Power system stabilization device and power system stabilization method

Abstract

To provide a power system stabilization device comprising a frequency stabilization control algorithm capable of calculating a controlled variable which is neither excessive nor deficient without grasping effective power for each inverter apparatus, and a power system stabilization method.SOLUTION: A power system stabilization device in a power system where a plurality of inverter apparatuses each using an inverter provided with an effective power control function is connected comprises a control target determination section which calculates a control target of the inverter apparatus, a stability computation section which executes a stability computation of the power system in a case where one or more kinds of system failures of a power source drop, a load drop or a system separation are estimated using data of the control target and system measurement information, and a control parameter characteristic formula calculation section which calculates a control parameter characteristic formula indicating a relation of a control parameter of a command value of effective power and an allowable drop amount based on a result of the stability computation section. The power system stabilization device also comprises an output section which outputs the control parameter characteristic formula.SELECTED DRAWING: Figure 1

Description

[Technical Field]

[0001] The present invention relates to a power system stabilization device and a power system stabilization method for maintaining the stability of a power system. [Background technology]

[0002] In order to decarbonize the power grid, the introduction of renewable energy sources (RES) such as solar power generation and wind power generation is expanding. As a result, the proportion of synchronous generators such as thermal power generation in the power grid is on a downward trend. In general, synchronous generators have the ability to maintain the frequency of the power grid by using their own rotational energy and inertia.

[0003] On the other hand, many renewable energy sources (RES) are inverter power sources (asynchronous power sources) that do not generate their own rotational force and therefore have a smaller inertia than synchronous generators. Therefore, if the proportion of synchronous generators decreases, there is a risk that frequency stability will decrease in emergencies such as when the power source goes out.

[0004] In response to these issues, in recent years, studies have been underway to equip renewable energy sources (RES) with a pseudo-inertial supply function. However, in order to ensure even greater adjustment capacity, it is also considered effective to equip demand-side inverters, such as those in electric vehicles (EVs) and home energy storage systems (BESS), which are expected to become more widespread in the future, with control functions that contribute to maintaining frequency stability.

[0005] As one example, Patent Document 1 aims to improve frequency stability by calculating and issuing commands to control the charging power of each electric vehicle (EV) and home storage battery (BESS) based on frequency measurement information. Specifically, the technology described calculates the total controllable charging power based on grid measurement information and the charging status of the electric vehicle (EV) and home storage battery (BESS), and calculates the charging power control amount based on frequency droop control and frequency measurement information to allocate it to each electric vehicle (EV) and home storage battery (BESS). [Prior art documents] [Patent documents]

[0006] [Patent Document 1] U.S. Patent Application Publication No. 2022 / 0340034 Summary of the Invention [Problem to be solved by the invention]

[0007] The frequency droop control in Patent Document 1 calculates a control amount of charging power proportional to the frequency deviation and rate of change of frequency (RoCoF) during a grid failure, and distributes this to the electric vehicles (EV) and home storage batteries (BESS) to be controlled, thereby maintaining frequency stability.

[0008] The control amount required to suppress frequency fluctuations varies not only depending on the amount of frequency fluctuation, but also on the power supply configuration at the time, the degree of system failure (such as the amount of power supply dropout), and whether or not frequency stabilization control is being performed by other equipment that is not the subject of control (such as a synchronous generator or a renewable energy power supply (RES)). When determining the required control amount using frequency droop control, it is important to adjust the proportional gain of the control (the gradient of the droop characteristics) taking into account the system conditions described above, but Patent Document 1 does not describe how to make this adjustment, so there is a possibility that the control amount may be excessive or insufficient.

[0009] Since system frequencies are generally maintained within a target range of around 50Hz / 60Hz, if there is an excess or deficiency in the control amount in response to frequency fluctuations, this can cause the system frequency to deviate from the target range, which is undesirable from an operational standpoint.

[0010] Therefore, a method is required that can adjust the control amount taking into account the power source configuration, the degree of system failure, and frequency stabilization control by non-controlled objects, so that there is no excess or deficiency in the active power control amount of electric vehicles (EVs) and home storage batteries (BESSs).

[0011] In addition, because there are countless demand-side devices, such as electric vehicles (EV) and home storage batteries (BESS), it is thought to be difficult for power system operators to grasp the status of each device, such as the active power, and calculate individual control variables.

[0012] Therefore, a method is required that can calculate an appropriate control amount without knowing the active power of each device.

[0013] In view of the above, the problem to be solved by the present invention is to provide a power system stabilization device and a power system stabilization method equipped with a frequency stabilization control algorithm that can calculate a control amount that is neither excessive nor insufficient, without knowing the active power of each inverter device. [Means for solving the problem]

[0014] In view of the above, the present invention provides "a power system stabilization device for a power system in which a plurality of inverter devices using inverters with an active power control function are connected, the power system stabilization device comprising: a control object determination unit that determines a control object of the inverter device; a stability calculation unit that performs stability calculations for the power system when one or more types of system failure, either power source dropout, load dropout, or system isolation, are assumed using data on the control object and system measurement information; and a control parameter characteristic equation calculation unit that determines a control parameter characteristic equation that expresses the relationship between a control parameter of an active power command value and an allowable dropout amount, based on the result of the stability calculation unit, and an output unit that outputs the control parameter characteristic equation."

[0015] Furthermore, the present invention provides "a power system stabilization device for a power system in which a plurality of inverter devices using inverters having an active power control function are connected, the power system stabilization device comprising: a control object determination unit that determines a control object of the inverter device; a stability calculation unit that performs stability calculations for the power system when one or more types of system failures of power source dropout, load dropout, or system isolation are assumed using data of the control object and system measurement information; a central processing unit that performs processing before the occurrence of a system failure, the central processing unit comprising: a control parameter characteristic equation calculation unit that determines a control parameter characteristic equation that expresses the relationship between a control parameter of a command value of active power and an allowable dropout amount based on the result of the stability calculation unit; a supply and demand imbalance estimation unit that estimates the amount of imbalance that will occur in power supply and demand due to the system failure; a control parameter determination unit that determines control parameters for the inverter device based on the estimated result of the imbalance amount and the control parameter characteristic equation; and a transmission unit that reflects the control parameters in the active power command value of the control object of the inverter device, the local processing unit that performs processing after the occurrence of a system failure."

