Method, device, storage medium and equipment for evaluating reactive power output capability

Abstract

The present invention discloses a reactive power output capacity evaluation method and device, a storage medium and equipment, which belong to the technical field of power system control, and mainly aims to solve the problem of lack of reactive power evaluation in BESS grid-connected technology in the prior art, including determining the balancing node and the load node in the power system to be analyzed, and performing system modeling processing on the power system to be analyzed based on the balancing node and the load node; performing load modeling processing based on the setting of the battery energy storage system in the power system to be analyzed; establishing a system power flow model based on the system modeling processing results and the load modeling processing results, and performing approximate characterization of reactive power injection of the balancing node based on the system power flow model; determining the output capacity evaluation objective function based on the reactive power injection approximate solution of the balancing node, and optimizing and solving the output capacity evaluation objective function to obtain the evaluation result of the reactive power output capacity corresponding to the power system to be analyzed.

Description

Technical Field

[0001] The present invention relates to the technical field of power system control, and in particular to a method and device for evaluating reactive power output capability, a storage medium, and equipment. Background Art

[0002] In response to climate change and energy crisis, the penetration rate of renewable energy such as wind power and solar energy in the power system has increased dramatically. However, these renewable energy sources are intermittent and uncertain. Relying solely on non-new energy power infrastructure and its operating system may not be able to effectively cope with the imminent challenges, resulting in increasing pressure on the operation of the power system. In order to alleviate the pressure on the power system, energy storage systems ESS are added to the power system. With the advantages of promoting the integration of renewable energy and improving the safety and efficiency of the power system, energy storage systems ESS have become a competitive technology, especially battery energy storage systems BESS. Although the capacity of each battery energy storage system BESS is still small relative to traditional system assets (such as synchronous generators), advanced grid interface technology and information technology can be used to coordinate a group of spatially dispersed BESS to form a more important aggregated dispatchable asset to provide grid services.

[0003] At present, the BESS grid connection technical guide and operation control specification (i.e., Q / GDW 6962011 specification) points out that when active power (frequency response) and reactive power (voltage response) are required at the same time, frequency response has a higher priority. Therefore, the existing technology mainly focuses on the active power aggregation of BESS. However, based on the interface control of power electronics, BESS can essentially act as a power quality conditioner, outputting specified reactive power support to compensate for instantaneous reactive power imbalance, thereby alleviating voltage fluctuations for customers. Therefore, an evaluation method is urgently needed to evaluate the reactive power output capability. Summary of the invention

[0004] In view of this, the present invention provides a method and device for evaluating reactive power output capability, a storage medium, and a device, the main purpose of which is to solve the problem that the prior art only evaluates the active power in the BESS grid-connected technology and ignores the evaluation of reactive power.

[0005] According to one aspect of the present invention, a method for evaluating reactive power output capability is provided, comprising:

[0006] Determine a balancing node and a load node in the power system to be analyzed, and perform system modeling processing on the power system to be analyzed based on the balancing node and the load node;

[0007] Acquire the setting of the battery energy storage system in the power system to be analyzed, and perform load modeling processing on the power system to be analyzed based on the setting;

[0008] Establishing a system power flow model corresponding to the power system to be analyzed based on the system modeling processing results and the load modeling processing results, and approximately characterizing the reactive power injection of the balancing node based on the system power flow model;

[0009] An output capacity evaluation objective function is determined based on an approximate solution of reactive power injection of a balancing node, and the output capacity evaluation objective function is optimized and solved to obtain an evaluation result of reactive power output capacity corresponding to the power system to be analyzed.

[0010] Further, the system modeling process of the power system to be analyzed based on the balancing node and the load node includes:

[0011] Let 0 be the index of the balancing node, is the index of the load node, with y ij =g ij +jb ij represents the admittance between nodes i and i, where i, j∈{0,...,n}, g ij and b ij denote the real values ​​of conductance and susceptance respectively;

[0012] Assume that The subgraph induced is connected, and the power system to be analyzed is lossless, and the phase angle difference between each node is small, then the system topology and route parameter information of the power system to be analyzed are encoded in the system susceptance matrix B:

[0013]

[0014] Among them, B 00 represents the admittance matrix between equilibrium nodes, B 0E and B E0 Both represent the admittance matrix between the balance node and the load node, B EE Represents the admittance matrix between load nodes.

[0015] Furthermore, the obtaining of the configuration of the battery energy storage system in the power system to be analyzed, and performing load modeling processing on the power system to be analyzed based on the configuration includes:

[0016] Determine the network injection power at the i-th load node: Q i (t) = PF i ·P i (t); where Pi (t) and Q i (t) are the active power injection and reactive power injection at the i-th load node at time step t, respectively. i is a positive coefficient related to the power factor;

[0017] Based on the reactive power injection at the i-th load node at time step t, the bus-level reactive power injection at each load node with the participation of the battery energy storage system is determined: Q ESS，i (t) = Q base，i +Q i (t); where Q ESS，i (t) represents the bus-level reactive power injection at the i-th load node at time t, Q base，i represents the base load injection power at the i-th load node.

[0018] Furthermore, the establishing of a system power flow model corresponding to the power system to be analyzed based on the system modeling processing result and the load modeling processing result includes:

[0019] All voltage amplitudes corresponding to the load nodes are recorded as a set V ESS =[V1,…,V n ] T ; and all bus-level reactive power injections corresponding to the load nodes are recorded as a set Q ESS =[Q ESS，1 , …, Q ESS，n ] T ;

[0020] Obtain the system susceptance matrix B from the system modeling processing result; and obtain the bus-level reactive power injection Q at each load node from the load modeling processing result. ESS，i (t);

[0021] Based on the voltage amplitude set V ESS , system susceptance matrix B and bus-level reactive power injection set Q ESS The system power flow model is determined as follows:

[0022] Q ESS =[V ESS ](B E0 V0+B EE V ESS )

[0023] Q0=V0(B 00 V0+B oE V ESS )

[0024] Wherein, V0 represents the voltage of the balancing node, and Q0 represents the reactive power injection at the balancing node.

