A static voltage stability margin evaluation method, system and terminal device

Abstract

The application discloses a static voltage stability margin evaluation method, system and terminal equipment, and belongs to the field of comprehensive energy system operation, and comprises the following steps: establishing a heat dynamic model of a heating system; establishing a thermal power coupling device model; establishing a power system static voltage stability margin model considering the heat dynamic of the heating system; and solving the model and obtaining a voltage stability margin. The application can obtain the static voltage stability margin considering the heat dynamic of the heating system, can obtain the Pareto boundary of the static voltage stability margin after the heat dynamic is considered through a double-target nonlinear optimization method, can reveal the influence of the thermal power coupling on the voltage stability and the influence of the heat inertia of the heating system on the voltage stability margin, can effectively depict the interaction between the power network and the heat network of the comprehensive energy system, and realizes the evaluation of the static voltage stability margin in the comprehensive energy system.

Description

Technical Field

[0001] This invention relates to the field of integrated energy system operation, specifically to a static voltage stability margin assessment method, system, and terminal equipment. Background Technology

[0002] Integrated energy systems combine multiple energy subsystems such as gas, electricity, heating, and transportation. Through the synergy between these subsystems, they can achieve cascaded utilization of primary energy, improve the utilization rate of renewable energy, and coordinate and complement multiple energy loads, thereby achieving the energy system's energy conservation and emission reduction goals. Static voltage stability margin, which quantifies voltage stability limits by measuring the distance from specified operating conditions to a safe limit point, has been widely used in power system operation and planning.

[0003] In integrated energy systems, the coupling relationships between various energy flows are highly complex, and there is an interdependence between the power network and the heating network, rendering static voltage stability margins inapplicable. Therefore, establishing a static voltage stability margin assessment method that considers the thermal dynamics of the heating system and addresses the complex energy flow coupling relationships and thermal dynamic characteristics of integrated energy systems is a pressing problem in engineering applications. However, existing technologies often consider the power system or the heating system in isolation, failing to account for the coupling relationships and mutual influences between the electrical and thermal systems, and the physical characteristics of the voltage stability margin in integrated heat and power energy systems remain unclear. Summary of the Invention

[0004] To address the shortcomings of existing technologies, the present invention aims to provide a method, system, and apparatus for evaluating static voltage stability margin considering the thermal dynamics of a heating system. The invention obtains the Pareto boundary of the voltage steady-state margin considering the thermal dynamics of the heating system under different scenarios through a dual-objective optimization method. The proposed method reveals the influence of thermoelectric coupling on voltage stability and the influence of the thermal inertia of the heating system on the voltage stability margin, effectively characterizing the interaction between the power network and the thermal network of an integrated energy system, and enabling the evaluation of the static voltage stability margin in an integrated energy system.

[0005] The objective of this invention can be achieved through the following technical solutions:

[0006] The first aspect of this application discloses a method for evaluating static voltage stability margin, comprising:

[0007] A thermal dynamic model of the heating system is constructed based on the temperature transmission of the heating network pipeline and the thermal dynamics of the building; a model of the thermoelectric coupling equipment is established based on the operation and coupling constraints of the thermoelectric coupling equipment.

[0008] A static voltage stability margin model is constructed based on the electrical load growth pattern and the thermal load growth pattern:

[0009] max(λ E ,λ H )

[0010] stg E (P,Q,V,θ,λ E )≤0

[0011] g H (H,T,m,λ H )≤0

[0012] g EH (P,H)≤0

[0013] Where, λ E , λ H These represent the electrical and thermal load factors, respectively; P and Q represent the active and reactive power of the generator or branch, respectively; V and θ represent the voltage magnitude and phase of the bus, respectively; H represents thermal energy; T represents the water temperature or indoor temperature; m represents the mass flow rate; g E (·)≤0、g H (·)≤0 and g EH (·)≤0 represent the constraints for the power system, heating system, and thermoelectric coupling relationship, respectively;

[0014] The voltage stability margin is obtained by solving the static voltage stability margin model.

[0015] Furthermore, constructing a static voltage stability margin model based on electrical load growth patterns and thermal load growth patterns also includes the following steps:

[0016] Establish a model for electricity load growth patterns:

[0017]

[0018] in, and These represent the active power at the current operating point and the safety limit point, respectively. and These represent the reactive power at the current operating point and the safety limit point, respectively; λ E This refers to the electrical load factor.

