Distributed high-inertia phase modifier optimal configuration method for multi-transient support

Abstract

The invention discloses a distributed high-inertia phase modifier optimal configuration method for multi-transient support, and relates to the field of power system planning, and the method comprises the steps: obtaining the network topology information of a power system in a planning region, calculating the critical inertia of a system and the node inertia of the system based on the network topology information, finding out a node lower than the critical inertia, and configuring a phase modifier; calculating the sensitivity of the inertia lower than the critical inertia node to the inertia of the phase modifier at each pre-configuration node, calculating the comprehensive sensitivity of each pre-configuration node by combining the critical inertia and the node inertia, and determining the configuration position with the dominant sensitivity according to the comprehensive sensitivity; inputting a target function and a constraint condition, and obtaining a configuration scheme by adopting a particle swarm optimization algorithm; network topology information is updated, the short-circuit ratio of each grid-connected node is calculated according to a system node admittance matrix, a phase modifier is configured at the node with the short-circuit ratio smaller than a preset critical short-circuit ratio, secondary comparative analysis is carried out, and a site selection scheme of the distributed high-inertia phase modifier is obtained; and the comprehensive supporting capability of the system is improved.

Description

Technical Field

[0001] The present invention relates to the field of power system planning, and more specifically, to a distributed high-inertia phase regulator optimization configuration method for multi-transient support. Background Art

[0002] In recent years, power outages caused by a high proportion of renewable energy have occurred from time to time. Accident analysis shows that the active and reactive support capabilities of the power grid have weakened, the frequency intensity and voltage intensity have decreased, the rotating reserve and inertia levels have decreased, the low short-circuit ratio and low damping characteristics are obvious, and the active-reactive-frequency-voltage interweaving coupling has fundamentally changed the frequency and voltage stability mechanism. In terms of frequency, the access of large-scale renewable energy bases has reduced the proportion of conventional synchronous generators with large mechanical rotation inertia and strong anti-interference ability, reduced the rotating reserve capacity of the power grid, decreased inertia and damping, and weakened the frequency intensity. Under fault conditions, the active-frequency support capacity of the new power grid is insufficient, the frequency response fluctuation amplitude is large, and the dynamic safety and stability of the frequency is deteriorated. In terms of voltage, the access of large-scale renewable energy bases has reduced the reactive support capacity of synchronous generators, shortened the electrical distance of the power grid, reduced the short-circuit ratio and impedance ratio, expanded the depth of voltage fluctuation propagation, and weakened the voltage intensity. Under fault conditions, the reactive-voltage support capacity of the new power grid is insufficient, the voltage recovery capacity is lacking, and the dynamic safety and stability of the voltage is deteriorated.

[0003] Deficiencies of existing technologies: From the perspective of application practice, this new type of distributed phase regulator is no longer just a device that provides reactive power and voltage compensation in modern power grids. In particular, the emergence of high-inertia energy storage phase regulators is more attractive to some low-inertia systems in terms of improving system frequency characteristics and enhancing system frequency support capabilities. However, this new type of phase regulator with small capacity and distributed access to new energy stations actively supports grid frequency and voltage, which is fundamentally different from the traditional grid support mainly based on large-capacity synchronous machines. At the optimization configuration level, how to achieve low-cost, high-performance stable support through the optimized configuration of phase regulators under the background of "multi-point access and multi-transient support" has become the key to promoting the emerging model of "new energy base + high-inertia phase regulator".

[0004] In view of the above problems, the present invention proposes a solution. Summary of the invention

[0005] In order to overcome the above-mentioned defects of the prior art, an embodiment of the present invention provides a distributed high-inertia phase regulator optimization configuration method for multi-transient support, which improves the comprehensive support capability and network source friendliness of the whole system through the configuration of high-inertia energy storage phase regulator.