[0025] Furthermore, the approximate characterization of reactive power injection of the balancing node based on the system power flow model includes:

[0026] Based on the formula in the system power flow model: Q ESS =[V ESS ](B E0 V0+B EE V ESS ), establish the voltage amplitude set V ESS and the bus-level reactive power injection set Q ESS The mapping relationship between them is: V ESS =Z EE [V ESS ] -1 Q ESS -Z EE B E0 V0; where Z EE is the admittance matrix B EE The inverse matrix of

[0027] Based on the voltage amplitude set V ESS and the bus-level reactive power injection set Q ESS The mapping relationship between them is adopted, and the bus-level reactive power injection set Q ESS To approximate the reactive power injection at the balancing node, the approximate solution of reactive power injection at the balancing node is obtained.

[0028] Furthermore, the output capacity evaluation objective function determined based on the reactive power injection approximate solution of the balancing node includes:

[0029] Determine the approximate solution of reactive power injection at the balancing node at each time step t The upper and lower limits of

[0030] Based on the reactive power injection approximate solution The upper and lower limits of determine the reactive power injection interval corresponding to each time step t;

[0031] The maximum value of the reactive power injection interval of the balancing node within the power cycle is determined as the output capacity evaluation objective function.

[0032] Furthermore, before optimizing and solving the output capacity evaluation objective function, the method further includes:

[0033] Constraints are set for the output capability evaluation objective function, including active power injection-related constraints, reactive power injection-related constraints, and residual energy-related constraints.

[0034] According to another aspect of the present invention, there is provided a reactive power output capability evaluation device, comprising:

[0035] A system modeling module, used to determine the balancing nodes and load nodes in the power system to be analyzed, and perform system modeling processing on the power system to be analyzed based on the balancing nodes and the load nodes;

[0036] A load modeling module, used to obtain the setting of the battery energy storage system in the power system to be analyzed, and perform load modeling processing on the power system to be analyzed based on the setting;

[0037] A reactive power characterization module, used to establish a system power flow model corresponding to the power system to be analyzed based on the system modeling processing results and the load modeling processing results, and to approximately characterize the reactive power injection of the balancing node based on the system power flow model;

[0038] The evaluation module is used to determine the output capacity evaluation objective function based on the reactive power injection approximate solution of the balancing node, and optimize and solve the output capacity evaluation objective function to obtain an evaluation result of the reactive power output capacity corresponding to the power system to be analyzed.

[0039] Furthermore, the system modeling module is also used for:

[0040] Let 0 be the index of the balancing node, is the index of the load node, with y ij =g ij +jb ij represents the admittance between nodes i and j, where i, j∈{0,…,n}, g ij and b ij denote the real values ​​of conductance and susceptance respectively;

[0041] Assume that The subgraph induced is connected, and the power system to be analyzed is lossless, and the phase angle difference between each node is small, then the system topology and route parameter information of the power system to be analyzed are encoded in the system susceptance matrix B:

[0042]

[0043] Among them, B 00 represents the admittance matrix between equilibrium nodes, B 0E and B E0Both represent the admittance matrix between the balance node and the load node, B EE Represents the admittance matrix between load nodes.

[0044] Furthermore, the load modeling module is also used for:

[0045] Acquiring the setting status of the battery energy storage system in the power system to be analyzed, and performing load modeling processing on the power system to be analyzed based on the setting status includes:

[0046] Determine the network injection power at the i-th load node: Q i (t) = PF i ·P i (t); where P i (t) and Q i (t) are the active power injection and reactive power injection at the i-th load node at time step t, respectively. i is a positive coefficient related to the power factor;

[0047] Based on the reactive power injection at the i-th load node at time step t, the bus-level reactive power injection at each load node with the participation of the battery energy storage system is determined: Q ESS，i (t) = Q base，i +Q i (t); where Q ESS，i (t) represents the bus-level reactive power injection at the i-th load node at time t, Q base，i represents the base load injection power at the i-th load node.

[0048] Further, the reactive power characterization module includes a system power modeling unit and a reactive power characterization unit;

[0049] The power modeling unit is used for:

[0050] All voltage amplitudes corresponding to the load nodes are recorded as a set V ESS =[V1,…,V n ] T ; and all bus-level reactive power injections corresponding to the load nodes are recorded as a set Q ESS =[Q ESS，1 , …, Q ESS，n ] T ;

[0051] Obtain the system susceptance matrix B from the system modeling processing result; and obtain the bus-level reactive power injection Q at each load node from the load modeling processing result. ESS，i (t);

[0052] Based on the voltage amplitude set VESS , system susceptance matrix B and bus-level reactive power injection set Q ESS The system power flow model is determined as follows:

[0053] Q ESS =[V ESS ](B E0 V0+B EE V ESS )

[0054] Q0=V0(B 00 V0+B oE V ESS )

[0055] Wherein, V0 represents the voltage of the balancing node, and Q0 represents the reactive power injection at the balancing node.

[0056] The reactive power characterization unit is used for:

[0057] Based on the formula in the system power flow model: Q ESS =[V ESS ](B E0 V0+B EE V ESS ), establish the voltage amplitude set V ESS and the bus-level reactive power injection set Q ESS The mapping relationship between them is: V ESS =Z EE [V ESS ] -1 Q ESS -Z EE B E0 V0; where Z EE is the admittance matrix B EE The inverse matrix of

[0058] Based on the voltage amplitude set V ESS and the bus-level reactive power injection set Q ESS The mapping relationship between them is adopted, and the bus-level reactive power injection set Q ESS To approximate the reactive power injection at the balancing node, the approximate solution of reactive power injection at the balancing node is obtained.

