Electro-thermal coupling system wind power absorption capability assessment method and related equipment

Abstract

The invention belongs to the field of electric power systems, and discloses a wind power consumption capability assessment method and related equipment for an electrothermal coupling system, and the method comprises the steps: firstly, carrying out the wind power consumption capability assessment of the electrothermal coupling system based on an electrothermal coupling system wind power consumption capability assessment index, a key index in a primary frequency modulation process, a cogeneration unit operation model and a quasi-one-dimensional operation model of a heat storage system; designing to obtain a target function and a constraint condition, and further completing the construction of a wind power consumption capability evaluation model of the electrothermal coupling system; solving the wind power consumption capability evaluation model of the electrothermal coupling system by considering a non-convex constraint condition, and calculating to obtain a wind power consumption capability evaluation result of the electrothermal coupling system considering frequency safety; in an electrothermal coupling system, the method fully considers the low inertia property of a power system when high-proportion new energy is accessed and the forward promotion effect of heat supply network flexibility transformation on wind power consumption, and the wind power consumption capability of the system is accurately evaluated on the premise of meeting the frequency stability and reliability of the system.

Description

Technical Field

[0001] The present invention belongs to the technical field of electric power systems, and in particular relates to a method for evaluating the wind power absorption capacity of an electric-thermal coupling system and related equipment. Background Art

[0002] Traditional power systems are dominated by thermal power units, which are the main source of carbon emissions in the power system. Transforming thermal power units into combined heat and power (CHP) units is an important way to improve energy efficiency and reduce carbon emissions. The development of CHP units is particularly suitable for areas with heating needs in winter. At the same time, the development of wind power is another effective means of reducing emissions.

[0003] In recent years, the penetration rate of wind power in many regions has been high, which has brought many challenges to the operation of the power system. Specifically, the high proportion of wind power access leads to a decrease in system inertia, affecting the frequency security of the system; and the deep coupling of electricity and heat will also limit the absorption of wind power during the peak heating period and the high wind power generation period at night. Therefore, under the premise of ensuring frequency security, it is very necessary to evaluate the wind power absorption capacity within the operating scale from the perspective of electricity-heat coupling.

[0004] However, existing studies on the assessment of wind power absorption capacity of electric-thermal coupled systems have not considered the impact of high proportion of wind power access on system frequency security, resulting in the existing assessment methods being difficult to adapt to the development and application of new power systems based on new energy in the future. Summary of the invention

[0005] The purpose of the present invention is to provide a method and related equipment for evaluating the wind power absorption capacity of an electrothermal coupling system, so as to solve the technical problem that the existing evaluation method does not take into account the impact of a high proportion of wind power access on the system frequency safety, resulting in difficulty in adapting to the development and application of new power systems based on new energy in the future.

[0006] In order to achieve the above object, the present invention adopts the following technical solution: A method for evaluating wind power absorption capacity of an electric-thermal coupling system, comprising: Based on the evaluation index of wind power absorption capacity of electric-thermal coupling system, key indexes in primary frequency regulation process, operation model of cogeneration unit and quasi-one-dimensional operation model of heat storage system, the objective function and constraint conditions are obtained. Based on the objective function and constraints, a wind power absorption capacity evaluation model for the electric-thermal coupling system is constructed; Based on the non-convex constraints of the wind power accommodation capacity assessment model of the electrothermal coupling system, the wind power accommodation capacity assessment model of the electrothermal coupling system is solved, and the wind power accommodation capacity assessment result of the electrothermal coupling system taking into account frequency safety is obtained.

[0007] Furthermore, the design steps of the wind power absorption capacity evaluation index of the electrothermal coupling system include: The DNE boundary is used as an evaluation index for the wind power absorption capacity of the electrothermal coupling system. The DNE boundary is used to characterize: under the uncertainty of wind power, the electrothermal coupling system does not generate load shedding and can absorb the maximum wind power range. The specific formula is as follows:

[0008]

[0009]

[0010]

[0011] In the formula, It is a wind farm w At the moment t The actual output, For wind farms w At the moment t The wind power curtailment It is a wind farm w At the moment t The prediction error, represents the wind farm collection, and Wind farms w The DNE boundary at time t The lower and upper limits of is the value-at-risk of the distributed robust joint chance constraint, and It is a man-made wind farm w The minimum and maximum allowed DNE boundaries, represents the wind curtailment ratio, It is a fuzzy set based on Wasserstein measure and is used to describe random variables. uncertainty.

[0012] Furthermore, for the primary frequency regulation process on the grid side in the electrothermal coupling system, a mathematical model of key indicators in the primary frequency regulation process is constructed, including: Based on the swing equation, the primary frequency regulation process on the grid side of the electrothermal coupling system is described, and the frequency drop rate constraint condition is constructed; according to the time when the lowest frequency point occurs, the lowest frequency point constraint condition is constructed; at the same time, the quasi-steady-state constraint condition is established; The expression of the frequency reduction rate constraint is as follows:

[0013]

[0014] In the formula, For the period t Internal Node i The power fluctuation at is the maximum frequency drop rate that the electrothermal coupling system can tolerate; represents the system inertia; The expression of the frequency minimum point constraint condition is as follows:

[0015]

[0016]

[0017]

[0018]

[0019] In the formula, and Represents CHP units g and traditional thermal power units u The inertia constant, and CHP units g and traditional thermal power units u 0-1 variable for the switch state, and Respectively represent CHP units g and traditional thermal power units u Maximum power generation capacity; is the rated frequency of the system; and are all constants; and CHP units g and traditional thermal power units u The lowest frequency point; is the total primary frequency regulation reserve capacity of the system at time t; The expression of the quasi-steady-state constraint condition is as follows:

[0020]

[0021] In the formula, is the maximum permissible frequency deviation in quasi-steady state; is the load damping; It is the time period t Internal Node i The electrical load value at is the set of load nodes.

[0022] Furthermore, the operation model of the cogeneration unit is constructed based on the road reconstruction technology, and the specific formula is as follows:

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[0024]

[0025]

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[0036]

[0037] In the formula, and CHP units g In the period t The power generation and heat generation of , and They represent the power generation at the endpoints A, D and J of the operation domain respectively, is the heat generation power at the end point B of the operating domain, It is a CHP unit g The capacity of the bypass retrofit technology installed, and are the slopes of side AB and side BC respectively; is a constant; , and They are 0-1 variables for the unit's on / off status, startup status, and shutdown status. Represents the primary frequency regulation reserve capacity of the CHP unit, and They are the upward reserve and downward reserve capacity used to balance the uncertainty of wind power. , and They are the primary frequency regulation reserve upper limit, the upward reserve capacity upper limit and the downward reserve capacity upper limit. and They are the minimum power-on time and the minimum power-off time. and are the maximum up-climbing rate and the maximum down-climbing rate respectively; The expression of the quasi-one-dimensional operation model of the heat storage system is as follows:

[0038]

[0039]

[0040]

[0041]

[0042]

[0043]

[0044]

[0045]

[0046]

[0047]

[0048]

[0049]

[0050]

[0051]

[0052]

[0053] In the formula, and Thermal storage system e In the period t The charging power and releasing power of and Represent the quality of water in the hot zone and the cold zone respectively, and are the water temperatures in the hot and cold zones, is the comprehensive heat loss coefficient of the heat storage system, is the thermal conductivity of water, represents the heat convection power between the hot zone and the cold zone, and They are the heat power received by the cold zone during heat release and the heat loss of the cold zone during heat charging. is the minimum charging and discharging power of the heat storage system, represents the cross-sectional area of ​​the thermal storage system water tank, and are the lateral areas of the hot zone and the cold zone, respectively, is the height of the pitcher, and Represents the minimum and maximum allowable water temperatures respectively.

