Multi-category control resource optimization control method suitable for urban power grid loop closing

Abstract

The invention discloses a multi-category control resource optimization control method suitable for loop closing of an urban power grid, and the method comprises the steps: calculating a loop closing steady-state current at a loop closing point according to an actual loop closing scene in the power grid; calculating a closed-loop steady-state current regulating variable according to the closed-loop steady-state current and a preset circuit breaker overload operating value; determining node injection current variable quantity of each current injection node in the power grid according to a current sensitivity factor of each current injection node in the power grid to a loop closing point and a loop closing steady-state current adjusting quantity which are determined in advance; determining a search area of the controllable resource node according to the electrical distance index, and determining a target function according to the adjustment priority of various controllable resources in the search area and the loop closing stable current adjustment quantity; and based on the objective function and a preset constraint condition, performing optimization calculation according to the node injection current variable quantity of each controllable resource in the search area by adopting an optimal particle swarm method, and determining a multi-category resource optimization control strategy of the power grid.

Description

Technical Field

[0001] The present invention relates to the technical field of urban power grids, and more specifically, to a multi-category control resource optimization control method suitable for urban power grid loop closure. Background Art

[0002] At present, my country's large-scale urban power grid has formed a grid structure dominated by 500kV, and the 220kV power grid has been gradually unblocked to realize the operation mode of 220kV zoned power supply. While the zoned operation of the power grid reduces the short-circuit capacity of the power grid, it also causes the increase of the electrical distance between the zone boundary points, resulting in an increase in the voltage amplitude difference and phase angle difference on both sides of the tie switch between different zones. Therefore, when the cross-zone power grid performs a closed-loop operation, its closed-loop current is often large. If the closed-loop current exceeds the setting value of the relay protection device, it will cause the closed-loop failure, which will bring hidden dangers to the safe operation and reliable power supply of the power grid. According to statistics, there are about 1,300 closed-loop switching operations in the Beijing power grid every year, of which about 140 are important mode switching operations. Therefore, it is urgent to propose an effective closed-loop current control method, effectively utilize the multi-category control resources such as generators, new energy, and controllable loads within the urban power grid, realize the effective suppression of the closed-loop current, and improve the success rate of the urban power grid closed-loop, especially the cross-zone closed-loop. Summary of the invention

[0003] In view of the deficiencies in the prior art, the present invention provides a multi-category control resource optimization control method suitable for urban power grid loop closure.

[0004] According to one aspect of the present invention, a multi-category control resource optimization control method applicable to a city power grid loop is provided, comprising:

[0005] According to the actual closing scenario in the power grid, the closing steady-state current at the closing point is calculated;

[0006] Calculate the closed-loop steady-state current adjustment amount according to the closed-loop steady-state current and the preset circuit breaker overload action value;

[0007] Determine the node injection current variation of each current injection node in the power grid according to the current sensitivity factor of each current injection node in the power grid to the closing point and the closing steady-state current regulation amount;

[0008] Determine the search area of ​​the controllable resource node according to the electrical distance index, and determine the objective function according to the adjustment priority of various controllable resources in the search area and the closed-loop stable current adjustment amount;

[0009] Based on the objective function and preset constraints, the optimal particle swarm method is used to optimize the calculation according to the node injection current change of each controllable resource in the search area to determine the multi-category resource optimization control strategy of the power grid.

[0010] Optionally, the closed-loop steady-state current calculation formula is:

[0011]

[0012] Among them, I s is the steady-state current value after loop closing, is the voltage vector difference of the nodes on both sides of the closing point, E1 and E2 are the voltage effective values ​​of the nodes on both sides of the closing point, δ 12 is the voltage phase difference between the nodes on both sides of the closed loop, and Z is the equivalent impedance of the closed loop.

[0013] Optionally, the calculation formula of the closed-loop steady-state current regulation amount is:

[0014] ΔI=α(I s -I ref )

[0015] In the formula, I ref is the overload action value of the circuit breaker, and α is the insurance coefficient.

[0016] Optionally, the relationship between the node injection current change of each node in the power grid and the current change on the closed-loop branch is:

[0017] ΔI Li =γ i-j ΔI j

[0018] Where i is the number of the branch where the closing point is located, ΔI Li is the current change on branch i, ΔI j is the change in the current injected into node j, γ i-j It is the sensitivity factor of the closed-loop current on branch i to the injected current at node j.

[0019] Optionally, determining a search area of ​​a controllable resource node according to an electrical distance indicator includes:

[0020] Starting from the nodes on both sides of the closing point, k neighboring nodes are extended to form a search area, where the nodes in the search area constitute a controllable resource node set, and the k value is an electrical distance index determined according to the actual closing scenario.