[0059] Furthermore, the evaluation module is also used for:

[0060] Determine the approximate solution of reactive power injection at the balancing node at each time step t The upper and lower limits of

[0061] Based on the reactive power injection approximate solution The upper and lower limits of determine the reactive power injection interval corresponding to each time step t;

[0062] The maximum value of the reactive power injection interval of the balancing node within the power cycle is determined as the output capacity evaluation objective function.

[0063] Furthermore, the evaluation module is also used for:

[0064] Constraints are set for the output capacity evaluation objective function, including active power injection-related constraints, reactive power injection-related constraints and residual energy-related constraints, so that the output capacity evaluation objective function is optimized and solved based on the constraints.

[0065] According to another aspect of the present invention, a storage medium is provided, wherein the storage medium stores at least one executable instruction, wherein the executable instruction enables a processor to execute operations corresponding to the above-mentioned reactive power output capability evaluation method.

[0066] According to another aspect of the present invention, there is provided a device, comprising a processor, a memory, a communication interface and a communication bus, wherein the processor, the memory and the communication interface communicate with each other via the communication bus;

[0067] The memory is used to store at least one executable instruction, and the executable instruction enables the processor to perform operations corresponding to the above-mentioned reactive power output capability evaluation method.

[0068] By means of the above technical solution, the technical solution provided by the embodiment of the present invention has at least the following advantages:

[0069] The present invention provides a method, device, storage medium and equipment for evaluating reactive power output capacity. Compared with the prior art, the present invention determines the balancing node and load node in the power system to be analyzed, and performs system modeling processing on the power system to be analyzed based on the balancing node and the load node; obtains the setting of the battery energy storage system in the power system to be analyzed, and performs load modeling processing on the power system to be analyzed based on the setting; establishes a system power flow model corresponding to the power system to be analyzed based on the system modeling processing result and the load modeling processing result, and approximates the reactive power injection of the balancing node based on the system power flow model; determines the output capacity evaluation objective function based on the reactive power injection approximate solution of the balancing node, and optimizes and solves the output capacity evaluation objective function to obtain the evaluation result of the reactive power output capacity corresponding to the power system to be analyzed. The present invention not only realizes the evaluation of the reactive power output capacity of the power system including the battery energy storage system, but also reduces the computational overhead of the optimization solution and improves the evaluation efficiency of the reactive power output capacity by mapping the high-dimensional BESS operation state space to the low-dimensional state.

[0070] The above description is only an overview of the technical solution of the present invention. In order to more clearly understand the technical means of the present invention, it can be implemented according to the contents of the specification. In order to make the above and other purposes, features and advantages of the present invention more obvious and easy to understand, the specific implementation methods of the present invention are listed below. BRIEF DESCRIPTION OF THE DRAWINGS

[0071] Various other advantages and benefits will become apparent to those of ordinary skill in the art by reading the detailed description of the preferred embodiments below. The accompanying drawings are only for the purpose of illustrating the preferred embodiments and are not to be considered as limiting the present invention. Moreover, the same reference symbols are used throughout the accompanying drawings to represent the same components. In the accompanying drawings:

[0072] Figure 1 A schematic flow chart of a reactive power output capability evaluation method provided by an embodiment of the present invention is shown;

[0073] Figure 2 A schematic structural diagram of a reactive power output capability evaluation device provided by an embodiment of the present invention is shown;

[0074] Figure 3 A schematic structural diagram of a device provided by an embodiment of the present invention is shown. DETAILED DESCRIPTION

[0075] The exemplary embodiments of the present disclosure will be described in more detail below with reference to the accompanying drawings. Although the exemplary embodiments of the present disclosure are shown in the accompanying drawings, it should be understood that the present disclosure can be implemented in various forms and should not be limited by the embodiments set forth herein. On the contrary, these embodiments are provided to enable a more thorough understanding of the present disclosure and to fully convey the scope of the present disclosure to those skilled in the art.

[0076] The embodiment of the present invention provides a method for evaluating reactive power output capability, such as Figure 1 As shown, the method includes:

[0077] 101. Determine a balancing node and a load node in a power system to be analyzed, and perform system modeling processing on the power system to be analyzed based on the balancing node and the load node;

[0078] In an embodiment of the present invention, the current execution end determines the balance node and the load node in the power system to be analyzed. Among them, the balance node is one of the nodes taken for power flow calculation in the power system, and generally only one balance node is set in a power system. The voltage amplitude and phase of the balance node are given, and the direction of the voltage vector at this point is taken as the reference axis in the calculation, which is equivalent to giving the angle of the voltage vector at this point as zero degrees. And its injected active power and reactive power are quantities to be determined. Among them, the load node is also called the PQ node, which corresponds to the pure load node (including the node with load), the generator node with given active and reactive output (including the node with load), and the contact node (the injected active and reactive power are equal to zero) in the actual system. Because there are many step-down substations in the system, the number of such nodes is the largest. After determining the balance node and the load node of the power system to be analyzed, the current execution end models the power system to be analyzed based on the balance node and the load node. Among them, the process of modeling the power system is the process of mathematically abstracting the equipment in the power system network using mathematical models. The power system network model obtained after abstraction is a data file that describes the global operating status of the power system and is the basis for various smart grid services.

[0079] 102. Obtain the setting of the battery energy storage system in the power system to be analyzed, and perform load modeling processing on the power system to be analyzed based on the setting;

[0080] In an embodiment of the present invention, the current execution end obtains the setting of the battery energy storage system in the power system to be analyzed, such as each load node in the power system to be analyzed is equipped with a BESS, or some load nodes are equipped with a BESS, etc., which is not specifically limited in the embodiment of the present invention. After obtaining the setting of the battery energy storage system, the current execution end performs load modeling processing on the power system to be analyzed based on the setting of the battery energy storage system. Among them, the process of load modeling processing is used to characterize the mathematical modeling process of the changes in the active power and reactive power taken by the power load from the power grid when the voltage or frequency of the power system changes.

