JPH07123593A - Supervisory system of operation stability of power system - Google Patents

Abstract

PURPOSE:To allow quick evaluation of estimated disturbance by determining a solution through linear programming employing the sensitivity coefficient at the real part of an eigenvalue for generator output and the distance up to the stability limit thereof as a part of data. CONSTITUTION:An operating state data of a system, representative of the generator output, voltage, etc., is collected (S10). A large number of estimated disturbances f1-fn prepared previously (S2) are then subjected to efficient operation stability evaluation by eigenvalue sensitivity analysis (S3). When a decision is made that all, estimated disturbances are stable, the margin of generator output up to the stability limit is calculated by linear programming for a most unstable eigenvalue (S4). The results are presented for a system operator (S5) and reflected on the operation of actual system. This system realizes a high speed operation algorithm for supervising the operational stability thus allowing high speed evaluation of estimated disturbance.

Description

Detailed Description of the Invention

[0001]

BACKGROUND OF THE INVENTION 1. Field of the Invention The present invention relates to a power system dynamic stability monitoring system for online monitoring and control of the power system dynamic stability.

[0002]

2. Description of the Related Art A conventional electric power system monitoring method is to judge whether the preset disturbance is stable or unstable and to calculate the adjustment amount of the generator output so as to be stable when it is unstable. (For example, Takashiba et al. “A proposal for a system integrated monitoring and control system” PE-89-8, Power Engineering Research Group, 1989.
0). However, in a normal system operation state, the probability that the system will become unstable due to an unexpected disturbance is very low, and in such a case, the conventional power system monitoring device simply outputs a result indicating that it is stable. It was

[0003]

In recent years, the rapid increase in the demand for electric power has forced the electric power system to operate near its facility limit. Under these circumstances, in order to operate the system more safely, it is necessary to understand the system status in more detail than before. Therefore, in the present invention, when it is determined that all assumed disturbances are stable, how stable the power system is, that is, monitoring of the power system dynamic stability capable of calculating the stability margin amount of the system It is intended to provide a scheme.

[0004]

In order to achieve the above object, the present invention performs an eigenvalue sensitivity analysis of a system in evaluating dynamic stability, and calculates an output margin of a generator as a stability margin. In doing so, a solution is obtained by linear programming with the sensitivity coefficient of the eigenvalue real part for the generator output and the distance to the stability limit of the eigenvalue real part obtained from the results of dynamic stability evaluation as part of the data, and this solution Are provided to the operators of the electric power system.

[0005]

Therefore, in such a power system dynamic stability monitoring method, an efficient eigenvalue sensitivity analysis method is applied to the evaluation of dynamic stability with respect to a large number of assumed disturbances, and there When it is judged that the eigenvalue is stable, the power generation is performed using the sensitivity coefficient of the eigenvalue real part with respect to the generator output and the distance to the stability limit of the eigenvalue real part obtained from the results of dynamic stability evaluation for the eigenvalue that is the most unstable The machine output margin can be obtained as a solution of the linear programming method.

[0006]

Embodiments will be described below with reference to the drawings. Figure 1
Shows an overall flow chart for explaining a power system dynamic stability monitoring method according to the present invention. First, in step S1, the current operating state of the system, that is, the operating state data of the system indicating the generator output, voltage, etc. is collected. Next, in step S2, a large number of prepared external disturbances f ₁ , f
_2, ..., with respect to f _n, performs an efficient kinetic stability evaluation by eigenvalue sensitivity analysis at step S3. If it is determined in the stability evaluation in step S3 that all assumed disturbances are stable, the margin of the generator output up to the stability limit is linearly calculated with respect to the eigenvalue that is the most unstable in step S4. Calculate using the planning method. This result is presented to the system operator in step S5 and reflected in the operation of the actual system. After the completion of a series of calculations, a certain period of time elapses, or the system operation state changes, and when the operator determines that it is necessary, the calculations of this monitoring method are restarted.

The above is the overall flow of the monitoring method. Here, the dynamic stability evaluation part by the eigenvalue sensitivity analysis method of step S3 and the output of the generator by the linear programming method of step S4, which are the features of the present invention. The specific content of the calculation part of the margin will be described. First, the dynamic stability evaluation by the eigenvalue sensitivity analysis method is described. A linear model that linearly approximates minute changes near the operating point is used as the system model for dynamic stability analysis. An eigenvalue analysis method has been conventionally used as a method for determining the stability of this model. However, if the dimension of the system is large and the number of analysis cases is large, the calculation time is too long, so this method cannot be directly used for online calculation. On the other hand, an eigenvalue sensitivity analysis method has been proposed as a method for analyzing how the eigenvalues of a target system change when the parameters of the system change (for example, JE Van Nees et al. Sensitities of Large-L
loop control Systems ”, IEEE
Trans on Automatic contro
1, Vol. 10, pages 308-315, July,
1965).