[0054] Furthermore, the objective function covers the DNE boundary and wind abandonment rate of all wind farms in a day:

[0055] In the formula, and Wind farms w In the period t The upper and lower bounds of the DNE boundary, is a weighting coefficient used to indicate the importance of each wind farm; μ represents the weight of wind abandonment in the objective function, For wind farms w In the period t The proportion of wind power abandoned; The constraints include power grid flow constraints, thermal network thermal flow constraints, traditional thermal power unit operation constraints and controllable unit uncertainty reserve constraints.

[0056] Furthermore, the steps for constructing the wind power absorption capacity evaluation model of the electrothermal coupling system are as follows: The DNE boundary is incorporated into the objective function of the wind power absorption capacity assessment model; the distributed blue stick joint chance constraint is used to characterize random variables such as the DNE boundary, branch power, and controllable unit standby; at the same time, considering the frequency safety constraints, power grid flow constraints, heat network energy flow constraints, and conventional thermal power unit operation constraints, an evaluation model for the wind power absorption capacity of the electric-thermal coupling system is constructed.

[0057] Furthermore, the non-convex constraints include distributed robust joint chance constraints containing uncertainty on the left or uncertainty on the right, and constraints containing differentials; the non-convex constraints are reconstructed to convert the high-dimensional non-convex model into a mixed integer second-order cone programming model; finally, the reconstructed mixed integer second-order cone programming model is solved to obtain an evaluation result of the wind power absorption capacity of the electrothermal coupling system that takes into account frequency safety.

[0058] A wind power absorption capacity evaluation system for an electric-thermal coupling system, comprising: The objective function and constraint design module is used to obtain the objective function and constraint conditions based on the wind power absorption capacity evaluation index of the electric-thermal coupling system, the key indicators in the primary frequency regulation process, the operation model of the cogeneration unit and the quasi-one-dimensional operation model of the heat storage system; Evaluation model building module, used to build an evaluation model for wind power absorption capacity of electric-thermal coupling system based on objective function and constraint conditions; The wind power absorption capacity assessment module is used to solve the wind power absorption capacity assessment model of the electrothermal coupling system based on the non-convex constraints of the wind power absorption capacity assessment model of the electrothermal coupling system, and obtain the wind power absorption capacity assessment result of the electrothermal coupling system that takes into account frequency safety.

[0059] A device comprising: Memory for storing computer programs; A processor is used to implement the steps of the above-mentioned method for evaluating the wind power absorption capacity of the electrothermal coupling system when executing the computer program.

[0060] A computer-readable storage medium stores a computer program, which, when executed by a processor, is used to implement the steps of the above-mentioned method for evaluating the wind power absorption capacity of an electrothermal coupling system.

[0061] Compared with the prior art, the present invention has the following beneficial effects: The present invention provides a method for evaluating the wind power absorption capacity of an electrothermal coupling system. The method first designs an objective function and constraint conditions based on the evaluation index of the wind power absorption capacity of the electrothermal coupling system, key indicators in the primary frequency regulation process, an operation model of a cogeneration unit and a quasi-one-dimensional operation model of a heat storage system, and then completes the construction of an evaluation model for the wind power absorption capacity of the electrothermal coupling system; considering non-convex constraint conditions, the evaluation model for the wind power absorption capacity of the electrothermal coupling system is solved, and an evaluation result of the wind power absorption capacity of the electrothermal coupling system taking into account frequency safety is calculated; in the electrothermal coupling system, the method fully takes into account the low inertia property of the power system when a high proportion of new energy is connected, and the positive promoting effect of the flexibility transformation of the heat network on wind power absorption, and accurately evaluates the wind power absorption capacity of the system under the premise of meeting the frequency stability and reliability of the system.

[0062] Preferably, in the present invention, the DNE boundary is introduced as an evaluation index for wind power absorption capacity, which can accurately reflect the wind power absorption capacity of the electrothermal coupling system under wind power uncertainty; factors such as the actual output of the wind farm, abandoned wind power, and prediction error are taken into account to improve the accuracy and practicality of the evaluation; at the same time, the introduction of distributed robust joint chance constraints makes the evaluation results more robust and able to cope with the impact of wind power uncertainty.

[0063] Preferably, in the present invention, a mathematical model of key indicators is constructed for the primary frequency regulation process on the grid side of the electrothermal coupling system, including frequency drop rate constraints, frequency minimum point constraints and quasi-steady-state constraints; by considering these constraints, it can be ensured that the evaluation results more accurately reflect the wind power absorption capacity of the electrothermal coupling system while meeting the frequency safety requirements.

[0064] Preferably, in the present invention, the introduction of the cogeneration unit operation model and the quasi-one-dimensional operation model of the heat storage system enables the evaluation method to more accurately reflect the actual operation conditions of the cogeneration unit and the heat storage system in the electric-thermal coupling system, thereby improving the accuracy and reliability of the evaluation results.

[0065] Preferably, in the present invention, the objective function covers the DNE boundaries and wind abandonment rates of all wind farms within a day, and can comprehensively reflect the wind power absorption capacity of the electrothermal coupling system and the utilization efficiency of wind power resources; the introduction of constraints ensures that the evaluation results more accurately reflect the wind power absorption capacity of the electrothermal coupling system while meeting the requirements of power grid current, thermal network thermal flow, operation of traditional thermal power units and uncertain standby of controllable units.

[0066] Preferably, in the present invention, the steps of constructing the wind power absorption capacity assessment model of the electric-thermal coupling system include incorporating the DNE boundary into the objective function, using distributed robust joint chance constraints to characterize random variables, and considering constraints such as frequency safety, grid flow, heat network energy flow, and operation of conventional thermal power units.

