Thermal power generating unit active power regulation capability assessment method considering deep peak regulation

Abstract

The invention discloses a thermal power generating unit active power regulation capability evaluation method considering deep peak regulation, which comprises the steps of determining key parameters influencing the active power regulation capability of a thermal power generating unit based on actual measurement parameters under a normal active power output level and a deep peak regulation active power output level of the thermal power generating unit; determining a parameter sensitivity analysis boundary of each key parameter according to the key parameters and difference parameters of the thermal power generating unit under a normal level and a deep peak regulation level; according to the parameter sensitivity analysis boundary of each key parameter, constructing a parameter change sequence of each key parameter; according to the parameter change sequence of each key parameter, constructing a normalized comprehensive quantitative index of active power adjustment of the thermal power generating unit; and substituting the key parameter measured value of the thermal power generating unit into the normalized comprehensive quantitative index to obtain a real-time normalized comprehensive quantitative index of the thermal power generating unit, and determining the active power regulation capability of the thermal power generating unit according to the real-time normalized comprehensive quantitative index.

Description

Technical Field

[0001] The present invention relates to the technical field of power system operation mode screening, and more specifically, to a method for evaluating the active regulation capability of a thermal power unit considering deep peak regulation. Background Art

[0002] The continuous increase in the penetration rate of renewable energy has compressed the power generation space of thermal power units. Especially during the period of large-scale renewable energy generation, the system thermal power units are often in deep peak regulation conditions, resulting in reduced regulation capacity of thermal power units. The reduction in active power regulation caused by large-scale thermal power deep peak regulation will significantly weaken the active power regulation level of the power system and threaten the safe and stable operation of the power system. However, the current research on the active power regulation capacity of thermal power units under deep peak regulation is still relatively preliminary, and there is a lack of methods to evaluate the changes in the active power regulation capacity of thermal power units under different working conditions. Therefore, an evaluation method for the active power regulation capacity of thermal power units under deep peak regulation is proposed, which is of great significance for evaluating the safety and stability capabilities of the power grid and maintaining the safe and stable operation of the power grid.

[0003] Based on the measured parameters of deep peak-shaving units, the regulation characteristics of the units under specific conditions can be obtained. However, there are many types of units, and the parameters of different units under different conditions vary. Due to the constraints of experimental costs and operating conditions, it is difficult to comprehensively evaluate the active regulation characteristics of deep peak-shaving units through refined experiments. Deep regulation thermal power conditions change the operating characteristics of the system. Since the measured parameters of deep regulation thermal power units are missing in the PSD Power Tools calculation data, the accuracy of the power grid safety and stability analysis and dispatching control schemes is seriously affected, and it is difficult to meet the requirements of future work and research. With a large number of conventional power sources participating in deep peak regulation, the safety and stability characteristics of the power grid will undergo major changes. Evaluating the changes in the active regulation capacity of thermal power units under different conditions is of great significance for evaluating the safety and stability capabilities of the power grid and maintaining the safe and stable operation of the power grid. In order to accurately grasp the active regulation capacity of the unit after the deep peak-shaving operation of the unit, it is urgent to conduct research on the evaluation of the active regulation capacity of deep peak-shaving units. Summary of the invention

[0004] In view of the deficiencies in the prior art, the present invention provides a method for evaluating the active regulation capability of a thermal power unit taking deep peak regulation into consideration.

[0005] According to one aspect of the present invention, a method for evaluating the active power regulation capability of a thermal power unit considering deep peak regulation is provided, comprising:

[0006] Based on the measured parameters of the thermal power units at normal active output levels and deep peak load active output levels, determine the key parameters that affect the active power regulation capability of the thermal power units;

[0007] According to the key parameters and the difference parameters of thermal power units at normal level and deep peak regulation level, the parameter sensitivity analysis boundary of each key parameter is determined;

[0008] According to the parameter sensitivity analysis boundary of each key parameter, the parameter change sequence of each key parameter is constructed;

[0009] According to the parameter change sequence of each key parameter, a normalized comprehensive quantitative index of active power regulation of thermal power units is constructed;

[0010] The measured values ​​of key parameters of the thermal power unit are brought into the normalized comprehensive quantitative index to obtain the real-time normalized comprehensive quantitative index of the thermal power unit, and the active power regulation capability of the thermal power unit is determined by the real-time normalized comprehensive quantitative index.

