KR102223625B1 - System and Method for Controlling Virtual Multi Slack Droop Based on Power Sensitivity Analysis - Google Patents

Abstract

The present invention relates to an apparatus and method for power sensitivity-based virtual multi-slack droop control in which a plurality of generators operate together as a slack generator in a power system with a high input amount of renewable energy to improve system stability. Synchronization data collection unit for collecting synchronization data; Multi-slack current calculation unit for calculating multi-slack current when operating point fluctuation is large, and power sensitivity calculation unit for calculating power sensitivity between load and generator; Power between load and generator A virtual multi-slack droop control unit that provides an optimal droop coefficient based on sensitivity in real time to enable power distribution between all generators, and controls the operation as a virtual multi-slack that indirectly controls the magnitude and phase angle of the bus voltage; It includes.

Description

System and Method for Controlling Virtual Multi Slack Droop Based on Power Sensitivity Analysis

The present invention relates to power system operation, and specifically, an apparatus for power sensitivity-based virtual multi-slack droop control in which a plurality of generators operate together as a slack generator in a power system with a high input amount of renewable energy to improve the stability of the system. And a method.

Along with the recent rise of smart grids, microgrid power grids independent from existing power grids have been widely used in islands and remote regions at home and abroad using distributed power sources such as wind power and solar power and energy storage devices.

In particular, research on an independent microgrid incorporating a renewable energy generator is actively being conducted.

Since these independent microgrids are disconnected from the existing power grid, maintaining power balance during operation is the most important factor and a technology that determines reliability and stability.

Therefore, in order to improve stability, in the standalone microgrid system, a droop control method in which distributed power supplies and energy storage devices each autonomously control is applied.

In the droop control method of the prior art, the active power output is determined by multiplying the frequency variation by a specific droop coefficient, and the reactive power output is determined by multiplying the voltage variation by a specific droop coefficient.

However, in the prior art, there is a problem in that the converter of renewable energy performs active and reactive power control by a constant droop coefficient, so that the constant fluctuation of the system cannot be reflected at all.

In particular, in the power system, active power-phase and reactive power-voltage are physically related, but the converter has a physical relationship between active power-DC voltage and reactive power-AC voltage, so the interdependence of active power and reactive power is conventional. Stronger than the generator.

In the prior art, there is a technology for controlling the converter by considering the characteristics of the power system and simulating the physical characteristics of the existing generator, but this has a side effect of eliminating the ability to maintain a constant frequency and fast response, which are strong advantages of the converter itself.

Therefore, there are many cases in which the voltage and frequency cannot be sufficiently stabilized without promptly responding to power system events.

In addition, precise droop coefficient calculation is required, and a new droop coefficient must be calculated according to not only changes in topology such as input of a new generator, but also changes in load and power generation, otherwise the system becomes unstable.

Among the recent technologies, there is a multi-slack control technology using GPS time synchronization. Until now, the system is the most powerfully stabilized and the response performance is excellent, but the current due to measurement and control errors when the electrical distances of different converters are very close. There is a problem that requires an electrical distance more than a certain amount because instability may occur.

Therefore, the most optimized generator combination response to load fluctuations is achieved, and there is a demand for the development of a new power system operation technology capable of minimizing computational system resources by eliminating the need for system analysis repetition in routine system changes. .

Korean Patent Registration No. 10-1219883 Republic of Korea Patent Publication No. 10-2017-0092976 Republic of Korea Patent Publication No. 10-2014-0098431

The present invention is to solve the problem of the power system operation technology of the prior art, in a power system with a high input amount of renewable energy, a plurality of generators operate together as a slack generator to improve system stability. An object thereof is to provide an apparatus and method for controlling slack droop.

In the present invention, the most optimized generator combination response to load fluctuations is achieved, and a power sensitivity-based virtual multi-slack droop control device capable of minimizing computational system resources by eliminating the need for a system analysis repetition in a daily system change, and Its purpose is to provide a method.