[0021] Optionally, the objective function is:

[0022]

[0023] In the formula, p(ΔI L ) is the penalty function generated when the closed-loop current is higher than the circuit breaker action value, C j is the unit control cost of controlling resource node j, ΔP j is the power adjustment amount for controlling resource node j.

[0024] Optionally, the preset constraint conditions include: active power balance constraint of the power grid, reactive power balance constraint and controllable resource output constraint in the search area, wherein the controllable resource output constraint is:

[0025]

[0026] Where P new , P st and P Load are the active power of new energy, energy storage and load respectively, P st.N is the rated power of the energy storage device, P new.t and P Load.t are the current power of new energy and load respectively, P Load.min is the minimum load power.

[0027] According to another aspect of the present invention, there is provided a multi-category control resource optimization control device applicable to a city power grid closed loop, comprising:

[0028] A first calculation module is used to calculate the closed-loop steady-state current at the closed-loop point according to an actual closed-loop scenario in the power grid;

[0029] The second calculation module is used to calculate the closed-loop steady-state current adjustment amount according to the closed-loop steady-state current and the preset circuit breaker overload action value;

[0030] A first determination module is used to determine the node injection current variation of each current injection node in the power grid according to the current sensitivity factor of each current injection node in the power grid to the closing point and the closing steady-state current regulation amount;

[0031] The second determination module is used to determine the search area of ​​the controllable resource node according to the electrical distance index, and determine the objective function according to the adjustment priority of various controllable resources in the search area and the closed-loop stable current adjustment amount;

[0032] The optimization calculation module is used to optimize the calculation based on the objective function and preset constraints, and adopt the optimal particle swarm method according to the node injection current change of each controllable resource in the search area to determine the multi-category resource optimization control strategy of the power grid.

[0033] According to another aspect of the present invention, a computer-readable storage medium is provided, wherein the storage medium stores a computer program, and the computer program is used to execute the method described in any one of the above aspects of the present invention.

[0034] According to another aspect of the present invention, an electronic device is provided, comprising: a processor; a memory for storing instructions executable by the processor; the processor is configured to read the executable instructions from the memory and execute the instructions to implement the method described in any one of the above aspects of the present invention.

[0035] Therefore, the present invention proposes a multi-category control method for optimizing control of control resources suitable for the closing of urban power grids. According to the actual closing scenario of the power grid, the current sensitivity factor of the closing current to each current injection node in the power grid is first calculated to clarify the control sensitivity of control resources at different positions to the closing current. Then, a method for determining the search area for controllable resources is proposed to clarify the node range of the control resources that can be included in the optimization algorithm, effectively avoiding the problem of low algorithm calculation efficiency caused by too many nodes. Finally, the optimal control amount of each category of resources is clarified in combination with the optimal particle swarm algorithm, so as to achieve effective suppression of the closing current of the urban power grid, thereby effectively improving the closing success rate of the urban power grid and the flexible and reliable operation capability. BRIEF DESCRIPTION OF THE DRAWINGS

[0036] A more complete understanding of exemplary embodiments of the present invention may be obtained by referring to the following drawings:

[0037] Figure 1 It is a flow chart of a multi-category control resource optimization control method applicable to a city power grid closed loop provided by an exemplary embodiment of the present invention;

[0038] Figure 2 is a schematic diagram of a controllable resource search area provided by an exemplary embodiment of the present invention;

[0039] Figure 3 This is a schematic diagram of a 220kV closed loop scenario in a large urban power grid provided by an exemplary embodiment of the present invention;

[0040] Figure 4 It is a schematic diagram of the change of the closed-loop current time-domain simulation curve before and after the closed-loop control strategy is adopted, provided by an exemplary embodiment of the present invention;

[0041] Figure 5 It is a structural schematic diagram of a multi-category control resource optimization control device applicable to a city power grid loop provided by an exemplary embodiment of the present invention;

[0042] Figure 6 This is a structure of an electronic device provided by an exemplary embodiment of the present invention. DETAILED DESCRIPTION

[0043] Below, the exemplary embodiments according to the present invention will be described in detail with reference to the accompanying drawings. Obviously, the described embodiments are only part of the embodiments of the present invention, rather than all the embodiments of the present invention, and it should be understood that the present invention is not limited to the exemplary embodiments described here.

[0044] It should be noted that the relative arrangement of components and steps, the numerical expressions and numerical values ​​set forth in these embodiments do not limit the scope of the present invention unless specifically stated otherwise.

[0045] Those skilled in the art can understand that the terms "first" and "second" in the embodiments of the present invention are only used to distinguish different steps, devices or modules, etc., and neither represent any specific technical meaning nor indicate the necessary logical order between them.