[0011] Optionally, according to the parameter sensitivity analysis boundary of each key parameter, a parameter change sequence of each key parameter is constructed, including:

[0012] Construct a single-unit infinite model of a thermal power unit;

[0013] Perform power flow calculation on the single-machine infinite model and obtain the power flow calculation file of the thermal power unit;

[0014] Build a thermal power plant model of a typical thermal power plant;

[0015] Based on the power flow calculation file, the values ​​are taken at equal intervals in the parameter sensitivity analysis boundary, the parameters are modified in an orderly manner from small to large, and the dynamic parameter files of each key parameter are generated according to the thermal power unit model;

[0016] According to the dynamic parameter files of each key parameter, the parameter change sequence of each key parameter is constructed respectively, wherein the parameter change sequence includes the key parameter change sequence, the maximum value sequence of active power change of thermal power unit and the maximum value time sequence of active power change of thermal power unit.

[0017] Optionally, according to the parameter change sequence of each key parameter, a normalized comprehensive quantitative index of active power regulation of the thermal power unit is constructed, including:

[0018] Fit the parameter change sequence based on the polynomial fitting method to obtain the time domain fitting curve function of each key parameter;

[0019] According to the time domain fitting curve function, the amplitude index and speed index of the active power regulation of the thermal power unit are constructed;

[0020] According to the amplitude index and speed index, a normalized comprehensive quantitative index for active power regulation of thermal power units is constructed.

[0021] Optionally, fitting the parameter variation sequence based on a polynomial fitting method to obtain a time domain fitting curve function includes:

[0022] The parameter change sequence is fitted based on the polynomial fitting method to obtain the first time domain fitting curve function of the maximum active power of the thermal power unit with respect to the key parameter change and the second time domain fitting area function of the key parameter change at the moment of the maximum active power.

[0023] Optionally, the expression for the amplitude index is:

[0024]

[0025] The expression of speed index is:

[0026]

[0027] In the formula, is the measured value of the key parameter, is the first time domain fitting curve function, is the second time domain fitting region function, and m is the number of key parameters.

[0028] Optionally, according to the amplitude index and the speed index, a normalized comprehensive quantitative index of active power regulation of the thermal power unit is constructed, including:

[0029] According to the amplitude index and speed index, a comprehensive quantitative index of active power regulation of thermal power units is constructed;

[0030] The comprehensive quantitative index is normalized to obtain a normalized comprehensive quantitative index.

[0031] Optionally, the expression of the comprehensive quantitative index is:

[0032]

[0033] In the formula, F A is the amplitude index, F S is the speed indicator;

[0034] The expression of normalized comprehensive quantitative index is:

[0035]

[0036] in,

[0037]

[0038] In the formula, F A,max is the maximum value of the amplitude index, F S,min is the minimum value of the speed index, f y,i,max (x i (t)) is the maximum value of the i-th parameter fitting function, f z,i,min (xi (t)) is the minimum value of the i-th parameter fitting function, is the measured value of the key parameter, and m is the number of key parameters.

[0039] According to another aspect of the present invention, there is provided a device for evaluating the active power regulation capability of a thermal power unit considering deep peak regulation, comprising:

[0040] The first determination module is used to determine the key parameters affecting the active power regulation capability of the thermal power unit based on the measured parameters of the normal active power output level and the deep peak load active output level of the thermal power unit;

[0041] The second determination module is used to determine the parameter sensitivity analysis boundary of each key parameter according to the key parameters and the difference parameters of the thermal power units at the normal level and the deep peak regulation level;

[0042] The first construction module is used to construct a parameter change sequence of each key parameter according to the parameter sensitivity analysis boundary of each key parameter;

[0043] The second building module is used to build a normalized comprehensive quantitative index of active power regulation of thermal power units according to the parameter change sequence of each key parameter;

[0044] The acquisition module is used to bring the measured values ​​of the key parameters of the thermal power unit into the normalized comprehensive quantitative index, obtain the real-time normalized comprehensive quantitative index of the thermal power unit, and determine the active regulation capability of the thermal power unit by normalizing the comprehensive quantitative index in real time.

[0045] According to another aspect of the present invention, a computer-readable storage medium is provided, wherein the storage medium stores a computer program, and the computer program is used to execute the method described in any one of the above aspects of the present invention.

[0046] According to another aspect of the present invention, an electronic device is provided, comprising: a processor; a memory for storing instructions executable by the processor; the processor is configured to read the executable instructions from the memory and execute the instructions to implement the method described in any one of the above aspects of the present invention.