The present invention provides an apparatus and method for controlling a virtual multi-slack droop based on power sensitivity so that a stable system operation capability can be secured even for events significantly exceeding the capacity of a single generator by multiple generators responding together in response to a large event in the system. It has its purpose.

The present invention provides an optimal droop coefficient based on the power sensitivity between the load and the generator in real time so that a plurality of converter generators operate as a virtual slack bus, and the virtual slack bus is a physical multi-slack based on the existing GPS time synchronization. An object of the present invention is to provide an apparatus and a method for controlling a virtual multi-slack droop based on power sensitivity, which is present in the space to increase system stability and responsiveness.

Other objects of the present invention are not limited to the above-mentioned objects, and other objects not mentioned will be clearly understood by those skilled in the art from the following description.

The apparatus for virtual multi-slack droop control based on power sensitivity according to the present invention for achieving the above object includes a synchronization data collection unit that collects synchronization data of distributed power sources; A multi-slack current calculation unit and a power sensitivity calculation unit that calculates the power sensitivity between the load and the generator; Provides an optimal droop coefficient in real time based on the power sensitivity between the load and the generator, enabling power distribution between all generators It characterized in that it comprises a; virtual multi-slack droop control unit for controlling to operate as a virtual multi-slack that indirectly controls the magnitude and phase angle of the voltage.

The method for virtual multi-slack droop control based on power sensitivity according to the present invention for achieving another object comprises: collecting synchronization data of distributed power supplies for power sensitivity-based virtual multi-slack droop control; based on previously calculated power sensitivity VMS power generation by adaptive droop control; Determine whether there is a change in operating point, calculate multi-slack current when violating a predefined operating voltage or phase range, and calculate power sensitivity between the load and the generator. Based on the power sensitivity between the load and the generator, the optimal droop coefficient is provided in real time to enable power distribution between all generators, and it can operate as a virtual multi-slack that indirectly controls the magnitude and phase angle of the bus voltage. Reconfiguring the VMS power generation as a secondary control to compensate for the deviation caused by the primary control based on the previously calculated power sensitivity; VMS droop control with the recalculated power sensitivity (S) It characterized in that it includes; updating to a new operating condition for.

The apparatus and method for virtual multi-slack droop control based on power sensitivity according to the present invention as described above has the following effects.

First, in a power system with a high input amount of renewable energy, a number of generators work together as a slack generator to improve system stability.

Second, the most optimized generator combination response to load fluctuations is achieved, and it is possible to minimize the computational system resources by eliminating the need for system analysis repetition in daily system changes.

Third, it is possible to secure a stable system operation capability even for events that greatly exceed the capacity of a single generator by allowing multiple generators to act together in response to a large event in the system.

Fourth, based on the power sensitivity between the load and the generator, the optimal droop coefficient is provided in real time so that a number of converter generators operate as a virtual slack bus, and the virtual slack bus is between physical multi-slack based on the existing GPS time synchronization It is present in the system and can increase system stability and responsiveness.