[0081] 103. Establish a system power flow model corresponding to the power system to be analyzed based on the system modeling processing results and the load modeling processing results, and perform an approximate characterization of reactive power injection of the balancing node based on the system power flow model;

[0082] In an embodiment of the present invention, the current execution end establishes a system power flow model corresponding to the power system to be analyzed based on the system modeling processing results and the load modeling processing results. Among them, the system power flow model is the most core part of the steady-state analysis of the power system. It can calculate the parameters such as active power, reactive power flow and power factor between nodes through the voltage of each node in the power system. After establishing the system power flow model, the current execution end approximates the reactive power injection of the balancing node based on the established system power flow model. Among them, the process of approximate characterization is the process of mapping the high-dimensional BESS operating state space to a low-dimensional state. This mapping helps to develop convex optimization problems with good computational performance.

[0083] 104. Determine an output capacity evaluation objective function based on an approximate solution of reactive power injection of a balancing node, and optimize and solve the output capacity evaluation objective function to obtain an evaluation result of reactive power output capacity corresponding to the power system to be analyzed.

[0084] In an embodiment of the present invention, the current execution end determines the output capacity evaluation objective function based on the reactive power injection approximate solution of the balancing node. Since the reactive power injection approximate solution of the balancing node has mapped the high-dimensional BESS operating state space to a low-dimensional state, the output capacity evaluation objective function determined based on the reactive power injection approximate solution is also a low-dimensional objective function, which is not specifically limited in the embodiment of the present invention. After determining the output capacity evaluation objective function, the current execution end optimizes and solves the output capacity evaluation objective function to obtain an evaluation result of the reactive power output capacity corresponding to the power system to be analyzed. Among them, the process of optimizing and solving the low-dimensional output capacity evaluation objective function is a linear programming process, and the solution methods for linear programming problems include but are not limited to the simplex method, the interior point method, the large-scale problem solution method, etc., which are not specifically limited in the embodiment of the present invention.

[0085] Furthermore, as a refinement and extension of the specific implementation of the above embodiment, in order to simplify the mathematical model of the power system, another evaluation method for reactive power output capability is provided.

[0086] In the embodiment of the present invention, the current execution end performs system modeling processing on the power system to be analyzed based on the balance node and the load node, including:

[0087] Let 0 be the index of the equilibrium node, that is, the subscript of the variable related to the equilibrium node is 0; is the index of the load node, that is, the subscript of the variable related to the load node is a number in {1, ..., n}, where n is the total number of load nodes included in the power system to be analyzed. ij =g ij +jb ij represents the admittance between nodes i and j, where i, j∈{0,…,n}, g ij and b ij denote the real values ​​of conductance and susceptance respectively; by definition, y ij = 0 indicates that there is no electrical connection between a pair of nodes. In addition, for each i, j∈{0,…,n}, let V i and θ i represents the voltage amplitude and angle. By convention, for a balanced node, V0 = 1 and θ0 = 0. In addition, the voltage amplitude needs to satisfy The operating constraints are given, where the variables with upper and lower bars represent the upper and lower limits of the corresponding voltage amplitudes.

[0088] In the embodiment of the present invention, the current execution end makes the following assumptions about the network structure of the power system to be analyzed:

[0089] (I) Assume that The induced subgraph is connected, i.e., deleting the equilibrium node will not disconnect the rest of the network;

[0090] (ii) The power system to be analyzed is lossless, so y ij ≈jb ij ;

[0091] (III) The phase angle difference between the nodes in the power system to be analyzed is very small, that is, |θ i -θ j |≈0;

[0092] The above assumptions are mild conditions suitable for working conditions. For the actual network, the first assumption is naturally satisfied; and when the r / x ratio in the network is negligible, the second and third assumptions are basically established. Therefore, the three assumptions are reasonable for the voltage stability and power grid optimization problems studied in the invention.

[0093] Based on the above three assumptions, the system topology and route parameter information of the power system to be analyzed in the embodiment of the present invention can be encoded in the system susceptance matrix B:

[0094]

[0095] Among them, B 00 represents the admittance matrix between equilibrium nodes, B 0E and B E0 Both represent the admittance matrix between the balance node and the load node, B EE Represents the admittance matrix between load nodes. Under the connectivity assumption, B EE It is a non-singular M matrix. The specific calculation formulas for each parameter in the system susceptance matrix are as follows:

[0096]

[0097] Among them, b shunt，i >0 is the parallel susceptance of each node.

[0098] Furthermore, as a refinement and extension of the specific implementation of the above embodiment, in order to quickly mathematically characterize the reactive power, another method for evaluating the reactive power output capability is provided.

[0099] In an embodiment of the present invention, the current execution end obtains the setting of the battery energy storage system in the power system to be analyzed, and performs load modeling processing on the power system to be analyzed based on the setting, including:

[0100] Determine the network injection power at the i-th load node: Q i (t) = PF i ·P i (t); where P i (t) and Q i (t) are the active power injection and reactive power injection at the i-th load node at time step t, respectively. i is a positive coefficient related to the power factor;

[0101] Based on the reactive power injection at the i-th load node at time step t, the bus-level reactive power injection at each load node with the participation of the battery energy storage system is determined: Q ESS，i (t) = Q base，i +Q i (t); where Q ESS，i (t) represents the bus-level reactive power injection at the i-th load node at time t, Q base，irepresents the base load injection power at the i-th load node. The bus-level reactive power injection at each load node is actually a function dynamically determined by the BESS.

[0102] It should be noted that the network injection power at the i-th load node is P i (t) is subject to the remaining energy: E i (t+1)=E i (t)+P i ,in, The underlined and overlined items represent the upper and lower limits of the respective variables.