[0006] To achieve the above-mentioned purpose, the present invention provides the following technical solutions: a distributed high-inertia phase-shifting optimization configuration method for multi-transient support, comprising the following steps: obtaining network topology information of a planned regional power system, calculating the system critical inertia and the system node inertia based on the network topology information, finding out nodes below the critical inertia, and configuring phase-shifting devices; calculating the sensitivity of the inertia of nodes below the critical inertia to the phase-shifting device inertia at each pre-configured node, calculating the comprehensive sensitivity at each pre-configured point based on the critical inertia and the node inertia, and determining the configuration position with the best sensitivity according to the comprehensive sensitivity; inputting an objective function and constraint conditions, and obtaining a configuration scheme by using a particle swarm optimization algorithm; updating the network topology information, calculating the short-circuit ratio of each grid-connected node according to the system node admittance matrix, configuring phase-shifting devices at nodes with a short-circuit ratio less than a preset critical short-circuit ratio, and performing a secondary comparative analysis to obtain a site selection scheme for distributed high-inertia phase-shifting devices.

[0007] In a preferred embodiment, the method for obtaining the critical inertia of the system is as follows: obtain the network topology information of the planned regional power system, obtain the maximum frequency change rate and the maximum frequency deviation limit value that can ensure the stable operation of the system based on the network topology information, and take the larger of the maximum frequency change rate and the maximum frequency deviation limit value as the critical inertia of the system.

[0008] In a preferred embodiment, the specific steps of determining the configuration position with the best sensitivity according to the comprehensive sensitivity are as follows: the inertia of each node below the critical inertia and the critical inertia of the system are combined with the sensitivity between the node and the pre-configured node to obtain the comprehensive sensitivity at each pre-configured point by summing; When the ratio of the difference between the critical inertia and the node inertia to the critical variable is the largest, that is, when the comprehensive sensitivity at the pre-configuration point is the largest, the phase regulator is configured at the pre-configuration point.

[0009] In a preferred embodiment, the particle swarm optimization algorithm steps are as follows: randomly generate a group of particle positions and initial velocities, calculate the initial fitness value, set the initial position of the particle as the individual extreme position of each particle; traverse the individual extreme fitness values ​​of all particles, find the minimum fitness value, and set the individual extreme position of the corresponding particle as the global extreme position; for each particle, update its own position according to the current speed and position, calculate the fitness value of the new position, and update the individual optimal position and the global optimal position of the particle based on the fitness value; when the system node inertia reaches the system critical inertia, stop iteration, and the particle update position is the phase shifter configuration position.

[0010] In a preferred embodiment, a specific method for obtaining the site selection plan of the distributed high-inertia phase regulator is as follows: when the short-circuit ratio is greater than the critical short-circuit ratio, a site selection and sizing construction plan of the distributed high-inertia phase regulator can be obtained; when the short-circuit ratio is less than the critical short-circuit ratio, a distributed high-inertia phase regulator is configured at the node, and the short-circuit ratio of the node less than the critical short-circuit ratio is calculated again. If it is higher than the critical short-circuit ratio, a site selection and sizing construction plan of the distributed high-inertia phase regulator can be obtained, and the phase regulators are deployed according to the site selection and sizing construction plan of the distributed high-inertia phase regulator to reduce transient overvoltage.

[0011] The technical effects and advantages of the distributed high-inertia phase regulator optimization configuration method for multiple transient supports of the present invention are as follows: 1. The present invention evaluates the system inertia distribution and identifies the weak areas of system frequency support through node inertia, and then selects the phase shifter configuration site based on the node inertia sensitivity index, and uses the critical inertia constrained by the frequency stability condition as an inequality constraint, with the minimum configuration capacity and the highest economy as the optimization goal. The site selection and capacity determination method for distributed high-inertia phase shifters is direct and efficient, and can more effectively improve the system frequency support strength under the premise of minimizing the total configuration capacity of the phase shifters and maximizing the economy. The method is highly practical and economical, and has practical significance for application in power grids; in actual engineering applications, the physical meaning of the provided indicators is clear, and it is easy for decision makers to understand and use the indicators to quantitatively analyze the advantages and disadvantages of different schemes.

