A method for evaluating wind power consumption capacity of an electrothermal coupling system and related equipment

Abstract

The present application belongs to the field of power system, discloses a kind of electric heating coupling system wind power consumption capacity evaluation method and related equipment, this method is first based on the wind power consumption capacity evaluation index of electric heating coupling system, the key index in primary frequency modulation process, the operation model of combined heat and power unit and the quasi-one-dimensional operation model of heat storage system, design to obtain objective function and constraint condition, then the construction of wind power consumption capacity evaluation model of electric heating coupling system is completed;Considering non-convex constraint condition, the wind power consumption capacity evaluation model of electric heating coupling system is solved, and the wind power consumption capacity evaluation result of electric heating coupling system considering frequency security is calculated;In electric heating coupling system, the present application fully considers the low inertia property of power system when high proportion of new energy is accessed, and the positive promoting effect of heat network flexibility reconstruction on wind power consumption, accurately evaluates the wind power consumption capacity of system under the premise of meeting system frequency stability and reliability.

Description

Technical Field

[0001] This invention belongs to the field of power system technology, specifically relating to a method and related equipment for assessing the wind power absorption capacity of an electrothermal coupling system. Background Technology

[0002] Traditional power systems are dominated by thermal power units, which are the primary source of carbon emissions. Converting thermal power units into combined heat and power (CHP) units is an important way to improve energy efficiency and reduce carbon emissions. Developing CHP units is particularly suitable for regions with heating needs in winter. Meanwhile, developing wind power is another effective means of emission reduction.

[0003] In recent years, wind power penetration has reached a high level in many regions, posing numerous challenges to power system operation. Specifically, the high proportion of wind power integration leads to reduced system inertia, affecting system frequency security; and the deep coupling of electricity and heat will limit the absorption of wind power during peak heating seasons and nighttime periods of high wind power generation. Therefore, it is essential to assess the wind power absorption capacity on an operational scale from the perspective of electricity-heat coupling, while ensuring frequency security.

[0004] However, existing studies on the wind power absorption capacity assessment of electrothermal coupling systems do not consider the impact of high-proportion wind power integration on system frequency security, making it difficult for existing assessment methods to adapt to the future development and application of new power systems dominated by new energy sources. Summary of the Invention

[0005] The purpose of this invention is to provide a method and related equipment for evaluating the wind power absorption capacity of an electrothermal coupling system, in order to solve the technical problem that existing evaluation methods do not consider the impact of high-proportion wind power integration on system frequency security, making it difficult to adapt to the development and application of new power systems dominated by new energy sources in the future.

[0006] To achieve the above objectives, the present invention adopts the following technical solution:

[0007] A method for assessing the wind power absorption capacity of an electrothermal coupling system includes:

[0008] Based on the evaluation index of wind power absorption capacity of electrothermal coupling system, key indicators in primary frequency regulation process, operation model of cogeneration unit and quasi-one-dimensional operation model of thermal storage system, the objective function and constraints are obtained.

[0009] A wind power absorption capacity assessment model for electrothermal coupling systems is constructed based on the objective function and constraints.

[0010] Based on the non-convex constraints of the wind power absorption capacity assessment model of the electrothermal coupling system, the model is solved to obtain the wind power absorption capacity assessment results of the electrothermal coupling system that take into account frequency security.

[0011] Furthermore, the design steps for the wind power absorption capacity evaluation index of the electrothermal coupling system include:

[0012] 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 the maximum range of wind power that the electrothermal coupling system can absorb without generating load shedding under wind power uncertainty. The specific formula is as follows:

[0013]

[0014]

[0015]

[0016]

[0017] In the formula, It is a wind farm w At any moment t Actual output For wind farm w At any moment t wind curtailment power, It is a wind farm w At any moment t The prediction error Indicates a collection of wind farms. and Wind farm w The DNE boundary at time t The lower limit and upper limit, It is the risk value of the joint opportunity constraint of the Brussels Bar. and It is a man-made wind farm w The minimum and maximum values ​​of the allowed DNE boundary. Represents the proportion of wind curtailment. It is a fuzzy set based on the Wasserstein measure, used to describe random variables. Uncertainty.

[0018] Furthermore, for the primary frequency regulation process on the grid side of the electrothermal coupling system, a mathematical model of key indicators in the primary frequency regulation process is constructed, including:

[0019] Based on the oscillation equation, the primary frequency regulation process on the grid side of the electrothermal coupling system is described, and the frequency drop rate constraint is constructed. According to the occurrence time of the frequency minimum point, the frequency minimum point constraint is constructed. At the same time, quasi-steady-state constraint is established.

[0020] The expression for the frequency descent rate constraint is as follows:

[0021]

[0022]

[0023] In the formula, For time period t internal nodes i Power fluctuation at the location; This is the maximum permissible frequency descent rate of the electrothermal coupling system. Represents system inertia;

[0024] The expression for the constraint condition of the lowest frequency point is as follows:

[0025]

[0026]

[0027]

[0028]

[0029]

[0030] In the formula, and Representing the CHP units g Compared with traditional thermal power units u The inertial constant, and CHP units g Compared with traditional thermal power units u The 0-1 variables of the switch state, and These represent the CHP units. g Compared with traditional thermal power units u Maximum power generation; It is the system's rated frequency; and All are constants; and CHP units g Compared with traditional thermal power units u The lowest frequency point; Let be the total primary frequency regulation reserve capacity of the system at time t;

[0031] The expression for the quasi-steady-state constraint is as follows:

[0032]

[0033]

[0034] In the formula, It is the maximum permissible frequency deviation in quasi-steady state; It is load damping; It is a time period t internal nodes i The electrical load value at the location, It is a set of load nodes.

[0035] Furthermore, the operating model of the combined heat and power unit is constructed based on road modification technology, and the specific formula is as follows:

[0036]

[0037]

[0038]

[0039]

[0040]

[0041]

[0042]

[0043]

[0044]

[0045]

[0046]

[0047]

[0048]

[0049]

[0050]

[0051] In the formula, and CHP units g During the period tPower generation and heat production capacity, , and These represent the power generation at endpoints A, D, and J of the operating domain, respectively. It is the heat generation power at endpoint B of the operating domain. It is a CHP unit g The capacity of the installed bypass retrofit technology, and These are the slopes of sides AB and BC, respectively. It is a constant; , and These are 0-1 variables representing the unit's on / off state, startup state, and shutdown state, respectively. This represents the primary frequency regulation reserve capacity of the CHP unit. and These are the upward and downward reserve capacities used to balance the uncertainties of wind power. , and These are the upper limit of primary frequency regulation reserve capacity, the upper limit of upward reserve capacity, and the upper limit of downward reserve capacity. and These are the minimum boot time and the minimum shutdown time, respectively. and These are the maximum uphill speed and the maximum downhill speed, respectively.