[0103] Furthermore, as a refinement and extension of the specific implementation of the above embodiment, in order to map the high-dimensional BESS operation state space to a low-dimensional state, another reactive power output capability evaluation method is provided.

[0104] In an embodiment of the present invention, the current execution end establishes a system power flow model corresponding to the power system to be analyzed based on the system modeling processing result and the load modeling processing result, including:

[0105] In the embodiment of the present invention, the current execution end records all voltage amplitudes corresponding to the load nodes as a set V ESS =[V1,…,V n ] T ; and all bus-level reactive power injections corresponding to the load nodes are recorded as the set Q ESS =[Q ESS，1 , …, Q ESS，n ] T ;

[0106] Obtain the system susceptance matrix B from the system modeling processing results; and obtain the bus-level reactive power injection Q at each load node from the load modeling processing results. ESS，i (t);

[0107] Based on the voltage amplitude set V ESS , system susceptance matrix B and bus-level reactive power injection set Q ESS Determine the system power flow model as follows:

[0108] Q ESS =[V ESS ](B E0 V0+B EE V ESS )

[0109] Q0=V0(B 00 V0+B oE V ESS )

[0110] Where V0 represents the voltage at the balancing node, and Q0 represents the reactive power injection at the balancing node. [] is an operator whose input parameter is a vector and whose output is a diagonal matrix whose diagonal elements are the elements of the vector. Due to the different bus types corresponding to the load nodes, the above two equations have different given coefficients and unknown variables. Specifically, equation Q ESS =[V ESS ](B E0 V0+B EE V ESS ) is the voltage magnitude vector, and then using the equation Q0 = V0 (B 00 V0+B oE V ESS ) to obtain the reactive power injection at the load node, the specific calculation logic can be expressed as follows:

[0111]

[0112] Since the equation Q ESS =[V ESS ](B E0 V0+B EE V ESS ) is a typical nonlinear quadratic equation, and it is composed of n quadratic equations. This mapping is very complicated to represent in high-dimensional space. When n is large, equation Q ESS =[V ESS ](B E0 V0+B EE V ESS ) cannot obtain an exact analytical solution. In addition, solving Q ESS =[V ESS ](B E0 V0+B EE V ESS ) requires the use of an iterative numerical solver, such as the Newton-Raphson method, etc., which is not specifically limited in the embodiments of the present invention, and these methods are difficult to characterize analytically.

[0113] In order to overcome the above difficulties, the current execution end in the embodiment of the present invention performs an approximate characterization of reactive power injection of the balancing node based on the system power flow model, including:

[0114] Based on the formula in the system power flow model: Q ESS =[V ESS ](B E0 V0+B EE V ESS ), establish the voltage amplitude set V ESS and the bus-level reactive power injection set Q ESS The mapping relationship between them is the equation Q ESS=[V ESS ](B E0 V0+B EE V ESS ) is organized into the following fixed-point self-mapping form:

[0115] Q ESS =[V ESS ](B E0 V0+B EE V ESS )

[0116]

[0117]

[0118] Among them, Z EE is the admittance matrix B EE The inverse matrix of the load node subgraph ensures that the matrix B EE reversibility.

[0119] Based on the voltage amplitude set V ESS and the bus-level reactive power injection set Q ESS The mapping relationship between them is adopted, and the bus-level reactive power injection set Q ESS To approximate the reactive power injection at the balancing node, the approximate solution of reactive power injection at the balancing node is obtained. The specific process is as follows:

[0120] (I) Order is the solution to the fixed-point mapping equation, and then applying Picard iteration yields:

[0121]

[0122] Among them, the variables with ~ represent the corresponding approximate solutions, and And b VQ =-Z EE B E0 V0, the above contents are all linear mappings, and the computational overhead is very small.

[0123] (ii) Given V ESS Under this premise, the above problem is transformed into a linear mapping between two related variables. Substituting into the formula Q0=V0(B 00 V0+B oE V ESS )get:

[0124]

[0125] Among them, M QQ =V0B0E M VQ 、b QQ =V0B 0E b VQ +V0B 00 V0.

[0126] Furthermore, as a refinement and extension of the specific implementation methods of the above-mentioned embodiments, in order to adopt low-dimensional equations to effectively characterize the optimization solution objectives and reduce the amount of calculation while ensuring the evaluation accuracy, another evaluation method for reactive power output capacity is provided.

[0127] In the embodiment of the present invention, the current execution end determines the output capacity evaluation objective function based on the reactive power injection approximate solution of the balancing node, including:

[0128] The current execution end determines the approximate solution of reactive power injection of the balancing node at each time step t The upper and lower limits of and

[0129] Approximate solution based on reactive power injection The upper and lower limits of determine the reactive power injection interval corresponding to each time step t, that is

[0130] The maximum value of the reactive power injection interval of the balancing node in the power cycle is determined as the output capacity evaluation objective function, as shown below:

[0131]

[0132]

[0133] It should be noted that before the current execution end optimizes and solves the output capacity evaluation objective function, the method further includes: setting constraints for the output capacity evaluation objective function, including active power injection-related constraints, reactive power injection-related constraints, and residual energy-related constraints. The specific formula is as follows:

[0134]

[0135]

[0136]

[0137]

[0138]

[0139]

[0140]

[0141] In the embodiment of the present invention, the current execution end converts the problem into a linear programming problem expressed in the above formula, which greatly reduces its computational overhead and maintains numerical efficiency and robustness. The present invention develops a simple explicit proxy model to replace the power flow equation, and conducts a simulation case study to verify that the proposed method only introduces a modeling error of less than 0.6%, while increasing the calculation speed by two orders of magnitude.