1 is a configuration diagram of an apparatus for virtual multi-slack droop control based on power sensitivity according to the present invention
2 is a flow chart showing a method for virtual multi-slack droop control based on power sensitivity according to the present invention
3 is a flow chart showing VMS droop control based on power sensitivity analysis
4 is a block diagram showing an example for implementing an independent microgrid and VMS droop control with a high input amount of renewable energy
5 shows the change in the total load of the independent microgrid with a high input amount of renewable energy, (a) active power (b) reactive power
Figure 6 is a graph showing the active power response of (a) diesel, CBG1, CBG3 (b) CBG2, CBG4, CBG5, CBG6 diesel generator without VMS droop control and CBG
7 is a graph showing the reactive power response of a diesel generator without VMS droop control of (a) diesel, CBG1 (b) CBG1, CBG2, CBG4, CBG5, and CBG6 and CBG
Figure 8 is a graph showing the active power response to the VMS droop control of (a) diesel, CBG1, CBG3 (b) CBG2, CBG4, CBG5, CBG6 diesel generator and CBG
9 is a graph showing the reaction of reactive power to the VMS droop control of (a) diesel, CBG3 (b) CBG1, CBG2, CBG4, CBG5, and CBG6 diesel generators and CBG
Figure 10 is a power sensitivity heat map relating to the relationship between the power change and CBG in the mothership of the island "D"
11 is a graph showing the response characteristics of the bus voltage magnitude of (a) a diesel generator without VMS droop control and (b) a diesel generator with VMS droop control and CBG
12 is a graph showing the bus phase response characteristics of (a) a diesel generator without VMS droop control and (b) a diesel generator with VMS droop control and CBG
13(a) and (b) are graphs showing the effective and reactive power loss and VMS droop control of the microgrid.
14 is a graph showing the change in power from CBG3 and CBG4 due to the intermittentness of renewable energy
15 and 16 are graphs of active and reactive power response characteristics of a diesel generator without VMS droop control and remaining CBG
17 is a power sensitivity heat map
18(a) and 19(a) are graphs showing magnitude and phase angle responses without VMS droop control, respectively
18(b) and 19(b) are graphs showing voltage characteristics by VMS droop control of the remaining CBGs.

Hereinafter, a preferred embodiment of an apparatus and method for controlling a virtual multi-slack droop based on power sensitivity according to the present invention will be described in detail.

Features and advantages of the apparatus and method for power sensitivity-based virtual multi-slack droop control according to the present invention will become apparent through detailed description of each embodiment below.

1 is a block diagram of an apparatus for controlling a virtual multi-slack droop based on power sensitivity according to the present invention, and FIG. 2 is a flow chart showing a method for controlling a virtual multi-slack droop based on power sensitivity according to the present invention.

An apparatus and method for virtual multi-slack droop control based on power sensitivity according to the present invention is to improve system stability by operating a plurality of generators together as a slack generator in a power system with a high input amount of renewable energy.

To this end, the present invention provides the most optimized generator combination response to load fluctuations, and includes a configuration for minimizing computational system resources by eliminating the need for repetition of system analysis in a daily system change.

The present invention provides an optimal droop coefficient based on the power sensitivity between the load and the generator in real time so that a plurality of converter generators operate as a virtual slack bus, and the virtual slack bus is a physical multi-slack based on the existing GPS time synchronization. It includes a configuration to be present in between to increase system stability and responsiveness.

The apparatus for controlling a virtual multi-slack droop based on power sensitivity according to the present invention includes a synchronization data collection unit 300 that collects synchronization data of distributed power 1 (100a) to distributed power source n (100n), as shown in FIG. 1, Based on the multi-slack current calculation unit 500 that calculates the multi-slack current when there is a load fluctuation and the power sensitivity calculation unit 400 that calculates the power sensitivity between the load and the generator, and the power sensitivity between the load and the generator. It includes a virtual multi-slack droop control unit 200 that provides an optimal droop coefficient in real time to enable power distribution between all generators to operate as a virtual multi-slack that indirectly controls the magnitude and phase angle of the bus voltage. .

The method for virtual multi-slack droop control based on power sensitivity according to the present invention collects synchronization data of distributed power sources (S201), and performs adaptive droop control based on the previously calculated power sensitivity, as shown in FIG. Make power (S202)

Subsequently, it is determined whether there is a load fluctuation (S203), when a predefined operating voltage or phase range is violated, a multi-slack current is calculated, and a power sensitivity between the load and the generator is calculated (S204).

In addition, by providing the optimal droop coefficient based on the power sensitivity between the load and the generator in real time, it enables power distribution between all generators and controls the operation as a virtual multi-slack that indirectly controls the magnitude and phase angle of the bus voltage. .(S205)

Subsequently, the VMS power generation is reconstructed as a secondary control to compensate for the deviation caused by the primary control (S206).