[0046] It should also be understood that, in the embodiments of the present invention, “plurality” may refer to two or more than two, and “at least one” may refer to one, two or more than two.

[0047] It should also be understood that any component, data or structure mentioned in the embodiments of the present invention can generally be understood as one or more, unless explicitly limited or otherwise indicated in the context.

[0048] In addition, the term "and / or" in the present invention is only a description of the association relationship of the associated objects, indicating that there can be three relationships. For example, A and / or B can represent: A exists alone, A and B exist at the same time, and B exists alone. In addition, the character " / " in the present invention generally indicates that the associated objects before and after are in an "or" relationship.

[0049] It should also be understood that the description of the various embodiments of the present invention focuses on the differences between the various embodiments, and the same or similar aspects thereof can be referenced to each other, and for the sake of brevity, they will not be described one by one.

[0050] At the same time, it should be understood that for the convenience of description, the sizes of the various parts shown in the drawings are not drawn according to the actual proportional relationship.

[0051] The following description of at least one exemplary embodiment is merely illustrative in nature and is in no way intended to limit the invention, its application, or uses.

[0052] Technologies, methods, and equipment known to ordinary technicians in the relevant art may not be discussed in detail, but where appropriate, the technologies, methods, and equipment should be considered part of the specification.

[0053] It should be noted that like reference numerals and letters refer to similar items in the following figures, and therefore, once an item is defined in one figure, it need not be further discussed in subsequent figures.

[0054] Embodiments of the present invention can be applied to electronic devices such as terminal devices, computer systems, servers, etc., which can operate with many other general or special computing system environments or configurations. Examples of well-known terminal devices, computing systems, environments and / or configurations suitable for use with electronic devices such as terminal devices, computer systems, servers, etc. include, but are not limited to: personal computer systems, server computer systems, thin clients, thick clients, handheld or laptop devices, microprocessor-based systems, set-top boxes, programmable consumer electronics, network personal computers, small computer systems, large computer systems, and distributed cloud computing technology environments including any of the above systems, etc.

[0055] Electronic devices such as terminal devices, computer systems, servers, etc. can be described in the general context of computer system executable instructions (such as program modules) executed by computer systems. Generally, program modules can include routines, programs, object programs, components, logic, data structures, etc., which perform specific tasks or implement specific abstract data types. Computer systems / servers can be implemented in a distributed cloud computing environment, where tasks are performed by remote processing devices linked through a communication network. In a distributed cloud computing environment, program modules can be located on local or remote computing system storage media including storage devices.

[0056] Exemplary Methods

[0057] Figure 1 1 is a flow chart of a multi-category control resource optimization control method applicable to a city power grid loop provided by an exemplary embodiment of the present invention. This embodiment can be applied to electronic devices, such as Figure 1 As shown, the multi-category control resource optimization control method 100 applicable to the urban power grid closed loop includes the following steps:

[0058] Step 101, calculating the closed-loop steady-state current at the closed-loop point according to the actual closed-loop scenario in the power grid;

[0059] Step 102, calculating the closed-loop steady-state current adjustment amount according to the closed-loop steady-state current and the preset circuit breaker overload action value;

[0060] Step 103, determining the node injection current variation of each current injection node in the power grid according to the current sensitivity factor of each current injection node in the power grid to the closing point and the closing steady-state current regulation amount;

[0061] Step 104, determining a search area for controllable resource nodes according to the electrical distance index, and determining an objective function according to the adjustment priority of various controllable resources in the search area and the closed-loop stable current adjustment amount;

[0062] Step 105, based on the objective function and preset constraints, an optimal particle swarm method is used to optimize the calculation according to the node injection current change of each controllable resource in the search area to determine the multi-category resource optimization control strategy of the power grid.

[0063] Specifically, the present invention aims at the practical problem that the closing current may be too large and the closing current may fail when the urban power grid is closed across zones, and proposes a multi-category control method for optimizing control of control resources suitable for the closing of urban power grids. According to the actual closing scenario of the power grid, the current sensitivity factor of the closing current to each current injection node in the power grid is first calculated to clarify the control sensitivity of control resources at different positions to the closing current. Then, a method for determining the search area for controllable resources is proposed to clarify the range of nodes where the control resources that can be included in the optimization algorithm are located, effectively avoiding the problem of low algorithm calculation efficiency caused by too many nodes. Finally, the optimal control amount of each category of resources is clarified in combination with the optimal particle swarm algorithm, so as to achieve effective suppression of the closing current of the urban power grid.

[0064] Step 1: According to the actual closed-loop scenario, calculate the current sensitivity factor of the closed-loop current to each current injection node in the power grid.