[0142] The embodiment of the present invention provides a method for evaluating reactive power output capacity. Compared with the prior art, the present invention determines the balancing node and the load node in the power system to be analyzed, and performs system modeling processing on the power system to be analyzed based on the balancing node and the load node; obtains the setting of the battery energy storage system in the power system to be analyzed, and performs load modeling processing on the power system to be analyzed based on the setting; establishes a system power flow model corresponding to the power system to be analyzed based on the system modeling processing result and the load modeling processing result, and approximates the reactive power injection of the balancing node based on the system power flow model; determines the output capacity evaluation objective function based on the reactive power injection approximate solution of the balancing node, and optimizes and solves the output capacity evaluation objective function to obtain the evaluation result of the reactive power output capacity corresponding to the power system to be analyzed. The present invention not only realizes the evaluation of the reactive power output capacity of the power system including the battery energy storage system, but also reduces the computational overhead of the optimization solution and improves the evaluation efficiency of the reactive power output capacity by mapping the high-dimensional BESS operation state space to the low-dimensional state.

[0143] As the above Figure 1 The embodiment of the present invention provides a reactive power output capability evaluation device, such as Figure 2 As shown, the device comprises:

[0144] A system modeling module 21, used to determine a balancing node and a load node in the power system to be analyzed, and perform system modeling processing on the power system to be analyzed based on the balancing node and the load node;

[0145] A load modeling module 22 is used to obtain the setting of the battery energy storage system in the power system to be analyzed, and perform load modeling processing on the power system to be analyzed based on the setting;

[0146] A reactive power characterization module 23, used to establish a system power flow model corresponding to the power system to be analyzed based on the system modeling processing results and the load modeling processing results, and to approximately characterize the reactive power injection of the balancing node based on the system power flow model;

[0147] The evaluation module 24 is used to determine the output capacity evaluation objective function based on the reactive power injection approximate solution of the balancing node, and optimize and solve the output capacity evaluation objective function to obtain an evaluation result of the reactive power output capacity corresponding to the power system to be analyzed.

[0148] Furthermore, the system modeling module 21 is also used for:

[0149] Let 0 be the index of the balancing node, is the index of the load node, with y ij =g ij +jb ij represents the admittance between nodes i and j, where i, j∈{0,…,n}, g ij and b ij denote the real values ​​of conductance and susceptance respectively;

[0150] Assume that The subgraph induced is connected, and the power system to be analyzed is lossless, and the phase angle difference between each node is small, then the system topology and route parameter information of the power system to be analyzed are encoded in the system susceptance matrix B:

[0151]

[0152] Among them, B 00 represents the admittance matrix between equilibrium nodes, B 0E and B E0 Both represent the admittance matrix between the balance node and the load node, B EE Represents the admittance matrix between load nodes.

[0153] Furthermore, the load modeling module 22 is also used for:

[0154] Acquiring the setting status of the battery energy storage system in the power system to be analyzed, and performing load modeling processing on the power system to be analyzed based on the setting status includes:

[0155] Determine the network injection power at the i-th load node: Q i (t) = PF i ·P i (t); where P i (t) and Q i (t) are the active power injection and reactive power injection at the i-th load node at time step t, respectively. i is a positive coefficient related to the power factor;

[0156] Based on the reactive power injection at the i-th load node at time step t, the bus-level reactive power injection at each load node with the participation of the battery energy storage system is determined: Q ESS，i (t) = Q base，i +Q i (t); where Q ESS，i (t) represents the bus-level reactive power injection at the i-th load node at time t, Q base，i represents the base load injection power at the i-th load node.

[0157] Further, the reactive power characterization module 23 includes a system power modeling unit and a reactive power characterization unit;

[0158] The power modeling unit is used for:

[0159] All voltage amplitudes corresponding to the load nodes are recorded as a set V ESS =[V1,…,V n ] T ; and all bus-level reactive power injections corresponding to the load nodes are recorded as a set Q ESS =[Q ESS，1 , …, Q ESS，n ] T ;

[0160] Obtain the system susceptance matrix B from the system modeling processing result; and obtain the bus-level reactive power injection Q at each load node from the load modeling processing result. ESS，i (t);

[0161] Based on the voltage amplitude set V ESS , system susceptance matrix B and bus-level reactive power injection set Q ESS The system power flow model is determined as follows:

[0162] Q ESS =[V ESS ](B E0 V0+B EE V ESS )

[0163] Q0=V0(B 00 V0+B oE V ESS )

[0164] Wherein, V0 represents the voltage of the balancing node, and Q0 represents the reactive power injection at the balancing node.

[0165] The reactive power characterization unit is used for:

[0166] Based on the formula in the system power flow model: Q ESS=[V ESS ](B E0 V0+B EE V ESS ), establish the voltage amplitude set V ESS and the bus-level reactive power injection set Q ESS The mapping relationship between them is: V ESS =Z EE [V ESS ] -1 Q ESS -Z EE B E0 V0; where Z EE is the admittance matrix B EE The inverse matrix of

[0167] Based on the voltage amplitude set V ESS and the bus-level reactive power injection set Q ESS The mapping relationship between them is adopted, and the bus-level reactive power injection set Q ESS To approximate the reactive power injection at the balancing node, the approximate solution of reactive power injection at the balancing node is obtained.

[0168] Furthermore, the evaluation module 24 is also used for:

[0169] Determine the approximate solution of reactive power injection at the balancing node at each time step t The upper and lower limits of

[0170] Based on the reactive power injection approximate solution The upper and lower limits of determine the reactive power injection interval corresponding to each time step t;

[0171] The maximum value of the reactive power injection interval of the balancing node within the power cycle is determined as the output capacity evaluation objective function.

[0172] Furthermore, the evaluation module 24 is also used for:

[0173] Constraints are set for the output capacity evaluation objective function, including active power injection-related constraints, reactive power injection-related constraints and residual energy-related constraints, so that the output capacity evaluation objective function is optimized and solved based on the constraints.