[0012] 2. The present invention establishes a mathematical relationship between the short-circuit ratio and transient overvoltage, reflects the severity of transient overvoltage caused by faults through the short-circuit ratio, and quantifies the impact of the voltage support strength of the new energy grid-connected system on transient overvoltage. The complex mathematical relationship between the voltage support strength and transient overvoltage under the new energy multi-station feed-in structure is revealed, while meeting the requirements of engineering practicality and accuracy; for the sending-end power grid with a high proportion of wind power, the frequency stability and voltage stability are comprehensively considered, and a distributed high-inertia phase-shifting optimization configuration method for wind farm stations in the sending-end power grid that simultaneously considers the improvement of inertia and short-circuit ratio is constructed, which will be more realistic for the stable operation of the power system. BRIEF DESCRIPTION OF THE DRAWINGS

[0013] Figure 1 It is a structural schematic diagram of the distributed high-inertia phase regulator optimization configuration method for multiple transient supports of the present invention. DETAILED DESCRIPTION

[0014] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0015] Embodiment 1, Figure 1 The invention provides a distributed high-inertia phase-shifting optimization configuration method for multiple transient supports.

[0016] S10, obtaining network topology information of the planned regional power system, calculating the system critical inertia and system node inertia based on the network topology information, finding out the nodes below the critical inertia, and configuring the phase regulator; Obtain the network topology information of the power system in the planned area, determine the maximum frequency change rate and the maximum frequency deviation limit that can ensure the stable operation of the system, and calculate the critical inertia of the system based on this; Calculate the system node inertia and find the nodes that are lower than the critical inertia. If they are lower than the critical inertia, a phase regulator needs to be configured. The frequency change rate Indicates the frequency change rate. If its value is too large, the frequency will drop rapidly or even exceed the threshold. The maximum frequency change rate is expressed as ; The frequency deviation Indicates the frequency drop amplitude. If the amplitude is too large, the protection device will be triggered, which may cause frequency collapse in severe cases. The maximum frequency deviation is expressed as ; The critical inertia of the system is and The constrained system obtains the grid inertia under two constraints respectively, and then takes the larger of the two as the system critical inertia; The critical inertia of the system The specific calculation formula is as follows:

[0017]

[0018] In the formula, is the critical inertia of the system, is the minimum value of system inertia when the frequency change rate does not exceed the threshold, is the minimum system inertia when the frequency deviation does not exceed the threshold, is the maximum disturbance power, is the reference frequency, is the moment when the lowest frequency point occurs, is the maximum frequency deviation, is the maximum frequency change rate; The specific calculation formula of the system node inertia is as follows:

[0019] In the formula, For Node The inertia of For the matrix Corresponding to the node and generator Elements of voltage relationships, Indicates taking Midpoint The element of the row; For generator Inertia; For generator The synchronous power factor; In the formula The method to obtain is as follows: Assume that one has The power system has a total of Generator end nodes, in addition to the generator end nodes there are network nodes, and the system obtains the augmented admittance array :

[0020] In the formula, It is the diagonal array formed after the transient reactance of the generator is converted into admittance. and is the self-admittance of the generator and other network nodes, and is the equivalent admittance of the loads at the generator and other network nodes after being simplified to equivalent admittances, and is the mutual admittance between the generator and other network nodes, neglecting the conductance; The network equation of the system is as follows:

[0021] In the formula, and is the voltage of the generator terminal node and other nodes, is the current input from the potential node in the generator to the network, , , , is the four regions of the augmented admittance matrix, where , , , ; The voltage of the network nodes other than the generator nodes in the power grid is expressed by the potential node voltage inside the generator. The formula is as follows:

[0022] In the formula, represents the correlation matrix between voltages, , the size of its elements is mainly affected by the admittance matrix of the power grid; Compare the system critical inertia with the system node inertia to find out the nodes that are lower than the critical inertia. If the system node inertia is lower than the critical inertia, a phase regulator needs to be configured. S20, calculating the sensitivity of the inertia of the node lower than the critical inertia to the inertia of the phase shifter at each pre-configured node, combining the critical inertia and the node inertia, calculating the comprehensive sensitivity at each pre-configured point, and determining the configuration position with the best sensitivity according to the comprehensive sensitivity; The node inertia sensitivity is the node inertia Inertia of generator The specific calculation formula is as follows:

[0023] The specific calculation formula for the comprehensive sensitivity at each pre-configured point is as follows:

