A real-time control method for an electro-thermal energy system based on a virtual asynchronous machine

Abstract

A real-time control method for an electro-thermal energy system based on a virtual asynchronous machine, comprising: establishing a dynamic response coupling time-scale model of electric energy and thermal energy for a regional electro-thermal coupled energy system based on different time scales; a virtual asynchronous machine control method based on the dynamic response coupling time-scale model of electric energy and thermal energy, performing real-time power balance control on the electric energy side to improve the frequency dynamic response when the power demand on the DC side changes; based on judging the inertia coefficient of temperature change, adjusting the temperature response on the thermal energy side to achieve real-time control of the electro-thermal energy system. The use of the virtual asynchronous machine control with large-inertia heat and fast-response-speed power in the method of the present invention can achieve real-time power balance, and has the advantages of adapting to load power changes and suppressing frequency oscillations.

Description

Technical Field

[0001] The present invention belongs to the field of electro-thermal energy systems, and relates to a real-time control method for an electro-thermal energy system based on a virtual asynchronous machine. Background Art

[0002] In the winter heating season in China, there is a concentrated heat demand and an unpredictable power drop. Generally, a regional electro-thermal energy system can make full use of the characteristics of electricity and heat, thereby improving energy efficiency. However, while meeting the heating demand, the stable operation of the regional electricity-heat coupled energy system is affected by its limited power output. This problem poses a major challenge to the supply-demand balance of the regional energy system. In the past few years, power balance strategies have been designed to regulate the electrical or thermal output when there is an electricity and heat coupling. The regional electricity-heat coupled energy system usually operates in two modes based on priority: the heat-oriented mode and the electricity-oriented mode. On the one hand, the main goal of the traditional regional electricity-heat coupled energy system operating in the heat-oriented mode is to meet the real-time heat demand, while power generation is regarded as a secondary goal. On the other hand, a relatively electricity-oriented mode is being considered for combined heat and power units. In this mode, the system adjusts the power output according to the electricity demand. In combined heat and power, there are two methods to regulate the electricity demand. One method is to adjust the heat output of the boiler and the fuel input while maintaining a constant heat power ratio. To achieve this goal, various control technologies can be used, such as advanced boiler-turbine coordinated control. Another method is to regulate the heat power ratio by manipulating the steam turbine bypass valve, that is, heat source regulation. Heat source regulation can enable combined heat and power to bypass the slower dynamic processes of the boiler and fuel handling and quickly increase the power output. Both of these methods involve a single control variable and cannot meet the requirements of power regulation, especially in a large-scale district heating network. Therefore, in order to, the present invention proposes a real-time power balance control method for a virtual asynchronous machine based on an electro-thermal energy system.

[0003] Due to the lack of flexibility in combined heat and power units, the reduction rate of wind power generation in some provinces of China has reached as high as 20%, and the lack of power flexibility has become obvious. In terms of the power-oriented mode, due to the large number of power electronic converters, microgrids face challenges due to their low inertia. Frequent load changes and intermittent distributed generation can lead to significant frequency fluctuations, which have a negative impact on the efficiency and stability of microgrids. In contrast, compared with the power system, heat sources exhibit a slow dynamic process and a large thermal inertia. The primary frequency control in a microgrid requires a rapid response within a few seconds. Therefore, the flexibility of heat sources can be fully utilized to achieve system power balance, thereby improving the frequency response of the system. The current small hybrid microgrids have significant defects in frequency control. Although the frequency changes can be adapted by dynamically adjusting the demand, isolated microgrids with low rated power often under-react when facing significant frequency deviations, which may lead to a decline in system stability. The existing frequency deviation correction methods rely on the locally measured frequency dead zone and the linear correlation between temperature and frequency, but this strategy will cause delays in the deactivation and recovery processes of controlled loads when the frequency drops below the threshold, affecting system reliability. At the same time, although the energy storage forms have been expanded to enhance the flexibility of the power system, the thermal inertia of indoor temperatures in multi-region buildings has not been fully considered in the integrated heat and power dispatch of large power supply networks. This factor is crucial for the response of power demand and supply, and neglecting it may lead to insufficient optimization and increase the vulnerability of the system under high load conditions. In addition, new battery models still face challenges in integration and application. Overall, these defects make it urgent to improve the electro-thermal energy system in achieving efficient and stable frequency control. Summary of the Invention