[0067] Preferably, in the present invention, the reconstruction and solution method of non-convex constraints improves the flexibility and applicability of the evaluation method, and can adapt to different evaluation needs and scenarios; the non-convex constraints in the evaluation model are reconstructed and converted into a mixed integer second-order cone programming model, thereby reducing the difficulty of solution and computational complexity. BRIEF DESCRIPTION OF THE DRAWINGS

[0068] Figure 1 A flow chart of a method for evaluating wind power absorption capacity of an electrothermal coupling system provided in an embodiment of the present invention; Figure 2 A schematic diagram of a frequency modulation process provided by an embodiment of the present invention; Figure 3 The operation domain of the CHP unit including the bypass compensation technology provided by the embodiment of the present invention; Figure 4 Schematic diagram of variables of the thermal energy storage operation model provided in an embodiment of the present invention, wherein (a) is heat charging; (b) is heat release; Figure 5 A schematic diagram of variables in the calculation of heat network energy flow provided by an embodiment of the present invention; Figure 6 A schematic diagram of a test system provided by an embodiment of the present invention; Figure 7 A comparison diagram of the DNE boundary provided by the embodiment of the present invention and the existing method, wherein (a) is W1; (b) is W2; Figure 8 A comparison chart of frequency indicators provided by an embodiment of the present invention and an existing method, wherein (a) is the frequency drop rate; (b) is the lowest frequency point; Fig. 9 A flow chart of a method for evaluating wind power absorption capacity of an electrothermal coupling system provided by the present invention; Fig.10 A schematic structural diagram of a wind power absorption capacity evaluation system for an electrothermal coupling system provided by the present invention. DETAILED DESCRIPTION

[0069] Example 1 As described in the background technology, existing studies on the assessment of wind power absorption capacity of electric-thermal coupling systems have not considered the impact of high proportion of wind power access on system frequency security, resulting in existing assessment methods being difficult to adapt to the development and application of new power systems based on new energy in the future.

[0070] In order to solve the above problem, the present invention provides a method for evaluating the wind power absorption capacity of an electrothermal coupling system. This method can fully consider the low inertia properties of the new power system and the positive promoting effect of the flexibility transformation of the thermal network on wind power absorption in the evaluation of the wind power absorption capacity of the electrothermal coupling system, and accurately evaluate the wind power absorption capacity of the system under the premise of meeting the system frequency stability and reliability.

[0071] like Figure 1 As shown, this embodiment provides a method for evaluating the wind power absorption capacity of an electrothermal coupling system. This evaluation method takes into account frequency safety, that is, focuses on the frequency safety of the electrothermal coupling system, and specifically includes the following steps: S1. Design evaluation indicators for wind power absorption capacity of electric-thermal coupling system, including: S1.1. Evaluation of wind power absorption capacity based on distributed robust joint opportunity constraints Considering the difficulties that wind power uncertainty brings to the evaluation of wind power consumption capacity, the present invention uses the distributed robust joint opportunity constraint method to characterize wind power uncertainty. The method provides a flexible consumption capacity evaluation boundary, that is, combining the system operation reliability with the wind power consumption capacity demand to determine the consumption boundary under different conservative degrees.

[0072] S1.2. Establishing a mathematical model of the DNE boundary The DNE boundary of the wind farm is expressed by formulas (1)-(4). Formula (1) is a distributed robust joint chance constraint, which represents the fuzzy set Under the given uncertainty environment, the probability that the wind power connected to the grid is within the DNE boundary should be no less than 1- Formula (2) constrains the range of the DNE boundary through artificially given upper and lower limits. Formula (3) represents that the actual wind power consists of the wind power forecast value and the random wind power forecast error. Formula (4) gives the linear relationship between the abandoned wind power and the actual wind power.

[0073] (1) (2) (3) (4) In the formula, It is a wind farm w At the moment t The actual output, For wind farms w At the moment t The wind power curtailment It is a wind farm w At the moment t The prediction error, represents the wind farm collection, and Wind farms w The DNE boundary at time t The lower and upper limits of is the value-at-risk of the distributed robust joint chance constraint, and It is a man-made wind farm w The minimum and maximum allowed DNE boundaries, Represents the proportion of wind power abandoned. It is a fuzzy set based on Wasserstein measure and is used to describe random variables. uncertainty.

[0074] S2. For the primary frequency regulation on the grid side of the electric-thermal coupling system, a mathematical model of key indicators in the frequency regulation process is proposed, including: S2.1. Selecting the key frequency safety indicators in the electrothermal coupling system When an unplanned frequency fluctuation occurs on the grid side of the electrothermal coupling system, its frequency change curve is as follows: Figure 2 Among them, the indicators that have a key impact on system safety include: frequency drop rate, frequency minimum point and quasi-steady-state frequency.

[0075] The frequency drop rate is the slope of the frequency curve. If the frequency drop rate exceeds the allowable range, it may trigger the relay protection and cause serious consequences such as machine tripping and load shedding. The magnitude of the frequency drop rate depends on the power fluctuation and the inertia value of the system.

[0076] The frequency minimum point is the lowest frequency in the primary frequency regulation process. If the frequency drops rapidly and is lower than the allowed frequency minimum point, low-frequency load shedding may be triggered in the electrothermal coupling system. Therefore, the frequency minimum point should be strictly limited to a safe range. The frequency minimum point is largely determined by the system inertia and the response speed of the primary frequency regulation resources.

[0077] Quasi-steady-state frequency is the frequency value of the power system at the end of primary frequency regulation, which is used to measure the steady-state frequency safety. In the quasi-steady state, the electrothermal coupling system re-establishes power balance, but the quasi-steady-state frequency is still lower than the rated frequency. This indicator is related to the power adjustment and load damping of primary frequency regulation.

[0078] S2.2. Derivation of the frequency drop rate constraint of the electrothermal coupling system When there is an unplanned power disturbance, the grid-side frequency deviation of the electric-thermal coupling system is expressed by the swing equation (5): (5) In the formula, Indicates time period t Internal time τ The system frequency offset, is the load damping, and It is the time period t Internal Node i The electrical load value at is the set of load nodes, and It is the time period t Internal Node i The power fluctuation at and They are t CHP units during the period g and traditional thermal power units u Power adjustment. and They are respectively a collection of CHP units and traditional thermal power units. Represents the system inertia and can be calculated by formula (6): (6) In the formula, and Represents CHP units g and traditional thermal power units u The inertia constant, and They represent CHP units respectively. g and traditional thermal power units u 0-1 variable for the switch state, and Respectively represent CHP units g and traditional thermal power units u Maximum power generation. is the rated frequency of the system.

[0079] The maximum frequency drop rate occurs at τ = 0, based on this condition, the frequency drop rate constraint can be derived from the swing equation as (7): (7) In the formula, Indicates the maximum frequency drop rate that the system can tolerate.

[0080] S2.3. Derivation of the frequency minimum point constraint of the electrothermal coupling system Assuming that the power adjustment of CHP units and traditional thermal power units is linear growth, solving the swing equation (5), we can get the system frequency offset in one frequency regulation process: for: (8) In the formula, for simplicity, let and , Indicates the dead zone of the unit. is the dead time, The length of time required to provide spare capacity for the unit; Represents the total primary frequency regulation reserve capacity of the system at time t; It represents the primary frequency regulation reserve capacity reserved by the cogeneration unit g at time t; It represents the primary frequency regulation reserve capacity reserved by the traditional thermal power unit u at time t.