And the recalculated power sensitivity ( S ) is updated to a new operating condition for VMS droop control (S207).

The present invention is for virtual multi-slack (VMS) droop control based on power sensitivity analysis, which allows all generators including CBG (Converter Based Generators) to distribute power between CBGs, thereby allowing the magnitude of bus voltage. It allows it to operate as a virtual multi-slack (one generator for physical slack) that indirectly controls the and phase angle.

As a result, real and virtual slack effectively share the load and resolve the power imbalance.

A hierarchical control architecture through VMS power flow analysis and VMS power flow analysis may be implemented in order to implement VMS droop control by the apparatus and method for power sensitivity-based virtual multislack droop control according to the present invention.

Basic control for local stability is achieved by pre-calculated VMS droop control based on power sensitivity analysis.

In addition, the VMS power flow can control not only the deviation caused by the primary control but also a long-term operation, and the VMS power flow analysis can effectively solve the power flow of the microgrid with a high input amount of renewable energy.

Power sensitivity that enables VMS droop control is derived by adaptively allocating power between CBGs.

VMS power flow analysis according to the present invention classifies the bus type into physical slack, virtual slack, voltage controlled and load buses.

The physical slack bus is the same as the slack bus of the existing power flow analysis, and the virtual slack bus may be basically a voltage control bus or an active power (P) and reactive power (Q) control bus (for CBG).

However, if the difference between power generation and load consumption is ideally compensated, it can operate as a slack bus, and voltage control and load bus are the same as conventional power flow analysis.

As a result, the real and virtual Slack busbars resolve the power imbalance with proper control.

n For power flow analysis of the bus system, the power mismatch can be defined as follows.

Here, P _i and Q _i are planned as active power and reactive power in bus i, respectively.

The second term to the right of Equation 1 and Equation 2 is the active power and reactive power at the bus i, respectively.

|V _i | and δ _i are the magnitude and phase angle of the voltage at bus i.

In addition, |Y _ij | and θ _ij are the magnitude and angle _{of the Y bus} element between the bus i and the bus j, respectively.

Y _bus is the nodal admittance matrix.

If Equations 1 and 2 are developed by Taylor expansion, ignoring the higher-order term, the initial linear equation for deriving the VMS power flow analysis according to the present invention is defined as follows.

와

는 각각 전력 및 전압 불일치의 벡터이다.here,

Wow

Is the vector of power and voltage mismatch, respectively.

The subscripts n and m represent the total number of buses and slack buses (m-1 virtual slack and 1 physical slack), respectively.

)의 서브 행렬, Jacobian procession (

) Submatrices,

는 모선 전압의 위상 각 및 크기에 대한 유효 및 무효 전력의 편미분이다.

Is the partial derivative of the active and reactive power with respect to the phase angle and magnitude of the bus voltage.

의 역행렬

는 다음과 같이 정의된다.For a more detailed explanation

Inverse matrix of

Is defined as

는 서브 행렬이다.here,

Is a sub-matrix.

Then, the power mismatch of the virtual slack bus can be divided into generation and load mismatch.

Therefore, the power and voltage mismatch of the virtual slack bus can be redefined as follows.

Here, the subscripts, GBG, and Load denote power generation and load consumption in the virtual slack busbar, respectively.

와

는 수학식 4에서 K의 원소를 사용하여 재결합된 행렬이다.

Wow

Is a matrix recombined using the element of K in Equation 4.

This is defined as in Equations 6 and 7.

The superscript and subscript represent the number of sub-matrices and elements of Equation 4, respectively.

The virtual slack bus ideally specifies a voltage and a phase angle that causes zero mismatch in the left term of Equation (5).

Equation 5 can be rearranged as follows.

The power flow equation represents the state of the system after convergence.

For example, when the physical system is in a steady state, all deviations in Equation 3 are zero.

Conversely, changes in the load of a physical system change the magnitude and phase angle of the voltage.

The load deviation of Equation 3 induces the same result in the conventional power flow analysis.