[0004] To solve the above problems, the technical solution adopted by the present invention is: a real-time control method for an electro-thermal energy system based on a virtual asynchronous machine, including:

[0005] Establish a coupled time-scale model of the dynamic responses of electric energy and thermal energy for a regional electro-thermal coupled energy system based on different time scales;

[0006] Based on the virtual asynchronous machine control method of the coupled time-scale model of the dynamic responses of electric energy and thermal energy, perform real-time power balance control on the electric energy side to improve the frequency dynamic response when the power demand on the DC side changes;

[0007] Based on the real-time temperature inside the building, use the inertia coefficient of temperature change to adjust the temperature response on the thermal energy side to achieve real-time control of the electro-thermal energy system.

[0008] Further, the process of the virtual asynchronous machine control method based on the coupled time-scale model of the dynamic responses of electric energy and thermal energy is as follows:

[0009] Based on the three-phase currents abc of an asynchronous motor, obtain the dq-axis currents through park transformation;

[0010] Furthermore, the electromagnetic torque is calculated respectively through the d-axis and q-axis currents and the angular velocity compensation amount ;

[0011] Then, the mechanical torque is obtained by calculating the output of the virtual induction machine converter, the real-time input power on the AC side, and the virtual rotor speed compensation amount ;

[0012] The electromagnetic torque and the mechanical torque After subtraction, the virtual rotor angular velocity compensation amount is calculated through an adaptive inertia link, and then the synchronous speed is calculated for adjusting the mechanical torque , and at the same time, the rated angular velocity of the microgrid is obtained through subtraction calculation, and then the electrical angle of the asynchronous motor is obtained through an integral link.

[0013] Furthermore, the expression of the virtual rotor angular velocity compensation amount is as follows:

[0014]

[0015] where: J represents the inertia coefficient of the temperature change of the electro-thermal energy system, D represents the friction damping coefficient, T L is the rotor mechanical torque, is the electromagnetic torque.

[0016] Furthermore, the expression of the inertia coefficient J of the temperature change is as follows:

[0017]

[0018] where: , is the positive inertia compensation coefficient, T indoor is the indoor temperature, T norm is the set temperature of the indoor temperature, T max and T min are the maximum and minimum values of the indoor temperature respectively, J 0 is the initial inertia coefficient, is the change rate of the indoor temperature with respect to time .

[0019] Furthermore, the virtual induction machine control method based on the dynamic response coupling time scale model of electric energy and thermal energy performs real-time power balance control on the electric energy side and improves the frequency dynamic response when the power demand on the AC side changes as follows:

[0020] By collecting the voltage and current signals on the AC side, the input power of the AC side is calculated in real time ;

[0021] The power signal is controlled by the power outer loop and the current inner loop to generate the reference values of the AC electromotive force on the d-axis and q-axis respectively and ;

[0022] The reference values of the AC electromotive force and , and then the reference value of the AC electromotive force in the abc reference frame of the induction motor is obtained through Park transformation ;

[0023] The reference value of the AC electromotive force in the abc reference frame of the induction motor is modulated by PWM to generate the trigger signal of the switch tube of the rectifier, realizing the control of the virtual induction motor converter, and further realizing the real-time power balance control of the power side and improving the frequency dynamic response when the power demand on the AC side changes

[0024] Furthermore, the small-signal modeling method of the virtual induction motor is used to verify the stability of the real-time control method

[0025] Furthermore, the process of verifying the stability of the real-time control method by the small-signal modeling method of the virtual induction motor is as follows

[0026] The small-signal equation of the virtual induction motor is as follows

[0027]

[0028]

[0029]