According to this method, the eigenvalue calculation basically needs to be performed only once for one operating point. The change in eigenvalue with respect to the change in parameter [Δλ] is

[Outer 1] Since it can be calculated using, the influence of the parameter can be obtained relatively easily. In order to apply this method to the dynamic stability evaluation for each assumed disturbance, the processing shown in FIG. 2 is performed. In this case, transmission line opening is the main assumed disturbance for dynamic stability evaluation, and its parameter is system impedance here. Figure 2
In step S11 to S14, the preparation calculation for the sensitivity analysis is performed. That is, in step S11, a power flow calculation for determining the current power flow distribution state is performed, and based on the power flow calculation result, a system coefficient matrix [A] ₀ is created in step S12.

Next, in steps S13 and S14, eigenvalues λi ₀ , i = 1 to n (n is a dimension) of [A] ₀ and eigenvectors [Wi], i = 1 for each eigenvalue are calculated by eigenvalue calculation.
~ N and the eigenvectors [Vi], i of the transposed matrix [A] ^t
= 1 to n is calculated. Steps S15 to S22 are a part of sensitivity analysis which is repeatedly calculated for each contingency case. That is,
Step S15 is a part for selecting one of the predetermined assumed accident cases (track open) from the file.
Step S16 is a part for performing a power flow calculation for determining the power flow distribution state after the line opening which is the assumed disturbance.
In step S17, the coefficient matrix [A] ₁ of the system after the line is opened is created based on the result of the power flow calculation in step S16.
Next, in step S18, the coefficient matrix [A] associated with opening the line
The change [ΔA] is calculated. Using this, step S
At 19, the predicted change value Δλi, i of the eigenvalue λi, i = 1 to n
= 1 to n are calculated. If this Δλi is obtained, the expected value λi of the eigenvalue after opening the line can be calculated in step S20. Therefore, using this λi, the dynamic stability is evaluated in step S21. That is, if the real part of the eigenvalue λi is positive, the vibration component is unstable, and if the real part is negative, it can be determined to be stable. If all assumed accident cases are not completed in step S22, the process returns to step S15, and steps S15 to S15.
Repeat up to 21. When all assumed accident cases are completed, the dynamic stability evaluation of Fig. 2 is completed.

Next, a method of calculating the margin of the generator output by the linear programming will be described. As a result of the stability determination with respect to the assumed disturbance, the dynamic stability is stable under the current system operating conditions, that is, when it is determined that there is no eigenvalue in which the real part is positive as a result of the calculation in step S3 of FIG. In addition, the output margin of the generator is calculated as the stability margin.

When the output adjustment ΔPj of the generator j changes the eigenvalue to be monitored, for example, the real part of the most unstable eigenvalue i by Δσ, the following equation is generally established.

[Equation 1] Then, as the margin of dynamic stability, the target eigenvalue i
The result is to obtain (ΔPj, j = 1 to m) so that the real part σi of is negative (stable) to zero (stable limit). However, in this case, the following conditions shall be added. (a) To maintain a balance between power supply and demand for the entire system. (b) Consider the output variation that is fixed for each generator. In order to facilitate mathematical processing in the linear programming, the output adjustment amount ΔPj is described as follows.

[Formula 2] ΔPj = ΔPj ⁺ −ΔPj ⁻ …………
(2) where ΔPj ⁺ : an increase in the output adjustment amount of the generator j, ΔPj ⁻ : a decrease in the output adjustment amount of the generator j,
Then, ΔPj ⁺ and ΔPj ⁻ ≧ 0 are always satisfied.