[0052] The expression for the quasi-one-dimensional operating model of the thermal storage system is as follows:

[0053]

[0054]

[0055]

[0056]

[0057]

[0058]

[0059]

[0060]

[0061]

[0062]

[0063]

[0064]

[0065]

[0066]

[0067]

[0068]

[0069] In the formula, and These are thermal storage systems e During the period t The heat charging power and heat dissipation power, and These represent the mass of water in the hot and cold zones, respectively. and These are the water temperatures in the hot and cold zones, respectively. It is the overall heat loss coefficient of the thermal storage system. It is the thermal conductivity of water. This represents the heat convection power between the hot and cold zones. and These are the heat power received by the cold zone during heat release and the heat loss of the cold zone during heat charging, respectively. It is the minimum heat charging and heat dissipation power of the thermal storage system. This indicates the cross-sectional area of ​​the water tank in the thermal storage system. and These are the lateral areas of the hot and cold zones, respectively. It is the height of the water tank. and These represent the minimum and maximum permissible water temperatures, respectively.

[0070] Furthermore, the objective function encompasses the DNE boundary and curtailment rate of all wind farms within a day:

[0071]

[0072] In the formula, and These are wind farms w During the period t The upper and lower bounds of the DNE boundary. It is a weighting factor used to represent the importance of each wind farm; μ This represents the weight of the curtailed wind volume in the objective function. For wind farm w During the period t The proportion of wind curtailment;

[0073] The constraints include power grid flow constraints, heating network heat flow constraints, traditional thermal power unit operation constraints, and uncertain reserve constraints for controllable units.

[0074] Furthermore, the construction steps of the wind power absorption capacity assessment model for the electrothermal coupling system are as follows:

[0075] The objective function of the wind power absorption capacity assessment model is incorporated into the DNE boundary; random variables such as DNE boundary, branch power, and controllable unit reserve are characterized by the use of bibliometric rod joint chance constraints; at the same time, considering frequency security constraints, power grid flow constraints, heat network energy flow constraints, and conventional thermal power unit operation constraints, an assessment model for the wind power absorption capacity of the electrothermal coupling system is constructed.

[0076] Furthermore, the non-convex constraints include the partial boolean joint chance constraint with left-hand or right-hand uncertainty, and the constraint with 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 wind power absorption capacity assessment result of the electrothermal coupling system that takes into account frequency safety.

[0077] A wind power absorption capacity assessment system for an electrothermal coupling system, comprising:

[0078] The objective function and constraint design module is used to obtain the objective function and constraint based on the evaluation index of wind power absorption capacity of electrothermal coupling system, key indicators in primary frequency regulation process, cogeneration unit operation model and quasi-one-dimensional operation model of thermal storage system.

[0079] The evaluation model building module is used to construct an evaluation model for the wind power absorption capacity of the electrothermal coupling system based on the objective function and constraints.

[0080] 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 model, and obtain the wind power absorption capacity assessment result of the electrothermal coupling system that takes into account frequency safety.

[0081] An apparatus comprising:

[0082] Memory, used to store computer programs;

[0083] A processor is used to implement the steps of the above-described method for evaluating the wind power absorption capacity of an electrothermal coupling system when executing the computer program.

[0084] A computer-readable storage medium storing a computer program, which, when executed by a processor, is used to implement the steps of the above-described method for assessing the wind power absorption capacity of an electrothermal coupling system.

[0085] Compared with existing technologies, the present invention has the following beneficial effects:

[0086] This invention provides a method for evaluating the wind power absorption capacity of an electrothermal coupling system. The method first designs an objective function and constraints based on evaluation indicators for the wind power absorption capacity of the electrothermal coupling system, key indicators during primary frequency regulation, a combined heat and power (CHP) unit operation model, and a quasi-one-dimensional operation model of the thermal storage system. This leads to the construction of an evaluation model for the wind power absorption capacity of the electrothermal coupling system. Considering non-convex constraints, the evaluation model is solved to obtain an evaluation result that balances frequency security. In the electrothermal coupling system, this method fully considers the low inertia of the power system when a high proportion of renewable energy is integrated, as well as the positive promoting effect of thermal network flexibility upgrades on wind power absorption. Under the premise of satisfying system frequency stability and reliability, it accurately evaluates the system's wind power absorption capacity.

[0087] Preferably, in this 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; the actual output of the wind farm, wind curtailment power, prediction error and other factors are considered, which improves the accuracy and practicality of the evaluation; at the same time, the introduction of the split-blown rod joint opportunity constraint makes the evaluation results more robust and can cope with the impact of wind power uncertainty.

[0088] Preferably, in this 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 descent rate constraint, frequency minimum point constraint, and quasi-steady-state constraint. 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 frequency safety requirements.

[0089] Preferably, in this invention, the introduction of the cogeneration unit operation model and the quasi-one-dimensional operation model of the thermal storage system enables the evaluation method to more accurately reflect the actual operation of the cogeneration unit and the thermal storage system in the electrothermal coupling system, thereby improving the accuracy and reliability of the evaluation results.

[0090] Preferably, in this invention, the objective function covers the DNE boundary and curtailment rate of all wind farms within a day, which can comprehensively reflect the wind power absorption capacity and wind power resource utilization efficiency of the electrothermal coupling system. The introduction of constraints ensures that the evaluation results more accurately reflect the wind power absorption capacity of the electrothermal coupling system under the premise of meeting the requirements of power grid flow, heat flow of the heating network, operation of traditional thermal power units and uncertain reserve of controllable units.

[0091] Preferably, in this invention, the construction steps of the wind power absorption capacity assessment model of the electrothermal coupling system include incorporating the DNE boundary into the objective function, using split-blown bar joint chance constraints to characterize random variables, and considering constraints such as frequency security, power grid flow, heat network energy flow, and conventional thermal power unit operation.

[0092] Preferably, in this invention, the introduction of reconstruction and solution methods for non-convex constraints improves the flexibility and applicability of the evaluation method, enabling it to 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 solving the problem and the computational complexity. Attached Figure Description

[0093] Figure 1 A flowchart of a method for evaluating the wind power absorption capacity of an electrothermal coupling system provided in an embodiment of the present invention;

[0094] Figure 2 This is a schematic diagram of a primary frequency modulation process provided in an embodiment of the present invention;

[0095] Figure 3 This refers to the operating domain of the CHP unit with bypass compensation technology provided in the embodiments of the present invention;

[0096] Figure 4 This is a schematic diagram of the variables in the thermal energy storage operation model provided in the embodiments of the present invention, wherein (a) represents heat charging; and (b) represents heat release.