[0030] Here

[0031] , , , ,

[0032] , , ,

[0033] , , , ,

[0034] , ,

[0035] In the formula , , , are the changes in stator current and voltage under the dq axes, and are the steady-state values of the stator current under the d-axis and q-axis respectively. is to describe the change in stator current and the change in rated angular velocity the relationship matrix between them. is to describe the change in stator current the relationship matrix; is to describe the change in stator current and the change in rotor d-axis magnetic flux and the change in stator current the change in rotor angular velocity the relationship matrix between them; is to describe the change in stator current and the change in stator voltage the relationship matrix between them; is to describe the change in stator current and the change in stator voltage the relationship matrix between them; is to describe the change in rotor d-axis magnetic flux and the change in stator current the relationship matrix between them; is to describe the change in rotor d-axis magnetic flux the relationship matrix; is to describe the change in rotor angular velocity and the change in rated angular velocity the relationship matrix between them; is to describe the change in rotor angular velocity and the change in stator current the relationship matrix between them; is to describe the change in rotor angular velocity and the change in rotor d-axis magnetic flux the relationship matrix between them; is to describe the change in rotor angular velocity the relationship matrix;

[0036] Matrix is composed of the stator q-axis current and the stator d-axis current at the rated operating point. The in the matrix is the rotational speed at the rated operating point, and are the stator and rotor resistances respectively, , and are the rotor leakage inductance, stator leakage inductance, and magnetizing inductance, respectively. Similarly, the matrix is also composed through operations of the system structure parameters and the angular velocity at the rated operating point. The in the matrix is the rotor d-axis magnetic flux at the rated operating point, . is the inertia coefficient, is the active power proportionality coefficient, is the damping coefficient;

[0037] The small-signal equation between and the amplitude of the inverter output voltage is expressed as follows:

[0038]

[0039] Here:

[0040] , ,

[0041] In the formula, is the stator voltage variation, is the relationship matrix of the stator voltage variation relative to the inverter voltage variation ; is the relationship matrix of the stator voltage variation relative to the phase angle variation ; , are the steady-state values of the power angle and voltage of the m th inverter, respectively, diag indicates that this matrix is a diagonal matrix;

[0042] Neglecting energy losses, according to the power balance on both sides of the AC-DC integrated circuit, there is:

[0043]

[0044] , , , are the stator d-axis voltage, stator q-axis voltage, stator d-axis current, and stator q-axis current, respectively; , are the DC-side voltage and current; is the DC-side capacitance value, is the time variation rate of the DC-side voltage, is the output current of the DC side;

[0045] Then, the variation of the DC-side voltage The small-signal model is written as:

[0046]

[0047] Where:

[0048] , , ,

[0049] In the formula, represents the variation of the DC-side voltage, , , , respectively represent the relationship matrices of the variation of the DC-side voltage with respect to the variation of the stator current , the variation of the stator voltage , itself, and the variation of the DC-side output current . And are the steady-state values of the stator voltage under the d-axis and q-axis respectively, C is the value of the DC-side capacitor. , are the steady-state values of the DC-side voltage and the output current respectively. And are the steady-state values of the stator current under the d-axis and q-axis respectively;

[0050] The electric boiler is simulated as a fixed resistor , which varies with the load condition and is described as follows:

[0051]

[0052] Therefore, the small-signal state space of the electric boiler is:

[0053]

[0054] Where:

[0055]

[0056] In the formula, is the admittance matrix reflecting the relationship between the variation of the DC-side voltage and the DC-side output current ;

[0057] The small-signal state space equation of the virtual asynchronous machine converter is expressed as follows:

[0058]

[0059] In the formula, is the state variable of the interconnection converter, is its derivative with respect to time, is the state variable on the AC side and the relationship matrix between the state variables of the interconnection converter ; is the relationship matrix reflecting the relationship between the state variables of the interconnection converter;

[0060] Here:

[0061]

[0062] , ,

[0063] ;

[0064] In the formula, is the power angle change, is the angular velocity change, is the voltage change, , are the line and load current changes on the AC side respectively, is the selection matrix;

[0065] The complete small-signal model of the AC side is written as:

[0066]

[0067] In the formula, is the relationship matrix reflecting the relationship between the state variables on the AC side, is the state variable of the interconnection converter and the relationship matrix between the state variables on the AC side ;

[0068] Here:

[0069]

[0070] ,

[0071] ,

[0072] , ,

[0073]

