γ i,t Indicates whether unit i switches to the shutdown state during period t; is the maximum output of unit i in period t, P i,t represents the output of unit i in period t; N represents the total number of units; The network constraints include: Determine the line power flow constraints: Where, P l max is the power transmission limit of line l; G l-i is the generator output power transfer distribution factor of the node where unit i is located on line l; G l-j is the generator output power transfer distribution factor of the node where the tie line j is located to the line l; K is the number of nodes in the system; G l-k is the generator output power transfer distribution factor of node k on line l; D k,t is the bus load value of node k in period t; are the forward and reverse power flow slack variables of line l respectively; NT is the total number of tie lines; Determine the cross-sectional power flow constraints: Where, are the tidal current transmission limits of section s; G s-i G is the generator output power transfer distribution factor of the node where unit i is located on section s; s-j G is the generator output power transfer distribution factor of the node where the tie line j is located on section s; s-k is the generator output power transfer distribution factor of node k to section s; are the forward and reverse tidal relaxation variables of section s respectively; T j,t It represents the planned power of tie line j in time period t, with input being positive and output being negative; Determine the backup network security constraints: Where, represent the transfer distribution factors above the sensitivity threshold in the forward and reverse directions, respectively; The target model is solved until the target model converges to obtain the effective spare capacity.

2. The method for determining effective reserve capacity considering grid congestion according to claim 1, characterized in that: The construction of the safety constraint unit commitment model without considering the positive reserve constraint includes: Where N is the total number of units; T is the total number of time periods considered; P i,t represents the output of unit i in period t; C i,t (P i,t ), are the operating cost and startup cost of unit i in period t, respectively, where the unit operating cost C i,t (P i,t ) is a multi-segment linear function related to the output ranges reported by the units and the corresponding energy prices; H is the network power flow constraint relaxation penalty factor used for market clearing optimization, usually 100 million; are the forward and reverse power flow slack variables of line l respectively; NL is the total number of lines; are the forward and reverse tidal flow relaxation variables of section s respectively; NS is the total number of sections.

3. The method for determining effective reserve capacity considering grid congestion according to claim 2, characterized in that: The system constraints also include system load balance constraints, system negative reserve capacity constraints and system spinning reserve constraints; wherein, The positive reserve variable constraint of each unit is established as follows: Where, α i,t represents the start and stop status of unit i in period t, α i,t =0 means the unit is shut down, α i,t =1 means the unit is on; is the maximum output of unit i in period t; PR i,t represents the maximum effective reserve that unit i can provide at time t; is the system positive reserve capacity requirement for period t; Establish the load balancing constraint for each time period t: Where, P i,t represents the output of unit i in period t, T j,t represents the planned power of tie line j in time period t, with input as positive and output as negative, NT as the total number of tie lines, D t is the system load during period t; Establish the negative spare capacity constraint of the system: Where, is the minimum output of unit i in period t; is the system negative reserve capacity requirement for period t; Establish the system spinning reserve constraints: Where ΔP i U is the maximum ramp rate of unit i, ΔP i D is the maximum down-slope rate of unit i; are the maximum and minimum outputs of unit i in period t respectively; They are respectively used to increase and decrease the spinning reserve requirement for period t.

4. The method for determining effective reserve capacity considering grid congestion according to claim 3, characterized in that: Determining the fleet constraints includes: Determine the upper and lower limits of the unit output: If the unit is shut down, α i,t = 0, then the unit output can be limited to 0 through this constraint; when the unit is turned on, α i,t =1, this constraint is the conventional upper and lower limit constraint of output; Determine the unit climbing constraints: Where ΔP i U is the maximum ramp rate of unit i, ΔP i D is the maximum down-slope rate of unit i; Determine the minimum continuous start and stop time constraints of the unit: Where, α i,t is the start and stop status of unit i in period t; T U 、T D The minimum continuous start time and minimum continuous stop time of the unit; The state variable α is the continuous start-up time and continuous shutdown time of unit i in period t. i,t (i=1~N, t=1~T) to express: Determine the maximum start and stop times constraint for the unit: Define the switching variables for start and stop, and define η i,t Is the unit i switched to the startup state in period t? Define γ i,t Indicates whether unit i switches to shutdown state during period t, η i,t , γ i,t The following conditions are met: The start and stop times limit for the corresponding unit i is: Where, are the maximum number of starts and stops of unit i respectively; Among them, η i,t , γ i,t satisfy: Determine the unit power constraints: Where T represents the total number of time periods considered; T0 is the length of a time period in the planning cycle. If 96 time periods are considered per day, each time period is 15 minutes, that is, T0 = 0.25 hours; are the maximum and minimum power of unit i respectively; Determine the unit's designated state constraints, including maintenance status, designated start and shutdown, and designated output.