[0097] Figure 5 This is a schematic diagram of variables in the calculation of energy flow in a heating network provided in an embodiment of the present invention;

[0098] Figure 6 A schematic diagram of the testing system provided in an embodiment of the present invention;

[0099] Figure 7 A comparison diagram of the DNE boundary between the present invention and the existing method is provided for an embodiment of the present invention, wherein (a) is W1; (b) is W2;

[0100] Figure 8 A comparison chart of frequency indices provided in this embodiment of the invention with existing methods, wherein (a) is the frequency decrease rate; and (b) is the lowest frequency point.

[0101] Figure 9 A flowchart of a method for evaluating the wind power absorption capacity of an electrothermal coupling system provided by the present invention;

[0102] Figure 10 This is a schematic diagram of a wind power absorption capacity assessment system for an electrothermal coupling system provided by the present invention. Detailed Implementation

[0103] Example 1

[0104] As described in the background section, existing studies on the wind power absorption capacity assessment of electrothermal coupling systems do not consider the impact of a high proportion of wind power integration on system frequency security, making it difficult for existing assessment methods to adapt to the future development and application of new power systems dominated by new energy sources.

[0105] To address the aforementioned issues, this invention provides a method for evaluating the wind power absorption capacity of an electrothermal coupling system. This method fully considers the low inertia of the new power system and the positive promoting effect of the thermal network flexibility transformation on wind power absorption in the evaluation of the wind power absorption capacity of the electrothermal coupling system. Under the premise of satisfying the system frequency stability and reliability, it accurately evaluates the wind power absorption capacity of the system.

[0106] like Figure 1 As shown in the figure, this embodiment provides a method for evaluating the wind power absorption capacity of an electrothermal coupling system. This evaluation method takes into account frequency security, that is, it focuses on the frequency security of the electrothermal coupling system, and specifically includes the following steps:

[0107] S1. Evaluation indicators for the wind power absorption capacity of the electrothermal coupling system, specifically including:

[0108] S1.1 Evaluation of wind power absorption capacity based on the joint opportunity constraint of split-blown rods

[0109] Considering the difficulties that wind power uncertainty brings to the assessment of grid integration capacity, this invention utilizes a split-Brow bar combined opportunity constraint method to characterize wind power uncertainty. This method provides a flexible grid integration capacity assessment boundary, that is, it combines system operational reliability with wind power grid integration capacity requirements to determine the grid integration boundary under different levels of conservatism.

[0110] S1.2 Establishing a mathematical model for the DNE boundary

[0111] The DNE boundary of the wind farm is represented by formulas (1)-(4). Formula (1) represents the fuzzy set joint chance constraint, where represents the fuzzy set... Under the given uncertainty environment, the probability that the grid-connected wind power is within the DNE boundary should be no less than 1- Formula (2) constrains the range of the DNE boundary by artificially given upper and lower limits. Formula (3) represents that the actual wind power is composed of the wind power prediction value and the random wind power prediction error. Formula (4) gives the linear relationship between the wind curtailment power and the actual wind power.

[0112] (1)

[0113] (2)

[0114] (3)

[0115] (4)

[0116] In the formula, It is a wind farm w At any moment t Actual output For wind farm w At any moment t wind curtailment power, It is a wind farm w At any moment t The prediction error Indicates a collection of wind farms. and Wind farm w The DNE boundary at time t The lower limit and upper limit, It is the risk value of the joint opportunity constraint of the Brussels Bar. and It is a man-made wind farm w The minimum and maximum values ​​of the allowed DNE boundary. This represents the proportion of wind curtailment. It is a fuzzy set based on the Wasserstein measure, used to describe random variables. Uncertainty.

[0117] S2. For the primary frequency regulation on the grid side of the electrothermal coupling system, a mathematical model for key indicators during the frequency regulation process is proposed, specifically including:

[0118] S2.1 Selecting key frequency safety indicators for the electrothermal coupling system

[0119] After an unplanned frequency fluctuation occurs on the grid side of the electrothermal coupling system, its frequency change curve is as follows: Figure 2 As shown. Among them, the indicators that have a critical impact on system safety include: frequency decay rate, minimum frequency point, and quasi-steady-state frequency.

[0120] The frequency descent rate is the slope of the frequency curve. If the frequency descent rate exceeds the allowable range, it may trigger relay protection, resulting in serious consequences such as power outage or load shedding. The magnitude of the frequency descent rate depends on the power fluctuation and the system's inertia.

[0121] The frequency minimum is the lowest frequency during primary frequency modulation. If the frequency drops rapidly below the permissible minimum, it may trigger low-frequency shimmy in the electrothermal coupling system. Therefore, the frequency minimum should be strictly limited to a safe range. The frequency minimum is largely determined by the system inertia and the response speed of the primary frequency modulation resources.

[0122] The quasi-steady-state frequency is the frequency value of the power system at the end of primary frequency regulation, used to measure steady-state frequency security. In quasi-steady state, the electrothermal coupling system re-establishes power balance, but the quasi-steady-state frequency remains below the rated frequency. This indicator is related to the power adjustment and load damping of primary frequency regulation.

[0123] S2.2, Derivation of the frequency descent rate constraint for electrothermal coupling systems

[0124] When unplanned power disturbances occur, the grid-side frequency deviation of the electrothermal coupling system is represented by the oscillation equation (5):

[0125] (5)

[0126] In the formula, Indicates time period t Inner Time τ The system frequency offset It is load damping. and It is a time period t internal nodes i The electrical load value at the location, It is a set of load nodes. and It is a time period t internal nodes i Power fluctuation at the location, and They are t CHP units during the period g Compared with traditional thermal power units u Power adjustment. and It is a combination of CHP units and traditional thermal power units. The system inertia can be calculated using formula (6):

[0127] (6)

[0128] In the formula, and Representing the CHP units g Compared with traditional thermal power units u The inertial constant, and These represent CHP units. g Compared with traditional thermal power units u The 0-1 variables of the switch state, and These represent the CHP units. g Compared with traditional thermal power units u Maximum power generation. It is the system's rated frequency.

[0129] The maximum rate of frequency decrease occurs τ At time =0, based on this condition, the frequency decrease rate constraint can be derived from the oscillation equation as (7):

[0130] (7)

[0131] In the formula, This indicates the maximum rate of frequency decay that the system can tolerate.

[0132] S2.3, Derivation of the minimum frequency constraint for the electrothermal coupling system

[0133] Assuming that the power adjustment of the CHP unit and the conventional thermal power unit is linear, by solving the oscillation equation (5), the system frequency offset during the first frequency regulation process can be obtained. for:

[0134] (8)

[0135] In the formula, for the sake of brevity, let and , Indicates the dead zone of the unit. It's dead time. The time required for the unit to output reserve capacity; This represents the total primary frequency regulation reserve capacity of the system at time t; This represents the primary frequency regulation reserve capacity reserved by the cogeneration unit g at time t; This represents the primary frequency regulation reserve capacity reserved by a traditional thermal power unit u at time t.