[0074] In the formula, is M×MThe unit matrix of size, is M×1 a column vector with all elements equal to 1 in size, M is the number of inverters, is the change in angular velocity and the relationship matrix between the change in dq-axis current of the inverter is the change in inverter voltage and the relationship matrix between the change in dq-axis current of the inverter is the change in angular velocity of the inverter and the relationship matrix between the change in inverter voltage is the relationship matrix of the change in inverter voltage with itself is the m steady-state operating point of the voltage of the th inverter. , are respectively the active and reactive droop coefficients of the th inverter, m is the angular velocity of the inverter. is the power angle relationship matrix of multiple inverters, which is composed of diagonalizing the power angle relationship matrix of a single inverter and is determined by by and and is the m steady-state value of the power angle of the th inverter. is the line incidence matrix in the DC section. In each row, the column elements corresponding to the line input or output are 1 or 1, and the other elements are 0;

[0075] , ,

[0076] , ,

[0077] ,

[0078] In the formula, is used to reflect the relationship between the output current and the power angle of the inverter under the dq-axis, and is composed of diagonalizing the matrix and is determined by the of a single inverter , and and respectively, which are the mThe steady-state values of the output currents under the d-axis and q-axis of an inverter, and the sine and cosine values of the power angle. Matrix is used to reflect the angular velocity relationship. It is a diagonal matrix, and all the diagonals of the matrix are ;

[0079] Finally, by synthesizing the above formulas, the small-signal model of the regional electro-thermal integrated system is obtained.

[0080] The small-signal model is expressed as follows:

[0081]

[0082] Here,[[]]END]] is a combined system overall matrix that reflects all the relationships of the system, are all the state variables of the system;

[0083] Here, there is:

[0084] , .

[0085] It is composed of the AC-side state variables and the interconnection converter state variables , is composed of the relationship matrix that reflects the AC-side relationship, the relationship matrix that reflects the interconnection converter relationship, the that reflects the coupling relationship between the AC side and the interconnection converter side, and combined and formed.

[0086] A real-time control method for an electro-thermal energy system based on a virtual asynchronous machine provided by the present invention uses heat with large inertia and electricity with fast response speed to control the virtual asynchronous machine, verifies the small-signal stability of the proposed control strategy, and realizes real-time power balance. It has the following characteristics:

[0087] This method provides the ability to achieve real-time power balance control. A coupled time-scale model based on the electrical and thermal dynamic responses at different time scales is established. This model utilizes the building heating system as a virtual energy storage system to adjust the thermal output with large inertia according to the power changes of the power grid. This process realizes the real-time power balance in the regional electro-thermal coupled energy system, thereby improving the frequency stability on the AC side. This achievement first proposes a virtual asynchronous machine control strategy based on the regional electro-thermal coupled energy system, improving the frequency dynamic response when the power demand on the AC side changes. Compared with the virtual synchronous generator control strategy, the virtual asynchronous machine strategy has the advantages of adapting to load power changes and suppressing frequency oscillations. To obtain a better temperature response, an adaptive inertia control method based on temperature changes is proposed, and a unified expression is established. When the indoor temperature deviates from the set temperature, a relatively large inertia is used, and when the indoor temperature stabilizes to the set temperature as soon as possible, a relatively small inertia is used, so that a better temperature response can be obtained.

[0088] Compared with the existing technologies, the advantages of the present invention are:

[0089] The virtual asynchronous machine control proposed in the present invention does not need to know the grid frequency and rotor frequency, because the frequency will automatically change with the power change. When the load power changes, the virtual asynchronous machine control can automatically optimize the frequency on the AC side. Different from the minute-level and hour-level power optimization scheduling methods of the traditional electro-thermal coupled energy system, the virtual asynchronous machine control using large-inertia heat and fast-response-speed power proposed in the present invention can achieve real-time power balance. Compared with the virtual synchronous generator control strategy, the virtual asynchronous machine method has the advantages of adapting to load power changes and suppressing frequency oscillations. BRIEF DESCRIPTION OF THE DRAWINGS

[0090] In order to more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the following will briefly introduce the drawings required for use in the description of the embodiments or the prior art. Obviously, the drawings in the following description are some embodiments of the present invention. For those of ordinary skill in the art, without creative efforts, other drawings can also be obtained based on these drawings.