In the VMS droop control according to the present invention, Equation 8 provides an appropriate allocation of CBG for primary control corresponding to a load change.

That is, the primary control determines an appropriate load sharing between virtual slacks for local power balance based on Equation 8.

는 다음과 같이 정의된다.Based on this relationship, the power sensitivity matrix

Is defined as

는 부하 변동에 대한 CBG의 전력 민감도를 나타낸다.Where, the sub-matrix

Represents the power sensitivity of the CBG to load fluctuations.

Thus , each element of S acts as a droop curve between the individual generator and the load.

Here, each droop curve is adaptively determined according to the system conditions.

Finally, VMS power flow analysis is performed by Equation 10.

는 VMS 관련 요소 또는 물리적 슬랙없이 구성된다.here,

It is constructed without VMS-related elements or physical slack.

VMS droop control and power flow analysis according to the present invention are implemented in the same manner as in FIG. 3.

3 shows a hierarchical control process of VMS droop control and power flow analysis according to the present invention.

The measured power is the net load, which is the vector sum of non-slack power generation and pure load, not physical and virtual slack.

Then, the VMS generation is easily determined based on the previously calculated power sensitivity for adaptive droop control. Therefore, the VMS droop control can act as a primary for a standalone microgrid with proper sharing and power balance between generators.

If the VMS droop control violates a predefined operating voltage or phase range taking into account the microgrid characteristics, the VMS power flow analysis reconstructs the VMS power generation as a secondary control to compensate for the deviation caused by the primary control.

In particular, the recalculated power sensitivity S is updated with new operating conditions for VMS droop control.

As a result, VMS droop control based on power sensitivity enables proper power allocation between VMS generations when small load changes occur in a standalone microgrid.

In addition, as long as the VMS droop control maintains the operating voltage or phase range, the computational work can be reduced because proper power distribution is performed with pre-calculated power sensitivity.

VMS power flow analysis and VMS droop control according to the present invention complement each other according to characteristics as shown in Table 1.

The main advantage of the VMS droop control according to the present invention is an accurate power balance by proper load sharing between the CBGs so that the system voltage is stabilized.

In order to verify this, a few load changes are simulated to apply a sudden power mismatch as shown in FIG. 5 as follows.

4 is a configuration diagram showing an example for implementing the independent microgrid and VMS droop control with a high input amount of renewable energy, and FIG. 5 is a diagram showing a change in the total load of the independent microgrid with a high input amount of renewable energy, (a) Active power (b) Reactive power.

As shown in Table 2, the total sum of the initial effective and reactive loads is set to 1770 kW and 177.6 kVAR, respectively.

Then, each load increases between 2.5 seconds and 22.5 seconds every 5 seconds as shown in FIG. 5(a).

Next, the load decreases again every 5 seconds from 27.5 seconds to 47.5 seconds.

As shown in Figures 6 and 7, the generation and total load requirements of the standalone microgrid are balanced by the only diesel generator (i.e., single slack) without VMS drop control.

Even if the input of renewable energy is high in this system, this is the same. In other words, all CBGs generate constant power regardless of load fluctuations.

Conversely, as in FIGS. 8 and 9, the VMS droop control system uses all of the CBGs as virtual multi-slack generators to balance power.

The VMS droop control system adaptively allocates power required for virtual slack operation based on power sensitivity.

The power sensitivity heat map for the relationship between the CBG and the power change of the bus is the same as in FIG. 10. A clear graphical representation of the power sensitivity matrix is provided by Equation 9 according to the system state.

Different strengths of power sensitivity are given in different colors and numbers.

For example, dark brown and white represent the highest sensitivity with 1 and zero with 0 respectively.

In Fig. 10, the power change of the busbars 2, 5, 16, 22, 27, 31 on which the CBG is installed is dominantly controlled by each CBG with a high sensitivity of 1. (dark brown)

This is because CBG operates as a virtual slack by specifying the magnitude and angle of the bus voltage with the proposed VMS droop control.