[0136] When the system frequency drops to its lowest point, the frequency offset for τ The derivative of is 0, and based on this condition, the time when the lowest frequency occurs can be determined. :

[0137] (9)

[0138] Substituting formula (9) into formula (8), we can obtain the constraint condition (10) for the point of lowest frequency:

[0139] (10)

[0140] In the formula, It is the only solution when equation (10) holds true. When equation (10) is true, equation (11) satisfies the following condition:

[0141] (11)

[0142] Finally, the Big M method is used to handle the implicit bilinear terms in formula (11). and The minimum frequency constraint (11) is replaced by formulas (12)-(16):

[0143] (12)

[0144] (13)

[0145] (14)

[0146] (15)

[0147] (16)

[0148] In the formula, and All are sufficiently large positive numbers.

[0149] S2.4, Deriving the quasi-steady-state frequency constraint of the electrothermal coupling system

[0150] When the first frequency modulation ends, the system reaches the quasi-steady-state frequency, at which point the rate of frequency decrease is equal to 0. Under this condition, the constraint condition regarding the quasi-steady-state frequency can be obtained from the oscillation equation as follows:

[0151] (17)

[0152] In the formula, It is the maximum permissible frequency deviation in quasi-steady state.

[0153] S3. Establish an operating model for cogeneration units that considers bypass modification technology, as well as a quasi-one-dimensional operating model for thermal storage systems, specifically including:

[0154] S3.1 Establish a CHP unit operation model that considers bypass modification technology.

[0155] Bypass modification technology is an effective means to improve the operational flexibility of CHP units. This technology can improve the waste heat recycling efficiency generated by the unit's power generation, thereby improving the heat generation capacity of CHP units when the power generation is low. Figure 3 The operating domains of the CHP unit are shown, where quadrilateral ABCD represents the operating domain before the modification, while polygon ABFECD represents the operating domain after the modification. The shaded area is the operating domain newly added through the modification.

[0156] The operating model of the CHP unit with bypass modification technology is shown in (18)-(32). Equations (18)-(23) describe the operating domain boundaries DC, CE, EF, FB, BA and AD, respectively. These equations consider the reserve capacity and electrothermal power, and together constrain the operating point within the operating domain. Equations (24)-(26) constrain the capacity of primary frequency regulation reserve, up-regulation reserve and down-regulation reserve, respectively. Equations (27)-(28) give the logical relationship between start-up, shutdown and the switching state of the CHP unit. Equations (29)-(30) constrain the minimum start-up and shutdown duration, respectively. Equations (31)-(32) constrain the ramp rate of the unit, respectively.

[0157] (18)

[0158] (19)

[0159] (20)

[0160] (twenty one)

[0161] (twenty two)

[0162] (twenty three)

[0163] (twenty four)

[0164] (25)

[0165] (26)

[0166] (27)

[0167] (28)

[0168] (29)

[0169] (30)

[0170] (31)

[0171] (32)

[0172] In the formula, and CHP units g During the period t Power generation and heat production capacity, , and These represent the power generation at endpoints A, D, and J of the operating domain, respectively. It is the heat generation power at endpoint B of the operating domain. It is a CHP unit g The capacity of the installed bypass retrofit technology, and These are the slopes of sides AB and BC, respectively. It is a sufficiently large positive number. , and These are 0-1 variables representing the unit's on / off state, startup state, and shutdown state, respectively. This represents the primary frequency regulation reserve capacity of the CHP unit. and These are the upward and downward reserve capacities used to balance the uncertainties of wind power. , and These are the upper limit of primary frequency regulation reserve capacity, the upper limit of upward reserve capacity, and the upper limit of downward reserve capacity. and These are the minimum boot time and the minimum shutdown time, respectively. and These are the maximum uphill speed and the maximum downhill speed, respectively.

[0173] S3.2 Establish a quasi-one-dimensional operating model of the thermal storage system

[0174] The main component of a thermal storage system is the storage tank, which contains a hot water zone and a cold water zone, separated by a thermocline. Figure 4 As shown. When the thermal storage system is charged, the thermocline descends, the hot water zone expands while the cold water zone shrinks, as... Figure 4 (a) When the thermal storage system releases heat, the thermocline rises, the hot water zone shrinks, and the cold water zone expands, such as... Figure 4(b). During the heat charging or releasing process, due to the time delay of heat convection, the process cannot be completed instantaneously and requires a dynamic process. This invention establishes a quasi-one-dimensional operating model of the thermal storage system, considering the dynamic process of the thermal storage system, as shown in (33)-(48). Formulas (33)-(34) describe the relationship between mass, energy and thermal power of the hot and cold zones respectively through ordinary differential equations. Formulas (35)-(36) represent the changes in mass of the hot and cold zones during the heat charging and releasing processes respectively. Formula (37) limits the total mass of water in the hot and cold zones, and formula (38) ensures the non-negativity of the mass of water. Formulas (39)-(40) ensure the daily circulation of thermal energy in the thermal storage system by limiting the initial and final states of mass and temperature. Formulas (41)-(42) calculate the heat charging and releasing power of the thermal storage system, and formulas (43)-(44) derive the thermal power of the cold zone during the heat charging and releasing stages respectively. Formula (45) constrains the minimum heat charging and discharging power of the thermal storage system. Formula (46) calculates the heat convection power between the hot and cold zones. Formula (47) ensures a single operating state for the thermal storage system. Formula (48) limits the average temperature to an allowable range.

[0175] (33)

[0176] (34)

[0177] (35)

[0178] (36)

[0179] (37)

[0180] (38)

[0181] (39)

[0182] (40)

[0183] (41)

[0184] (42)

[0185] (43)

[0186] (44)

[0187] (45)

[0188] (46)

[0189] (47)

[0190] (48)

[0191] In the formula, and These are thermal storage systems e During the period t The heat charging power and heat dissipation power, and These represent the mass of water in the hot and cold zones, respectively. and These are the water temperatures in the hot and cold zones, respectively. It is the overall heat loss coefficient of the thermal storage system. It is the thermal conductivity of water. This represents the heat convection power between the hot and cold zones. and These are the heat power received by the cold zone during heat release and the heat loss of the cold zone during heat charging, respectively. It is the minimum heat charging and heat dissipation power of the thermal storage system. This indicates the cross-sectional area of ​​the water tank in the thermal storage system. and These are the lateral areas of the hot and cold zones, respectively. It is the height of the water tank. and These represent the minimum and maximum permissible water temperatures, respectively.

[0192] S4. Design the objective function and constraints, and construct an evaluation model for the wind power absorption capacity of the electro-thermal coupling system considering frequency security. Specifically, this includes:

[0193] S4.1, Objective function of the wind power absorption capacity assessment model for electrothermal coupling system

[0194] The purpose of this model is to evaluate the wind power absorption capacity of the electrothermal coupling system. An objective function (49) is designed, which covers the DNE boundary and curtailment rate of all wind farms within a day:

[0195] (49)

[0196] In the formula, and These are wind farms w During the period t The upper and lower bounds of the DNE boundary. It is a weighting factor used to represent the importance of each wind farm. μ This represents the weight of the curtailed wind volume in the objective function. For wind farmw During the period t The proportion of wind curtailment.