[0091] Figure 1 is a schematic structural diagram of the regional integrated electro-thermal energy system;

[0092] Figure 2 is a schematic diagram of the model architecture of the electric boiler heating system of the present invention;

[0093] Figure 3 is a schematic diagram of the charge and discharge model of the virtual energy storage system;

[0094] Figure 4 is a schematic diagram of the virtual asynchronous machine converter model;

[0095] Figure 5 It is the structure diagram and vector schematic diagram of the asynchronous machine;

[0096] Figure 6 It is the schematic diagram of the power and current controller;

[0097] Figure 7 It is the schematic diagram of the virtual asynchronous machine controller. Specific implementation manners

[0098] It should be noted that, without conflict, the embodiments in the present invention and the features in the embodiments can be combined with each other. The present invention will be described in detail below with reference to the drawings and in combination with the embodiments.

[0099] To make the objectives, technical solutions and advantages of the embodiments of the present invention clearer, the technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention. Obviously, the described embodiments are only a part rather than all of the embodiments of the present invention. The description of at least one exemplary embodiment below is actually only illustrative and in no way limits the present invention and its application or use. All other embodiments obtained by those of ordinary skill in the art based on the embodiments of the present invention without creative efforts shall fall within the protection scope of the present invention.

[0100] A real-time control method for an electro-thermal energy system based on a virtual asynchronous machine, comprising:

[0101] S1. Establish a dynamic response coupling time-scale model of electric energy and heat energy for a regional electro-thermal coupling energy system based on different time scales;

[0102] S2. Based on the virtual asynchronous machine control method of the dynamic response coupling time-scale model of electric energy and heat energy, perform real-time power balance control on the electric energy side to improve the frequency dynamic response when the power demand on the AC side changes;

[0103] S3. Based on the real-time temperature in the building, adopt the inertia coefficient of the temperature change to adjust the temperature response on the heat energy side to achieve real-time control of the electro-thermal energy system.

[0104] The steps S1 / S2 / S3 are executed in sequence;

[0105] Figure 1 It is the structure schematic diagram of the regional integrated electro-thermal energy system;

[0106] The regional electro-thermal coupling energy system is composed of a microgrid, a virtual asynchronous machine converter, an electric boiler system and a building heat load,

[0107] The virtual asynchronous machine converter converts the alternating current of the AC microgrid into direct current to meet the requirements of the electric boiler system; the electric boiler, as a DC load, converts electrical energy into heat energy to provide the required heat for the building. Through this connection structure, the regional electric-thermal coupling energy system realizes the efficient conversion and coordinated utilization of electrical energy and heat energy, improving the overall energy utilization efficiency.

[0108] The dynamic response coupling time-scale model of electrical energy and heat energy includes an electric boiler system model, a building thermal model, and a virtual energy storage system model;

[0109] S1-1. The construction process of the electric boiler system model is as follows: As Figure 2 shown:

[0110] The electric power consumed by the heat storage electric boiler P eb is as follows:

[0111]

[0112] In the formula: P i1 is the electric power of the direct heating part of the heat storage electric boiler; P i2 is the electric power of the heat storage part of the heat storage electric boiler; is the abandoned wind and light flag. When b = 1, it means there is abandoned wind and light. When b = 0, it means there is no abandoned wind and light.

[0113] The electric power of the electric boiler P i1 and P i2 The expression is as follows:

[0114]

[0115]

[0116] In the formula: I i1 is the current of the direct heating part of the heat storage electric boiler, I i2 is the current of the heat storage part of the heat storage electric boiler, and the voltage U is 220V.

[0117] The output heating power of the heat storage electric boiler is:

[0118]

[0119] The heat release power of the heat storage type electric boiler and its heat storage device is very high and has a linear relationship with the power consumption of electric energy, that is:

[0120]

[0121]

[0122] In the formula: Q 01 ( t ) is the output heat power of the heat storage type electric boiler; is a constant representing the electro-thermal conversion efficiency of the electric boiler; Q i2 ( t ) is the heat storage power of the heat storage device of the heat storage type electric boiler.