[0047] Therefore, the present invention provides a method for evaluating the active power regulation capability of thermal power units considering deep peak regulation, which aims to address the problem of insufficient understanding of the active power regulation capability of thermal power units under the current deep peak regulation state. Through the actual measurement of parameters under conventional operating conditions and extreme deep peak regulation operating conditions, the difference parameters under deep regulation conditions and conventional conditions and the possible change range of the difference parameters are determined. The trend of the influence of unit parameters on the change of active power regulation capability is fitted based on parameter sensitivity analysis, and the quantitative index of active power regulation capability is constructed based on the regulation amplitude index and the regulation speed index. Based on the quantitative index of active power regulation capability proposed in this article, it can provide a reference for evaluating the active power regulation capability of deep regulation units and provide support for the safety and stability analysis of power systems. BRIEF DESCRIPTION OF THE DRAWINGS

[0048] A more complete understanding of exemplary embodiments of the present invention may be obtained by referring to the following drawings:

[0049] Figure 1 It is a flow chart of a method for evaluating the active power regulation capability of a thermal power unit considering deep peak regulation provided by an exemplary embodiment of the present invention;

[0050] Figure 2 It is an extreme value time sensitivity analysis curve of the PID proportional link coefficient and a polynomial fitting schematic diagram thereof provided by an exemplary embodiment of the present invention;

[0051] Figure 3 It is a schematic diagram of a power extreme value sensitivity analysis curve of a PID proportional link coefficient and a polynomial fitting schematic diagram thereof provided by an exemplary embodiment of the present invention;

[0052] Figure 4 It is an extreme value time sensitivity analysis curve of the PID integral link coefficient and a polynomial fitting schematic diagram thereof provided by an exemplary embodiment of the present invention;

[0053] Figure 5 It is a power extreme value sensitivity analysis curve of the PID integral link coefficient and a polynomial fitting schematic diagram thereof provided by an exemplary embodiment of the present invention;

[0054] Figure 6 It is a structural schematic diagram of an active power regulation capability evaluation device for a thermal power unit considering deep peak regulation provided by an exemplary embodiment of the present invention;

[0055] Figure 7 This is a structure of an electronic device provided by an exemplary embodiment of the present invention. DETAILED DESCRIPTION

[0056] Below, the exemplary embodiments according to the present invention will be described in detail with reference to the accompanying drawings. Obviously, the described embodiments are only part of the embodiments of the present invention, rather than all the embodiments of the present invention, and it should be understood that the present invention is not limited to the exemplary embodiments described here.

[0057] It should be noted that the relative arrangement of components and steps, the numerical expressions and numerical values ​​set forth in these embodiments do not limit the scope of the present invention unless specifically stated otherwise.

[0058] Those skilled in the art can understand that the terms "first" and "second" in the embodiments of the present invention are only used to distinguish different steps, devices or modules, etc., and neither represent any specific technical meaning nor indicate the necessary logical order between them.

[0059] It should also be understood that, in the embodiments of the present invention, “plurality” may refer to two or more than two, and “at least one” may refer to one, two or more than two.

[0060] It should also be understood that any component, data or structure mentioned in the embodiments of the present invention can generally be understood as one or more, unless explicitly limited or otherwise indicated in the context.

[0061] In addition, the term "and / or" in the present invention is only a description of the association relationship of the associated objects, indicating that there can be three relationships. For example, A and / or B can represent: A exists alone, A and B exist at the same time, and B exists alone. In addition, the character " / " in the present invention generally indicates that the associated objects before and after are in an "or" relationship.

[0062] It should also be understood that the description of the various embodiments of the present invention focuses on the differences between the various embodiments, and the same or similar aspects thereof can be referenced to each other, and for the sake of brevity, they will not be described one by one.

[0063] At the same time, it should be understood that for the convenience of description, the sizes of the various parts shown in the drawings are not drawn according to the actual proportional relationship.

[0064] The following description of at least one exemplary embodiment is merely illustrative in nature and is in no way intended to limit the invention, its application, or uses.

[0065] Technologies, methods, and equipment known to ordinary technicians in the relevant art may not be discussed in detail, but where appropriate, the technologies, methods, and equipment should be considered part of the specification.

[0066] It should be noted that like reference numerals and letters refer to similar items in the following figures, and therefore, once an item is defined in one figure, it need not be further discussed in subsequent figures.

[0067] Embodiments of the present invention can be applied to electronic devices such as terminal devices, computer systems, servers, etc., which can operate with many other general or special computing system environments or configurations. Examples of well-known terminal devices, computing systems, environments and / or configurations suitable for use with electronic devices such as terminal devices, computer systems, servers, etc. include, but are not limited to: personal computer systems, server computer systems, thin clients, thick clients, handheld or laptop devices, microprocessor-based systems, set-top boxes, programmable consumer electronics, network personal computers, small computer systems, large computer systems, and distributed cloud computing technology environments including any of the above systems, etc.

[0068] Electronic devices such as terminal devices, computer systems, servers, etc. can be described in the general context of computer system executable instructions (such as program modules) executed by computer systems. Generally, program modules can include routines, programs, object programs, components, logic, data structures, etc., which perform specific tasks or implement specific abstract data types. Computer systems / servers can be implemented in a distributed cloud computing environment, where tasks are performed by remote processing devices linked through a communication network. In a distributed cloud computing environment, program modules can be located on local or remote computing system storage media including storage devices.