[0174] The embodiment of the present invention provides an evaluation device for reactive power output capacity. Compared with the prior art, the present invention determines the balancing node and the load node in the power system to be analyzed, and performs system modeling processing on the power system to be analyzed based on the balancing node and the load node; obtains the setting of the battery energy storage system in the power system to be analyzed, and performs load modeling processing on the power system to be analyzed based on the setting; establishes a system power flow model corresponding to the power system to be analyzed based on the system modeling processing result and the load modeling processing result, and approximates the reactive power injection of the balancing node based on the system power flow model; determines the output capacity evaluation objective function based on the reactive power injection approximate solution of the balancing node, and optimizes and solves the output capacity evaluation objective function to obtain the evaluation result of the reactive power output capacity corresponding to the power system to be analyzed. The present invention not only realizes the evaluation of the reactive power output capacity of the power system including the battery energy storage system, but also reduces the computational overhead of the optimization solution and improves the evaluation efficiency of the reactive power output capacity by mapping the high-dimensional BESS operation state space to the low-dimensional state.

[0175] According to an embodiment of the present invention, a storage medium is provided, wherein the storage medium stores at least one executable instruction, and the computer executable instruction can execute the reactive power output capability evaluation method in any of the above method embodiments.

[0176] Figure 3 A schematic diagram of the structure of a device provided according to an embodiment of the present invention is shown, and the specific embodiment of the present invention does not limit the specific implementation of the device.

[0177] like Figure 3 As shown, the device may include: a processor (processor) 302 , a communication interface (Communications Interface) 304 , a memory (memory) 306 , and a communication bus 308 .

[0178] The processor 302 , the communication interface 304 , and the memory 306 communicate with each other via the communication bus 308 .

[0179] The communication interface 304 is used to communicate with other devices such as clients or other servers.

[0180] The processor 302 is used to execute the program 310, and specifically can execute the relevant steps of the above-mentioned reactive power output capability evaluation method.

[0181] Specifically, the program 310 may include program codes, which include computer operation instructions.

[0182] The processor 302 may be a central processing unit (CPU), or an application-specific integrated circuit (ASIC), or one or more integrated circuits configured to implement the embodiments of the present invention. The one or more processors included in the device may be processors of the same type, such as one or more CPUs; or processors of different types, such as one or more CPUs and one or more ASICs.

[0183] The memory 306 is used to store the program 310. The memory 306 may include a high-speed RAM memory, and may also include a non-volatile memory (non-volatile memory), such as at least one disk memory.

[0184] The program 310 may be specifically configured to enable the processor 302 to perform the following operations:

[0185] Determine a balancing node and a load node in the power system to be analyzed, and perform system modeling processing on the power system to be analyzed based on the balancing node and the load node;

[0186] Acquire the setting of the battery energy storage system in the power system to be analyzed, and perform load modeling processing on the power system to be analyzed based on the setting;

[0187] Establishing a system power flow model corresponding to the power system to be analyzed based on the system modeling processing results and the load modeling processing results, and approximately characterizing the reactive power injection of the balancing node based on the system power flow model;

[0188] An output capacity evaluation objective function is determined based on an approximate solution of reactive power injection of a balancing node, and the output capacity evaluation objective function is optimized and solved to obtain an evaluation result of reactive power output capacity corresponding to the power system to be analyzed.

[0189] Obviously, those skilled in the art should understand that the above modules or steps of the present invention can be implemented by a general computing device, they can be concentrated on a single computing device, or distributed on a network composed of multiple computing devices, and optionally, they can be implemented by a program code executable by a computing device, so that they can be stored in a storage device and executed by the computing device, and in some cases, the steps shown or described can be executed in a different order than here, or they can be made into individual integrated circuit modules, or multiple modules or steps therein can be made into a single integrated circuit module for implementation. Thus, the present invention is not limited to any specific combination of hardware and software.

[0190] The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. For those skilled in the art, the present invention may have various modifications and variations. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present invention shall be included in the protection scope of the present invention.

Claims

1. A method for evaluating reactive power output capability, characterized in that: include: Determine a balancing node and a load node in the power system to be analyzed, and perform system modeling processing on the power system to be analyzed based on the balancing node and the load node to obtain a system modeling processing result; The system modeling processing result represents a system susceptance matrix that combines system topology and route parameter information of the power system; Acquire the setting of the battery energy storage system in the power system to be analyzed, and perform load modeling processing on the power system to be analyzed based on the setting to obtain a load modeling processing result; The load modeling processing result is a mathematical model representing the change of active power and reactive power taken from the power grid by the power load when the voltage or frequency of the power system changes; A system power flow model corresponding to the power system to be analyzed is established based on the system modeling processing results and the load modeling processing results, and an approximate characterization of the reactive power injection of the balancing node is performed based on the system power flow model; the approximate characterization enables the operation state space of the high-dimensional battery energy storage system to be mapped to a low-dimensional state; The establishing of a system power flow model corresponding to the power system to be analyzed based on the system modeling processing result and the load modeling processing result comprises: All voltage amplitudes corresponding to the load nodes are recorded as a set V ESS =[V1,…,V n ] T ; and all bus-level reactive power injections corresponding to the load nodes are recorded as a set Q ESS =[Q ESS，1 , …, Q ESS，n ] T ; Obtain the system susceptance matrix B from the system modeling processing result; and obtain the bus-level reactive power injection Q at each load node from the load modeling processing result. ESS，i (t); Based on the voltage amplitude set V ESS , system susceptance matrix B and bus-level reactive power injection set Q ESS The system power flow model is determined as follows: Q ESS =[V ESS ](B E0 V0+B EE V Ess ) Q0=V0(B 00 V0+B oE V ESS ) Where V0 represents the voltage at the balancing node, Q0 represents the reactive power injection at the balancing node; Determine an output capacity evaluation objective function based on an approximate solution of reactive power injection of a balancing node, and optimize and solve the output capacity evaluation objective function to obtain an evaluation result of reactive power output capacity corresponding to the power system to be analyzed; The output capability evaluation objective function is: in, and They are the approximate solutions of reactive power injection at the balancing node at each time step t. upper and lower limits.