[0081] When the system frequency drops to the lowest point, the frequency offset for τ The derivative of is 0, and based on this condition, the time when the lowest frequency point appears is solved : (9) Substituting formula (9) into formula (8), we can obtain the constraint condition (10) about the lowest frequency point: (10) In the formula, It is the only solution when formula (10) takes the equal sign. When formula (10) is established, formula (11) satisfies the following conditions: (11) Finally, the Big M method is used to deal with the implicit bilinear term in formula (11): and , and replace the frequency minimum point constraint (11) by formulas (12)-(16): (12) (13) (14) (15) (16) In the formula, and are all sufficiently large normal numbers.

[0082] S2.4. Derivation of quasi-steady-state frequency constraints for electrothermal coupling systems When the frequency modulation ends, the system reaches the quasi-steady-state frequency, and the frequency drop rate is equal to 0. Under this condition, the constraint condition on the quasi-steady-state frequency can be obtained through the swing equation: (17) In the formula, It is the maximum allowable frequency deviation in quasi-steady state.

[0083] S3. Establish an operation model of the cogeneration unit considering the bypass transformation technology, and a quasi-one-dimensional operation model of the heat storage system, including: S3.1. Establishment of CHP unit operation model considering bypass modification technology Bypass modification technology is an effective means to improve the operating flexibility of CHP units. This technology can improve the waste heat circulation efficiency generated by the unit's power generation, thereby improving the heat production capacity of the CHP unit when the power generation power is low. Figure 3 The operating domain of the CHP unit is shown, where the quadrilateral ABCD is the operating domain before the transformation, and the polygon ABFECD is the operating domain after the transformation, and the shaded part is the operating domain newly added through the transformation.

[0084] The operation model of the CHP unit with bypass transformation technology is shown in (18)-(32). Formulas (18)-(23) describe the operating domain boundaries DC, CE, EF, FB, BA and AD respectively. These equations take into account the reserve capacity and electric and thermal power, and jointly constrain the operating points within the operating domain. Formulas (24)-(26) respectively constrain the capacity of primary frequency regulation reserve, upward reserve and downward reserve. Formulas (27)-(28) give the logical relationship between start-up, shutdown and the switch state of the CHP unit. Formulas (29)-(30) respectively constrain the minimum start-stop duration. Formulas (31)-(32) respectively constrain the unit's climbing rate.

[0085] (18) (19) (20) (twenty one) (twenty two) (twenty three) (twenty four) (25) (26) (27) (28) (29) (30) (31) (32) In the formula, and CHP units g In the period t The power generation and heat generation of , and They represent the power generation at the endpoints A, D and J of the operation domain respectively, is the heat generation power at the end point B of the operating domain, It is a CHP unit g The capacity of the bypass retrofit technology installed, and are the slopes of side AB and side BC respectively. is a sufficiently large positive number. , and They are 0-1 variables for the unit's on / off status, startup status, and shutdown status. Represents the primary frequency regulation reserve capacity of the CHP unit, and They are the upward reserve and downward reserve capacity used to balance the uncertainty of wind power. , and They are the primary frequency regulation reserve upper limit, the upward reserve capacity upper limit and the downward reserve capacity upper limit. and They are the minimum power-on time and the minimum power-off time. and They are the maximum up-climbing rate and the maximum down-climbing rate respectively.

[0086] S3.2. Establishing a quasi-one-dimensional operation model of the heat storage system The main component of the thermal storage system is the thermal storage tank, which contains a hot water area and a cold water area separated by a thermocline layer, e.g. Figure 4 As shown in Figure 2, when the heat storage system is charged, the thermocline layer drops, the hot water area expands and the cold water area shrinks, as shown in Figure 2. Figure 4 (a); When the heat storage system releases heat, the thermocline rises, the hot water area shrinks and the cold water area expands, such as Figure 4 (b). During the charging or releasing process, due to the time delay of heat convection, the process cannot be completed instantly, but needs to go through a dynamic process. The present invention establishes a quasi-one-dimensional operation model of the heat storage system, considering the dynamic process of the heat storage system, and the model is shown in (33)-(48). Formulas (33)-(34) describe the relationship between the mass, energy and thermal power of the hot zone and the cold zone respectively through ordinary differential equations. Formulas (35)-(36) respectively represent the changes in mass of the hot zone and the cold zone during the charging and releasing processes. Formula (37) limits the total mass of water in the hot zone and the cold zone, and formula (38) ensures the non-negativity of the mass of water. Formulas (39)-(40) ensure the daily circulation of thermal energy in the heat storage system by limiting the initial and final states of mass and temperature. Formulas (41)-(42) calculate the charging and releasing power of the heat storage system, and formulas (43)-(44) derive the thermal power of the cold zone in the charging and releasing stages respectively. Formula (45) constrains the minimum charging and discharging power of the heat storage system. Formula (46) calculates the heat convection power between the hot zone and the cold zone. Formula (47) ensures a single operating state of the heat storage system. Formula (48) limits the average temperature to an allowable range.

[0087] (33) (34) (35) (36) (37) (38) (39) (40) (41) (42) (43) (44) (45) (46) (47) (48) In the formula, and Thermal storage system e In the period t The charging power and releasing power of and Represent the quality of water in the hot zone and the cold zone respectively, and are the water temperatures in the hot and cold zones, is the comprehensive heat loss coefficient of the heat storage system, is the thermal conductivity of water, represents the heat convection power between the hot zone and the cold zone, and They are the heat power received by the cold zone during heat release and the heat loss of the cold zone during heat charging. is the minimum charging and discharging power of the heat storage system, represents the cross-sectional area of ​​the thermal storage system water tank, and are the lateral areas of the hot zone and the cold zone, respectively. is the height of the pitcher, and Represents the minimum and maximum allowable water temperatures respectively.

[0088] S4. Design objective functions and constraints to build a wind power absorption capacity assessment model for the electric-thermal coupling system considering frequency safety, including: S4.1. Design of objective function of wind power absorption capacity evaluation model for electric-thermal coupling system The purpose of the model is to evaluate the wind power absorption capacity of the coupled electric and thermal system and to design an objective function (49) that covers the DNE boundaries and wind curtailment rates of all wind farms within a day: (49) In the formula, and Wind farms w In the period t The upper and lower bounds of the DNE boundary, is a weighting coefficient used to indicate the importance of each wind farm. μ represents the weight of wind abandonment in the objective function, For wind farms w In the period t The proportion of wind power abandoned.

[0089] S4.2. Grid flow constraints for establishing wind power absorption capacity assessment model for electric-thermal coupling system The DC power flow is used to describe the power flow constraints on the grid side of the electric-thermal coupling system, and the uncertainty in the power flow is characterized based on the distributed robust joint opportunity constraint. Formula (50) represents the power balance on the grid side, which takes into account the uncertainty of wind power and the upward / downward power adjustment of the controllable units. Formula (52) is the distributed robust joint opportunity constraint, which represents the fuzzy set Under the given uncertainty environment, the probability of meeting the branch power safety constraint should not be lower than the confidence level 1- .