[0065] According to the actual closing scenario in the power grid, the steady-state current at the closing point after closing is first calculated:

[0066]

[0067] Among them, I L is the steady-state current value on the line where the closing point is located after the closing of the loop, is the voltage vector difference of the nodes on both sides of the closing point, E1 and E2 are the voltage effective values ​​of the nodes on both sides of the closing point, δ 12 is the voltage phase difference between the nodes on both sides of the closed loop, and Z is the equivalent impedance of the closed loop.

[0068] Compare the closing current with the overload current action value of the circuit breakers at both ends of the line. When the calculated closing current exceeds the action value, the circuit breaker at the closing point will be activated after the closing, resulting in closing failure. To avoid this situation, various controllable resources near the closing point should be controlled, such as controllable loads, centralized or distributed new energy, generators, energy storage power stations, etc., to achieve effective suppression of the closing current. Based on formula (1), the adjustment amount of the closing current ΔI is obtained: L for:

[0069] ΔI L =α(I L -I L.ref ) (2)

[0070] Among them, I L.ref is the overload action value of the circuit breaker, α is the insurance factor, and the recommended value range is [1.2,1.5].

[0071] The practice of power grid operation shows that different types of resources at different locations in the power grid have different regulating effects on the closed-loop current. Therefore, it is very important to clarify the regulating ability of different resources at different locations on the closed-loop current. A current sensitivity factor index is proposed, which is:

[0072] ΔI Li =γ i-j ΔI j (3)

[0073] Among them, i is the number of the branch where the closing point is located, ΔI Li is the current change on branch i, ΔI j is the change in the current injected into node j, γ i-j It is the sensitivity factor of the closed-loop current on branch i to the injected current at node j.

[0074] Since the steady-state value of the closed-loop current depends on the magnitude of the power flow on the branch after the closed loop, the influence of the injected current of different nodes on the branch power flow after the closed loop switch is closed should be considered when calculating the sensitivity factor. According to the power flow calculation formula of the fast decomposition method, we have:

[0075] Δθ=XΔP (4)

[0076] Among them, ΔP is the column vector of node injection power change, Δθ is the column vector of voltage phase angle change, B0 is the susceptance matrix established with 1 / x as the branch parameter, and X is the inverse matrix of B0.

[0077] The relationship vector between the node injection power vector and the injection current vector is:

[0078] ΔP=UΔI (5)

[0079]

[0080] Among them U j is the voltage value of node j, j=1,2,...,n.

[0081] According to equations (4), (5), and (6), the change in the closed-loop current on branch i (assuming that the node numbers at both ends of the branch where the closed-loop point is located are m and n respectively) caused by the change in the injected current at node j is:

[0082]

[0083] Among them, X mi and X ni are the mth and nth row elements in the i-th column of matrix X, respectively, and U m is the voltage value of node m.

[0084] Therefore, the current sensitivity factor is:

[0085]

[0086] Step 2: Define the search area for controllable resource nodes based on the electrical distance index, and clarify the distribution and adjustable capacity of various controllable resources within the area.

[0087] The nodes contained in the urban power grid, as well as adjustable resources such as generators and loads, are massive. If the resources of the entire network are calculated uniformly, the calculation time will be too long and even the algorithm will fall into the "curse of dimensionality", making it impossible to obtain the optimal solution. To avoid this situation, it is necessary to divide the distribution area of ​​controllable resources according to the closed-loop scenario, and only adjust the controllable resources within the area, effectively suppressing the closed-loop current while improving the calculation efficiency of the algorithm. Therefore, a simple method for dividing the controllable resource area that is easy for dispatchers to actually use is proposed.

[0088] A large number of simulation calculations and practical experience in power grid operation have found that when the electrical distance between the controllable resource and the closing point is close, the closing current control effect is better. On the contrary, the greater the electrical distance, the smaller the impact on the closing current. Therefore, in actual operation, based on the actual closing scenario, starting from the nodes on both sides of the closing point, k neighboring nodes can be extended to form a controllable resource node set R = {···i···j···}. The k value can be determined by the dispatching operation personnel according to the actual closing scenario, such as Figure 2 As shown, the red part is the closed-loop switch. If k is taken as 2, the controllable resource search area is the area surrounded by the dotted line.

[0089] After the closed-loop resource control area is identified, resources that can participate in the closed-loop current control are sought in the area, such as traditional generators, centralized or distributed new energy, energy storage devices, and controllable loads, etc. The adjustable range of each type of resource is identified.