[0069] Exemplary Methods

[0070] Figure 1 1 is a flow chart of a method for evaluating the active power regulation capability of a thermal power unit considering deep peak regulation provided by an exemplary embodiment of the present invention. This embodiment can be applied to electronic devices, such as Figure 1 As shown, the active regulation capability evaluation method 100 of a thermal power unit considering deep peak regulation includes the following steps:

[0071] Step 101, based on the measured parameters of the normal active power output level and the deep peak load active power output level of the thermal power unit, determine the key parameters that affect the active power regulation capability of the thermal power unit;

[0072] Step 102, determining the parameter sensitivity analysis boundary of each key parameter according to the key parameters and the difference parameters of the thermal power units at the normal level and the deep peak regulation level;

[0073] Step 103, constructing a parameter change sequence of each key parameter according to the parameter sensitivity analysis boundary of each key parameter;

[0074] Step 104, constructing a normalized comprehensive quantitative index of active power regulation of the thermal power unit according to the parameter change sequence of each key parameter;

[0075] Step 105, bringing the measured values ​​of the key parameters of the thermal power unit into the normalized comprehensive quantitative index, obtaining the real-time normalized comprehensive quantitative index of the thermal power unit, and determining the active regulation capability of the thermal power unit by the real-time normalized comprehensive quantitative index.

[0076] Specifically, the present invention provides a method for evaluating the active regulation capability of thermal power units taking into account deep peak regulation, which aims to address the problem of insufficient understanding of the active regulation capability of thermal power units under the current deep peak regulation state. By measuring parameters under conventional operating conditions and extreme deep peak regulation operating conditions, the difference parameters under deep regulation conditions and conventional conditions and the possible range of variation of the difference parameters are determined. Based on parameter sensitivity analysis, the trend of the influence of unit parameters on the change of active regulation capability is clarified. Based on polynomial fitting, the approximate function of the active regulation extreme value and the extreme value moment is obtained, thereby establishing a mapping relationship between the deep regulation unit parameters and the active regulation capability, and establishing an evaluation index for the active regulation capability of the deep regulation unit. The specific implementation process of this method is as follows:

[0077] Step 1: Based on the measured parameter identification results of the GJ / GJ+ / GA / TB card model in PSD PowerTools under the normal active output level and deep peak load active output level of the thermal power unit, compare the parameter differences of the prime mover, turbine control system, actuator and other models to identify the key parameters that affect the active power regulation capability of the thermal power unit.

[0078] Step 2: For the difference parameters in the key parameters under normal level and deep peak-shaving level, take the model parameter values ​​under normal active output level and deep peak-shaving active output level as the upper and lower bounds of the parameters respectively, and appropriately expand them to both sides to fully cover the parameter variation range, and use the expanded parameter values ​​as the boundary of parameter sensitivity analysis. Each parameter must have an upper and lower bound.

[0079] Step 3: Generate massive operating mode data of thermal power units:

[0080] Step 3.1: Based on the PSD Power Tools standard parameter library, build a single-machine infinite model of the thermal power unit, perform power flow calculation, and obtain the power flow calculation file.

[0081] Step 3.2: Build a typical thermal power unit model in PSD Power Tools. Based on the power flow calculation file, sample values ​​at equal intervals within the sensitivity analysis boundary of the difference parameters, modify the parameters in an orderly manner from small to large, and generate dynamic parameter files respectively to build massive unit parameter data.

[0082] Step 3.3: Set the frequency difference disturbance, calculate the dynamic parameter files generated by changing each difference parameter one by one, extract the extreme value and extreme value moment of the active power change curve of the thermal power unit, and each parameter file generates a power change curve.

[0083] Step 3.4: Based on the above steps, three sets of parameter sequences are generated for each difference parameter, namely, difference parameter change sequence X i ={x i,1 ,x i,2 ,…,x i,j ,…x i,n}, the maximum value sequence of active power change of thermal power units Y i ={y i,1 ,y i,2 ,…,y i,j ,…y i,n}, and the maximum value of the active power change time series Z of the thermal power unit i ={z i,1 ,z i,2 ,…,z i,j ,…z i,n}. Wherein, subscript i is the i-th parameter, subscript j is the j-th parameter of the equally spaced sensitivity analysis, and n represents the number of equally spaced values ​​of a single parameter.

[0084] Step 4: Based on the polynomial fitting method, obtain the time domain fitting curve function of the active output extreme value and extreme value time of the thermal power unit with respect to the change of difference parameters The superscript “^” represents an approximate value.

[0085] Step 5: Based on the fitting curve function of each difference parameter, construct the active power regulation amplitude index F of the thermal power unit A as follows:

[0086]

[0087] Where: the superscript “*” represents the measured value of the difference parameter; m is the number of difference parameters.