[0123] The heat obtained by the radiator from the heat network pipeline Q sink is as follows:

[0124]

[0125] The heat obtained inside the building Q HEAT is:

[0126]

[0127] In the formula: density and specific heat capacity C w can be obtained by looking up the table according to the water temperature, and the water flow V w can be measured using a flowmeter, is the water temperature difference between the inlet and outlet of the radiator, S sink is the total heat dissipation area of the radiator, is the logarithmic mean temperature difference.

[0128] S1-2. The construction process of the building thermal model is as follows:

[0129] Ignoring factors such as the heat released by the activities of indoor personnel in the building rooms and the heat transfer between adjacent rooms, etc., through applying the building heat balance equation, a quantitative mathematical relationship can be established among the indoor temperature, outdoor temperature, and heating demand. Its expression is as follows:

[0130]

[0131]

[0132]

[0133] Wherein, represents the variable relative time change amount of. Q HEAT is the heat output by the radiator, T HEAT is the radiator temperature, T indoor is the indoor temperature, T outdoor is the outdoor temperature, M dot is the air mass flow rate through the radiator, Q loss is the lost heat, M air is the indoor air quality, c is the specific heat capacity of air under constant pressure, R eq is the equivalent resistance of the lost temperature.

[0134] S1-3. Construction of the virtual energy storage system model, as Figure 3 shown.

[0135] Considering the main heat exchange factors, the building heat balance equation is specifically obtained as:

[0136]

[0137] Wherein: is the total heat absorbed indoors, is the heat transfer through the exterior wall, is the heat transfer through the roof, is the solar radiation passing through the window.

[0138]

[0139] Wherein: is the heat lost through the exterior wall heat transfer, is the heat increased through the exterior wall heat transfer, towards i total wall area (square meters) of the wall, is the building i heat transfer coefficient of the wall.

[0140]

[0141] Wherein: is the heat lost through the roof heat transfer, is the heat increased through the roof heat transfer, towards j total roof area (square meters) of the roof, Building j Heat transfer coefficient of the roof.

[0142]

[0143] Where: is the total heat transfer through the window, is the glass transmittance coefficient, is the solar intensity coefficient, is the building l heat transfer coefficient of the window, is i total solar radiation (kW / m²) on the wall when facing the sun.

[0144] When the indoor temperature rises ( dT indoor > 0), the thermal energy of the indoor air also increases , which indicates that there is energy storage during dt .

[0145] Conversely, when the indoor temperature drops ( dT indoor < 0), the thermal energy of the indoor air decreases , which means that there is energy release during dt . Therefore, the heat storage capacity of the building and the indoor temperature are adjusted according to the dynamic power demand.

[0146]

[0147] Among them, represents the power flow for charging and discharging the virtual energy storage system at time t ; a positive value indicates discharging, and a negative value indicates charging; represents the heat load demand when the virtual energy storage system performs power balance regulation; represents the heat load demand without using the virtual energy storage system (VESS) for power balance regulation.

[0148] According to the physical model of the induction motor, the mathematical model of the induction motor needs to be derived, and then the control model of the virtual induction machine needs to be derived. Before studying the mathematical model of the induction motor, in order to exclude the influence of mechanical manufacturing and installation, environmental factors, etc., certain idealized assumptions need to be made for the induction motor, and the assumptions are as follows:

[0149] Assumption 1: Ignoring space harmonics and slot effects, the three-phase windings are symmetric, and the electrical angles are 120° apart in space, and the magnetomotive force generated is distributed sinusoidally around the air gap;

[0150] Assumption 2: Ignoring magnetic circuit saturation, the self-inductance and mutual inductance of each winding are linear;

[0151] Hypothesis 3: Core loss is ignored;

[0152] Hypothesis 4: The influence of temperature and frequency on the winding resistance is not considered;

[0153] Hypothesis 5: The motor rotor is transformed to the stator side, and the number of turns per phase is equal before and after the transformation.

[0154] In the virtual asynchronous machine control method of the regional electro-thermal coupling system described in step S2, calculation formulas are derived from the basic structure and principle of the asynchronous machine, thereby obtaining the virtual asynchronous machine converter model, as Figure 4 shown. The specific process is as follows:

[0155] S2-1. Basic characteristics of the asynchronous motor.