[0016] Furthermore, the present invention provides "a power system stabilization method using a computer for maintaining frequency stability of a power system by using inverter equipment that uses an inverter with an active power control function, the power system stabilization method comprising the steps of: a control object determination step for determining a control object of the inverter equipment; a stability calculation step for performing stability calculations of the power system assuming one or more types of system failure, either power source dropout, load dropout, or system isolation, using data on the control object and system measurement information; a control parameter characteristic equation calculation step for determining a control parameter characteristic equation that expresses the relationship between a control parameter of an active power command value and an allowable dropout amount, based on the result of the stability calculation step; and an output step for outputting the results of each step."

[0017] Furthermore, the present invention provides a "power system stabilization method using a computer for maintaining frequency stability of a power system by using inverter equipment that uses an inverter having an active power control function, the method comprising the steps of: determining a control target of the inverter equipment; using data on the control target and system measurement information, performing stability calculations for the power system assuming one or more types of system failure of power source dropout, load dropout, or system isolation; performing processing to determine a control parameter characteristic equation that expresses the relationship between a control parameter of an active power command value and an allowable dropout amount based on the result of the stability calculations before the system failure occurs; estimating the amount of imbalance in power supply and demand that will occur due to the system failure; determining control parameters for the inverter equipment based on the estimated result of the imbalance amount and the control parameter characteristic equation; and performing processing to reflect the control parameters in the active power command value of the control target of the inverter equipment after the system failure occurs." [Effects of the Invention]

[0018] According to the present invention, it is possible to calculate the control amount required to maintain frequency stability without knowing the active power of each inverter device. [Brief explanation of the drawings]

[0019] [Figure 1] 1 is a diagram showing an example of the functional configuration of a power system stabilization device according to a first embodiment of the present invention; [Figure 2] 1 is a diagram showing an example of the hardware configuration of a power system stabilization device and an example of the power system configuration according to a first embodiment of the present invention; [Figure 3] FIG. 2 is a diagram showing an example of the configuration of a program held in a program database. [Figure 4] FIG. 2 is a diagram showing an example of the data structure of system configuration data D11. [Figure 5] FIG. 10 is a diagram showing an example of the data structure of system measurement value data D12. [Figure 6] FIG. 10 is a diagram showing an example of the data structure of frequency maintenance target data D13. [Figure 7] FIG. 10 is a diagram showing an example of the data structure of system model data D14. [Figure 8] FIG. 10 is a diagram showing an example of the data structure of contingent fault list data D15. [Figure 9] FIG. 10 is a diagram showing an example of the data structure of control target data D41. [Figure 10] FIG. 10 is a diagram showing an example of the data structure of control parameter pattern data D16. [Figure 11] FIG. 3 is a diagram showing an example of processing contents of a pre-calculation unit 20. [Figure 12] FIG. 10 is a diagram showing an image of a control parameter characteristic formula. [Figure 13] FIG. 10 is a diagram for theoretically explaining why the control parameter characteristic equation has the shape of a linear function. [Figure 14] FIG. 10 is a diagram showing an example of the data structure of inverter operation status data D31. [Figure 15] FIG. 10 is a diagram showing an example of a data structure of fault detection threshold data. [Figure 16] FIG. 4 is a diagram showing an example of a data structure of frequency measurement data. [Figure 17] FIG. 4 is a diagram showing an example of a data structure of synchronous machine data. [Figure 18] FIG. 4 is a diagram showing an example of a data structure of control parameter characteristic equation data. [Figure 19] FIG. 10 is a diagram showing the overall flow of a post-calculation unit 40b. [Figure 20] FIG. 4 is a diagram showing an example of a result display on the display unit 6. [Figure 21A] FIG. 10 is a diagram showing an example of response before application of control parameters according to the present invention. [Figure 21B] FIG. 10 is a diagram showing an example of response after applying control parameters according to the present invention. [Figure 22] FIG. 10 is a diagram showing an example of the functional configuration of a power system stabilizing device according to a second embodiment of the present invention. [Figure 23] FIG. 10 is a diagram showing an example of the data structure of non-control target data. DETAILED DESCRIPTION OF THE INVENTION

[0020] Hereinafter, an embodiment of the present invention will be described with reference to the drawings. In this invention, "stability" and "stability" are explained as synonyms. Furthermore, "synchronous machine" and "RES" are used as abbreviations for "synchronous generator" and "renewable energy power source," respectively. "Inverter equipment" is used as a general term for equipment that uses inverters with active power control functions, such as electric vehicles, storage batteries, renewable energy power sources, and heat pumps. [Example]

[0021] First, an example of the functional configuration of a power system stabilizing device 1 according to a first embodiment of the present invention will be described with reference to FIG.

[0022] The power system stabilization device 1 is composed of a central processing unit 2 that performs pre-calculation before a power system failure occurs, a local control unit 4 that creates input data necessary for the pre-calculation by the central processing unit 2 and executes control in the event of a failure using the results of the pre-calculation by the central processing unit 2, a communication unit 3 that handles information communication between the central processing unit 2 and the local control unit 4, and a display unit 6 that displays input / output data of the central processing unit 2 and the local control unit 4.

[0023] The central processing unit 2 is composed of a pre-computation input database DB1 that holds pre-computation input data D1 held by a power system operator or planner, a pre-computation unit 20 that performs pre-computation based on the pre-computation input data D1, and a pre-computation output database DB2 that holds pre-computation output data D2 in which the calculation results of the pre-computation unit 20 are stored.