[0090] (50) (51) In the formula, and After considering the upward / downward power adjustment, the CHP unit g Compared with traditional thermal power units u The power generation capacity, is the load power at node i. , , and is the CHP unit corresponding to the transfer matrix g , Traditional thermal power units u , Wind Farm w and load i With branch l The submatrix of association relationships. represents the value-at-risk of the distributed robust joint chance constraint.

[0091] S4.3. Establishment of thermal network thermal flow constraints for wind power absorption capacity assessment model of electric-thermal coupling system Based on the constant flow rate variable temperature control strategy, the thermal flow constraints (52)-(60) on the heat network side of the electric-thermal coupling system are established to describe the working fluid temperature, working fluid flow rate and other characteristics in the heat network. Formula (52) calculates the heat generation power of the CHP unit at the heat source node, and formulas (53)-(54) respectively model the thermal power of the load nodes connected to and not connected to the heat storage system. Formula (55) ensures the mass conservation of the working fluid during the transmission process of any branch. Formula (56) ensures the energy conservation when the working fluids of different branches converge into the same node. Formula (57) calculates the inlet temperature of the pipeline based on the temperature of the first node, formula (58) takes into account the time delay of mass transmission and obtains the outlet temperature of the pipeline, while formula (59) corrects the working fluid temperature at the outlet by considering the temperature loss during mass transmission. Formula (60) constrains the temperature boundary of the working fluid.

[0092] (52) (53) (54) (55) (56) (57) (58) (59) (60) In the formula, and The nodes are k The heat generation power and heat load power of the CHP unit at represents the set of nodes in the heat network, and are respectively the charging power and releasing power of the heat storage system to the heat network, and are the working fluid flow rates at the CHP unit and heat load, respectively. and Represents the water supply network nodes k Injection temperature and return network node k The outflow temperature at and Water supply network nodes k Outflow temperature and return network node k The injection temperature at Indicates branch b The working fluid flow rate, and Node k is the set of branches of the start and end nodes, is the working fluid temperature of the water supply network (if x=S) or the return network (if x=R), and Branch b The working fluid inflow temperature and working fluid outflow temperature, Represents a branch where transmission temperature loss is ignored b The working fluid outlet temperature, is the specific heat capacity of the working fluid, is the density of the working fluid, and Branch b length and cross-sectional area, is the heat transfer coefficient of the pipe, , and are the number of working fluid blocks, and are the total working fluid mass in the pipeline respectively. The above variables can be obtained by Figure 5 shown.

[0093] S4.4. Establishing the traditional thermal power unit operation constraints of the wind power absorption capacity assessment model of the electric-thermal coupling system For traditional thermal power units that only generate electricity but not heat, their operating constraints are shown in (61)-(71). Formulas (61)-(62) respectively limit the maximum and minimum power output of traditional thermal power units when considering the primary frequency regulation reserve capacity. Formula (63) constrains the upper limit of the power generation power and primary frequency regulation reserve of traditional thermal power units. Formulas (64)-(65) respectively limit the upper limit of the upward reserve and downward reserve of traditional thermal power units. Formulas (66)-(67) define the logical relationship between the switch, start-up and shutdown states of traditional thermal power units. Formulas (68)-(69) respectively limit the minimum start-up and stop duration of traditional thermal power units. Formulas (70)-(71) respectively constrain the upward and downward climbing rates of traditional thermal power units.

[0094] (61) (62) (63) (64) (65) (66) (67) (68) (69) (70) (71) In the formula, Represents traditional thermal power unit u In the period t The power generation capacity, , and They are 0-1 variables representing the switch, start and shutdown of the unit. and It is a traditional thermal power unit u The maximum and minimum output of It is the primary frequency regulation reserve capacity of traditional thermal power units. and Indicates uphill and downhill climbing reserve, , and They are the maximum permissible primary frequency regulation reserve, upward ramp reserve and downward ramp reserve of traditional thermal power units. and Indicates the minimum startup and shutdown time. and It is the upper limit of climbing up and climbing down.

[0095] S4.5. Establishment of uncertainty reserve constraints for controllable units in the wind power absorption capacity assessment model of the electric-thermal coupling system Due to the strong uncertainty of wind power, it is necessary to use units equipped with automatic power generation control systems to offset wind power prediction errors, thereby ensuring the balance of power supply and demand in the electric-thermal coupling system. Formulas (72)-(73) represent the power generation of CHP units and traditional thermal power units after adjustment based on the affine local strategy. Formulas (74)-(75) ensure that the wind power prediction error can be completely offset by the power adjustment of the controllable units. Fuzzy set Under the given uncertainty environment, the distributed robust joint chance constraints (76)-(77) respectively indicate that the risk that the reserve capacity of CHP units and traditional thermal power units cannot offset the wind power forecast error should not be less than the given confidence level 1- and 1- .

[0096] (72) (73) (74) (75) (76) (77) In the formula, and CHP units g and traditional thermal power units u The coefficient vector involved in power balancing, each element in the vector and Indicates CHP unit g and traditional thermal power units u For wind farm w The prediction error The response, and , is the number of wind farms in the system. and are all risk values ​​constrained by the joint chance constraint.

[0097] S5. Considering the non-convex constraints in the model, a solution method for the distributed robust joint chance constrained optimization model is designed, including: S5.1. Reconstructing the distributed robust joint chance constraint with uncertainty on the left The distributed robust joint chance constraints (51), (76) and (77) with uncertainty on the left can be expressed in the following general form: (78) In the formula, is the first The coefficient vector corresponding to the constraints, represents a set of constraints, is the transpose of the matrix, x and ξ are vectors of decision variables and random variables, respectively. is the risk value.

[0098] The non-convex constraints (78) can be transformed into the following set of mixed integer constraints (79)-(84): (79) (80) (81) (82) (83) (84) In the formula, , and is an auxiliary variable, represents a sufficiently large positive number, n Representative sample set The number in is the number of samples in the set.

[0099] S5.2. Reconstructing the distributed robust joint chance constraint with uncertainty on the right side The distributed robust joint chance constraint (1) with uncertainty on the right side can be written in the following general form: (85) In the formula, is the risk value.

[0100] The non-convex constraints (85) can be transformed into the following mixed integer programming (86)-(89): (86) (87) (88) (89) In the formula, , and is an auxiliary variable, is a sufficiently large normal number.

[0101] S5.3. Reconstructing constraints involving differentials For the constraints (33)-(36) containing differentials, they can be transformed into the following mixed integer programming: (90) (91) (92) (93) In the formula, is the scheduling time resolution of the electrothermal coupling system.

[0102] S5.4. Reconstructing constraints involving bilinear terms For constraints (21)-(22), (41)-(44) and (48) containing bilinear terms, they can be expressed in the following general form: (94) In the formula, and is a continuous variable, z is a 0-1 variable.

[0103] According to the Big M method, (94) can be transformed into (95)-(96): (95) (96) In the formula, Λ represents a sufficiently large positive constant.

[0104] For constraints (90)-(91) containing quadratic terms, the quadratic terms can be expressed in the following general form: (97) In the formula, , and are all continuous decision variables.