[0019] Establish a model for heat load growth patterns:

[0020]

[0021] in, and These represent the heat loads at the current operating point and the safety limit point, respectively; λ H This is the heat load factor;

[0022] Establish a hydraulic regulation strategy model:

[0023]

[0024] in, and These are the mass flow rates of pipe j at the current operating point and the safety limit point, respectively. To avoid hydraulic instability and pipe corrosion, the water velocity is capped;

[0025] A static voltage stability margin model is established based on the electrical load growth model, the thermal load growth model, and the hydraulic regulation strategy model.

[0026] Furthermore, constructing a thermal dynamics model of the thermal system includes the following steps:

[0027] Establish a temperature transfer model for heating network pipelines:

[0028]

[0029] Where t is the set of scheduling periods; j is the set of pipelines; and the parameter... Let j be the coefficient related to the transmission delay. The insulation coefficient; Let t be the ambient temperature of the pipeline. and These are the temperatures of the heat medium at the pipe outlet and inlet at time t, respectively.

[0030] parameter and The calculation formula is as follows:

[0031]

[0032] Where Δt is the time interval; ρ w c is the density of the heat transfer medium. w Specific heat capacity of the heat transfer medium; Let be the cross-sectional area of ​​pipe j; Let j be the length of pipe; This refers to the heat loss coefficient of the pipeline. This refers to the mass flow rate of the heat medium in the pipeline. It is a rounding function;

[0033] Establish a thermal dynamic model of the building:

[0034]

[0035] Where k is the set of buildings; and These parameters depend on the building's heat capacity and heat resistance.

[0036] Furthermore, solving the static voltage stability margin model to obtain the voltage stability margin includes the following steps:

[0037] The static voltage stability margin model is optimized as follows:

[0038] λ E (ε)=maxλ E

[0039] stλ H =ε

[0040] g E ≤0,g H ≤0,g EH ≤0

[0041] Where ε is a predefined λ H The constant;

[0042] Initialize ε = 0, Flag = 1, k = 0 and Δε, and solve according to the following iterative steps;

[0043] The loop steps are as follows:

[0044] renew And calculate mass flow rate parameter and

[0045] Solve the optimized static voltage stability margin model. If a solution is found, update... Otherwise, update Flag←0;

[0046] Update k←k+1, ε←ε+Δε;

[0047] If Flag = 1, repeat the above loop steps; if Flag = 0, exit the loop steps.

[0048] Furthermore, the thermoelectric coupling equipment model includes operating constraints of the cogeneration unit, coupling constraints between the cogeneration unit and the heating network, and water temperature constraints of the heating system.

[0049] Furthermore, the coupling constraints between the cogeneration unit and the heating network are as follows:

[0050]

[0051] in, For heat source mass flow rate; and These are the supply water temperature and return water temperature of the heat source, respectively.

[0052] Furthermore, the water temperature constraint for the heating system is as follows:

[0053]

[0054] in, and These are the lower and upper limits of the water supply temperature of the heat source, respectively. and These are the lower and upper limits of the return water temperature of the heat source, respectively.

[0055] The second aspect of this application discloses a static voltage stability margin assessment system as described in the first aspect, comprising:

[0056] Heating system thermal dynamics model module: Constructs a thermal dynamics model of the heating system based on the temperature transmission of the input heating network pipelines and the thermal dynamics of the buildings;

[0057] Thermoelectric Coupled Device Model Module: Establishes a thermoelectric coupled device model based on the operation and coupling constraints of the thermoelectric coupled device;

[0058] Static voltage stability margin model module: Constructs a static voltage stability margin model based on electrical load growth patterns and thermal load growth patterns;

[0059] Calculation module: Combining the heating system thermal dynamics model module, the thermoelectric coupling equipment model module, and the static voltage stability margin model module, the static voltage stability margin model is solved to obtain the voltage stability margin.

[0060] The third aspect of this application discloses a terminal device, including a memory, a processor, and a computer program stored in the memory and capable of running on the processor. The memory stores the computer program capable of running on the processor, and when the processor loads and executes the computer program, it employs a static voltage stability margin evaluation method as disclosed in the first aspect.