[0024] The pre-calculation input database DB1 holding the pre-calculation input data D1 is composed of a system configuration database DB11 holding system configuration data D11, a system measurement value database DB12 holding system measurement value data D12, a frequency maintenance target database DB13 holding frequency maintenance target data D13, a system model database DB14 holding system model data D14, a contingency fault list database DB15 holding contingency fault list data D15, a control object database DB41 holding control object data D41, and a control parameter pattern database DB16 holding control parameter pattern data D16.

[0025] The pre-calculation unit 20 comprises the processing functions of an analytical cross section creation unit 21, a stability calculation unit 22, a stability evaluation unit 23, and a control parameter characteristic equation calculation unit 24, and executes processing in this order.

[0026] The pre-calculation output database DB2 that holds the pre-calculation output data D2 is composed of an analysis cross section database DB21 that holds analysis cross section data D21, a stability calculation result database DB22 that holds stability calculation result data D22, a stability evaluation result database DB23 that holds stability evaluation result data D23, and a control parameter characteristic equation database DB24 that holds control parameter characteristic equation data D24.

[0027] The local control device 4 is composed of a local calculation input database DB3 that holds local calculation input data D3 including pre-calculation results from the central processing unit 2 and data acquired from the power system during normal operation or after a fault occurs; a pre-calculation input data creation unit 40a that creates pre-calculation input data D1 for the central processing unit 2 based on inverter operating status data D31 in the local calculation input data D3; a post-calculation unit 40b that performs post-calculation based on data in the local calculation input data D3 (fault detection threshold data D32, frequency measurement data D33, synchronous machine data D34); a local calculation output database DB4 that stores local calculation output data D4 that is the output of the pre-calculation input data creation unit 40a and the post-calculation unit 40b; and a transmission unit 5 that transmits a control parameter change command to the control target determined by the pre-calculation input data creation unit 40a.

[0028] The local calculation input database DB3 is composed of an inverter operation status database DB31 that holds inverter operation status data D31, a fault detection threshold database DB32 that holds fault detection threshold data D32, a frequency measurement database DB33 that holds frequency measurement data D33, a synchronous machine database DB34 that holds synchronous machine data D34, and a control parameter characteristic equation database DB24 received from the central processing unit 2 via the communication unit 3.

[0029] The pre-calculation input data creation unit 40a is composed of a control target determination unit 41. The post-calculation unit 40b is composed of the processing functions of a fault detection unit 42, a supply and demand imbalance estimation unit 43, and a control parameter determination unit 44, and executes processing in this order.

[0030] The local calculation output database DB4 is composed of a control object database DB41 that holds control object data D41, a fault detection result database DB42 that holds fault detection result data D42, a supply and demand imbalance estimated quantity database DB43 that holds supply and demand imbalance estimated quantity data D43, and a control parameter database DB44 that holds control parameter data D44.

[0031] Fig. 2 shows an example of the hardware configuration of the power system stabilization device 1 and an example of the power system configuration of the first embodiment. The upper part of Fig. 2 shows an example of the hardware configuration of the power system stabilization device 1, and the lower part shows an example of the configuration of the power system 100 that is the control target thereof, and a communication network 200 that handles information communication between the power system stabilization device 1 and the power system 100.

[0032] The power system stabilization device 1 is composed of various input / output databases (DB11 to DB16, DB21 to DB24, DB31 to DB34, DB41 to DB44), a program database DB5, a communication unit 3, a control unit 5, a display unit 6, an input unit 7, a processor 8, a memory 9, and a bus line 10 connecting these.

[0033] The programs held in the program database DB5 are shown in Figure 3. The program database DB5 consists of an analytical cross-section creation program Pr1, a stability calculation program Pr2, a stability evaluation program Pr3, a control parameter characteristic equation calculation program Pr4, a fault detection program Pr5, a control target determination program Pr6, a supply-demand imbalance estimation program Pr7, and a control parameter determination program Pr8.

[0034] Returning to FIG. 2, the communication unit 3 exchanges data with the power system 100 via the communication network 200.

[0035] The transmitter 5 transmits the control parameter data D44 created by the local control device 4 via the communication network 200 to the inverter device to be controlled.

[0036] The display unit 6 is configured by, for example, any one or more of a display device, a printer device, a projector device, an audio output device, etc. The display unit 6 displays any one or more of various input / output data (D11 to D16, D21 to D24, D31 to D34, D41 to D44) on a screen. Examples of the screen to be displayed will be described later.

[0037] The input unit 7 is configured with, for example, one or more of a keyboard, a switch, a mouse, a touch panel, a voice input device, and the like.

[0038] The processor 8 reads a program Pr necessary for processing by the calculation unit 2 from the various programs Pr in Fig. 3 that make up the program database DB5, and executes calculations. The processor may be configured with one or more semiconductor chips, or may be configured with a computer or calculator.

[0039] The memory 9 is configured by a storage device such as a RAM (Random Access Memory), and stores the program Pr read from the program database DB5, various input / output data (D11 to D16, D21 to D24, D31 to D34, D41 to D44), and the like.

[0040] An example power system 100 shown in the lower part of FIG. 2 is composed of generators 110a-110b such as synchronous machines or renewable energy power sources, nodes (busbars) 120a-120c and 121a-121d, transformers 130a-130c, branches (lines) 140a-140d, inverter devices 150a-150c such as electric vehicles and storage batteries, and their control terminals 151a-151c.

[0041] The power system 100 also includes a measurement device 30. The measurement device 30 is connected to the power system stabilization device 1 via a communication network 200.

[0042] The measuring device 30 acquires one or more of the following as system measurement value data D12: the output of the generators 110a to 110b, the voltage values ​​at each of the nodes 120a to 120c and 121a to 121d, information such as the values ​​of active power and reactive power flowing through the transformers 130a to 130c and branches 140a to 140d, and information on the on / off status of circuit breakers at the nodes, transformers, branches, and phase modifying equipment; and acquires frequency measurement values ​​at each of the nodes 120a to 120c and 121a to 121d as frequency measurement data D33 and transmits them to the communication unit 3.