2. The method according to claim 1, characterized in that The system modeling process of the power system to be analyzed based on the balancing node and the load node includes: Let 0 be the index of the balancing node, is the index of the load node, with y ij =g ij +jb ij represents the admittance between nodes i and j, where i, j∈{0,…,n}, g ij and b ij denote the real values ​​of conductance and susceptance respectively; Assume that The subgraph induced is connected, and the power system to be analyzed is lossless, and the phase angle difference between each node is small, then the system topology and route parameter information of the power system to be analyzed are encoded in the system susceptance matrix B: Among them, B 00 represents the admittance matrix between equilibrium nodes, B 0E and B E0 Both represent the admittance matrix between the balance node and the load node, B EE Represents the admittance matrix between load nodes.

3. The method according to claim 1, characterized in that The obtaining of the setting of the battery energy storage system in the power system to be analyzed, and performing load modeling processing on the power system to be analyzed based on the setting comprises: Determine the network injection power at the i-th load node: Q i (t) = PF i ·P i (t); where P i (t) and Q i (t) are the active power injection and reactive power injection at the i-th load node at time step t, respectively. i is a positive coefficient related to the power factor; Based on the reactive power injection at the i-th load node at time step t, the bus-level reactive power injection at each load node with the participation of the battery energy storage system is determined: Q ESS，i (t) = Q base，i +Q i (t); where Q ESS，i (t) represents the bus-level reactive power injection at the i-th load node at time t, Q base，i represents the base load injection power at the i-th load node.

4. The method according to claim 1, characterized in that The approximate characterization of reactive power injection of the balancing node based on the system power flow model includes: Based on the formula in the system power flow model: Q ESS =[V ESS ](B E0 V0+B EE V ESS ), establish the voltage amplitude set V ESS and the bus-level reactive power injection set Q ESS The mapping relationship between them is: ESS =Z EE [V ESS ] -1 Q ESS -Z EE B E0 V0; where Z EE is the admittance matrix B EE The inverse matrix of Based on the voltage amplitude set V ESS and the bus-level reactive power injection set Q ESS The mapping relationship between them is adopted, and the bus-level reactive power injection set Q ESS To approximate the reactive power injection at the balancing node, the approximate solution of reactive power injection at the balancing node is obtained.

5. The method according to claim 1, characterized in that The output capacity evaluation objective function determined based on the reactive power injection approximate solution of the balancing node includes: Determine the approximate solution of reactive power injection at the balancing node at each time step t The upper and lower limits of Based on the reactive power injection approximate solution The upper and lower limits of determine the reactive power injection interval corresponding to each time step t; The maximum value of the reactive power injection interval of the balancing node within the power cycle is determined as the output capacity evaluation objective function.

6. The method according to any one of claims 1 to 5, characterized in that: Before optimizing and solving the output capacity evaluation objective function, the method further includes: Constraints are set for the output capability evaluation objective function, including active power injection-related constraints, reactive power injection-related constraints, and residual energy-related constraints.

7. A reactive power output capability evaluation device, characterized in that: include: A system modeling module, used to determine the balancing nodes and load nodes in the power system to be analyzed, and perform system modeling processing on the power system to be analyzed based on the balancing nodes and the load nodes to obtain a system modeling processing result; The system modeling processing result represents a system susceptance matrix that combines system topology and route parameter information of the power system; A load modeling module is used to obtain the setting of the battery energy storage system in the power system to be analyzed, and perform load modeling processing on the power system to be analyzed based on the setting to obtain a load modeling processing result; The load modeling processing result is a mathematical model representing the change of active power and reactive power taken from the power grid by the power load when the voltage or frequency of the power system changes; A reactive power characterization module is used to establish a system power flow model corresponding to the power system to be analyzed based on the system modeling processing results and the load modeling processing results, and to approximate the reactive power injection of the balancing node based on the system power flow model; the approximate characterization enables the operation state space of the high-dimensional battery energy storage system to be mapped to a low-dimensional state; The establishing of a system power flow model corresponding to the power system to be analyzed based on the system modeling processing result and the load modeling processing result comprises: All voltage amplitudes corresponding to the load nodes are recorded as a set V ESS =[V1,…,V n ] T ; and all bus-level reactive power injections corresponding to the load nodes are recorded as a set Q ESS =[Q ESS，1 , …, Q ESS，n ] T ; Obtain the system susceptance matrix B from the system modeling processing result; and obtain the bus-level reactive power injection Q at each load node from the load modeling processing result. ESS，i (t); Based on the voltage amplitude set V ESS , system susceptance matrix B and bus-level reactive power injection set Q ESS The system power flow model is determined as follows: Q ESS =[V ESS ](B E0 V0+B EE V ESS ) Q0=V0(B 00 V0+B oE V ESS ) Where V0 represents the voltage at the balancing node, Q0 represents the reactive power injection at the balancing node; An evaluation module is used to determine an output capacity evaluation objective function based on an approximate solution of reactive power injection of a balancing node, and optimize and solve the output capacity evaluation objective function to obtain an evaluation result of reactive power output capacity corresponding to the power system to be analyzed; The output capability evaluation objective function is: in, and They are the approximate solutions of reactive power injection at the balancing node at each time step t. upper and lower limits.

8. A storage medium, wherein at least one executable instruction is stored in the storage medium, and the executable instruction executes an operation corresponding to the method for evaluating reactive power output capability according to any one of claims 1 to 6.

9. A device comprising a processor, a memory, a communication interface and a communication bus, wherein the processor, the memory and the communication interface communicate with each other via the communication bus; The memory is used to store at least one executable instruction, and the executable instruction enables the processor to perform operations corresponding to the method for evaluating reactive power output capability as described in any one of claims 1-6.

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