[0061] The fourth aspect of this application discloses a computer-readable storage medium storing a computer program that, when loaded and executed by a processor, employs a static voltage stability margin assessment method as disclosed in the first aspect.

[0062] The beneficial effects of this invention are:

[0063] This invention obtains the Pareto boundary of voltage steady-state margin considering the thermal dynamics of the heating system under different scenarios through a dual-objective optimization method. The proposed method can reveal the influence of thermoelectric coupling on voltage stability and the influence of the thermal inertia of the heating system on voltage stability margin. It can effectively characterize the interaction between the power network and the thermal network of the integrated energy system and realize the evaluation of the static voltage stability margin of the integrated energy system. Attached Figure Description

[0064] The invention will now be further described with reference to the accompanying drawings.

[0065] Figure 1 This is a structural diagram of the integrated energy system of the present invention;

[0066] Figure 2 This is a flowchart of the static voltage stability margin assessment method for considering the thermal dynamics of a heating system according to the present invention.

[0067] Figure 3 This is a structural diagram of the integrated energy system of Embodiment 2 of the present invention;

[0068] Figure 4 This is the Pareto front of the static voltage stability margin result considering the thermal dynamics of the heating system in Embodiment 2 of the present invention;

[0069] Figure 5 In Embodiment 2 of the present invention, λ is the static voltage stability margin result considering the thermal dynamics of the heating system. H The operating point of the CHP unit when =1.5;

[0070] Figure 6 In Embodiment 2 of the present invention, λ H Generator active power output results under four scenarios when = 1.5;

[0071] Figure 7 In Embodiment 2 of the present invention, λ H Heat load results for four scenarios when = 1.5. Detailed Implementation

[0072] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0073] In the description of this specification, references to terms such as "an embodiment," "example," "specific example," etc., indicate that a specific feature, structure, material, or characteristic described in connection with that embodiment or example is included in at least one embodiment or example of the invention. In this specification, illustrative expressions of the above terms do not necessarily refer to the same embodiment or example. Furthermore, the specific features, structures, materials, or characteristics described may be combined in any suitable manner in one or more embodiments or examples.

[0074] Example 1

[0075] This embodiment is applied to an integrated energy system, the structure of which is as follows: Figure 1 As shown.

[0076] A method for assessing the static voltage stability margin considering the thermal dynamics of a heating system, such as... Figure 2 As shown, it includes the following steps:

[0077] S1. Establish a thermal dynamic model of the heating system:

[0078] S11. Establish a temperature transmission model for the heating network pipeline, wherein the temperature transmission model for the heating network pipeline is as follows:

[0079]

[0080] Where t is the set of scheduling periods; j is the set of pipelines; and the parameter... Let j be the coefficient related to the transmission delay. The insulation coefficient; Let t be the ambient temperature of the pipeline. and These are the temperatures of the heat transfer medium at the pipe outlet and inlet at time t, respectively.

[0081] parameter and The calculation formula is as follows:

[0082]

[0083] Where Δt is the time interval; ρ w c is the density of the heat transfer medium. w Specific heat capacity of the heat transfer medium; Let be the cross-sectional area of ​​pipe j; Let j be the length of pipe; This refers to the heat loss coefficient of the pipeline. This refers to the mass flow rate of the heat medium in the pipeline. This is the floor function.

[0084] S12. Establish a thermal dynamic model of the building:

[0085]

[0086] Where k is the set of buildings; and These parameters depend on the building's heat capacity and heat resistance.

[0087] S2. Establish a thermoelectric coupling device model:

[0088] S21. Establish operating constraints for combined heat and power units:

[0089] S211. Establish operating constraints for extraction-condensing cogeneration units:

[0090]

[0091] Where i is the set of generator units; j is the set of limit points of the feasible region; and These are the unit parameters; These represent the electrical and thermal outputs of the CHP unit, respectively.

[0092] S212. Establish operating constraints for back-pressure cogeneration units:

[0093]

[0094] in, This refers to the heat-to-power ratio of the CHP unit.

[0095] S22. Establish coupling constraints between cogeneration units and the heating network:

[0096]

[0097] in, For heat source mass flow rate; and These are the supply water temperature and return water temperature of the heat source, respectively.