[0043] The power system stabilizing device 1 can periodically acquire the system measurement value data D12 and the frequency measurement data D33 from the measurement device 30 via the communication network 200 and store them in various databases.

[0044] In addition, the communication network 200 transmits inverter operating status data D31 acquired from the inverter devices 150a to 150c and their control terminals 151a to 151c to the communication unit 3, and also transmits control parameter data D44 transmitted from the transmission unit 5 in the event of a system failure to the control terminals 151a to 151c.

[0045] The power system stabilization device 1 of the present invention having the hardware and software configuration shown in Figures 1, 2 and 3 basically determines the control parameter formula D24 for inverter devices in the power system by pre-calculation processing, and in post-calculation processing when a power system accident occurs, provides the control parameter D44 determined from the control parameter formula D24 to the inverter devices and controls them, thereby stabilizing the power system.

[0046] Here, an example of the control parameter D44 that is ultimately given from the local control device 4 will be explained to clarify the concept.

[0047] In the power system stabilization device 1 of the present invention, the active power command value P ref is controlled based on equation (1) or (2). ref0 is the normal active power command value [pu], β is the control parameter [%pu / Hz], and Δf is the local frequency deviation [Hz].

[0048]

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[0049]

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[0050] Equation (1) applies to inverter equipment that consumes active power, such as electric vehicles (EV) that are charging and home storage batteries, while equation (2) applies to inverter equipment that outputs active power, such as renewable energy power sources (RES), electric vehicles (EV) that are discharging, and home storage batteries (BESS).

[0051] The method of controlling the active power to a value proportional to the frequency deviation Δf, as in equations (1) and (2), is generally called frequency droop control, and the control parameter β corresponds to the gain of the frequency droop control.

[0052] In this way, in the present invention, the control parameter β is calculated by the local control device 4, and the inverter device side controls and operates the inverter device in accordance with equations (1) and (2). A specific method for deriving the control parameter β will be explained below, but here, we will explain in order the data to be used and the data calculated by the pre-calculation side, and the data to be used and the data calculated by the post-calculation side.

[0053] First, the pre-computation side in the central processing unit 2 will be explained. The pre-computation input data D1 used here is as follows. First, Fig. 4 shows an example of system configuration data D11 held in the system configuration database DB11. In the configuration example of the system configuration database DB11 in Fig. 4, as shown vertically, in addition to information about the branches (lines) and synchronous generators that make up the power system, power system component devices such as loads, renewable energy power sources, transformers, and phase modifying equipment are listed.

[0054] Furthermore, information about these devices is written and stored horizontally in Figure 4. The data that should be held for these devices is the transmission line number, number of lines, node numbers at both ends, resistance, reactance, etc. in the case of branches, and the synchronous generator number, interconnected node, number of parallel units, rated capacity, rated output, reactance, etc. in the case of the same equipment. In the case of loads, renewable energy sources, transformers, phase modifying equipment, etc., appropriate information will also be held.

[0055] 5 shows an example of system measurement data D12 held in the system measurement database DB12. The system measurement database DB12 stores so-called system measurement values, which are acquired via the communication network 200, including one or more of the output of generators 110a-110c of the power system 100, voltage values ​​at each of the nodes 120a-120c and 121a-121c, values ​​of active power and reactive power flowing through transformers 130a-130c and branches 140a-140c, and on / off information of circuit breakers at nodes, transformers, branches, and phase modifying equipment. This information is stored in chronological order for each measurement location (measurement point) linked to timestamp information indicating the date and time of measurement.

[0056] 6 shows an example of frequency maintenance target data D14 stored in the frequency maintenance target database DB13. The frequency maintenance target database DB13 stores the target range of the frequency (49.0-50.5 Hz in the illustrated example) to be maintained by the power system stabilization device 1 through control of the inverter devices in chronological order, linked to timestamp information of the measurement date and time. The target value of the frequency is set by the operator of the power system, for example, as the minimum value of the system frequency in the event of a power system failure.

[0057] 7 shows an example of the system model data D14 held in the system model database DB14. The system model database DB14 stores information such as synchronous generators (SG1-SG3), inverter devices (IBR1-IBR3), and model types related to load models that are required for numerical analysis of power systems using computers or calculators, as well as information on constants used therein.

[0058] 8 shows an example of the contingent fault list data D15 held in the contingent fault list database DB15. The contingent fault list database DB15 stores information such as the name and type of contingent fault in the power system (power supply tripping and system isolation are shown as examples in the illustrated example, but load drop should also be considered), the location of the fault, and the amount of imbalance in power supply and demand caused by the fault. The amount of imbalance in power supply and demand indicates, for example, the amount of power drop in the case of a power supply tripping fault.

[0059] 9 shows an example of the control target data D41 held in the control target database DB41. In the control target database DB41, information such as the name, connection area, initial active power, and controllable amount of the control target determined by the pre-calculation input data creation unit 40a of the local control device 4 is stored in chronological order, linked to timestamp information of the measurement date and time.

[0060] 10 shows an example of control parameter pattern data D16 held in the control parameter pattern database DB16. The control parameter pattern database DB16 stores patterns of control parameters β of inverter devices used in the stability calculation unit 22 of the pre-calculation unit 20.

[0061] Specific examples of the pre-computation input data D1 in Fig. 1 have been described above using Fig. 4 to Fig. 10. Next, the processing performed by the pre-computation unit 20 using the pre-computation input data D1 will be described.

[0062] The processing contents of the pre-calculation unit 20 will be described with reference to Fig. 11. Fig. 11 shows the overall flow of processing by the central processing unit 2 in the first embodiment. This processing is executed periodically when the power system 100 is in normal operation. The flow of the calculation processing will be described for each processing step.