5. The method for determining effective reserve capacity considering grid congestion according to claim 1, characterized in that: Determining the group constraints includes: Determine the upper and lower limits of the generator group output: Where, is the maximum and minimum output of group I in time period t; Determine the power constraints of the unit group: Where T0 is the total number of time periods on D day, which is 96. The upper limit of power consumption of unit group I on day D.

6. The method for determining effective reserve capacity considering grid congestion according to claim 1, characterized in that: The unit operation cost modeling includes: Determine the unit output: Where, M is the total number of sections in the unit quotation, P i,t,m is the winning bid power of unit i in the mth output interval during period t, are the upper and lower bounds of the mth output interval declared by unit i; Determine the unit operating costs: Where, M is the total number of sections in the unit quotation, C i,t,m is the energy price corresponding to the mth output segment declared by unit i in period t; Determine the unit startup cost: Where, is the single startup cost of unit i, η i,t Indicates whether unit i switches to the startup state during period t.

7. The method for determining effective reserve capacity considering grid congestion according to claim 1, characterized in that: Solving the target model until the target model converges to obtain effective spare capacity includes: When the target model output does not converge, the positive reserve demand is reduced according to the preset conditions and the target model solution process is returned until the target model converges and the effective reserve capacity is obtained.

8. A device for determining effective spare capacity considering grid congestion, characterized in that: include: A model building unit, used for building a safety constraint unit commitment model without considering positive reserve constraints; a constraint construction unit, configured to determine the constraint conditions of the safety constraint unit commitment model, perform unit operation cost modeling, and generate a target model; the constraint conditions include system constraints, unit constraints, unit group constraints, and network constraints; the system constraints include establishing positive standby variable constraints for each unit; The unit constraints also include determining the unit operating state and the coupling constraints of the standby variables, including: If the start-stop curve is not considered, the following constraints are established: Where, α i,t represents the start and stop status of unit i in period t, α i,t =0 means the unit is shut down, α i,t =1 means the unit is on; is the maximum output of unit i in period t; PR i,t represents the maximum effective reserve that unit i can provide at time t; P i,t represents the output of unit i in period t; If the start-stop curve is considered, the following constraints are established: Where UD is the duration of the startup process, calculated to the minimum output; DD is the duration of the shutdown process, calculated from the minimum output; β i,t 0-1 variable indicating the start of the unit, γ i,t Indicates whether unit i switches to the shutdown state during period t; is the maximum output of unit i in period t, P i,t represents the output of unit i in period t; N represents the total number of units; The network constraints include: Determine the line power flow constraints: Where, P l max is the power transmission limit of line l; G l-i is the generator output power transfer distribution factor of the node where unit i is located on line l; G l-j is the generator output power transfer distribution factor of the node where the tie line j is located to the line l; K is the number of nodes in the system; G l-k is the generator output power transfer distribution factor of node k on line l; D k,t is the bus load value of node k in period t; are the forward and reverse power flow slack variables of line l respectively; NT is the total number of tie lines; Determine the cross-sectional power flow constraints: Where, are the tidal current transmission limits of section s; G s-i G is the generator output power transfer distribution factor of the node where unit i is located on section s; s-j G is the generator output power transfer distribution factor of the node where the tie line j is located on section s; s-k is the generator output power transfer distribution factor of node k to section s; are the forward and reverse tidal relaxation variables of section s respectively; T j,t It represents the planned power of tie line j in time period t, with input being positive and output being negative; Determine the backup network security constraints: Where, represent the transfer distribution factors above the sensitivity threshold in the forward and reverse directions, respectively; The solving unit is used to solve the target model until the target model converges to obtain the effective spare capacity.

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