[0098] S23. Establish water temperature constraints for the heating system:

[0099]

[0100] in, and (or and These are the lower and upper limits of the supply water temperature (or return water temperature) of the heat source, respectively.

[0101] S3. Establish a static voltage stability margin model that considers the thermal dynamics of the heating system:

[0102] S31. Establish a load growth model:

[0103] S311. Establish a model for electricity load growth patterns:

[0104]

[0105] in, and (or and ) represent the active (or reactive) power at the current operating point and the safety limit point, respectively; λ E This represents the electrical load factor.

[0106] S312. Establish a model for the heat load growth pattern based on the current operating point:

[0107]

[0108] in, and These represent the heat loads at the current operating point and the safety limit point, respectively; λ H This is the heat load factor.

[0109] S313. Establish a hydraulic regulation strategy model:

[0110]

[0111] in, and These are the mass flow rates of pipe j at the current operating point and the safety limit point, respectively. To avoid hydraulic instability and pipe corrosion, the upper limit of water velocity is set.

[0112] S32. Establish a static voltage stability margin model that considers the thermal dynamics of the heating system. Its mathematical form is as follows:

[0113] max(λ E ,λ H )

[0114] stg E (P,Q,V,θ,λ E )≤0

[0115] g H (H,T,m,λ H )≤0

[0116] g EH (P,H)≤0

[0117] Where, λ E , λ H These represent the electrical and thermal load factors, respectively; P and Q represent the active and reactive power of the generator or branch, respectively; V and θ represent the voltage magnitude and phase of the bus, respectively; H represents thermal energy; T represents the water temperature or indoor temperature; m represents the mass flow rate; g E (·)≤0、g H (·)≤0 and g EH (·)≤0 represent the constraints for the power system, heating system, and thermoelectric coupling relationship, respectively.

[0118] S4. Solve the model and obtain the voltage stability margin:

[0119] S41. Convert the bi-objective optimization model established in S32 into:

[0120] λ E(ε)=maxλ E

[0121] stλ H =ε

[0122] g E ≤0,g H ≤0,g EH ≤0

[0123] Where ε is a predefined λ H The constant.

[0124] S42. Solve the model established in S41 using the following algorithm:

[0125] S421. Initialize ε = 0, Flag = 1, k = 0 and Δε;

[0126] S422, Update And calculate mass flow rate parameter and

[0127] S423. Solve the model in step S41. If a solution is found, update... Otherwise, update Flag←0.

[0128] S424. Update k←k+1,ε←ε+Δε.

[0129] S425. If Flag = 1, repeat steps S422-S424. If Flag = 0, exit the loop.

[0130] Example 2

[0131] The integrated energy system in this embodiment consists of a 9-node power system and a 12-node heating system, such as Figure 3 As shown, the system includes two 300MW coal-fired units, one 300MW CHP unit, and one 300MW gas-fired boiler operating 24 hours a day. The dispatch interval is 1 hour, the heat source supply temperature is set to a constant (90℃), and the indoor temperature is set to an ideal value (20℃). H The step size, Δε, is set to 0.05.

[0132] According to the steps of the present invention, the static voltage stability margin considering the thermal dynamics of the heating system is solved, and the Pareto front obtained by the solution is as follows: Figure 4 As shown, in the static voltage stability margin results considering the thermal dynamics of the heating system, λ H The distribution of operating points of the CHP unit when the value is 1.5 is as follows: Figure 5 As shown, λ HWhen the value is 1.5, the active power output and heat load results of the generator under the four scenarios are as follows: Figure 6 and Figure 7 As shown, the electro-thermal coupling relationship in a combined heat and power (CHP) system can negatively impact voltage stability. However, the thermal inertia of the heating system (especially buildings) can be utilized to increase the operating point of the CHP unit, thereby improving the voltage stability margin of the power system.

[0133] Therefore, this method can comprehensively consider the grid constraints, heating network constraints, and building heat load constraints of the integrated energy system, accurately characterize the thermal dynamic characteristics, thermoelectric coupling, and voltage stability margin of the integrated heat and power energy system, effectively characterize the interaction between the power network and the heating network of the integrated energy system, and realize the assessment of the static voltage stability margin of the integrated energy system.