[0063] First, in processing step S21, the analytical cross section creation program Pr1 is executed using the system configuration data D11 and the system measurement value data D12 to create analytical cross section data D21 of the power system 100 at the current time. The analytical cross section data D21 is stored in the analytical cross section database DB21.

[0064] Next, in processing step S22, one or more contingency faults to be used for stability calculation in processing step S24, which will be described later, are selected from the contingency fault list data D15.

[0065] Next, in process step S23, one or more control parameters are selected from the control parameter pattern data D16 as targets for stability calculation in process step S24, which will be described later.

[0066] Next, in processing step S24, the stability calculation program Pr2 is executed using the frequency maintenance target data D13, the system model data D14, the control object data D41, and the analysis section data D21 to calculate frequency stability under the conditions of the contingency fault and control parameters selected in processing steps S22 to S23. As an example of the calculation method, a time domain simulation that simulates the temporal response of the power system in the event of a fault is used. The simulation results are output as stability calculation result data D22. The stability calculation result data D22 is stored in a stability calculation result database DB22.

[0067] Next, in processing step S25, the stability evaluation program Pr3 is executed using the stability calculation result data D22 to evaluate the frequency stability for each contingency fault and each control parameter. As an example of the evaluation method, it is confirmed whether the rotation speed of each synchronous machine or its center of inertia is within the frequency maintenance target range specified in the frequency maintenance target data D13, and if it is within the range, it is judged as stable, and if it is outside the range, it is judged as unstable. The evaluation result is output as stability evaluation result data D23. The stability evaluation result data D23 is stored in a stability evaluation result database DB23.

[0068] Next, in process step S26, it is determined whether all control parameters have been selected in process step S23. If all have been selected ("YES" in process step S26), the process proceeds to process step S27, which will be described later. If any control parameters have not been selected ("NO" in process step S26), the process returns to process step S23.

[0069] Next, in process step S27, it is determined whether all contingency faults have been selected in process step S22. If all have been selected ("YES" in process step S27), the process proceeds to process step S28, which will be described later. If any contingency faults have not been selected ("NO" in process step S27), the process returns to process step S22.

[0070] Next, in processing step S28, the stability evaluation result data D23 is used to calculate the allowable drop amount for each control parameter. Here, when the contingency failure is, for example, a power source drop or load drop, the allowable drop amount refers to the maximum drop amount that can maintain the system frequency within the target range. In addition, in the case of a system isolation failure, the system on the frequency drop side exhibits a similar response to the system at the time of a power source drop, and the system on the frequency increase side exhibits a similar response to the system at the time of a load drop. Therefore, the maximum drop amount that can maintain the system frequency within the target range is calculated for each of the frequency drop side and the frequency increase side. As an example of calculating the allowable drop amount, the maximum amount of supply and demand imbalance that occurs among the contingency failures determined to be stable in processing step S25 is calculated as the allowable drop amount.

[0071] Next, in process step S29, the control parameter characteristic equation calculation program Pr4 is executed using the control parameters calculated in process step S28 and the two-dimensional data of the allowable dropout amount, and the control parameter characteristic equation is derived. The derived result is output as control parameter characteristic equation data D24.

[0072] The control parameter characteristic equation data D24 is stored in the control parameter characteristic equation database DB24, and is also stored as part of the local calculation input data D3 in the local calculation input database DB3 of the local control device via the communication unit 3. Here, since the control parameter characteristic equation data D24 is used by the local control device 4, the data structure thereof will be described later in the local calculation input database DB3 with reference to FIG.

[0073] The specific methods of the above-mentioned creation processing (analysis cross section creation, stability calculation, stability evaluation, control parameter characteristic equation) in the pre-calculation unit 20 are well known to those skilled in the art, and any of them may be adopted in the present invention, so detailed explanation will be omitted here.

[0074] An image of the control parameter characteristic formula is shown in Figure 12. The graph in Figure 12 plots the control parameter β on the horizontal axis and the allowable drop amount on the vertical axis. Since the control parameter β and the allowable drop amount are roughly proportional to each other, the approximate straight line created from these two-dimensional data can be used as the control parameter characteristic formula.

[0075] Here, the reason why the control parameter β and the allowable dropout amount are roughly proportional will be theoretically explained using the simplified system diagram in Figure 13. In the system in Figure 13, synchronous machines G1 and G2 are connected via a transformer and a transmission line, and a large-scale renewable energy power source RES is connected near synchronous machine G1. In addition, photovoltaic power generation (PV), electric vehicles (EV), and a home storage battery (BESS), which are to be controlled, are connected to a lower system near the large-scale renewable energy power source RES.

[0076] Consider the system frequency f (= frequency of synchronous machine G1) when synchronous machine G2 trips in the system shown in Figure 13. The oscillation equation for synchronous machine G1 is expressed by equation (3). In equation (3), Δf is the rotational speed deviation of synchronous machine G1 (≒ system frequency deviation) [pu], Pm is the mechanical input power [pu] of synchronous machine G1, Pe is the electrical output power [pu] of synchronous machine G1, M is the inertia constant, and D is the damping coefficient.

[0077]

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[0078] Here, the time when the frequency is lowest (df / dt) is t nadir Then, equation (3) can be transformed into equation (4).

[0079]

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[0080] The electrical output Pe of the synchronous machine G1 reflects both the increase in output due to the tripping of the synchronous machine G2 and the frequency control of the renewable energy power source RES, electric vehicle EV, home storage battery BESS, etc., so we consider the approximate formula shown in equation (5). Here, P drop is the amount of power loss [pu], K FD (=β / 100) is the droop control gain [pu / Hz], ΔP other (t nadir ) is the active power control amount [pu] of the non-controlled target at the time of the minimum frequency.

[0081]

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[0082] Substituting equation (5) into equation (4), Δf(t nadir ) is solved to obtain equation (6).