[0156] The slip rate of the asynchronous motor is defined as:

[0157]

[0158] where: 、 and are the synchronous frequency, rotor frequency, and slip frequency, respectively.

[0159] Using space vector notation, the stator voltage and rotor voltage equations of the asynchronous motor with a short-circuited rotor are as follows:

[0160]

[0161]

[0162] where: p represents the differential operator, r and s represent the rotor and stator respectively, and the stator inductance 、rotor inductance ,where L lr 、L ls and L m are the rotor leakage inductance, stator leakage inductance, and magnetizing inductance respectively. represents the stator resistance, represents the rotor resistance, represents the stator current, represents the rotor current, is the system angular velocity, j is the imaginary part of the complex number, and =-1.

[0163] The formula for calculating the air-gap power P ag is:

[0164]

[0165] In the formula, represents the absolute value of the rotor current, is the slip.

[0166] The estimated formulas for the output converted mechanical power ( P mech ) and torque ( T e ) of the induction motor are:

[0167]

[0168]

[0169] Assume that the grid frequency drops, and the power / torque waveform corresponding to this grid frequency shifts to the left. In this case, the rotor speed will also converge to a new unknown equilibrium point. That is to say, the frequency of the induction motor will automatically change with the change of power. There is no need to know the grid frequency and the rotor frequency because they change and adjust simultaneously.

[0170] S2-2. The physical model of the induction motor is as Figure 5 shown. The matrix form of the voltage equation of the induction motor is as follows (using the differential operator p to replace the differential symbol):

[0171]

[0172] In the formula: is the stator resistance, , , respectively represent the three-phase stator phase voltages, , , are the instantaneous values of the three-phase stator currents, , , are the instantaneous values of the three-phase stator flux linkages. is the rotor resistance, , , the instantaneous values of the three-phase rotor currents, , , are the instantaneous values of the three-phase rotor flux linkages, , , respectively represent the three-phase rotor phase voltages.

[0173] The flux linkages of the three-phase stator and rotor windings are equal to the sum of the self-inductance flux linkages and the mutual inductance flux linkages of other windings. The flux linkage equations of each phase winding can be expressed as:

[0174]

[0175] In the formula: , , are the three-phase stator flux linkages, , , are the three-phase rotor flux linkages, , , , , , are the self-inductances of their respective windings, , , , , , , , , , , , , , , , , , , , , , , , , , , , , , are the mutual inductances of their respective corresponding windings, , , , , , are the currents flowing through their respective windings.

[0176] L ms is used to represent the maximum mutual inductance magnetic flux linked to the stator winding one, and is called the stator mutual inductance; L mr is used to represent the maximum mutual inductance magnetic flux linked to the rotor winding one, and is called the rotor mutual inductance.

[0177] Since the number of turns of the stator and rotor windings is equal after the motor conversion, the mutual inductance magnetic flux between the windings passes through the air gap and the magnetic resistance is equal, the stator mutual inductance is equal to the rotor mutual inductance, that is:

[0178]

[0179] For each phase winding, the sum of the mutual inductance and leakage flux of the motor constitutes the flux linkage. Therefore, the self-inductance of each stator phase is as follows:

[0180]

[0181] where: L ls is the leakage inductance of the stator.

[0182] The self-inductance of each rotor phase is as follows:

[0183]

[0184] where: L lr is the leakage inductance of the rotor.

[0185] The mutual inductance between the motor windings can be divided into two categories: one is the mutual inductance between the stator and stator, and between the rotor and rotor of the motor, and the other is the mutual inductance between the stator and rotor.

[0186] The first type of mutual inductance is constant because the positions of the phase windings in space are fixed, so the mutual inductance is constant. Assuming that the phase difference of the axes of the three-phase windings in space is 120°, and assuming that the air-gap flux of the motor is distributed according to a sine function, the expression of the first mutual inductance can be obtained.

[0187]

[0188]

[0189] where, is the cosine function, and its function is to compensate for the angle difference between phases

[0190] Since the relative position between any phase of the motor stator and any phase of the motor rotor is not fixed, the second type of mutual inductance is not a constant, but a function of the space angular displacement variable as follows:

[0191]

[0192]

[0193]

[0194] The equivalent model of the induction motor on the dq axes is as follows:

[0195]

[0196]

[0197]

[0198]

[0199] Wherein: and are the synchronous frequency and the slip frequency respectively; , , , , and are the dq-axis voltage, current, and stator flux respectively.