[0134] This application discloses a static voltage stability margin evaluation system, including:

[0135] Heating system thermal dynamics model module: Constructs a thermal dynamics model of the heating system based on the temperature transmission of the input heating network pipelines and the thermal dynamics of the buildings;

[0136] Thermoelectric Coupled Device Model Module: Establishes a thermoelectric coupled device model based on the operation and coupling constraints of the thermoelectric coupled device;

[0137] Static voltage stability margin model module: Constructs a static voltage stability margin model based on electrical load growth patterns and thermal load growth patterns;

[0138] Calculation module: Combining the heating system thermal dynamics model module, the thermoelectric coupling device model module, and the static voltage stability margin model module, the static voltage stability margin model is solved to obtain the voltage stability margin.

[0139] This application also discloses a terminal device, including a memory, a processor, and a computer program stored in the memory and capable of running on the processor, wherein when the processor executes the computer program, it employs any of the static voltage stability margin evaluation methods described in the above embodiments.

[0140] The terminal device can be a computer device such as a desktop computer, a laptop computer, or a cloud server. The terminal device includes, but is not limited to, a processor and a memory. For example, the terminal device may also include input / output devices, network access devices, and buses.

[0141] The processor can be a central processing unit (CPU). Of course, depending on the actual use, it can also be other general-purpose processors, digital signal processors (DSPs), application-specific integrated circuits (ASICs), off-the-shelf programmable gate arrays (FPGAs), or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. The general-purpose processor can be a microprocessor or any conventional processor, etc., and this application does not limit it in this regard.

[0142] The memory can be an internal storage unit of the terminal device, such as a hard disk or RAM of the terminal device, or an external storage device of the terminal device, such as a plug-in hard disk, smart memory card (SMC), secure digital card (SD), or flash memory card (FC) equipped on the terminal device. Furthermore, the memory can be a combination of internal storage units and external storage devices of the terminal device. The memory is used to store computer programs and other programs and data required by the terminal device. The memory can also be used to temporarily store data that has been output or will be output. This application does not limit this.

[0143] In this terminal device, any one of the static voltage stability margin assessment methods in the above embodiments is stored in the memory of the terminal device and loaded and executed on the processor of the terminal device for convenient use.

[0144] This application also discloses a computer-readable storage medium, which stores a computer program, wherein when the computer program is executed by a processor, it employs any of the static voltage stability margin assessment methods described in the above embodiments.

[0145] The computer program can be stored in a computer-readable medium. The computer program includes computer program code, which can be in the form of source code, object code, executable file, or certain middleware. The computer-readable medium includes any entity or device capable of carrying computer program code, recording media, USB flash drive, portable hard drive, magnetic disk, optical disk, computer memory, read-only memory (ROM), random access memory (RAM), electrical carrier signals, telecommunication signals, and software distribution media, etc. It should be noted that the computer-readable medium includes, but is not limited to, the above-mentioned components.

[0146] In this computer-readable storage medium, any one of the static voltage stability margin assessment methods in the above embodiments is stored in the computer-readable storage medium and loaded and executed on the processor to facilitate the storage and application of the above methods.

[0147] The foregoing has shown and described the basic principles, main features, and advantages of the present invention. Those skilled in the art should understand that the present invention is not limited to the above embodiments. The embodiments and descriptions in the specification are merely illustrative of the principles of the invention. Various changes and modifications can be made to the invention without departing from its spirit and scope, and all such changes and modifications fall within the scope of the claimed invention.