[0090] For traditional generators, their active output P tr Generally, the maximum rated power can reach P tr.N , there is a minimum limit P tr.min , for thermal power units, it is generally 30% to 50% of the rated power. Under normal circumstances, new energy units operate at maximum power, the output range of energy storage devices is between positive and negative rated values, and the load should consider the actual load allowed to be removed in the power grid. Therefore, considering the above factors, the active output adjustment range of various controllable resources is as follows:

[0091]

[0092] Among them, P new , P st and P Load are the active power of new energy, energy storage and load respectively, P st.Nis the rated power of the energy storage device, P new.t and P Load.t are the current power of new energy and load respectively, P Load.min is the minimum load power.

[0093] Step 3: Determine the objective function based on the adjustment priority of various adjustment resources, and formulate a multi-category resource optimization control strategy based on the optimal particle swarm algorithm

[0094] The optimal particle swarm algorithm is adopted to optimize the calculation of all regulating resources in the search area, and finally the optimal control strategy of each regulating resource is obtained.

[0095] For the controllable resource node set R = {···i···j···} formed in step 2, assuming that the node set contains M controllable resources, any particle in the particle swarm can be expressed as

[0096] α i =[α i.1 α i.2 ··· α i.M ] (10)

[0097] The particle velocity can be expressed as:

[0098] v i =[v i.1 v i.2 ··· v i.N ] (11)

[0099] The objective function is composed of a penalty function consisting of the closed-loop current being higher than the circuit breaker action value and various resource control costs:

[0100]

[0101] Among them, p(ΔI L ) is the penalty function generated when the closed-loop current is higher than the circuit breaker action value, C j is the unit control cost of controlling resource node j, ΔP j is the power adjustment amount for controlling resource node j.

[0102] The constraints include the active and reactive power balance constraints of the power grid and the controllable resource output constraints of formula (9).

[0103] Since the optimal particle swarm algorithm is already very mature, its specific calculation process will not be described here.

[0104] Through iterative calculation of the optimal particle swarm, the global optimal particle is finally obtained as the optimal control strategy for each type of control resource.

[0105] Taking a large urban power grid in my country as an example, two 220kV power grid divisions in the power grid are as follows: Figure 3 As shown in the figure, the black switch is the closing circuit breaker between two partitions. In this example, the k value is 3. According to step 2, three neighboring nodes are extended from nodes 1 and 2 on both sides of the closing point, and the search area is as shown in the figure below. Figure 2 As shown by the dashed line, the controllable resources in the area include 2 conventional units (numbered GE1 and GE2) and 3 new energy units (numbered NE1, NE2, and NE3). The conventional units are all running at maximum power. According to local dispatch requirements, each unit can reduce its output by a maximum of 100MW. The output of the three new energy units is 100MW, and the output adjustment range is 0-100MW. Since the city's power grid has high requirements for power supply reliability, load shedding control measures are not considered.

[0106] In the initial mode, after the closing circuit breaker is closed, the steady-state current value of the closing branch is 1182A, and the overload action value of the closing circuit breaker is 950A. Therefore, if no closing current suppression measures are taken, the circuit breaker will be disconnected again after closing, resulting in closing failure. To avoid this phenomenon, reasonable control measures must be taken to suppress the closing current.

[0107] According to the formula in step 1, the current sensitivity factors of the closed-loop current to the conventional unit and the new energy unit are calculated respectively, and the calculation results are shown in Table 1. Among them, a positive sensitivity factor indicates that the closed-loop current is positively correlated with the generator output. At this time, reducing the generator output can suppress the closed-loop current, and vice versa.

[0108] Table 1 Current sensitivity factors of different generators

[0109]

[0110]

[0111] The insurance coefficient α in formula (2) is taken as 1.2, and the closed-loop current suppression value is 278 A. In step 3, the optimal particle swarm algorithm is used to optimize the adjustment amount of each generator, and finally the optimal control strategy is obtained as shown in Table 2, that is, the active output of the generator GE1 is controlled to be reduced by 100MW, and the active output of the new energy unit NE1 is controlled to be reduced by 82.7MW.

[0112] Table 2 Closed-loop current optimization control strategy

[0113]

[0114] The above optimal control strategy was simulated and verified. The closed-loop current curve obtained by time domain simulation is shown in the figure below: Figure 4As shown, it can be found that after the generator set is controlled according to the proposed control strategy, the stable current after closing the loop drops from 1182A to 932A, which is lower than the overcurrent protection action value of the circuit breaker. The loop is closed successfully, thus verifying the effectiveness of the proposed method.