Conversely, the power change of another bus without CBG connection is balanced by several CBGs based on the sensitivity strength between CBGs as shown in FIG. 10.

For example, the power change in the bus 37 of Fig. 4 can be controlled by power generation from CBG2, CBG3 and CBG6.

As shown in FIG. 10, the power sensitivity is expressed in blue (intensity 0.1571 and 0.2548, respectively) for CBG2 and CBG3 and yellow-green (intensity 0.6058) for CBG6.

In addition, as in the results of Figs. 5 and 8, the change of the load of 17.5 seconds (see Fig. 5) from 1.90 MW to 1.94 MW in the bus 37 is from CBG2, CBG3 and CBG6 (see Fig. 8) according to the power sensitivity. Balanced by power generation.

As a result, the proposed VMS droop control reduces the burden on the diesel generator for power balancing, as shown in Figs. 8(a) and 9(a).

In other words, VMS droop control enables higher input of renewable energy in a standalone microgrid against load fluctuations.

The proposed VMS droop control improves the voltage profile (magnitude and phase angle) by allowing proper power sharing between CBGs as shown in FIGS. 11 and 12.

11(a) and 12(a), when there is no VMS droop control, the magnitude and phase angle of the voltage are changed by a maximum of 0.01 pu and 0.5 degrees, respectively.

This is because the diesel generator is powered by Slack.

However, this change is eliminated by the VMS droop control due to the improved voltage and angular stability due to the CBG's VMS operation.

The magnitude and phase angle response of the increased voltage are shown in Figs. 11(b) and 12(b), respectively.

In addition, VMS droop control can reduce power loss as shown in FIG. 13. Under normal conditions of the distribution line, the greater the voltage and phase angle difference, the greater the current, resulting in power loss.

13(a) and (b) show the effective and reactive power loss and VMS droop control of the microgrid.

A description of the change in power generation is as follows.

For reliable operation of a stand-alone microgrid with a high amount of renewable energy input, it is necessary to properly manage power fluctuations in CBG due to renewable energy.

Uncertainty in renewable energy resources can be dealt with as reserve power from the main grid when the microgrid is connected to a large-capacity power system.

In contrast, a standalone microgrid with a high input of renewable energy has limited reserve power.

As a result, RI-ESS is essential for the reliable operation of a standalone microgrid with a high input of renewable energy.

RI-ESS alleviates the intermittency of each renewable CBG.

Nevertheless, CBG must reduce its output power if renewable energy does not produce enough power.

In this case, the CBG can operate in a constant power control mode.

VMS droop control is verified with CBG to change power.

That is, the load remains unchanged and the CBG changes assuming the uncertainty of renewable energy.

The power change from CBG3 and CBG4 due to the intermittent nature of renewable energy is shown in FIG. 14.

CBG4 increases the output for 10 seconds. The RI-ESS of CBG4 increases the power generated by CBG4 due to a temporary increase in renewable energy.

Similarly, CBG3 reduces the power generated for 10 seconds. This is because the RI-ESS for CBG3 is completely discharged and the renewable energy of CBG3 is also temporarily reduced.

The active and reactive power responses of the diesel generator without VMS droop control and the remaining CBG are as in FIGS. 15 and 16.

The only diesel generator response power change is observed in CBG3 and CBG4 due to the intermittent nature of renewable energy without the proposed VMS droop control.

In contrast, other CBGs provide adequate control of power generation while diesel generators continue to provide near constant power when VMS droop control is applied.

When CBGs change their output power due to the uncertainty of renewable energy, they can be classified as outputs (i.e. negative loads) to resolve the VMS power flow.

In other words, the change in generation amount of CBG3 and CBG4 is regarded as a negative load change in buses 16 and 22, respectively.

The corresponding power sensitivity heat map is shown in FIG. 17.