[0105] Using the McCormick Envelope method, (97) is transformed into the following set of mixed integer programming: (98) (99) (100) (101) (102) In the formula, , , and The variables are and The upper and lower limits of .

[0106] S5.5. Summary of the mixed-integer second-order cone model After the above reconstruction process, the increased-dimensional non-convex model can be converted into a mixed-integer second-order cone programming model. The objective function and constraints contained in the mixed-integer second-order cone programming model are summarized as (103). The model can be solved using commercial solving software.

[0107] (103) The following uses the test system in Table 1 as an example to compare the performance of the existing method and the method of this embodiment.

[0108] First, a brief introduction to the test system is given: the test system consists of a wind farm, CHP units, traditional thermal power units, a heat storage system, electrical loads and thermal loads. The system topology is as follows: Figure 6The capacity of each device is shown in Table 1, the total power load is 385MW, and the total thermal load is 31MW. Other parameters in the simulation are shown in Table 2. The time scale of the daily wind power forecast curve, daily load curve, and daily thermal load curve selected in the simulation is 24h, and the time resolution is 1 hour. All simulations are completed on the MATLAB platform and solved using the GUROBI solver.

[0109] Table 1 shows the capacity of each device

[0110] Table 2 shows other parameters in the simulation

[0111] The following three schemes are used for simulation analysis: Solution 1: The wind power absorption capacity assessment method of the electric-thermal coupling system considering frequency constraints proposed in this application; Scheme 2: wind power absorption capacity assessment method for electric-thermal coupling system ignoring dynamic frequency constraints (7) and (10); Solution 3: Ignore the bypass compensation technology of the CHP unit and the quasi-one-dimensional model of the heat storage system, and use the commonly used heat storage system model that ignores the dynamic process to evaluate the wind power absorption capacity of the electric-thermal coupling system.

[0112] Figure 7 The DNE boundaries of wind farms W1 and W2 obtained by Scheme 1 and Scheme 2 are compared. In Scheme 1, when the frequency constraint is introduced into the wind power absorption capacity evaluation, the DNE boundaries of the two wind farms are narrowed in the midnight period. To quantitatively measure the bandwidth of the DNE boundary, the first term of the objective function (49) is used To quantify. In Scheme 1 and Scheme 2 F 1 The values ​​of are 600.75 MW and 610.01 MW, respectively. This can be explained by the unit combination schemes in Tables 3 and 4. Table 4 shows that due to the lack of frequency maintenance tasks, U1 and U2 are shut down respectively at midnight when the power demand is low, allowing the electric-thermal coupling system to absorb more wind power. In contrast, as shown in Table 3, due to system inertia limitations, only U2 with a smaller capacity is shut down at the 4th and 5th hours. Therefore, the unit combination in Scheme 2, which ignores frequency safety, is more flexible in reducing load, which is conducive to wind power acceptance. Specifically, the daily wind power abandonment rates of Scheme 1 and Scheme 2 are 4.98% and 3.37%, respectively.

[0113] Table 3 shows the unit combination scheme 1

[0114] Table 4 shows the unit combination scheme 2

[0115] However, the scheduling scheme of Scheme 2 is not safe in terms of frequency stability. Figure 8 The frequency change rate and minimum frequency index of Scheme 1 and Scheme 2 throughout the day are compared. It can be observed that Scheme 1 strictly ensures frequency safety during the entire time period, but when there are different unit combination schemes in Tables 3 and 4, the frequency change rate of Scheme 2 violates . This shows that the unit combination scheme in Scheme 1 is able to withstand the sharp drop in frequency. More seriously, the frequency minimum point in Scheme 2 violates the lower limit of 49.5 Hz in all periods due to system inertia and insufficient primary frequency regulation reserve. Compared with Scheme 1, the daily primary frequency regulation reserve in Scheme 2 is reduced by 35.45%. These comparison results show that the DNE boundary in Scheme 1 can ensure the frequency security of the electric-thermal coupling system under an acceptable wind power curtailment rate.

[0116] In addition, by comparing Scheme 1 and Scheme 3, the impact of the flexibility transformation of the heating network on wind power consumption can be analyzed. The daily wind energy curtailment rates in Scheme 1 and Scheme 3 are 4.98% and 10.10%, respectively. The significant wind curtailment in Scheme 3 is due to the insufficient flexibility of CHP unit G1. In Scheme 3, the power generation and primary frequency regulation reserve with G1 are limited by Figure 3 This constraint limits its ability to adjust downward to accommodate large amounts of wind power. In contrast, the CHP units in Scenario 1 operate at 13 times a day. Figure 3 This allows it to reduce power generation during peak wind hours while maintaining thermal energy supply to accommodate more wind energy.

[0117] This embodiment provides a method for evaluating the wind power absorption capacity of an electrothermal coupling system. In the evaluation of the wind power absorption capacity of the electrothermal coupling system, the low inertia property of the new power system and the positive promoting effect of the flexibility transformation of the thermal network on wind power absorption can be fully considered, and the wind power absorption capacity of the system can be accurately evaluated under the premise of meeting the system frequency stability and reliability.

[0118] Example 2 like Fig. 9 As shown, this embodiment provides a method for evaluating the wind power absorption capacity of an electrothermal coupling system, comprising the following steps: Based on the evaluation index of wind power absorption capacity of electric-thermal coupling system, key indexes in primary frequency regulation process, operation model of cogeneration unit and quasi-one-dimensional operation model of heat storage system, the objective function and constraint conditions are obtained. Based on the objective function and constraints, a wind power absorption capacity evaluation model for the electric-thermal coupling system is constructed; Based on the non-convex constraints of the wind power accommodation capacity assessment model of the electrothermal coupling system, the wind power accommodation capacity assessment model of the electrothermal coupling system is solved, and the wind power accommodation capacity assessment result of the electrothermal coupling system taking into account frequency safety is obtained.

[0119] like Fig.10 As shown, this embodiment also provides a wind power absorption capacity assessment system for an electrothermal coupling system, including: an objective function and constraint condition design module, which is used to obtain the objective function and constraint conditions based on the electrothermal coupling system wind power absorption capacity assessment index, the key indicators in the primary frequency regulation process, the cogeneration unit operation model and the quasi-one-dimensional operation model of the heat storage system; an assessment model construction module, which is used to construct the electrothermal coupling system wind power absorption capacity assessment model based on the objective function and the constraint conditions; a wind power absorption capacity assessment module, which is used to solve the electrothermal coupling system wind power absorption capacity assessment model based on the non-convex constraint conditions of the electrothermal coupling system wind power absorption capacity assessment model, and obtain the electrothermal coupling system wind power absorption capacity assessment result that takes into account frequency safety.

[0120] The present invention also provides a device, comprising: a memory for storing a computer program; and a processor for implementing the steps of the method for evaluating the wind power absorption capacity of an electrothermal coupling system when executing the computer program.