[0115] Therefore, the present invention proposes a multi-category control method for optimizing control of control resources suitable for the closing of urban power grids. According to the actual closing scenario of the power grid, the current sensitivity factor of the closing current to each current injection node in the power grid is first calculated to clarify the control sensitivity of control resources at different positions to the closing current. Then, a method for determining the search area for controllable resources is proposed to clarify the node range of the control resources that can be included in the optimization algorithm, effectively avoiding the problem of low algorithm calculation efficiency caused by too many nodes. Finally, the optimal control amount of each category of resources is clarified in combination with the optimal particle swarm algorithm, so as to achieve effective suppression of the closing current of the urban power grid, thereby effectively improving the closing success rate of the urban power grid and the flexible and reliable operation capability.

[0116] Exemplary Devices

[0117] Figure 5 1 is a schematic diagram of a multi-category control resource optimization control device applicable to a city power grid loop provided by an exemplary embodiment of the present invention. Figure 5 As shown, the device 500 includes:

[0118] A first calculation module 510 is used to calculate the closed-loop steady-state current at the closed-loop point according to an actual closed-loop scenario in the power grid;

[0119] The second calculation module 520 is used to calculate the closed-loop steady-state current adjustment amount according to the closed-loop steady-state current and the preset circuit breaker overload action value;

[0120] A first determination module 530 is used to determine the node injection current variation of each current injection node in the power grid according to the current sensitivity factor of each current injection node in the power grid to the closing point and the closing steady-state current regulation amount;

[0121] The second determination module 540 is used to determine the search area of ​​the controllable resource node according to the electrical distance index, and determine the objective function according to the adjustment priority of each type of controllable resource in the search area and the closed-loop stable current adjustment amount;

[0122] The optimization calculation module 550 is used to perform optimization calculation based on the objective function and preset constraints, using the optimal particle swarm method according to the node injection current change of each controllable resource in the search area, and determine the multi-category resource optimization control strategy of the power grid.

[0123] Optionally, the closed-loop steady-state current calculation formula is:

[0124]

[0125] Among them, I s is the steady-state current value after loop closing, is the voltage vector difference of the nodes on both sides of the closing point, E1 and E2 are the voltage effective values ​​of the nodes on both sides of the closing point, δ 12 is the voltage phase difference between the nodes on both sides of the closed loop, and Z is the equivalent impedance of the closed loop.

[0126] Optionally, the calculation formula of the closed-loop steady-state current regulation amount is:

[0127] ΔI=α(I s -I ref )

[0128] In the formula, I ref is the overload action value of the circuit breaker, and α is the insurance coefficient.

[0129] Optionally, the relationship between the node injection current change of each node in the power grid and the current change on the closed-loop branch is:

[0130] ΔI Li =γ i-j ΔI j

[0131] Where i is the number of the branch where the closing point is located, ΔI Li is the current change on branch i, ΔI j is the change in the current injected into node j, γ i-j It is the sensitivity factor of the closed-loop current on branch i to the injected current at node j.

[0132] Optionally, the second determining module 540 determines the search area of ​​the controllable resource node according to the electrical distance index, including:

[0133] The submodule is used to extend k neighboring nodes from the nodes on both sides of the loop point to form a search area, where the nodes in the search area constitute a controllable resource node set, and the k value is an electrical distance indicator determined according to the actual loop scenario.

[0134] Optionally, the objective function is:

[0135]

[0136] In the formula, p(ΔI L ) is the penalty function generated when the closed-loop current is higher than the circuit breaker action value, C j is the unit control cost of controlling resource node j, ΔP j is the power adjustment amount for controlling resource node j.

[0137] Optionally, the preset constraint conditions include: active power balance constraint of the power grid, reactive power balance constraint and controllable resource output constraint in the search area, wherein the controllable resource output constraint is:

[0138]

[0139] Where P new , P st and P Load are the active power of new energy, energy storage and load respectively, P st.N is the rated power of the energy storage device, P new.t and P Load.t are the current power of new energy and load respectively, P Load.min is the minimum load power.

[0140] Exemplary Electronic Devices

[0141] Figure 6 This is a structure of an electronic device provided by an exemplary embodiment of the present invention. Figure 6 As shown, the electronic device 60 includes one or more processors 61 and a memory 62 .

[0142] The processor 61 may be a central processing unit (CPU) or other forms of processing units having data processing capabilities and / or instruction execution capabilities, and may control other components in the electronic device to perform desired functions.

[0143] The memory 62 may include one or more computer program products, and the computer program product may include various forms of computer-readable storage media, such as volatile memory and / or non-volatile memory. The volatile memory may include, for example, random access memory (RAM) and / or cache memory (cache), etc. The non-volatile memory may include, for example, read-only memory (ROM), hard disk, flash memory, etc. One or more computer program instructions may be stored on the computer-readable storage medium, and the processor 61 may run the program instructions to implement the methods of the software programs of the various embodiments of the present invention described above and / or other desired functions. In one example, the electronic device may also include: an input device 63 and an output device 64, which are interconnected via a bus system and / or other forms of connection mechanisms (not shown).