[0083]

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[0084] The target value of the system frequency deviation is Δf thld Then, in order to maintain the minimum frequency value within the target range, it is necessary to satisfy equation (7).

[0085]

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[0086] By transforming equation (7), we obtain equation (8).

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number

[0088] where P drop_max is the allowable power supply dropout amount. From equation (8), the allowable power supply dropout amount P drop_max is the droop control gain K FD (=β / 100) and is proportional to each other.

[0089] The above explanation shows an example of a power supply dropout failure, but in the case of load dropout or system separation, the power supply dropout amount P drop This can be explained in a similar way by replacing it with the amount of load drop or the amount of supply-demand imbalance caused by system separation.

[0090] Based on the above background explanation, in the above explanation, the control parameter characteristic equation D24 is calculated by pre-calculation in the central processing unit 2 in Fig. 1. In response to this, the local control unit 4 finally calculates the control parameter D44.

[0091] For this purpose, the local control device 4 comprises a local calculation input database DB3, a pre-calculation data creating section 40a, a post-calculation section 40b, and a local calculation output database DB4.

[0092] First, the local calculation input database DB3 includes the following databases (DB31-DB34) in addition to the control parameter characteristic equation database DB24 that stores the control parameter characteristic equation D24 created in advance.

[0093] 14 shows an example of inverter operation status data D31 stored in the inverter operation status database DB31. In the inverter operation status database DB31, information such as the name, installed capacity, active power, and available adjustment capacity of each inverter device acquired by the local control device 4 is stored in chronological order, linked to timestamp information of the measurement date and time.

[0094] 15 shows an example of the fault detection threshold data D32 held in the fault detection threshold database DB32. The fault detection threshold database DB32 stores information such as fault detection methods (indexes such as frequency deviation and RoCoF) and thresholds for each method.

[0095] 16 shows an example of frequency measurement data D33 held in the frequency measurement database DB33. In the frequency measurement database DB33, frequency information of each measurement point acquired by the local control device 4 is linked to timestamp information of the measurement date and time and stored in chronological order.

[0096] 17 shows an example of synchronous machine data D34 held in the synchronous machine database DB34. In the synchronous machine database DB34, information such as the name, rated capacity, inertia constant, and active power output of each synchronous machine in the power system 100 is stored in chronological order, linked to timestamp information of the measurement date and time.

[0097] 18 shows an example of the control parameter characteristic equation data D24 held in the control parameter characteristic equation database DB24. In the control parameter characteristic equation database DB24, information on constants such as slopes and intercepts in control parameter characteristic equations that are approximated to linear functions is stored in chronological order, linked to timestamp information of the measurement date and time.

[0098] 1, the processing contents of the control object determination unit 41 in the pre-calculation input data creation unit 40a will be described. The control object determination unit 41 extracts inverter devices that are connected to the power system 100 and have adjustable capacity that can be used by the power system stabilization device 1 using the inverter operation status data D31 in Fig. 14 and the control object determination program Pr5, and determines them as control objects. The extracted inverter devices to be controlled are stored in a control object database DB41 as control object data D41.

[0099] Next, the processing content of the post-calculation unit 40b will be described with reference to Fig. 19. Fig. 19 shows the overall flow of the processing of the post-calculation unit 40b in the first embodiment. This processing is executed when the power system 100 is in normal operation. The flow of the calculation processing will be described for each processing step.

[0100] First, in processing step S42a, the RoCoF is calculated using the frequency measurement data D33. Subsequently, in processing step S42b, the fault detection program Pr6 is executed using the frequency measurement data D33, the RoCoF calculated in processing step S42a, and the fault detection threshold data D32 to determine whether or not a fault has occurred. The processing up to this point is the processing content of the fault detection unit 42 in FIG. 1. As a result, if there is a fault ("YES" in S42b), the process proceeds to processing step S43 described below, and if there is no fault ("NO" in S42b), this processing flow ends. The determination result of whether or not there is a fault is output as fault detection result data D42.

[0101] Next, in processing step S43, the supply and demand imbalance estimation program Pr7 is executed using the RoCoF calculated in processing step S42a and the synchronous machine data D34 to estimate the amount of supply and demand imbalance caused by the failure. For example, in the case of a power supply disconnection failure, the imbalance amount (= amount of power supply disconnection) is estimated using equation (9). The estimation result is output as supply and demand imbalance estimated amount data D43 and stored in the supply and demand imbalance estimated amount database DB43.

[0102]

number

[0103] where ΔP loss is the estimated shedding amount [MW], P total is the total output of the synchronous machine [MW], RoCoF is the inverter device's own terminal RoCoF [Hz / s], F0 is the reference frequency [Hz], MVA rate is the ratio of the total capacity to the total output of the synchronous machine [MVA / MW], M avg is the average inertia constant of the synchronous machine [s].

[0104] Next, in processing step S44, the control parameter determination program Pr8 is executed using the control parameter characteristic equation data D24 and the supply and demand imbalance estimated amount data D43 to determine common control parameters to be instructed to all controlled objects. The control parameters are determined to be values ​​obtained by substituting the supply and demand imbalance estimated amount for the allowable dropout amount term in the control parameter characteristic equation. The processing results are output as determined data for the control parameters D44 and stored in the control parameter database DB44.

[0105] The determined control parameters D44 are transmitted to all inverter devices selected as control targets via the transmitter 5 in FIG. 1, and the inverter devices that receive them perform active power control according to equations (1) and (2).

[0106] As described above, by obtaining a common control parameter for all devices that is used to control the active power command value, rather than the active power control amount for each individual inverter device, it is possible for the power system operator to set the control amount required to maintain frequency stability without having to grasp the state of each device.