[0121] When the processor executes the computer program, the steps of evaluating the wind power absorption capacity of the above-mentioned electrothermal coupling system are implemented, for example: based on the evaluation index of the wind power absorption capacity of the electrothermal coupling system, the key index in the primary frequency regulation process, the operation model of the cogeneration unit and the quasi-one-dimensional operation model of the heat storage system, the objective function and the constraint conditions are obtained; based on the objective function and the constraint conditions, the wind power absorption capacity evaluation model of the electrothermal coupling system is constructed; based on the non-convex constraint conditions of the wind power absorption capacity evaluation model of the electrothermal coupling system, the wind power absorption capacity evaluation model of the electrothermal coupling system is solved to obtain the wind power absorption capacity evaluation result of the electrothermal coupling system taking into account frequency safety.

[0122] Alternatively, when the processor executes the computer program, the functions of each module in the above system are implemented, for example: an objective function and constraint design module, which is used to obtain the objective function and constraint conditions based on the wind power absorption capacity evaluation index of the electric thermal coupling system, the key indicators in the primary frequency regulation process, the cogeneration unit operation model and the quasi-one-dimensional operation model of the heat storage system; an evaluation model construction module, which is used to construct the wind power absorption capacity evaluation model of the electric thermal coupling system based on the objective function and the constraint conditions; a wind power absorption capacity evaluation module, which is used to solve the wind power absorption capacity evaluation model of the electric thermal coupling system based on the non-convex constraint conditions of the wind power absorption capacity evaluation model of the electric thermal coupling system, and obtain the wind power absorption capacity evaluation result of the electric thermal coupling system that takes into account frequency safety.

[0123] Exemplarily, the computer program may be divided into one or more modules / units, which are stored in the memory and executed by the processor to complete the present invention. The one or more modules / units may be a series of computer program instruction segments capable of completing preset functions, and the instruction segments are used to describe the execution process of the computer program in the wind power absorption capacity assessment device of the electric-thermal coupling system. For example, the computer program can be divided into an objective function and constraint design module, an evaluation model construction module and a wind power absorption capacity evaluation module; the specific functions of each module are as follows: an objective function and constraint design module, which is used to obtain the objective function and constraints based on the wind power absorption capacity evaluation indicators of the electric thermal coupling system, the key indicators in the primary frequency regulation process, the cogeneration unit operation model and the quasi-one-dimensional operation model of the heat storage system; an evaluation model construction module, which is used to construct an electric thermal coupling system wind power absorption capacity evaluation model based on the objective function and constraints; a wind power absorption capacity evaluation module, which is used to solve the electric thermal coupling system wind power absorption capacity evaluation model based on the non-convex constraints of the electric thermal coupling system wind power absorption capacity evaluation model, and obtain the electric thermal coupling system wind power absorption capacity evaluation result that takes into account frequency safety.

[0124] The wind power absorption capacity assessment device of the electrothermal coupling system can be a computing device such as a desktop computer, a notebook, a PDA, and a cloud server. The wind power absorption capacity assessment device of the electrothermal coupling system can include, but is not limited to, a processor and a memory. Those skilled in the art can understand that the above is an example of a wind power absorption capacity assessment device of an electrothermal coupling system, and does not constitute a limitation on the wind power absorption capacity assessment device of the electrothermal coupling system, and can include more components than the above, or a combination of certain components, or different components. For example, the wind power absorption capacity assessment device of the electrothermal coupling system can also include input and output devices, network access devices, buses, etc.

[0125] The processor may be a central processing unit (CPU), or other general-purpose processors, digital signal processors (DSP), application-specific integrated circuits (ASIC), field-programmable gate arrays (FPGA) or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. The general-purpose processor may be a microprocessor or the processor may be any conventional processor, etc. The processor is the control center of the wind power absorption capacity assessment of the electrothermal coupling system, and uses various interfaces and lines to connect various parts of the entire electrothermal coupling system wind power absorption capacity assessment device.

[0126] The memory can be used to store the computer program and / or module, and the processor implements various functions of the wind power absorption capacity assessment device of the electrothermal coupling system by running or executing the computer program and / or module stored in the memory, and calling the data stored in the memory.

[0127] The memory may mainly include a program storage area and a data storage area, wherein the program storage area may store an operating system, an application required for at least one function (such as a sound playback function, an image playback function, etc.), etc.; the data storage area may store data created according to the use of the mobile phone (such as audio data, a phone book, etc.), etc. In addition, the memory may include a high-speed random access memory, and may also include a non-volatile memory, such as a hard disk, a memory, a plug-in hard disk, a smart memory card (Smart Media Card, SMC), a secure digital (Secure Digital, SD) card, a flash card (Flash Card), at least one disk storage device, a flash memory device, or other volatile solid-state storage devices.

[0128] The present invention also provides a computer-readable storage medium, which stores a computer program. When the computer program is executed by a processor, the steps of the method for evaluating the wind power absorption capacity of an electrothermal coupling system are implemented.

[0129] If the modules / units integrated in the wind power absorption capacity assessment system of the electrothermal coupling system are implemented in the form of software functional units and sold or used as independent products, they can be stored in a computer-readable storage medium.

[0130] Based on such understanding, the present invention implements all or part of the processes in the above-mentioned method for evaluating the wind power absorption capacity of the electrothermal coupling system, and can also be completed by instructing related hardware through a computer program, and the computer program can be stored in a computer-readable storage medium, and when the computer program is executed by a processor, the steps of the above-mentioned method for evaluating the wind power absorption capacity of the electrothermal coupling system can be implemented. Among them, the computer program includes computer program code, and the computer program code can be in source code form, object code form, executable file or preset intermediate form, etc.

[0131] The computer-readable storage medium may include: any entity or device capable of carrying the computer program code, recording medium, USB flash drive, mobile hard disk, magnetic disk, optical disk, computer memory, read-only memory (ROM), random access memory (RAM), electrical carrier signal, telecommunication signal and software distribution medium, etc.

[0132] It should be noted that the content contained in the computer-readable storage medium can be appropriately increased or decreased according to the requirements of legislation and patent practice in the jurisdiction. For example, in some jurisdictions, according to legislation and patent practice, computer-readable storage media do not include electrical carrier signals and telecommunication signals.

[0133] The above embodiment is only one of the implementation methods that can realize the technical solution of the present invention. The scope of protection claimed by the present invention is not limited only to this embodiment, but also includes changes, replacements and other implementation methods that can be easily thought of by any technician familiar with the technical field within the technical scope disclosed by the present invention.

Claims

1. A method for evaluating the wind power absorption capacity of an electrothermal coupling system, characterized in that: include: Based on the evaluation index of wind power absorption capacity of electric-thermal coupling system, key indexes in primary frequency regulation process, operation model of cogeneration unit and quasi-one-dimensional operation model of heat storage system, the objective function and constraint conditions are obtained. Construct a wind power absorption capacity evaluation model for the electric-thermal coupling system based on the objective function and constraints; Based on the non-convex constraints of the wind power accommodation capacity assessment model of the electrothermal coupling system, the wind power accommodation capacity assessment model of the electrothermal coupling system is solved, and the wind power accommodation capacity assessment result of the electrothermal coupling system taking into account frequency safety is obtained.