[0144] In addition, the input device 63 may also include, for example, a keyboard, a mouse, etc.

[0145] The output device 64 can output various information to the outside, and can include, for example, a display, a speaker, a printer, a communication network and a remote output device connected thereto.

[0146] Of course, to simplify, Figure 6 Only some of the components related to the present invention in the electronic device are shown, and components such as a bus, an input / output interface, etc. are omitted. In addition, the electronic device may further include any other appropriate components according to specific application conditions.

[0147] Exemplary computer program products and computer-readable storage media

[0148] In addition to the above-mentioned methods and devices, an embodiment of the present invention may also be a computer program product, which includes computer program instructions, which, when executed by a processor, enable the processor to execute the steps of the method according to various embodiments of the present invention described in the above-mentioned "Exemplary Method" section of this specification.

[0149] The computer program product may be written in any combination of one or more programming languages ​​to write program code for performing the operations of the embodiments of the present invention, including object-oriented programming languages ​​such as Java, C++, etc., and conventional procedural programming languages ​​such as "C" or similar programming languages. The program code may be executed entirely on the user computing device, partially on the user device, as a separate software package, partially on the user computing device and partially on a remote computing device, or entirely on a remote computing device or server.

[0150] In addition, an embodiment of the present invention may also be a computer-readable storage medium having computer program instructions stored thereon, which, when executed by a processor, enable the processor to execute the steps of the method according to various embodiments of the present invention described in the above “Exemplary Method” section of this specification.

[0151] The computer readable storage medium can adopt any combination of one or more readable media. The readable medium can be a readable signal medium or a readable storage medium. The readable storage medium can include, for example, but is not limited to, a system, system or device of electricity, magnetism, light, electromagnetic, infrared, or semiconductor, or any combination of the above. More specific examples (non-exhaustive list) of readable storage media include: an electrical connection with one or more wires, a portable disk, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disk read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the above.

[0152] The basic principle of the present invention is described above in conjunction with specific embodiments. However, it should be pointed out that the advantages, strengths, effects, etc. mentioned in the present invention are only examples and not limitations, and it cannot be considered that these advantages, strengths, effects, etc. must be possessed by each embodiment of the present invention. In addition, the specific details disclosed above are only for the purpose of illustration and facilitation of understanding, rather than limitation, and the above details do not limit the present invention to being implemented by adopting the above specific details.

[0153] Each embodiment in this specification is described in a progressive manner, and each embodiment focuses on the differences from other embodiments. The same or similar parts between the embodiments can be referred to each other. For the system embodiment, since it basically corresponds to the method embodiment, the description is relatively simple, and the relevant parts can be referred to the partial description of the method embodiment.

[0154] The block diagrams of the devices, systems, equipment, and systems involved in the present invention are only illustrative examples and are not intended to require or imply that they must be connected, arranged, and configured in the manner shown in the block diagram. As will be appreciated by those skilled in the art, these devices, systems, equipment, and systems can be connected, arranged, and configured in any manner. Words such as "including", "comprising", "having", etc. are open words, referring to "including but not limited to", and can be used interchangeably with them. The words "or" and "and" used here refer to the words "and / or" and can be used interchangeably with them, unless the context clearly indicates otherwise. The word "such as" used here refers to the phrase "such as but not limited to", and can be used interchangeably with it.

[0155] The method and system of the present invention may be implemented in many ways. For example, the method and system of the present invention may be implemented by software, hardware, firmware or any combination of software, hardware, firmware. The above order of steps for the method is only for illustration, and the steps of the method of the present invention are not limited to the order specifically described above, unless otherwise specifically stated. In addition, in some embodiments, the present invention may also be implemented as a program recorded in a recording medium, which includes machine-readable instructions for implementing the method according to the present invention. Thus, the present invention also covers a recording medium storing a program for executing the method according to the present invention.

[0156] It should also be noted that in the system, device and method of the present invention, each component or each step can be decomposed and / or recombined. These decompositions and / or recombinations should be regarded as equivalent schemes of the present invention. The above description of the disclosed aspects is provided to enable any technician in the field to make or use the present invention. Various modifications to these aspects are very obvious to those skilled in the art, and the general principles defined here can be applied to other aspects without departing from the scope of the present invention. Therefore, the present invention is not intended to be limited to the aspects shown here, but in accordance with the widest range consistent with the principles and novel features disclosed here.