Claims

1. A method for evaluating static voltage stability margin, characterized in that, include: A thermal dynamic model of the heating system is constructed based on the temperature transmission of the heating network pipeline and the thermal dynamics of the building. A thermoelectric coupling device model is established based on the operation and coupling constraints of the thermoelectric coupling device; A static voltage stability margin model is constructed based on the electrical load growth pattern and the thermal load growth pattern: in, , These are the electrical and thermal load factors, respectively. and These represent the active / reactive power of the generator or branch, respectively. and These represent the voltage magnitude and phase of the busbar, respectively. It is thermal energy; This refers to the water temperature or room temperature. For mass flow rate; , and These are constraints on the power system, heating system, and thermoelectric coupling relationship, respectively. The voltage stability margin is obtained by solving the static voltage stability margin model; The construction of the static voltage stability margin model based on the electrical load growth mode and the thermal load growth mode also includes the following steps: Establish a model for electricity load growth patterns: in, and These represent the active power at the current operating point and the safety limit point, respectively. and These are the reactive power at the current operating point and the safety limit point, respectively; This refers to the electrical load factor. Establish a model for heat load growth patterns: in, and These are the heat loads at the current operating point and the safety limit point, respectively. This is the heat load factor; Establish a hydraulic regulation strategy model: in, and Pipelines at the current operating point and the safety limit point, respectively. mass flow rate; To avoid hydraulic instability and pipe corrosion, the water velocity is capped; A static voltage stability margin model is established based on the electrical load growth model, the thermal load growth model, and the hydraulic regulation strategy model. Constructing a thermal dynamics model of a thermal system includes the following steps: Establish a temperature transfer model for heating network pipelines: in, For the set of scheduling periods; For a collection of pipes; parameters , For pipelines Coefficients related to transmission delay; The insulation coefficient; for Constant pipeline ambient temperature; and They are respectively The temperature of the heat medium at the pipeline outlet and inlet at all times; parameter , and The calculation formula is as follows: in, For time intervals; Density of the heat transfer medium; Specific heat capacity of the heat transfer medium; For pipelines The cross-sectional area; For pipelines Length; This refers to the heat loss coefficient of the pipeline. This refers to the mass flow rate of the heat medium in the pipeline. It is a rounding function; Establish a thermal dynamic model of the building: in, A collection of buildings; , and These parameters depend on the building's heat capacity and heat resistance.

2. The static voltage stability margin evaluation method according to claim 1, characterized in that, Solving the static voltage stability margin model to obtain the voltage stability margin involves the following steps: The static voltage stability margin model is optimized as follows: in, For a predefined The constant; initialization and And solve it by following the cyclical steps below; The loop steps are as follows: renew And calculate the mass flow rate. ,parameter , and ; Solve the optimized static voltage stability margin model. If a solution is found, update... Otherwise, update. ; renew ; like Repeat the above cyclical steps; if Exit the loop step.

3. The static voltage stability margin evaluation method according to claim 1, characterized in that, The thermoelectric coupling equipment model includes the operating constraints of the cogeneration unit, the coupling constraints between the cogeneration unit and the heating network, and the water temperature constraints of the heating system.

4. The static voltage stability margin evaluation method according to claim 3, characterized in that, The coupling constraints between the combined heat and power (CHP) unit and the heating network are: in, These represent the thermal power output of the CHP unit. For heat source mass flow rate; and These are the supply water temperature and return water temperature of the heat source, respectively.

5. The static voltage stability margin evaluation method according to claim 3, characterized in that, The water temperature constraint for the heating system is: in, and These are the lower and upper limits of the water supply temperature of the heat source, respectively. and These are the lower and upper limits of the return water temperature of the heat source, respectively.

6. A system applying the static voltage stability margin assessment method as described in any one of claims 1 to 5, characterized in that, include: Heating system thermal dynamics model module: Constructs a thermal dynamics model of the heating system based on the temperature transmission of the input heating network pipelines and the thermal dynamics of the buildings; Thermoelectric Coupled Device Model Module: Establishes a thermoelectric coupled device model based on the operation and coupling constraints of the thermoelectric coupled device; Static voltage stability margin model module: Constructs a static voltage stability margin model based on electrical load growth patterns and thermal load growth patterns; Calculation module: Combining the heating system thermal dynamics model module, the thermoelectric coupling equipment model module, and the static voltage stability margin model module, the static voltage stability margin model is solved to obtain the voltage stability margin.

7. A terminal device, comprising a memory, a processor, and a computer program stored in the memory and capable of running on the processor, characterized in that, The memory stores a computer program that can run on the processor. When the processor loads and executes the computer program, it employs a static voltage stability margin assessment method according to any one of claims 1 to 5.

8. A computer-readable storage medium storing a computer program, characterized in that, When the computer program is loaded and executed by the processor, it employs a static voltage stability margin evaluation method according to any one of claims 1 to 5.

Images