2. The method for evaluating wind power absorption capacity of an electric-thermal coupling system according to claim 1, characterized in that: in, The design steps of the wind power absorption capacity evaluation index of the electrothermal coupling system include: The DNE boundary is used as an evaluation index for the wind power absorption capacity of the electrothermal coupling system. The DNE boundary is used to characterize: under the uncertainty of wind power, the electrothermal coupling system does not generate load shedding and can absorb the maximum wind power range. The specific formula is as follows: In the formula, It is a wind farm w At the moment t The actual output, For wind farms w At the moment t The wind power curtailment It is a wind farm w At the moment t The prediction error, represents the wind farm collection, and Wind farms w The DNE boundary at time t The lower and upper limits of is the value-at-risk of the distributed robust joint chance constraint, and It is a man-made wind farm w The minimum and maximum allowed DNE boundaries, represents the wind curtailment ratio, It is a fuzzy set based on Wasserstein measure and is used to describe random variables. uncertainty.

3. The method for evaluating wind power absorption capacity of an electric-thermal coupling system according to claim 1, characterized in that: in, Aiming at the primary frequency regulation process on the grid side in the electrothermal coupling system, a mathematical model of key indicators in the primary frequency regulation process is constructed, including: Based on the swing equation, the primary frequency regulation process on the grid side of the electrothermal coupling system is described, and the frequency drop rate constraint condition is constructed; according to the time when the lowest frequency point occurs, the lowest frequency point constraint condition is constructed; at the same time, the quasi-steady-state constraint condition is established; The expression of the frequency reduction rate constraint is as follows: In the formula, For the period t Internal Node i The power fluctuation at is the maximum frequency drop rate that the electrothermal coupling system can tolerate; represents the system inertia; The expression of the frequency minimum point constraint condition is as follows: In the formula, and Represents CHP units g and traditional thermal power units u The inertia constant, and CHP units g and traditional thermal power units u 0-1 variable for the switch state, and Respectively represent CHP units g and traditional thermal power units u Maximum power generation capacity; is the rated frequency of the system; and are all constants; and CHP units g and traditional thermal power units u The lowest frequency point; is the total primary frequency regulation reserve capacity of the system at time t; The expression of the quasi-steady-state constraint condition is as follows: In the formula, is the maximum permissible frequency deviation in quasi-steady state; is the load damping; It is the time period t Internal Node i The electrical load value at is the set of load nodes.

4. The method for evaluating wind power absorption capacity of an electric-thermal coupling system according to claim 1, characterized in that: The operation model of the cogeneration unit is constructed based on the road reconstruction technology, and the specific formula is as follows: In the formula, and CHP units g In the period t The power generation and heat generation of , and They represent the power generation at the endpoints A, D and J of the operation domain respectively, is the heat generation power at the end point B of the operating domain, It is a CHP unit g The capacity of the bypass retrofit technology installed, and are the slopes of side AB and side BC respectively; is a constant; , and They are 0-1 variables for the unit's on / off status, startup status, and shutdown status. Represents the primary frequency regulation reserve capacity of the CHP unit, and They are the upward reserve and downward reserve capacity used to balance the uncertainty of wind power. , and They are the primary frequency regulation reserve upper limit, the upward reserve capacity upper limit and the downward reserve capacity upper limit. and They are the minimum power-on time and the minimum power-off time. and are the maximum up-climbing rate and the maximum down-climbing rate respectively; The expression of the quasi-one-dimensional operation model of the heat storage system is as follows: In the formula, and Thermal storage system e In the period t The charging power and releasing power of and Represent the quality of water in the hot zone and the cold zone respectively, and are the water temperatures in the hot and cold zones, is the comprehensive heat loss coefficient of the heat storage system, is the thermal conductivity of water, represents the heat convection power between the hot zone and the cold zone, and They are the heat power received by the cold zone during heat release and the heat loss of the cold zone during heat charging. is the minimum charging and discharging power of the heat storage system, represents the cross-sectional area of ​​the thermal storage system water tank, and are the lateral areas of the hot zone and the cold zone, respectively. is the height of the pitcher, and Represents the minimum and maximum allowable water temperatures respectively.

5. The method for evaluating wind power absorption capacity of an electric-thermal coupling system according to claim 1, characterized in that: The objective function covers the DNE boundary and wind curtailment rate of all wind farms in a day: In the formula, and Wind farms w In the period t The upper and lower bounds of the DNE boundary, is a weighting coefficient used to indicate the importance of each wind farm; μ represents the weight of wind abandonment in the objective function, For wind farms w In the period t The proportion of wind curtailment; The constraints include power grid flow constraints, thermal network thermal flow constraints, traditional thermal power unit operation constraints and controllable unit uncertainty reserve constraints.

6. The method for evaluating wind power absorption capacity of an electric-thermal coupling system according to claim 1, characterized in that: The steps for constructing the wind power absorption capacity evaluation model of the electrothermal coupling system are as follows: The DNE boundary is incorporated into the objective function of the wind power absorption capacity assessment model; the distributed blue stick joint chance constraint is used to characterize random variables such as the DNE boundary, branch power, and controllable unit standby; at the same time, considering the frequency safety constraints, power grid flow constraints, heat network energy flow constraints, and conventional thermal power unit operation constraints, an evaluation model for the wind power absorption capacity of the electric-thermal coupling system is constructed.

7. The method for evaluating wind power absorption capacity of an electric-thermal coupling system according to claim 1, characterized in that: The non-convex constraints include distributed robust joint chance constraints containing uncertainty on the left or uncertainty on the right, and constraints containing differentials; the non-convex constraints are reconstructed to convert the high-dimensional non-convex model into a mixed integer second-order cone programming model; finally, the reconstructed mixed integer second-order cone programming model is solved to obtain the evaluation result of the wind power absorption capacity of the electrothermal coupling system taking into account frequency safety.

8. A wind power absorption capacity assessment system for an electrothermal coupling system, characterized in that: include: The objective function and constraint design module is used to obtain the objective function and constraint conditions based on the wind power absorption capacity evaluation index of the electric-thermal coupling system, the key indicators in the primary frequency regulation process, the operation model of the cogeneration unit and the quasi-one-dimensional operation model of the heat storage system; Evaluation model building module, used to build an evaluation model for wind power absorption capacity of electric-thermal coupling system based on objective function and constraint conditions; The wind power absorption capacity assessment module is used to solve the wind power absorption capacity assessment model of the electrothermal coupling system based on the non-convex constraints of the wind power absorption capacity assessment model of the electrothermal coupling system, and obtain the wind power absorption capacity assessment result of the electrothermal coupling system that takes into account frequency safety.

9. A device, characterized in that: include: Memory for storing computer programs; A processor is used to implement the steps of the method for evaluating the wind power absorption capacity of an electrothermal coupling system according to any one of claims 1 to 7 when executing the computer program.

10. A computer-readable storage medium storing a computer program, characterized in that: When the computer program is executed by a processor, it is used to implement the steps of the method for evaluating the wind power absorption capacity of an electrothermal coupling system according to any one of claims 1 to 7.

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