Unlike FIG. 10 in which all CBGs use VMS droop control, CBG3 and CBG4 cannot participate in the proposed VMS droop control due to the intermittent nature of renewable energy, so the power sensitivity of FIG. 17 is changed.

That is, in FIG. 10, the load change from the bus 10 to the bus 17 is mainly controlled from cyan to red by CBG3. CBG2 and CBG6 have a lower blue color than CBG3.

However, if CBG3 is not operated by VMS droop control, the intensity of power sensitivity to load change from bus 10 to 17 of CBG2 and CBG6 is yellow-green (in the case of CBG2) and cyan (CBG6) as shown in FIG. In the case of), it increases with the color of.

As mentioned above, the change in power in CBG3 is considered a negative load in bus 16.

Therefore, it is controlled by CBG2 and CBG6.

As shown in Figs. 14 and 16, the power change from 600kW to 500kW of CBG3 in 7.5 seconds (see Fig. 14) in the bus 16 is due to the power generation from CBG2 and CBG6 (see Fig. 14) according to the power sensitivity. Is handled by

In summary, even if some of the CBGs do not participate in the VMS droop control, other CBGs can sufficiently take charge of the proposed VMS droop control based on the recalculated power sensitivity.

18(a) and 19(a) show magnitude and phase angle responses without VMS droop control, respectively.

The magnitude and phase angle of the voltage at the ends of the feeder lines such as the bus 16 and the bus 27 (brown and cyan in Figs. 18(a) and 19(a)) are changed according to the power change of CBG3 and CBG4.

On the other hand, as in FIGS. 18(b) and 19(b), the remaining CBG maintains a constant voltage by VMS droop control.

As a result, the voltage of the bus 16 and the bus 27 is kept constant.

The apparatus and method for virtual multi-slack droop control based on power sensitivity according to the present invention described above provides an optimal droop coefficient in real time based on the power sensitivity between a load and a generator, so that a plurality of converter generators operate as a virtual slack bus. In addition, the virtual slack bus is present between physical multi-slack based on the existing GPS time synchronization, so that system stability and responsiveness can be improved.

In particular, it is possible to secure stable system operation capability even for events that greatly exceed the capacity of a single generator by allowing multiple generators to act together in response to large events in the system.

As described above, it will be understood that the present invention is implemented in a modified form without departing from the essential characteristics of the present invention.

Therefore, the specified embodiments should be considered from a descriptive point of view rather than a limiting point of view, and the scope of the present invention is indicated in the claims rather than the above description, and all differences within the scope equivalent thereto are included in the invention It will have to be interpreted.

100a. 100n. Distributed power
200. Virtual Multi Slack Droop Control
300. Synchronization data collection unit
400. Power sensitivity calculation unit
500. Multi Slack Current Calculator

Claims (13)

A synchronization data collection unit for collecting synchronization data of distributed power sources;
A multi-slack current calculation unit that calculates a multi-slack current when the operating point fluctuation is large, and a power sensitivity calculation unit that calculates a power sensitivity between the load and the generator; And
Based on the power sensitivity between the load and the generator, the optimal droop coefficient is provided in real time, enabling power distribution between all generators, and controlling the operation as a virtual multi-slack that indirectly controls the magnitude and phase angle of the bus voltage. Including; Virtual Multi Slack (VMS) droop control unit,
The virtual multi-slack droop control unit,
Based on the previously calculated power sensitivity, adaptive droop control is performed to perform primary control to generate VMS, and when VMS droop control violates a predefined operating voltage or phase range, the deviation caused by the primary control An apparatus for virtual multi-slack droop control based on power sensitivity, characterized in that by reconfiguring VMS power generation as a secondary control for compensating for, and enabling power allocation between VMS power generation when a load fluctuation occurs. delete The power sensitivity-based virtual multi-slack droop control according to claim 1, wherein the recalculated power sensitivity ( S ) is updated to a new operating condition for VMS droop control when there is a load fluctuation in the power sensitivity calculator. Device for. The method of claim 1, wherein for VMS power flow analysis for virtual multislack droop control based on power sensitivity,
Classify the bus type into physical slack, virtual slack, voltage controlled and load buses,
The virtual slack bus is a voltage control bus or an active power (P) and reactive power (Q) control bus. The method of claim 4, wherein when analyzing the power flow of the n bus system to compensate for the difference between power generation and load consumption,
Power mismatch,