[0088] Step 6: Based on the fitting curve function of each difference parameter, construct the active power regulation speed index F of the thermal power unit S as follows:

[0089]

[0090] Step 7: Based on the speed adjustment amplitude and speed adjustment index, construct the comprehensive quantitative index η of the active power adjustment capability of the thermal power unit:

[0091]

[0092] Step 8: Based on the normalization of the comprehensive quantitative index, the normalized index η of the comprehensive quantitative index of the active power regulation capability of the thermal power unit is obtained: * :

[0093]

[0094] Where:

[0095]

[0096] Among them, F A,max is the maximum value of the active power regulation amplitude index of the thermal power unit, F S,min is the minimum value of the active power regulation speed index of the thermal power unit, f y,i,max (x i (t)) is the maximum value of the i-th parameter fitting function, f z,i,min (x i (t)) is the minimum value of the i-th parameter fitting function.

[0097] Step 9: Substitute the actual parameters of the thermal power unit into equations (1) to (5) to obtain the normalized index of the comprehensive quantitative index of the active power regulation capability of the thermal power unit. The closer the index is to 1, the stronger the active power regulation capability of the thermal power unit.

[0098] In order to provide a general process for implementing an evaluation method for the active power regulation capability of thermal power units considering deep peak regulation and verify its effectiveness, an analysis was conducted based on the measured parameters of an actual thermal power unit under normal operation and deep peak regulation.

[0099] An active power regulation capability evaluation model for thermal power units is constructed, and the measured parameters under normal operation and deep regulation operation are compared. The difference parameters that affect the regulation capability in this example are the PID proportional link coefficient and the PID integral link coefficient.

[0100] Based on the measured parameters under normal operation and deep adjustment operation, the value range of each difference parameter is clarified. In this example, the PID proportional link coefficient range is [0,2], and the PID integral link coefficient is [0,0.4]; and the value of each difference parameter is changed with a step size of 0.01 to generate a dynamic parameter file. Based on PSD Power Tools simulation analysis, the extreme values ​​and extreme moments of active power changes in the simulation results of each dynamic file are extracted to form a difference parameter change sequence Xi = {xi,1,xi,2,…,xi,j,…xi,n}, and the maximum value sequence of active power change of thermal power units Y i ={y i,1 ,y i,2 ,…,y i,j ,…y i,n}, and the maximum value of the active power change time series Z of the thermal power unit i ={z i,1 ,z i,2 ,…,z i,j ,…z i,n}.

[0101] Based on the polynomial fitting method, the time domain fitting curve function of the active output extreme value and extreme value time of the thermal power unit with respect to the change of difference parameters is obtained. like Figure 2 to Figure 4 shown.

[0102] Table 1 Results of polynomial fitting expressions

[0103]

[0104] Then, the comprehensive quantitative index is calculated based on the proposed formula:

[0105]

[0106] The maximum value of the comprehensive quantitative index is:

[0107]

[0108] There are two sets of thermal power unit parameters. The first set of parameters has a PID proportional coefficient of 0.5 and a PID integral coefficient of 0.1; the second set of parameters has a PID proportional coefficient of 0.7 and a PID integral coefficient of 0.3:

[0109]

[0110] It can be seen from the indicators that the regulation ability of the thermal power units under the first set of parameters is slightly better.

[0111] Therefore, the present invention provides a method for evaluating the active power regulation capability of thermal power units considering deep peak regulation, which aims to address the problem of insufficient understanding of the active power regulation capability of thermal power units under the current deep peak regulation state. Through the actual measurement of parameters under conventional operating conditions and extreme deep peak regulation operating conditions, the difference parameters under deep regulation conditions and conventional conditions and the possible change range of the difference parameters are determined. The trend of the influence of unit parameters on the change of active power regulation capability is fitted based on parameter sensitivity analysis, and the quantitative index of active power regulation capability is constructed based on the regulation amplitude index and the regulation speed index. Based on the quantitative index of active power regulation capability proposed in this article, it can provide a reference for evaluating the active power regulation capability of deep regulation units and provide support for the safety and stability analysis of power systems.

[0112] Exemplary Devices

[0113] Figure 6 FIG. 1 is a schematic diagram of a structure of a device for evaluating the active power regulation capability of a thermal power unit considering deep peak regulation provided by an exemplary embodiment of the present invention. Figure 6 As shown, the device 600 includes:

[0114] The first determination module 610 is used to determine the key parameters affecting the active power regulation capability of the thermal power unit based on the measured parameters of the normal active power output level and the deep peak load active output level of the thermal power unit;

[0115] The second determination module 620 is used to determine the parameter sensitivity analysis boundary of each key parameter according to the key parameters and the difference parameters of the thermal power units at the normal level and the deep peak regulation level;

[0116] A first construction module 630 is used to construct a parameter change sequence of each key parameter according to the parameter sensitivity analysis boundary of each key parameter;

[0117] The second construction module 640 is used to construct a normalized comprehensive quantitative index of active power regulation of the thermal power unit according to the parameter change sequence of each key parameter;

[0118] The acquisition module 650 is used to bring the measured values ​​of the key parameters of the thermal power unit into the normalized comprehensive quantitative index, obtain the real-time normalized comprehensive quantitative index of the thermal power unit, and determine the active regulation capability of the thermal power unit by the real-time normalized comprehensive quantitative index.