[0024] In the formula, is the comprehensive sensitivity at each pre-configured point, For pre-configured points, For Node With pre-configured points The sensitivity between is the critical inertia of the system, For Node Inertia; The inertia of each node below the critical inertia and the critical inertia of the system are combined with the sensitivity between the node and the pre-configured node, and the comprehensive sensitivity at each pre-configured point is obtained by summing. When the ratio of the difference between the critical inertia and the node inertia to the critical variable is the largest, that is, when the comprehensive sensitivity at each pre-configured point is the largest, the phase regulator is configured at the pre-configured point; S30, inputting the objective function and constraint conditions, and using the particle swarm optimization algorithm to obtain a configuration solution; The objective function is the total capacity of the phase regulator configuration, and the constraint condition is the critical inertia of the system; The objective function is the total capacity of the phase regulator configuration, and the specific calculation formula is as follows:

[0025] In the formula, Configure the total capacity for the condenser. The phase-shifting capacity configured at the new energy station. is the number of new energy stations in the system; The particle swarm optimization algorithm steps are as follows: First, a group of particle positions and initial velocities are randomly generated, and the initial fitness value is calculated. The fitness value is the total capacity of the phase regulator configuration, and the initial position of the particle is set to the individual extreme position of each particle; Traverse the individual extreme fitness values ​​of all particles, find the minimum fitness value, and set the individual extreme position of the corresponding particle as the global extreme position; For each particle, update its position according to its current speed and position, calculate the fitness value of the new position, and update the individual best position and global best position of the particle based on the fitness value; The specific formula for updating the particle speed and position is as follows:

[0026]

[0027] In the formula, and Represents particles exist In the The velocity and position at the iteration, is the inertia weight, and is the learning factor, and is a random number between 0 and 1, Represents particles In the The individual extreme value position at the iteration, Indicates that the entire particle group is The global extremum position at the iteration; When the system node inertia reaches the system critical inertia, the iteration is stopped, and the particle update position is the phase shifter configuration position; The core idea of ​​the particle swarm optimization algorithm is to represent the potential solutions of the problem as "particles". These particles search for the optimal solution by updating their speed and position in the search space. Each particle has two important properties: Position: represents the current solution; Speed: controls the direction and amplitude of particle movement in the search space; Each particle adjusts its speed and position based on two things: Individual optimal solution: the best position found by the particle itself in history; Global optimal solution: the best position found in the entire particle swarm; The inertia of the system node below the critical inertia is checked again to determine whether it is greater than the critical inertia. If it is greater than the critical inertia, the inertia-based distributed high-inertia phase-shifting optimization configuration is completed; S40, updating the network topology information, calculating the short-circuit ratio of each grid-connected node according to the system node admittance matrix, configuring the phase regulator at the node with a short-circuit ratio less than a preset critical short-circuit ratio, and performing a secondary comparative analysis to obtain a site selection plan for the distributed high-inertia phase regulator; The relationship between the short-circuit ratio and the transient overvoltage is as follows: Transient overvoltage is usually a phenomenon of instantaneous voltage rise in the system after the short-circuit condition is removed. The higher the short-circuit ratio, the smaller the short-circuit current of the generator, the stronger the stability of the system, and the smaller the impact of transient overvoltage. The mathematical relationship between the short-circuit ratio and the transient overvoltage is calculated as follows:

[0028] In the formula, For the The grid connection point voltage; For AC system and grid connection point The longitudinal component of the voltage; For the Rated voltage of each grid connection point; is the system potential; The system node admittance matrix is matrix, is the number of buses, the system node admittance matrix The specific calculation formula is as follows:

[0029] In the formula, For the The self-admittance at the busbar, Busbar and The admittance between The node admittance matrix The inverse matrix is ​​the impedance matrix of the power grid , the equivalent impedance of each grid connection point , the specific calculation formula is as follows:

[0030] In the formula, The impedance matrix is diagonal elements; The specific calculation formula for the short-circuit ratio of the new energy base grid connection point is as follows:

[0031] In the formula, is the equivalent impedance of the grid connection point to the system; The short circuit ratio is greater than the critical short circuit ratio As the basis for judging whether the AC power grid has strong voltage support capability, the specific calculation formula is as follows:

[0032] When the short-circuit ratio is greater than the critical short-circuit ratio, the site selection and capacity construction plan of the distributed high-inertia phase regulator can be obtained; the distributed high-inertia phase regulator is configured at the node where the short-circuit ratio is less than the critical short-circuit ratio; The short-circuit ratio of the node less than the critical short-circuit ratio is calculated again. If it is higher than the critical short-circuit ratio, the site selection and capacity determination construction plan of the distributed high-inertia phase-shifting machine can be obtained. Distributed high-inertia phase regulators are deployed according to their site selection, capacity determination and construction plan to reduce transient overvoltages.