[0197] S4.2 Power Flow Constraints for Establishing a Wind Power Absorption Capacity Assessment Model for Electrothermal Coupled Systems

[0198] DC power flow is used to describe the power flow constraints on the grid side of the electrothermal coupling system, and the uncertainties in the power flow are characterized based on the sub-Brook bar joint opportunity constraint. Equation (50) represents the power balance on the grid side, which considers the uncertainty of wind power and the upward / downward power adjustment of controllable units. Equation (52) is the sub-Brook bar joint opportunity constraint, representing the fuzzy set Under the given uncertainty environment, the probability of satisfying the branch power safety constraint should not be less than confidence level 1- .

[0199] (50)

[0200] (51)

[0201] In the formula, and These are the CHP units after considering upward / downward power adjustments. g Compared with traditional thermal power units u Power generation capacity, Let be the load power at node i. , , and For the corresponding CHP unit in the transfer matrix g Traditional thermal power units u Wind farm w and load i and branch road l Submatrices representing relationships. This represents the risk value of the joint opportunity constraint of the Brussels Bar.

[0202] S4.3 Establishing a thermal flow constraint for the heating network in the assessment model of the wind power absorption capacity of the electrothermal coupling system.

[0203] Based on the constant flow rate and variable temperature control strategy, thermal flow constraints (52)-(60) are established on the heat network side of the electrothermal coupling system to describe the characteristics of the working fluid temperature and flow rate in the heat network. Formula (52) calculates the heat generation power of the CHP unit at the heat source node, and formulas (53)-(54) model the heat power of the load nodes connected to and not connected to the thermal storage system, respectively. Formula (55) ensures the mass conservation of the working fluid during the transmission process in any branch. Formula (56) ensures the energy conservation when the working fluids from 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 to obtain the outlet temperature of the pipeline, and 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.

[0204] (52)

[0205] (53)

[0206] (54)

[0207] (55)

[0208] (56)

[0209] (57)

[0210] (58)

[0211] (59)

[0212] (60)

[0213] In the formula, and These are nodes k The heat output and heat load of the CHP unit at the location, This represents the set of nodes in the heating network. and These are the heat charging power and heat dissipation power of the thermal storage system to the heating network, respectively. and These are the working fluid flow rates at the CHP unit and the heat load, respectively. and These represent nodes in the water supply network. k Injection temperature and return water network nodes k The outflow temperature at that point and These are water supply network nodesk Outflow temperature and return water network nodes k Injection temperature at the location, Indicates a branch b The working fluid flow rate, and Each is based on a node k Let be the set of branches starting at the first node and ending at the last node. It is the working fluid temperature of the water supply network (if x=S) or the return network (if x=R). and They are branch roads b The working fluid inflow temperature and the working fluid outflow temperature, Branches that ignore transmission temperature loss b The working fluid outflow temperature, It is the specific heat capacity of the working fluid. It is the density of the working fluid. and They are branch roads b Length and cross-sectional area, It is the thermal conductivity coefficient of the pipe. , and These refer to the number of working fluid blocks. and These are the total working fluid mass inside the pipeline, and the above variables can be derived from... Figure 5 As shown.

[0214] S4.4, Establishing an evaluation model for the wind power absorption capacity of an electrothermal coupling system: Operational constraints of traditional thermal power units.

[0215] For traditional thermal power units that generate electricity but not heat, the operating constraints are as shown in (61)-(71). Formulas (61)-(62) limit the maximum and minimum power output of traditional thermal power units when considering primary frequency regulation reserve capacity. Formula (63) constrains the power generation capacity and primary frequency regulation reserve upper limit of traditional thermal power units. Formulas (64)-(65) limit the upper limit of upward and downward reserve of traditional thermal power units. Formulas (66)-(67) define the logical relationship between the switching, starting, and stopping states of traditional thermal power units. Formulas (68)-(69) limit the minimum start-stop duration of traditional thermal power units. Formulas (70)-(71) constrain the upward and downward ramp rates of traditional thermal power units.

[0216] (61)

[0217] (62)

[0218] (63)

[0219] (64)

[0220] (65)

[0221] (66)

[0222] (67)

[0223] (68)

[0224] (69)

[0225] (70)

[0226] (71)

[0227] In the formula, Indicates traditional thermal power units u During the period t Power generation capacity, , and These are 0-1 variables representing unit switching, startup, and shutdown. and Traditional thermal power units u Maximum and minimum output, It is the primary frequency regulation reserve capacity of traditional thermal power units. and This indicates uphill and downhill climbing for future use. , and These are the maximum permissible primary frequency regulation reserve, uphill reserve, and downhill reserve for traditional thermal power units. and Indicates the minimum start-up and shutdown duration. and It represents the upper limit for both upward and downward climbing.

[0228] S4.5. Uncertainty and Reserve Constraints of Controllable Units in Establishing an Assessment Model for the Wind Power Absorption Capacity of an Electrothermal Coupled System

[0229] Due to the strong uncertainty in wind power output, it is necessary to use generator sets equipped with automatic power generation control systems to offset wind power prediction errors, thereby ensuring the power supply and demand balance of the electrothermal coupling system. Formulas (72)-(73) represent the power generation of the CHP generator set and the conventional thermal power unit 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 generator set. Fuzzy set Under the given uncertainty environment, the joint chance constraints (76)-(77) indicate that the risk that the reserve capacity of CHP units and conventional thermal power units cannot offset the wind power prediction error should not be lower than the given confidence level of 1- and 1- .

[0230] (72)

[0231] (73)

[0232] (74)

[0233] (75)

[0234] (76)

[0235] (77)

[0236] In the formula, and These are the CHP units g Compared with traditional thermal power units u The coefficient vector involved in power balance, and the elements of the vector. and Indicates CHP unit g Compared with traditional thermal power units u For stabilizing wind farms w Prediction error The reaction made, and , It refers to the number of wind farms in the system. and All are risk values ​​under the joint opportunity constraint of the Bruker bar.

[0237] S5. Considering the non-convex constraints in the model, design a solution method for the optimization model containing split-bar joint chance constraints, specifically including:

[0238] S5.1 Reconstructing the joint chance constraint of the split-bars containing left-hand uncertainty

[0239] The joint chance constraints of the sub-Brussels bar containing left-hand uncertainty (51), (76), and (77) can be expressed in the following general form:

[0240] (78)

[0241] In the formula, It is the first one contained in the joint chance constraint of the blue bar. The coefficient vector corresponding to each constraint. Represents a set of constraints. This is the transpose of the matrix. x and ξ These are vectors composed of decision variables and random variables, respectively. It is a risk value.