[0119] Optionally, the first building module 630 includes:

[0120] The first construction submodule is used to construct a single-machine infinite model of a thermal power unit;

[0121] The calculation submodule is used to perform power flow calculation on the single-machine infinite model and obtain the power flow calculation file of the thermal power unit;

[0122] Build submodules to build a thermal power plant model of a typical thermal power plant;

[0123] A generation submodule is used to adopt values ​​at equal intervals in the parameter sensitivity analysis boundary based on the power flow calculation file, modify the parameters in an orderly manner from small to large, and generate dynamic parameter files of each key parameter according to the thermal power unit model;

[0124] The second construction submodule is used to construct the parameter change sequence of each key parameter according to the dynamic parameter file of each key parameter, wherein the parameter change sequence includes the key parameter change sequence, the maximum value sequence of active power change of thermal power unit and the maximum value moment sequence of active power change of thermal power unit.

[0125] Optionally, the second building module 640 includes:

[0126] The fitting submodule is used to fit the parameter change sequence based on the polynomial fitting method to obtain the time domain fitting curve function of each key parameter;

[0127] The third construction submodule is used to construct the amplitude index and speed index of the active power regulation of the thermal power unit according to the time domain fitting curve function;

[0128] The fourth construction submodule is used to construct a normalized comprehensive quantitative index of active power regulation of the thermal power unit according to the amplitude index and the speed index.

[0129] Optionally, the fitting submodule includes:

[0130] The fitting unit is used to fit the parameter change sequence based on the polynomial fitting method to obtain the first time domain fitting curve function of the maximum active power of the thermal power unit regarding the change of key parameters and the second time domain fitting area function of the maximum active power moment regarding the change of key parameters.

[0131] Optionally, the expression for the amplitude index is:

[0132]

[0133] The expression of speed index is:

[0134]

[0135] In the formula, is the measured value of the key parameter, is the first time domain fitting curve function, is the second time domain fitting region function, and m is the number of key parameters.

[0136] Optionally, the fourth building block includes:

[0137] A construction unit, used for constructing a comprehensive quantitative index of active power regulation of a thermal power unit according to an amplitude index and a speed index;

[0138] The normalization unit is used to normalize the comprehensive quantitative index to obtain a normalized comprehensive quantitative index.

[0139] Optionally, the expression of the comprehensive quantitative index is:

[0140]

[0141] In the formula, F A is the amplitude index, F S is the speed indicator;

[0142] The expression of normalized comprehensive quantitative index is:

[0143]

[0144] in,

[0145]

[0146] In the formula, F A,max is the maximum value of the amplitude index, F S,minis the minimum value of the speed index, f y,i,max (x i (t)) is the maximum value of the i-th parameter fitting function, f z,i,min (x i (t)) is the minimum value of the i-th parameter fitting function, is the measured value of the key parameter, and m is the number of key parameters.

[0147] Exemplary Electronic Devices

[0148] Figure 7 This is a structure of an electronic device provided by an exemplary embodiment of the present invention. Figure 7 As shown, the electronic device 70 includes one or more processors 71 and a memory 72 .

[0149] The processor 71 may be a central processing unit (CPU) or other forms of processing units having data processing capabilities and / or instruction execution capabilities, and may control other components in the electronic device to perform desired functions.

[0150] The memory 72 may include one or more computer program products, which may include various forms of computer-readable storage media, such as volatile memory and / or non-volatile memory. The volatile memory may include, for example, random access memory (RAM) and / or cache memory (cache), etc. The non-volatile memory may include, for example, read-only memory (ROM), hard disk, flash memory, etc. One or more computer program instructions may be stored on the computer-readable storage medium, and the processor 71 may run the program instructions to implement the methods of the software programs of the various embodiments of the present invention described above and / or other desired functions. In one example, the electronic device may also include: an input device 73 and an output device 74, which are interconnected via a bus system and / or other forms of connection mechanisms (not shown).

[0151] In addition, the input device 73 may also include, for example, a keyboard, a mouse, and the like.

[0152] The output device 74 can output various information to the outside, and can include, for example, a display, a speaker, a printer, a communication network and a remote output device connected thereto.