[0033] The above formulas are all dimensionless and numerical calculations. The formula is a formula for the most recent real situation obtained by collecting a large amount of data and performing software simulation. The preset parameters in the formula are set by technicians in this field according to actual conditions.

[0034] The above embodiments may be implemented in whole or in part by software, hardware, firmware or any other combination. When implemented by software, the above embodiments may be implemented in whole or in part in the form of a computer program product.

[0035] Those of ordinary skill in the art will appreciate that the modules and algorithm steps of each example described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are performed in hardware or software depends on the specific application and design constraints of the technical solution. Professional and technical personnel can use different methods to implement the described functions for each specific application, but such implementation should not be considered to be beyond the scope of this application.

[0036] In addition, each functional module in each embodiment of the present application may be integrated into one processing module, or each module may exist physically separately, or two or more modules may be integrated into one module.

[0037] The above is only a specific implementation of the present application, but the protection scope of the present application is not limited thereto. Any person skilled in the art who is familiar with the present technical field can easily think of changes or substitutions within the technical scope disclosed in the present application, which should be included in the protection scope of the present application. Therefore, the protection scope of the present application should be based on the protection scope of the claims.

[0038] Finally: The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent substitutions, improvements, etc. made within the spirit and principles of the present invention should be included in the protection scope of the present invention.

Claims

1. A distributed high-inertia phase-shifting optimization configuration method for multiple transient supports, characterized in that: The following steps are involved: Obtain the network topology information of the power system in the planned area, calculate the system critical inertia and system node inertia based on the network topology information, find out the nodes below the critical inertia, and configure the phase regulator; Calculate the sensitivity of the inertia of the node below the critical inertia to the inertia of the condenser at each pre-configured node, calculate the comprehensive sensitivity at each pre-configured point by combining the critical inertia and the node inertia, and determine the configuration position with the best sensitivity based on the comprehensive sensitivity; Input the objective function and constraints, and use the particle swarm optimization algorithm to obtain the configuration solution; Update the network topology information, calculate the short-circuit ratio of each grid-connected point based on the system node admittance matrix, configure phase regulators at nodes with a short-circuit ratio less than the preset critical short-circuit ratio, and perform a secondary comparative analysis to obtain the site selection plan for distributed high-inertia phase regulators.

2. The distributed high-inertia phase-shifting optimization configuration method for multiple transient supports according to claim 1 is characterized in that: The method for obtaining the critical inertia of the system is as follows: The network topology information of the power system in the planned area is obtained, and the maximum frequency change rate and the maximum frequency deviation limit value that can ensure the stable operation of the system are obtained according to the network topology information, and the larger of the maximum frequency change rate and the maximum frequency deviation limit value is taken as the critical inertia of the system.

3. The distributed high-inertia phase-shifting optimization configuration method for multiple transient supports according to claim 1 is characterized in that: The specific steps of determining the configuration position with the best sensitivity according to the comprehensive sensitivity are as follows: The inertia of each node below the critical inertia and the critical inertia of the system are combined with the sensitivity between the node and the pre-configured node, and the comprehensive sensitivity at each pre-configured point is obtained by summing them up; When the ratio of the difference between the critical inertia and the node inertia to the critical variable is the largest, that is, when the comprehensive sensitivity at the pre-configuration point is the largest, the phase regulator is configured at the pre-configuration point.

4. The distributed high-inertia phase-shifting optimization configuration method for multiple transient supports according to claim 1 is characterized in that: The particle swarm optimization algorithm steps are as follows: Randomly generate a set of particle positions and initial velocities, calculate the initial fitness value, and set the initial position of the particle to the individual extreme position of each particle; Traverse the individual extreme fitness values ​​of all particles, find the minimum fitness value, and set the individual extreme position of the corresponding particle as the global extreme position; For each particle, update its position according to the current speed and position, calculate the fitness value of the new position, and update the individual best position and global best position of the particle based on the fitness value; When the system node inertia reaches the system critical inertia, the iteration is stopped, and the particle update position is the phase shifter configuration position.