[0242] The non-convex constraint (78) can be transformed into the following set of mixed integer constraints (79)-(84):

[0243] (79)

[0244] (80)

[0245] (81)

[0246] (82)

[0247] (83)

[0248] (84)

[0249] In the formula, , and It is an auxiliary variable. Represents sufficiently large positive numbers. n Representative sample set The number in It is the number of samples in the set.

[0250] S5.2 Reconstructing the joint chance constraint of the split-bars containing right-hand uncertainty

[0251] The joint chance constraint (1) of the sub-Brussels bar containing right-hand uncertainty can be written in the following general form:

[0252] (85)

[0253] In the formula, It is a risk value.

[0254] The non-convex constraint (85) can be transformed into the following mixed integer programming problems (86)-(89):

[0255] (86)

[0256] (87)

[0257] (88)

[0258] (89)

[0259] In the formula, , and It is an auxiliary variable. It is a sufficiently large positive number.

[0260] S5.3 Reconstructing Constraints Containing Differentials

[0261] For the constraints (33)-(36) containing differentials, they can be transformed into the following mixed integer programming problem:

[0262] (90)

[0263] (91)

[0264] (92)

[0265] (93)

[0266] In the formula, It is the scheduling time resolution of the electrothermal coupling system.

[0267] S5.4 Reconstructing constraints containing bilinear terms

[0268] The constraints (21)-(22), (41)-(44), and (48) containing bilinear terms can be expressed in the following general form:

[0269] (94)

[0270] In the formula, and It is a continuous variable. z It is a 0-1 variable.

[0271] According to the Big M method, (94) can be transformed into (95)-(96):

[0272] (95)

[0273] (96)

[0274] In the formula, Λ represents a sufficiently large positive constant.

[0275] For constraints (90)-(91) containing quadratic terms, the quadratic terms can be expressed in the following general form:

[0276] (97)

[0277] In the formula, , and All are continuous decision variables.

[0278] Using the McCormick Envelope method, (97) is transformed into the following set of mixed integer programming problems:

[0279] (98)

[0280] (99)

[0281] (100)

[0282] (101)

[0283] (102)

[0284] In the formula, , , and They are variables and The upper and lower limits.

[0285] S5.5 Summary of Mixed Integer Second-Order Cone Model

[0286] After the above reconstruction process, the improved 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). This model can be solved using commercial solution software.

[0287] (103)

[0288] The following uses the test system in Table 1 as an example to compare the performance of existing methods with that of the method in this embodiment.

[0289] First, a brief introduction to the testing system: The testing system consists of a wind farm, CHP turbines, a traditional thermal power unit, a thermal storage system, electrical loads, and thermal loads. The system topology is as follows: Figure 6 As shown in Table 1, the capacity of each device is as follows: total power load is 385MW, and total thermal load is 31MW. Other parameters in the simulation are shown in Table 2. The time scale for the daily wind power forecast curve, daily power load curve, and daily thermal load curve selected in the simulation is 24h, and the time resolution is 1 hour. All simulations were completed on the MATLAB platform and solved using the GUROBI solver.

[0290] Table 1 shows the capacity of each device.

[0291]

[0292] Table 2 lists other parameters used in the simulation.

[0293]

[0294] The following three schemes were used for simulation analysis:

[0295] Option 1: The wind power absorption capacity assessment method for electrothermal coupling systems considering frequency constraints proposed in this application;

[0296] Scheme 2: Evaluation method for wind power absorption capacity of electrothermal coupling system ignoring dynamic frequency constraints (7) and (10);

[0297] Option 3: Ignore the bypass compensation technology of the CHP unit and the quasi-one-dimensional model of the thermal storage system, and use the commonly used thermal storage system model that ignores dynamic processes to evaluate the wind power absorption capacity of the electrothermal coupling system.

[0298] Figure 7 The DNE boundaries of wind farms W1 and W2 obtained from Scheme 1 and Scheme 2 were compared. In Scheme 1, when frequency constraints were introduced into the wind power absorption capacity assessment, the DNE boundaries of the two wind farms narrowed during the midnight period. To quantitatively measure the bandwidth of the DNE boundary, the first term of the objective function (49) was used. To quantify. In Scheme 1 and Scheme 2 F The values ​​for 1 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 absence of frequency maintenance tasks, U1 and U2 are shut down during the lower electricity demand at midnight, allowing the electrothermal coupling system to absorb more wind power. In contrast, as shown in Table 3, due to system inertia limitations, only the smaller capacity U2 is shut down in the 4th and 5th hours. Therefore, the unit combination in Scheme 2, which ignores frequency safety, is more flexible in terms of load reduction and is beneficial for wind power absorption. Specifically, the daily wind curtailment rates for Schemes 1 and 2 are 4.98% and 3.37%, respectively.

[0299] Table 3 shows the unit combination scheme 1.

[0300]

[0301] Table 4 shows the unit combination scheme 2.

[0302]

[0303] However, the scheduling scheme of Scheme 2 is not safe in terms of frequency stability. Figure 8The frequency change rate and minimum frequency value indicators of Scheme 1 and Scheme 2 throughout the day were compared. It can be observed that Scheme 1 strictly ensured frequency safety throughout the entire time period. However, in Tables 3 and 4, when different unit combination schemes exist, the frequency change rate of Scheme 2 violated the requirements. This indicates that the unit combination scheme in Scheme 1 can withstand a sharp drop in frequency. More seriously, the lowest frequency point in Scheme 2 violated the lower limit of 49.5 Hz in all time periods due to system inertia and insufficient primary frequency regulation reserve. Compared with Scheme 1, Scheme 2 reduces the daily primary frequency regulation reserve by 35.45%. These comparative results show that the DNE boundary in Scheme 1 can ensure the frequency safety of the electrothermal coupling system under acceptable wind curtailment rates.

[0304] Furthermore, by comparing Scheme 1 and Scheme 3, the impact of heating network flexibility upgrades 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 stems from the insufficient flexibility of CHP unit G1. In Scheme 3, the power generation and primary frequency regulation reserve of G1 are limited by… Figure 3 The boundary BC in the equation limits its ability to adjust downwards to accommodate large amounts of wind energy. Conversely, the CHP unit in Scheme 1 operates in 13 time slots throughout the day. Figure 3 The BFEC region allows it to reduce power generation during peak wind power periods while maintaining thermal energy supply to accommodate more wind energy.

[0305] This embodiment provides a method for evaluating the wind power absorption capacity of an electrothermal coupling system. It can fully consider the low inertia of the new power system and the positive promoting effect of the heat network flexibility transformation on wind power absorption in the evaluation of the wind power absorption capacity of the electrothermal coupling system. Under the premise of meeting the system frequency stability and reliability, it can accurately evaluate the wind power absorption capacity of the system.