[0153] Of course, to simplify, Figure 7 Only some of the components related to the present invention in the electronic device are shown, and components such as a bus, an input / output interface, etc. are omitted. In addition, the electronic device may further include any other appropriate components according to specific application conditions.

[0154] Exemplary computer program products and computer-readable storage media

[0155] In addition to the above-mentioned methods and devices, an embodiment of the present invention may also be a computer program product, which includes computer program instructions, which, when executed by a processor, enable the processor to execute the steps of the method according to various embodiments of the present invention described in the above-mentioned "Exemplary Method" section of this specification.

[0156] The computer program product may be written in any combination of one or more programming languages ​​to write program code for performing the operations of the embodiments of the present invention, including object-oriented programming languages ​​such as Java, C++, etc., and conventional procedural programming languages ​​such as "C" or similar programming languages. The program code may be executed entirely on the user computing device, partially on the user device, as a separate software package, partially on the user computing device and partially on a remote computing device, or entirely on a remote computing device or server.

[0157] In addition, an embodiment of the present invention may also be a computer-readable storage medium having computer program instructions stored thereon, which, when executed by a processor, enable the processor to execute the steps of the method according to various embodiments of the present invention described in the above “Exemplary Method” section of this specification.

[0158] The computer readable storage medium can adopt any combination of one or more readable media. The readable medium can be a readable signal medium or a readable storage medium. The readable storage medium can include, for example, but is not limited to, a system, system or device of electricity, magnetism, light, electromagnetic, infrared, or semiconductor, or any combination of the above. More specific examples (non-exhaustive list) of readable storage media include: an electrical connection with one or more wires, a portable disk, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disk read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the above.

[0159] The basic principle of the present invention is described above in conjunction with specific embodiments. However, it should be pointed out that the advantages, strengths, effects, etc. mentioned in the present invention are only examples and not limitations, and it cannot be considered that these advantages, strengths, effects, etc. must be possessed by each embodiment of the present invention. In addition, the specific details disclosed above are only for the purpose of illustration and facilitation of understanding, rather than limitation, and the above details do not limit the present invention to being implemented by adopting the above specific details.

[0160] Each embodiment in this specification is described in a progressive manner, and each embodiment focuses on the differences from other embodiments. The same or similar parts between the embodiments can be referred to each other. For the system embodiment, since it basically corresponds to the method embodiment, the description is relatively simple, and the relevant parts can be referred to the partial description of the method embodiment.

[0161] The block diagrams of the devices, systems, equipment, and systems involved in the present invention are only illustrative examples and are not intended to require or imply that they must be connected, arranged, and configured in the manner shown in the block diagram. As will be appreciated by those skilled in the art, these devices, systems, equipment, and systems can be connected, arranged, and configured in any manner. Words such as "including", "comprising", "having", etc. are open words, referring to "including but not limited to", and can be used interchangeably with them. The words "or" and "and" used here refer to the words "and / or" and can be used interchangeably with them, unless the context clearly indicates otherwise. The word "such as" used here refers to the phrase "such as but not limited to", and can be used interchangeably with it.

[0162] The method and system of the present invention may be implemented in many ways. For example, the method and system of the present invention may be implemented by software, hardware, firmware or any combination of software, hardware, firmware. The above order of steps for the method is only for illustration, and the steps of the method of the present invention are not limited to the order specifically described above, unless otherwise specifically stated. In addition, in some embodiments, the present invention may also be implemented as a program recorded in a recording medium, which includes machine-readable instructions for implementing the method according to the present invention. Thus, the present invention also covers a recording medium storing a program for executing the method according to the present invention.

[0163] It should also be noted that in the system, device and method of the present invention, each component or each step can be decomposed and / or recombined. These decompositions and / or recombinations should be regarded as equivalent schemes of the present invention. The above description of the disclosed aspects is provided to enable any technician in the field to make or use the present invention. Various modifications to these aspects are very obvious to those skilled in the art, and the general principles defined here can be applied to other aspects without departing from the scope of the present invention. Therefore, the present invention is not intended to be limited to the aspects shown here, but in accordance with the widest range consistent with the principles and novel features disclosed here.

[0164] The above description has been given for the purpose of illustration and description. In addition, this description is not intended to limit the embodiments of the present invention to the forms disclosed herein. Although a number of example aspects and embodiments have been discussed above, those skilled in the art will recognize certain variations, modifications, changes, additions and sub-combinations thereof.