[0157] The above description has been given for the purpose of illustration and description. In addition, this description is not intended to limit the embodiments of the present invention to the forms disclosed herein. Although a number of example aspects and embodiments have been discussed above, those skilled in the art will recognize certain variations, modifications, changes, additions and sub-combinations thereof.

Claims

1. A multi-category control resource optimization control method suitable for urban power grid ring closure, characterized in that: include: According to the actual closing scenario in the power grid, the closing steady-state current at the closing point is calculated; Calculating a closed-loop steady-state current adjustment amount according to the closed-loop steady-state current and a preset circuit breaker overload action value; Determine the node injection current variation of each current injection node in the power grid according to the current sensitivity factor of each current injection node in the power grid to the closing point and the closing steady-state current regulation amount; Determine a search area for controllable resource nodes according to the electrical distance index, and determine an objective function according to the adjustment priority of various controllable resources in the search area and the closed-loop stable current adjustment amount; Based on the objective function and preset constraints, the optimal particle swarm method is used to optimize the calculation according to the node injection current change of each controllable resource in the search area to determine the multi-category resource optimization control strategy of the power grid.

2. The method according to claim 1, characterized in that: The closed-loop steady-state current calculation formula is: Among them, I s is the steady-state current value after loop closing, is the voltage vector difference of the nodes on both sides of the closing point, E1 and E2 are the voltage effective values ​​of the nodes on both sides of the closing point, δ 12 is the voltage phase difference between the nodes on both sides of the closed loop, and Z is the equivalent impedance of the closed loop.

3. The method according to claim 1, characterized in that The calculation formula of the closed-loop steady-state current regulation amount is: ΔI=α(I s -I ref ) In the formula, I ref is the overload action value of the circuit breaker, and α is the insurance coefficient.

4. The method according to claim 1, characterized in that: The relationship between the node injection current change of each node in the power grid and the current change on the closed-loop branch is: I Li =c i-j I j Where i is the number of the branch where the closing point is located, ΔI Li is the current change on branch i, ΔI j is the change in the current injected into node j, γ i-j It is the sensitivity factor of the closed-loop current on branch i to the injected current at node j.

5. The method according to claim 1, characterized in that The search area of ​​the controllable resource node is determined according to the electrical distance index, including: Starting from the nodes on both sides of the closing point, k neighboring nodes are extended to form a search area, where the nodes in the search area constitute a controllable resource node set, and the k value is an electrical distance index determined according to the actual closing scenario.

6. The method according to claim 1, characterized in that: The objective function is: In the formula, p(ΔI L ) is the penalty function generated when the closed-loop current is higher than the circuit breaker action value, C j is the unit control cost of controlling resource node j, ΔP j is the power adjustment amount for controlling resource node j.

7. The method according to claim 1, characterized in that: The preset constraints include: grid active power balance constraints, reactive power balance constraints, and controllable resource output constraints in the search area, wherein the controllable resource output constraints are: Where P new , P st and P Load are the active power of new energy, energy storage and load respectively, P st.N is the rated power of the energy storage device, P new.t and P Load.t are the current power of new energy and load respectively, P Load.min is the minimum load power.

8. A multi-category control resource optimization control device suitable for urban power grid ring closure, characterized in that: include: A first calculation module is used to calculate the closed-loop steady-state current at the closed-loop point according to an actual closed-loop scenario in the power grid; A second calculation module is used to calculate the closed-loop steady-state current adjustment amount according to the closed-loop steady-state current and a preset circuit breaker overload action value; A first determination module is used to determine the node injection current variation of each current injection node in the power grid according to the current sensitivity factor of each current injection node in the power grid to the closing point and the closing steady-state current adjustment amount; A second determination module is used to determine a search area for controllable resource nodes according to an electrical distance index, and determine an objective function according to the adjustment priority of various controllable resources in the search area and the closed-loop stable current adjustment amount; The optimization calculation module is used to optimize the calculation according to the change of the node injection current of each controllable resource in the search area based on the objective function and preset constraints, and determine the optimization control strategy of multiple categories of resources in the power grid.

9. The device according to claim 8, characterized in that The second determination module determines the search area of ​​the controllable resource node according to the electrical distance index, including: The submodule is used to extend k neighboring nodes from the nodes on both sides of the loop closing point to form a search area, wherein the nodes in the search area constitute a controllable resource node set, and the k value is an electrical distance index determined according to the actual loop closing scenario.

10. A computer-readable storage medium, characterized in that: The storage medium stores a computer program, and the computer program is used to execute the method according to any one of claims 1 to 7.

11. An electronic device, characterized in that: The electronic device comprises: processor; a memory for storing instructions executable by the processor; The processor is used to read the executable instructions from the memory and execute the instructions to implement the method described in any one of claims 1 to 7.

Images