[0306] Example 2

[0307] like Figure 9 As shown in the figure, this embodiment provides a method for evaluating the wind power absorption capacity of an electrothermal coupling system, including the following steps:

[0308] Based on the evaluation index of wind power absorption capacity of electrothermal coupling system, key indicators in primary frequency regulation process, operation model of cogeneration unit and quasi-one-dimensional operation model of thermal storage system, the objective function and constraints are obtained.

[0309] A wind power absorption capacity assessment model for electrothermal coupling systems is constructed based on the objective function and constraints.

[0310] Based on the non-convex constraints of the wind power absorption capacity assessment model of the electrothermal coupling system, the model is solved to obtain the wind power absorption capacity assessment results of the electrothermal coupling system that take into account frequency security.

[0311] like Figure 10 As shown in the figure, this embodiment also provides a wind power absorption capacity assessment system for an electrothermal coupling system, including: an objective function and constraint design module, used to obtain the objective function and constraint conditions based on the wind power absorption capacity assessment index of the electrothermal coupling system, key indicators in the primary frequency regulation process, the cogeneration unit operation model, and the quasi-one-dimensional operation model of the thermal storage system; an assessment model construction module, used to construct an assessment model of the wind power absorption capacity of the electrothermal coupling system based on the objective function and constraint conditions; and a wind power absorption capacity assessment module, used to solve the wind power absorption capacity assessment model of the electrothermal coupling system based on the non-convex constraint conditions of the wind power absorption capacity assessment model of the electrothermal coupling system, and obtain the assessment result of the wind power absorption capacity of the electrothermal coupling system that takes into account frequency safety.

[0312] The present invention also provides an apparatus comprising: a memory for storing a computer program; and a processor for executing the computer program to implement the steps of the method for evaluating the wind power absorption capacity of the electrothermal coupling system.

[0313] When the processor executes the computer program, it implements the steps for evaluating the wind power absorption capacity of the electrothermal coupling system, such as: obtaining the objective function and constraints based on the evaluation indicators of the wind power absorption capacity of the electrothermal coupling system, key indicators in the primary frequency regulation process, the cogeneration unit operation model, and the quasi-one-dimensional operation model of the thermal storage system; constructing an evaluation model for the wind power absorption capacity of the electrothermal coupling system based on the objective function and constraints; and solving the evaluation model for the wind power absorption capacity of the electrothermal coupling system based on the non-convex constraints of the evaluation model to obtain the evaluation result of the wind power absorption capacity of the electrothermal coupling system that takes into account frequency safety.

[0314] Alternatively, when the processor executes the computer program, it implements the functions of each module in the above system, such as: an objective function and constraint design module, used to obtain the objective function and constraints based on the evaluation index of the wind power absorption capacity of the electrothermal coupling system, key indicators in the primary frequency regulation process, the cogeneration unit operation model, and the quasi-one-dimensional operation model of the thermal storage system; an evaluation model construction module, used to construct an evaluation model of the wind power absorption capacity of the electrothermal coupling system based on the objective function and constraints; and a wind power absorption capacity evaluation module, used to solve the evaluation model of the wind power absorption capacity of the electrothermal coupling system based on the non-convex constraints of the evaluation model, and obtain the evaluation result of the wind power absorption capacity of the electrothermal coupling system that takes into account frequency safety.

[0315] Exemplarily, the computer program can 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 can be a series of computer program instruction segments capable of performing preset functions, wherein the instruction segments describe the execution process of the computer program in the wind power absorption capacity assessment device of the electrothermal 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: the objective function and constraint design module is used to obtain the objective function and constraints based on the wind power absorption capacity evaluation index of the electrothermal coupling system, key indicators in the primary frequency regulation process, the cogeneration unit operation model, and the quasi-one-dimensional operation model of the thermal storage system; the evaluation model construction module is used to construct the wind power absorption capacity evaluation model of the electrothermal coupling system based on the objective function and constraints; the wind power absorption capacity evaluation module is used to solve the wind power absorption capacity evaluation model of the electrothermal coupling system based on the non-convex constraints of the wind power absorption capacity evaluation model of the electrothermal coupling system, and obtain the wind power absorption capacity evaluation result of the electrothermal coupling system that takes into account frequency safety.

[0316] The electrothermal coupling system wind power absorption capacity assessment device can be a desktop computer, laptop, handheld computer, or cloud server, etc. This device may include, but is not limited to, processors and memory. Those skilled in the art will understand that the above are examples of electrothermal coupling system wind power absorption capacity assessment devices and do not constitute a limitation on such devices. The device may include more components than described above, or combine certain components, or use different components. For example, the electrothermal coupling system wind power absorption capacity assessment device may also include input / output devices, network access devices, buses, etc.

[0317] The processor referred to can be a Central Processing Unit (CPU), or other general-purpose processors, digital signal processors (DSPs), application-specific integrated circuits (ASICs), field-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. The processor is the control center for the wind power absorption capacity assessment of the electrothermal coupling system, connecting various parts of the entire electrothermal coupling system wind power absorption capacity assessment equipment via various interfaces and lines.

[0318] The memory can be used to store the computer program and / or modules. The processor realizes various functions of the electrothermal coupling system wind power absorption capacity assessment device by running or executing the computer program and / or modules stored in the memory and calling the data stored in the memory.

[0319] The memory may primarily include a program storage area and a data storage area. The program storage area may store the operating system and at least one application program required for a function (such as sound playback, image playback, etc.). The data storage area may store data created based on the use of the mobile phone (such as audio data, phonebook, etc.). Furthermore, the memory may include high-speed random access memory and non-volatile memory, such as hard disks, RAM, plug-in hard disks, smart media cards (SMC), secure digital cards (SD cards), flash cards, at least one disk storage device, flash memory device, or other volatile solid-state storage devices.

[0320] The present invention also provides a computer-readable storage medium storing a computer program, which, when executed by a processor, implements the steps of the method for evaluating the wind power absorption capacity of an electrothermal coupling system.

[0321] If the modules / units integrated in the electrothermal coupling system wind power absorption capacity assessment system are implemented as software functional units and sold or used as independent products, they can be stored in a computer-readable storage medium.

[0322] Based on this understanding, the present invention can implement all or part of the processes in the above-mentioned method for assessing the wind power absorption capacity of an electrothermal coupling system, or it can be accomplished by a computer program instructing related hardware. The computer program can be stored in a computer-readable storage medium, and when executed by a processor, it can implement the steps of the above-mentioned method for assessing the wind power absorption capacity of an electrothermal coupling system. The computer program includes computer program code, which can be in the form of source code, object code, executable file, or a preset intermediate form, etc.

[0323] The computer-readable storage medium may include: any entity or device capable of carrying the 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 signal, telecommunication signal, and software distribution medium, etc.

[0324] It should be noted that the content contained in the computer-readable storage medium may 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, the computer-readable storage medium does not include electrical carrier signals and telecommunication signals.