Claims

1. A method for evaluating the active power regulation capability of a thermal power unit considering deep peak regulation, characterized in that: include: Based on the measured parameters of the thermal power units at normal active output levels and deep peak load active output levels, determine the key parameters that affect the active power regulation capability of the thermal power units; Determining the parameter sensitivity analysis boundary of each key parameter according to the key parameters and the difference parameters of the thermal power unit at a normal level and a deep peak regulation level; Constructing a parameter change sequence of each key parameter according to the parameter sensitivity analysis boundary of each key parameter; According to the parameter change sequence of each key parameter, a normalized comprehensive quantitative index of active power regulation of the thermal power unit is constructed; The measured values ​​of the key parameters of the thermal power unit are brought into the normalized comprehensive quantitative index to obtain the real-time normalized comprehensive quantitative index of the thermal power unit, and the real-time normalized comprehensive quantitative index is used to determine the active regulation capability of the thermal power unit.

2. The method according to claim 1, characterized in that According to the parameter sensitivity analysis boundary of each key parameter, a parameter change sequence of each key parameter is constructed, including: Construct a single-unit infinite model of a thermal power unit; Performing power flow calculation on the single-machine infinite model to obtain a power flow calculation file of the thermal power unit; Build a thermal power plant model of a typical thermal power plant; Based on the power flow calculation file, adopting values ​​at equal intervals within the parameter sensitivity analysis boundary, modifying parameters in an orderly manner from small to large, and generating a dynamic parameter file of each key parameter according to the thermal power unit model; According to the dynamic parameter files of each key parameter, the parameter change sequence of each key parameter is constructed respectively, wherein the parameter change sequence includes the key parameter change sequence, the maximum value sequence of active power change of thermal power unit and the maximum value time sequence of active power change of thermal power unit.

3. The method according to claim 1, characterized in that According to the parameter change sequence of each key parameter, a normalized comprehensive quantitative index of active power regulation of the thermal power unit is constructed, including: Fitting the parameter change sequence based on a polynomial fitting method to obtain a time domain fitting curve function of each key parameter; According to the time domain fitting curve function, construct an amplitude index and a speed index of active power regulation of the thermal power unit; According to the amplitude index and the speed index, a normalized comprehensive quantitative index for active power regulation of the thermal power unit is constructed.

4. The method according to claim 3, characterized in that Fitting the parameter change sequence based on a polynomial fitting method to obtain a time domain fitting curve function includes: The parameter change sequence is fitted based on a polynomial fitting method to obtain a first time domain fitting curve function of the maximum active power value of the thermal power unit with respect to the key parameter change and a second time domain fitting area function of the key parameter change at the moment of the maximum active power value.

5. The method according to claim 4, characterized in that The expression of the amplitude index is: The expression of the speed index is: In the formula, is the measured value of the key parameter, is the first time domain fitting curve function, is the second time domain fitting region function, and m is the number of key parameters.

6. The method according to claim 3, characterized in that According to the amplitude index and the speed index, a normalized comprehensive quantitative index of active power regulation of thermal power units is constructed, including: According to the amplitude index and the speed index, a comprehensive quantitative index of active power regulation of the thermal power unit is constructed; The comprehensive quantitative index is normalized to obtain the normalized comprehensive quantitative index.

7. The method according to claim 6, characterized in that The expression of the comprehensive quantitative index is: In the formula, F A is the amplitude index, F S is the speed indicator; The expression of the normalized comprehensive quantitative index is: in, In the formula, F A,max is the maximum value of the amplitude index, F S,min is the minimum value of the speed index, f y,i,max (x i (t)) is the maximum value of the i-th parameter fitting function, f z,i,min (x i (t)) is the minimum value of the i-th parameter fitting function, is the measured value of the key parameter, and m is the number of key parameters.

8. A device for evaluating the active power regulation capability of a thermal power unit considering deep peak regulation, characterized in that: include: The first determination module is used to determine the key parameters affecting the active power regulation capability of the thermal power unit based on the measured parameters of the normal active power output level and the deep peak load active output level of the thermal power unit; A second determination module is used to determine the parameter sensitivity analysis boundary of each key parameter according to the key parameters and the difference parameters of the thermal power unit at a normal level and a deep peak regulation level; A first construction module is used to construct a parameter change sequence of each key parameter according to the parameter sensitivity analysis boundary of each key parameter; The second construction module is used to construct a normalized comprehensive quantitative index of active power regulation of the thermal power unit according to the parameter change sequence of each key parameter; The acquisition module is used to bring the measured values ​​of the key parameters of the thermal power unit into the normalized comprehensive quantitative index, obtain the real-time normalized comprehensive quantitative index of the thermal power unit, and determine the active regulation capability of the thermal power unit by the real-time normalized comprehensive quantitative index.

9. A computer-readable storage medium, characterized in that: The storage medium stores a computer program, and the computer program is used to execute the method according to any one of claims 1 to 7.

10. An electronic device, characterized in that: The electronic device comprises: processor; a memory for storing instructions executable by the processor; The processor is used to read the executable instructions from the memory and execute the instructions to implement the method described in any one of claims 1 to 7.

Images