[0107] Next, an example of the results displayed by the display unit 6 will be described with reference to FIG. 20. In the "Search Settings" field on the display screen of FIG. 20, the date and time for which the calculation results are to be displayed are set. In the "Power System Diagram" field of FIG. 20, the positions of the inverter devices to be controlled are displayed on the system diagram based on the control object data D41, and the total amount of active power of the controlled object is also shown. In addition, the locations of anticipated faults may also be displayed on the system diagram. In the "Calculation Results" field of FIG. 20, for example, the control parameter characteristic equations found by the pre-calculation unit 20 are displayed in graph form. In addition, the effect of improving frequency stability by changing the control parameters may also be displayed.

[0108] Figures 21A and 21B show the effect of the present invention on the frequency stability of a power system. Figures 21A and 21B show the difference in the time fluctuation of the system frequency before and after changing the control parameters, with the target frequency maintenance range set to 49.0 to 50.5 Hz.

[0109] Before the control parameters were changed (Fig. 21A), the effect of increasing the frequency was excessive, causing it to deviate from the upper limit of the target range, which was 50.5 Hz. In contrast, after the control parameters were changed (Fig. 21B), minimal control was achieved so that the frequency did not deviate from the target range, making it possible to keep the grid frequency stable while minimizing interference with the charging and discharging of electric vehicles (EVs), home storage batteries (BESSs), and other devices. [Example]

[0110] The pre-calculation unit 20 in the power system stabilizing device 1 of the first embodiment derives a control parameter characteristic equation for each period by calculating the frequency stability on a simulation basis for each of the contingency faults recorded in the contingency fault list data D15 and the control parameters recorded in the control parameter pattern data D16. Therefore, when the number of combinations of contingency faults and control parameters is enormous, it is expected that a large calculation load will be required.

[0111] Therefore, the power system stabilizing device 1 of the second embodiment addresses the above-mentioned problem of the computation load by deriving the control parameter characteristic equation based on the theoretical equation shown in equation (8) rather than on a simulation basis.

[0112] 22 shows an example of the functional configuration of a power system stabilizing device 1 according to a second embodiment of the present invention. The differences in configuration between the first embodiment and the second embodiment are that a non-controlled object database DB17 is newly added to the pre-calculation input database DB1, and that the analytical cross section creation unit 21, the stability calculation unit 22, the stability evaluation unit 23, and the input / output data associated with them are omitted from the pre-calculation unit 20. The configuration of the local control device 4 is unchanged between the first embodiment and the second embodiment, so the notation is simplified.

[0113] The pre-calculation input database DB11 of the second embodiment stores various constant data in the equation (8). Specifically, the frequency maintenance target database DB13 stores the target value Δf of the system frequency deviation. thld The system model database DB14 stores the damping coefficient D of the synchronous machine. As will be described later, the non-control object data D17 stores the active power control amount ΔP of the non-control object at the time of the minimum frequency. other (t nadir ) is stored.

[0114] 23 shows an example of non-control object data D17 held in the non-control object database DB17. The non-control object database DB17 stores data relating to the failure record in the power system 100 and the control amount record of the non-control object power source at the time of the failure. If the control amount record data is insufficient, control amount data calculated by offline simulation may be stored and used to derive the control parameter characteristic equation.

[0115] By deriving the control parameter characteristic equation using the second embodiment, the accuracy is lower than that of the characteristic equation of the first embodiment derived on a simulation basis, but the calculation load involved in the derivation can be significantly reduced.

[0116] The present invention is not limited to the above-described embodiments and includes various modifications. For example, the above-described embodiments have been described in detail to clearly explain the present invention, and are not necessarily limited to those including all of the described configurations. Furthermore, it is possible to replace part of the configuration of one embodiment with the configuration of another embodiment, or to add the configuration of another embodiment to the configuration of one embodiment. Furthermore, it is possible to add, delete, or replace part of the configuration of each embodiment with other configurations. Furthermore, part or all of the above-described configurations, functions, processing units, etc. may be realized in hardware, for example, by designing them as integrated circuits. [Explanation of symbols]

[0117] 1: Power system stabilizer 2: Central processing unit 3: Communications Department 4: Local control device 5: Transmitter 6: Display section 7: Input section 8: Processor 9: Memory 10: Bus line 20: Pre-calculation section 21:Analysis section creation part 22:Stability calculation part 23: Stability evaluation section 24: Control parameter characteristic equation calculation section 40a: Pre-calculation input data creation unit 40b: Post-operation section 41: Control target determination unit 42: Fault detection unit 43: Supply and demand imbalance estimation part 44: Control parameter determination unit 30: Measuring equipment 100: Power system 110a-110b: Synchronous machines and renewable energy power sources 120a~120c, 121a~121d: Node (bus line) 130a~130c: Transformers 140a~140d: Branch (railway) 150a~150c: Inverter equipment 151a to 151c: inverter device control terminal 200: Communication Network D1: Pre-calculated input data D2: Pre-calculated output data D3: Local calculation input data D4: Local calculation output data DB1: Pre-computed input database DB2: Pre-computed output database DB3: Local calculation input database DB4: Local calculation output database D11: System configuration data DB11: System configuration database D12: System measurement data DB12: System measurement data database D13: Frequency maintenance target data DB13: Frequency Maintenance Target Database D14: System model data DB14: System model database D15: List of expected failures DB15: Contingency list database D16: Control parameter pattern data DB16: Control parameter pattern database D17: Uncontrolled Data DB17: Uncontrolled database D21: Analysis cross-sectional data DB21: Analysis cross section database D22: Stability calculation result data DB22: Stability calculation results database D23: Stability evaluation result data DB23: Stability evaluation results database D24: Control parameter characteristic formula data DB24: Control parameter characteristic formula database D31: Inverter operation status data DB31: Inverter operation status database D32: Fault detection threshold data DB32: Fault detection threshold database D33: Frequency measurement data DB33: Frequency measurement database D34: Synchronous machine data DB34: Synchronous Machine Database D41: Controlled data DB41: Controlled database D42: Fault detection result data DB42: Fault detection result database D43: Supply and demand imbalance estimate data DB43: Database of supply and demand imbalance estimates D44: Control parameter data DB44: Control parameter database DB50: Program Database Pr1: Analysis cross section creation program Pr2: Stability calculation program Pr3: Stability evaluation program Pr4: Control parameter characteristic formula calculation program Pr5: Control target determination program Pr6: Fault detection program Pr7: Supply and demand imbalance estimation program Pr8: Control parameter determination program

Claims

1. A power system stabilization device in a power system to which a plurality of inverter devices using inverters having an active power control function are connected, a stability calculation unit that uses data on the control object and system measurement information to perform stability calculations on the power system when one or more types of system failure, either power source dropout, load dropout, or system isolation, are assumed; and a control parameter characteristic equation calculation unit that determines a control parameter characteristic equation that expresses the relationship between a control parameter of an active power command value and an allowable dropout amount, based on a result of the stability calculation unit, and an output unit that outputs the control parameter characteristic equation.