Is defined as,
Here, P _i and Q _i are planned as active power and reactive power in bus i, respectively, and the second term on the right is active power and reactive power in bus i, respectively,
|V _i | and δ _i are the magnitude and phase angle of the voltage at the bus i, and |Y _ij | and θ _{ij are the magnitude and angle of the Y bus} elements between the bus i and the bus j, respectively, Y _bus is a device for virtual multislack droop control based on power sensitivity, characterized in that the bus is a nodal admittance matrix. The method of claim 5, wherein the initial linear equation that derives the VMS power flow analysis is:

Is defined as,
here,

Wow

Is a vector of power and voltage mismatch, and the subscripts n and m represent the number of total buses and slack buses (m-1 virtual slack and 1 physical slack), respectively. Device for. The method of claim 6, wherein the Jacobian matrix (

) Submatrices,

Is the partial derivative of the active and reactive power with respect to the phase angle and magnitude of the bus voltage,

Inverse matrix of

silver

Is defined as,
here,

A device for virtual multi-slack droop control based on power sensitivity, characterized in that is a sub-matrix. The method of claim 7, wherein the power and voltage mismatch of the virtual slack bus bar,

Is defined as,
Here, the subscripts, GBG and Load denote the power generation and load consumption in the virtual slack busbar, respectively,

Wow

A device for virtual multislack droop control based on power sensitivity, characterized in that is a matrix recombined using an element of K. The method of claim 8,

ego,
Superscript and subscript represent the number of submatrices and elements, respectively,
The virtual slack bus is an apparatus for controlling a virtual multi-slack droop based on power sensitivity, characterized in that ideally designating a voltage and a phase angle causing zero mismatch in a left term. The method of claim 9, wherein the rearranged power flow equation,

ego,
Using this, a device for power sensitivity-based virtual multi-slack droop control, characterized in that it provides an appropriate allocation of CBG for primary control in response to a change in load, and determines appropriate load sharing between virtual slacks for local power balance. . The power sensitivity matrix of claim 10

silver,

ego,
Where, the sub-matrix

Represents the CBG's power sensitivity to load fluctuations, each element of S serves as a droop curve between individual generators and loads, and each droop curve is adaptively determined according to system conditions. A device for virtual multi-slack droop control based on power sensitivity. The method of claim 11, wherein the VMS power flow analysis,

Is done using,
here,

A device for virtual multi-slack droop control based on power sensitivity, characterized in that it is configured without VMS-related elements or physical slack. Collecting synchronization data of distributed power sources for power sensitivity-based virtual multi-slack droop control;
Generating VMS by performing adaptive droop control based on the previously calculated power sensitivity;
Determining whether there is a change in operating point, calculating multi-slack current when violating a predefined operating voltage or phase range, and calculating a power sensitivity between a load and a generator;
Based on the power sensitivity between the load and the generator, the optimal droop coefficient is provided in real time, enabling power distribution between all generators, and a virtual multi-slack (VMS) that indirectly controls the magnitude and phase angle of the bus voltage. Controlling to be able to operate as );
Based on the previously calculated power sensitivity, adaptive droop control is performed to perform primary control for VMS power generation, and when VMS droop control violates a predefined operating voltage or phase range, the deviation caused by the primary control Reconfiguring the VMS power generation as a secondary control to compensate for; And
Updating the recalculated power sensitivity ( S ) to a new operating condition for VMS droop control; including, and power sensitivity-based virtual multi-slack droop control, characterized in that it enables power allocation between VMS power generation when a load change occurs Way for.

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