As a solution for such a problem, linear programming can be applied as it is. That is,

[Equation 3] ΔPj ⁺ and ΔPj ⁻ that minimize

Here, σm in the equation (5) is the maximum of the real part of the eigenvalue i (closest to the most unstable) among all the assumed accident cases, and this is the case of step S3 in FIG. It can be obtained in the process of dynamic stability evaluation by the eigenvalue sensitivity analysis method. Further, ωj ⁺ and ωj ⁻ in the equation (6) are weighting factors in the increasing and decreasing directions of the output of the generator j, respectively. By appropriately setting these weighting factors, the generators (group: It is also possible to use multiple generators) as a result. That is, as follows, ωj ⁺ , ωj
^- By setting, it is possible to obtain a power margin of the generator (s) to be determined as a solution of the linear programming problem. (1) Setting of ωj ⁺ : Generator (group) for which output margin is desired
Set the weight of to a very small value compared to other generators. For example, the generator (group) whose output margin is desired is ωj
⁺ = 1 and other generators ωj ⁺ = 100. (2) .omega.j ^- Setting: (1) contrary to the very set to a larger value than power margin amount determined wish generator weights (s) to the other generators. For example, the output allowance look like the generator (s) .omega.j ⁺ = 100, other generator .omega.j ⁺ = 1
And

FIG. 3 shows the overall flow of the process of calculating the generator output margin by the linear programming method described above. That is, as shown in FIG. 3, in step S101, the target eigenvalue, for example, the most unstable eigenvalue is determined, and | σm
| Is calculated, and the weighting factors ωj ⁺ , ωj ⁻ are calculated so that the output margin of the corresponding generator (group) is obtained in step S102.
To set. In step S103, the eigenvalue sensitivity coefficient αij for the generator output is calculated. Step S10
4 is an adjustment amount ΔPj ⁺ of the generator for moving the target eigenvalue from stable to stable limit by applying linear programming based on the conditions formulated in the above equations (3) to (6). ΔP
This is a part for calculating j ⁻ . The ΔPj ⁺ calculated in step S104 is the output margin of the generator.

In this embodiment, if the steps S3 and S4 shown in FIG. 1 are configured as shown in FIGS. 2 and 3, respectively, the eigenvalue of the system with respect to a preset assumed disturbance (open line) can be set. Since changes can be grasped, efficient dynamic stability evaluation with fast calculation speed can be realized. Further, when all of the results of this evaluation are determined to be stable, the output margin of the corresponding generator with respect to the target eigenvalue can be uniquely determined by applying the linear programming method.

[0016]

As described above, according to the present invention, an efficient eigenvalue sensitivity analysis method is applied to the evaluation of dynamic stability against a large number of assumed disturbances, and it is determined that all assumed disturbances are stable there. If the output margin of the generator for the target eigenvalue is the sensitivity coefficient of the eigenvalue real part for the generator output, and the size of the eigenvalue real part obtained from the result of the dynamic stability evaluation, Since the output margin of the generator up to the stability limit is obtained as a solution of the linear programming method, it is possible to realize a high-speed calculation algorithm for monitoring the dynamic stability, which allows the estimated disturbance to be evaluated at high speed. When stable, it is possible to provide a method for monitoring the stability of the power system dynamics, which can calculate the output margin of the generator.

[Brief description of drawings]

FIG. 1 is an overall flowchart showing an embodiment for explaining a power system dynamic stability monitoring method according to the present invention.

FIG. 2 is a flowchart showing the specific contents of a dynamic stability evaluation part by the eigenvalue sensitivity analysis method in FIG.

FIG. 3 is a flowchart showing the specific content of a calculation portion of the output margin of the generator by the linear programming method in FIG.

[Explanation of symbols]

 S1 System state data collection S2 Assumed disturbance S3 Dynamic stability evaluation S4 Calculation of output margin of generator S5 Presentation to system operator

 ─────────────────────────────────────────────────── ─── Continuation of the front page (72) Kaoru Koyanagi No. 1 Toshiba-cho, Fuchu-shi, Tokyo Inside the Fuchu factory, Toshiba Corporation (72) Junichi Nagata 1-1-1, Shibaura, Minato-ku, Tokyo Toshiba Headquarters Co., Ltd. In the office

Claims (1)

[Claims] 1. A eigenvalue sensitivity of a system for evaluating dynamic stability in a power system dynamic stability monitoring method that evaluates the dynamic stability of the power system with respect to a preset assumed disturbance and performs necessary control in advance. When analysis is performed and all expected disturbances are evaluated as stable, the sensitivity coefficient of the eigenvalue real part to the generator output and the distance to the stability limit of the eigenvalue real part obtained from the results of the dynamic stability evaluation are data. The power system dynamic stability monitoring method is characterized by calculating the output margin of the generator as the stability margin by the linear programming method that is a part of the above, and presenting it to the operators of the power system.