[0325] The above embodiments are merely one of the implementation methods for achieving the technical solution of the present invention. The scope of protection claimed by the present invention is not limited to this embodiment, but also includes any variations, substitutions and other implementation methods that can be easily conceived by those skilled in the art within the scope of the technology disclosed in the present invention.

Claims

1. A method for evaluating the wind power absorption capacity of an electrothermal coupling system, characterized in that, include: S1. Evaluation indicators for the wind power absorption capacity of the electrothermal coupling system, specifically including: S1.1 Evaluation of wind power absorption capacity based on the joint opportunity constraint of split-blown rods S1.2 Establish the mathematical model of the DNE boundary, the specific formula is as follows: In the formula, It is a wind farm w At any moment t Actual output For wind farm w At any moment t wind curtailment power, It is a wind farm w At any moment t The prediction error Indicates a collection of wind farms. and Wind farm w The DNE boundary at time t The lower and upper limits, It is the risk value of the joint opportunity constraint of the Brussels Bar. and It is a man-made wind farm w The minimum and maximum values ​​of the allowed DNE boundary. Represents the proportion of wind curtailment; It is a fuzzy set based on the Wasserstein measure, used to describe random variables. The uncertainty; p is a subset of the fuzzy set; S2. For the primary frequency regulation on the grid side of the electrothermal coupling system, a mathematical model for key indicators during the frequency regulation process is proposed, specifically including: Based on the oscillation equation describing the primary frequency regulation process on the grid side of the electrothermal coupling system, a frequency descent rate constraint is constructed; based on the occurrence time of the frequency minimum point, a frequency minimum point constraint is constructed; simultaneously, a quasi-steady-state constraint is established. S3. Establish an operating model for cogeneration units that considers bypass modification technology, as well as a quasi-one-dimensional operating model for thermal storage systems. S4. Design the objective function and constraints, and construct an evaluation model for the wind power absorption capacity of the electrothermal coupling system considering frequency security. Specifically, this includes: S4.1 Design the objective function of the wind power absorption capacity assessment model for the electrothermal coupling system. This objective function covers the DNE boundary and curtailment rate of all wind farms within a day: In the formula, and These are wind farms w During the period t The upper and lower bounds of the DNE boundary, It is a weighting factor used to represent the importance of each wind farm; μ This represents the weight of the curtailed wind volume in the objective function. For wind farm w During the period t The proportion of wind curtailment; The constraints include power grid flow constraints, heating network heat flow constraints, traditional thermal power unit operation constraints, and uncertain reserve constraints for controllable units. S5. Considering the non-convex constraints in the model, design a solution method for the optimization model containing split-bar joint chance constraints, specifically including: The non-convex constraints include joint chance constraints with left-hand or right-hand uncertainties, as well as constraints involving differentials. The non-convex constraints are reconstructed to transform 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. The wind power absorption capacity assessment results of the electrothermal coupling system that takes into account frequency safety were obtained.

2. The method for evaluating the wind power absorption capacity of an electrothermal coupling system according to claim 1, characterized in that, in: The expression for the frequency descent rate constraint is as follows: In the formula, For time period t internal nodes i Power fluctuation at the location; This is the maximum permissible frequency descent rate of the electrothermal coupling system. Represents system inertia; It is a set of load nodes; The expression for the constraint condition of the lowest frequency point is as follows: In the formula, and Representing the CHP units g Compared with traditional thermal power units u The inertial constant, and CHP units g Compared with traditional thermal power units u The 0-1 variables of the switch state, and These represent the CHP units. g Compared with traditional thermal power units u Maximum power generation; It is the system's rated frequency; and All are constants; and CHP units g Compared with traditional thermal power units u The lowest frequency point; Let be the total primary frequency regulation reserve capacity of the system at time t; The expression for the quasi-steady-state constraint is as follows: In the formula, It is the maximum permissible frequency deviation in quasi-steady state; It is load damping; It is a time period t internal nodes i The electrical load value at the location.

3. The method for evaluating the wind power absorption capacity of an electrothermal coupling system according to claim 1, characterized in that, The operating model for the combined heat and power unit is constructed based on bypass modification technology, and the specific formula is as follows: In the formula, and CHP units g During the period t Power generation and heat production capacity, , and These represent the power generation at endpoints A, D, and J of the operating domain, respectively. It is the heat generation power at endpoint B of the operating domain. It is a CHP unit g The capacity of the installed bypass retrofit technology, and These are the slopes of sides AB and BC, respectively. It is a constant; , and These are 0-1 variables representing the unit's on / off state, startup state, and shutdown state, respectively. This represents the primary frequency regulation reserve capacity of the CHP unit. and These are the upward and downward reserve capacities used to balance the uncertainties of wind power. , and These are the upper limit of primary frequency regulation reserve capacity, the upper limit of upward reserve capacity, and the upper limit of downward reserve capacity. and These are the minimum boot time and the minimum shutdown time, respectively. and These are the maximum uphill speed and the maximum downhill speed, respectively. The quasi-one-dimensional operating model of the thermal storage system specifically includes: In the formula, and These are thermal storage systems e During the period t The heat charging power and heat dissipation power, and These represent the mass of water in the hot and cold zones, respectively. and These are the water temperatures in the hot and cold zones, respectively. It is the overall heat loss coefficient of the thermal storage system. It is the thermal conductivity of water. This represents the heat convection power between the hot and cold zones. and These are the heat power received by the cold zone during heat release and the heat loss of the cold zone during heat charging, respectively. It is the minimum heat charging and heat dissipation power of the thermal storage system. This indicates the cross-sectional area of ​​the water tank in the thermal storage system. and These are the lateral areas of the hot and cold zones, respectively. It is the height of the water tank. and These represent the minimum and maximum permissible water temperatures, respectively.

4. A wind power absorption capacity assessment system for an electrothermal coupling system, used to implement the steps of the wind power absorption capacity assessment method for an electrothermal coupling system according to any one of claims 1-3, characterized in that, include: The objective function and constraint design module is used to obtain the objective function and constraint based on the evaluation index of wind power absorption capacity of electrothermal coupling system, key indicators in primary frequency regulation process, cogeneration unit operation model and quasi-one-dimensional operation model of thermal storage system. The evaluation model building module is used to construct an evaluation model for the wind power absorption capacity of the electrothermal coupling system based on the objective function and constraints. 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 model, and obtain the wind power absorption capacity assessment result of the electrothermal coupling system that takes into account frequency safety.

5. A device, characterized in that, include: Memory, used to store computer programs; A processor, configured 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 1-3 when executing the computer program.

6. A computer-readable storage medium storing a computer program, characterized in that, When the computer program is executed by the processor, it is used to implement the steps of the method for evaluating the wind power absorption capacity of the electrothermal coupling system according to any one of claims 1-3.

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