5. The distributed high-inertia phase-shifting optimization configuration method for multiple transient supports according to claim 1 is characterized in that: The specific method for obtaining the site selection plan of the distributed high-inertia phase regulator is as follows: When the short-circuit ratio is greater than the critical short-circuit ratio, the site selection and capacity determination construction plan for the distributed high-inertia phase-shifting machine can be obtained; When the short-circuit ratio is less than the critical short-circuit ratio, a distributed high-inertia phase-shifting condenser is configured at the node, and the short-circuit ratio of the node less than the critical short-circuit ratio is calculated again. If it is higher than the critical short-circuit ratio, the site selection and capacity determination construction plan of the distributed high-inertia phase-shifting condenser can be obtained. Distributed high-inertia phase regulators are deployed according to their site selection, capacity determination and construction plan to reduce transient overvoltages.

6. The distributed high-inertia phase-shifting optimization configuration method for multiple transient supports according to claim 1 is characterized in that: The specific calculation formula of the critical inertia of the system is as follows: In the formula, is the critical inertia of the system, is the minimum value of system inertia when the frequency change rate does not exceed the threshold, is the minimum value of system inertia when the frequency deviation does not exceed the threshold, is the maximum disturbance power, is the reference frequency, is the moment when the lowest frequency point occurs, is the maximum frequency deviation, is the maximum rate of frequency change.

7. The distributed high-inertia phase-shifting optimization configuration method for multiple transient supports according to claim 1 is characterized in that: The specific calculation formula of the system node inertia is as follows: In the formula, For Node The inertia of For the matrix Corresponding to the node and generator Elements of voltage relationships, Indicates taking Midpoint The element of the row, For generator The inertia of For generator Internal potential nodes and fault nodes The electrical conductivity.

8. The distributed high-inertia phase-shifting optimization configuration method for multiple transient supports according to claim 1 is characterized in that: The node inertia sensitivity is the sensitivity of the node inertia to the generator inertia, and the specific calculation formula is as follows: In the formula, For Node The inertia of For generator The inertia of For generator The synchronous power factor, For the matrix Corresponding to the node and generator Elements of voltage relationships, Indicates taking Midpoint The element of the row; The specific calculation formula for the comprehensive sensitivity at each pre-configured point is as follows: In the formula, is the comprehensive sensitivity at each pre-configured point, For pre-configured points, For Node With pre-configured points The sensitivity between is the critical inertia of the system, For Node inertia.

9. The distributed high-inertia phase-shifting optimization configuration method for multiple transient supports according to claim 1 is characterized in that: The specific formula for particle update speed and position in the particle swarm optimization algorithm is as follows: In the formula, and Represents particles exist In the The speed and position at the iteration, is the inertia weight, and is the learning factor, and is a random number between 0 and 1, Represents particles In the The individual extreme value position at the iteration, Indicates that the entire particle group is The global extremum position at iteration .

10. The distributed high-inertia phase-shifting optimization configuration method for multiple transient supports according to claim 5 is characterized in that: The mathematical relationship between the short-circuit ratio and the transient overvoltage is calculated as follows: In the formula, For the The grid connection point voltage; For AC system and grid connection point The longitudinal component of the voltage; For the Rated voltage of each grid connection point; is the system potential; is the short-circuit ratio of the grid-connected point.

11. The distributed high-inertia phase-shifting optimization configuration method for multiple transient supports according to claim 1 is characterized in that: The specific calculation formula of the short-circuit ratio of the grid connection point is as follows: In the formula, is the short-circuit ratio of the grid connection point, is the equivalent impedance of the grid connection point to the system; The specific calculation formula of the equivalent impedance of each grid connection point is as follows: In the formula, is the equivalent impedance of each grid connection point, The impedance matrix is diagonal elements, is the impedance matrix of the grid, The inverse matrix of the impedance matrix of the power grid is the node admittance matrix. The specific calculation formula of the system node admittance matrix is ​​as follows: In the formula, is the system node admittance matrix, For the The self-admittance at the busbar, It is a busbar and The admittance between is the number of buses.

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