2. 2. The power system stabilization device according to claim 1, A power system stabilization device comprising a fault detection unit that detects the occurrence of a system fault based on frequency measurement data.

3. 2. The power system stabilization device according to claim 1, The power system stabilization device further comprises a supply and demand imbalance estimation unit that estimates the amount of imbalance in power supply and demand that occurs due to the system failure.

4. 4. The power system stabilization device according to claim 3, a control parameter determination unit that determines control parameters for the inverter device based on the estimated imbalance amount and the control parameter characteristic equation.

5. 5. The power system stabilization device according to claim 4, a transmission unit that reflects the control parameter in an active power command value of the inverter device to be controlled;

6. 2. The power system stabilization device according to claim 1, The power system stabilization device is characterized in that the allowable drop amount indicates the maximum drop amount that can maintain the system frequency within a target range for a power source dropout failure or a load dropout failure.

7. 2. The power system stabilization device according to claim 1, The power system stabilization device is characterized in that, in the case of a system isolation fault, the allowable power drop amount indicates the maximum power drop amount that can maintain the minimum frequency value within a target range, with the amount of power drop being considered to be the amount of power flow on the faulted line before the system isolation.

8. 5. The power system stabilization device according to claim 4, The power system stabilization device, wherein the control parameter determination unit determines a control parameter that is common to all of the controlled objects.

9. 6. The power system stabilization device according to claim 5, A power system stabilization device comprising a central processing unit that pre-calculates the control parameter characteristic equation before a system fault occurs, and a local control unit that determines and reflects the control parameters after the system fault occurs.

10. 2. The power system stabilization device according to claim 1, The power system stabilization device, characterized in that the control target determination unit is executed using inverter operating status data acquired from the inverter device before a system fault occurs as an input.

11. 2. The power system stabilization device according to claim 1, The power system stabilization device is characterized in that the control parameter characteristic equation calculation unit expresses the relationship between the control parameter and the allowable drop amount as a linear function.

12. The power system stabilization device according to claim 11, the control parameter characteristic equation calculation unit calculates the control parameter characteristic equation based on a theoretical equation of the linear function using frequency maintenance target data, system model data, and non-controlled object data.

13. 13. The power system stabilization device according to claim 12, The power system stabilization device, wherein the non-control object data includes data on active power control amounts of non-control objects of the power system stabilization device.

14. 2. The power system stabilization device according to claim 1, A power system stabilization device comprising a display unit that displays at least one of system configuration data, system measurement value data, frequency maintenance target data, system model data, contingent fault list data, control parameter pattern data, non-controlled object data, analysis cross-section data, stability calculation result data, stability evaluation result data, control parameter characteristic equation data, inverter operating status data, fault detection threshold data, frequency measurement data, synchronous machine data, controlled object data, fault detection result data, supply and demand imbalance occurrence amount data, and control parameter data.

15. A power system stabilization device in a power system to which a plurality of inverter devices using inverters having an active power control function are connected, a control object determination unit that determines a control object of the inverter device; a stability calculation unit that uses data on the control object and system measurement information to perform stability calculations for the power system when one or more types of system failures of power source dropout, load dropout, or system separation are assumed; and a central processing unit that performs processing before the system failure occurs, the central processing unit comprising: a control parameter characteristic equation calculation unit that determines a control parameter characteristic equation that represents the relationship between a control parameter of an active power command value and an allowable dropout amount based on the result of the stability calculation unit; a supply and demand imbalance amount estimation unit that estimates an amount of imbalance in power supply and demand due to the grid failure; a control parameter determination unit that determines control parameters for the inverter device based on a result of the estimation of the amount of imbalance and the control parameter characteristic equation; and a transmission unit that reflects the control parameters in an active power command value of a control target of the inverter device, and a local arithmetic unit that executes processing after the grid failure occurs.

16. A computer-assisted power system stabilization method for maintaining frequency stability of a power system using an inverter device that uses an inverter having an active power control function, comprising: a stability calculation step of calculating the stability of the power system assuming one or more types of system failure, either a power source drop, a load drop, or system isolation, using data on the control object and system measurement information; a control parameter characteristic equation calculation step of calculating a characteristic equation expressing the relationship between a control parameter of an active power command value and an allowable amount of drop, based on the result of the stability calculation step; and an output step of outputting the results of each step.

17. A computer-assisted power system stabilization method for maintaining frequency stability of a power system using an inverter device that uses an inverter having an active power control function, comprising: the computer determines a control target of the inverter device, and performs a stability calculation of the power system assuming one or more types of system failures of power source dropout, load dropout, or system separation using data of the control target and system measurement information, and performs a process of determining a control parameter characteristic equation that expresses the relationship between a control parameter of an active power command value and an allowable dropout amount based on the result of the stability calculation before the system failure occurs; a power system stabilization method comprising: estimating an amount of imbalance in power supply and demand due to the power system failure; determining control parameters for the inverter device based on the estimated amount of imbalance and the control parameter characteristic equation; and reflecting the control parameters in an active power command value of a control target of the inverter device after the power system failure occurs.

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