[0200] The control expressions of the rotor and stator flux links can be described as:

[0201]

[0202]

[0203]

[0204]

[0205] Wherein: the stator inductance and the rotor inductance .

[0206] The virtual torque of the virtual synchronous machine is expressed as follows:

[0207]

[0208] In addition, assuming that in the steady state, the virtual rotor flux is aligned with the d-axis, i.e., . The virtual torque can be reformulated as

[0209]

[0210] Formulas and are simplified to:

[0211]

[0212]

[0213] Wherein, is the slip frequency, is the change in angular velocity.

[0214] According to the above formulas, it can be obtained that

[0215]

[0216]

[0217] Substituting, it can be obtained:

[0218]

[0219]

[0220] In the formula: 。

[0221] The mechanical power of the asynchronous motor is expressed as follows:

[0222]

[0223] Where J represents the sum of the inertia coefficients of the temperature change of the electrothermal energy system, D represents the friction damping coefficient, is the virtual rotor electrical angular velocity, T m is the mechanical torque, and there is:

[0224]

[0225] That is, the mechanical power of the asynchronous motor is as follows:

[0226]

[0227] T L is the rotor mechanical torque, and its calculation formula is:

[0228]

[0229] Where, is the exchange power between the DC side and the AC side, is the virtual regulator part, the rated set point of the AC microgrid frequency, is the active power coefficient.

[0230] If we set as the deviation of the virtual rotor frequency from the initial value the formula will become:

[0231]

[0232] It has the characteristics of a first-order low-pass filter in the frequency domain, that is:

[0233]

[0234] Synchronous speed and angle reference can be obtained from 、 and the angular velocity difference as follows:

[0235]

[0236]

[0237] When the indoor temperature deviates from the set temperature, , a relatively large inertia is used according to the adaptive inertia coefficient formula, which can weaken the impact of temperature changes on user comfort; the set temperature is 20 °C

[0238] On the other hand, when the indoor temperature stabilizes to the set temperature as soon as possible, that is , a relatively small inertia is used according to the adaptive inertia coefficient formula.

[0239] Therefore, based on the temperature adaptive inertia coefficient the following conclusions are drawn:

[0240]

[0241] Where: , is the positive inertia compensation coefficient, is the sign function. T indoor is the indoor temperature, T norm is the set temperature of the indoor temperature, T max and T min are the maximum and minimum values of the indoor temperature respectively, and J 0 is the initial inertia coefficient.

[0242] In summary, the schematic diagrams of the power and current controllers and the virtual asynchronous machine controller are respectively as Figure 6 and Figure 7 shown, which gives the virtual asynchronous machine control structure of the regional electro-thermal coupling energy system, where the electro-thermal network is not directly connected, but is linked together through multiple coupling devices. In this case, the heating network is simulated as a system of partial differential-algebraic hybrid equations. Its step size is usually between a few seconds and a few minutes and is denoted as the large step size component set.

[0243] The numerical differential method solution steps are summarized as:

[0244] ① Select the iteration step size h ;

[0245] ② Select a suitable numerical solution method;

[0246] ③ Establish a recurrence formula for the numerical solution, and gradually deduce the solution of the subsequent moment from the current sampling value and the estimated value of the previous moment. To reduce the estimation error and make the model calculation converge, the key is to select a small step size or use a high-precision algorithm.

[0247] Considering the characteristics of distribution parameters, the power network is simulated as a system of partial differential algebraic equations, which requires a simulation step size in the microsecond range. Therefore, it can be separately set as a small-step component.

[0248] The control method of the virtual asynchronous machine based on the coupled time-scale model of the dynamic responses of electric energy and thermal energy is as follows:

[0249] Based on the three-phase currents abc of the asynchronous motor, the dq-axis currents are obtained through Park transformation;

[0250] Furthermore, the electromagnetic torque and the angular velocity compensation amount are calculated respectively through the currents in the dq-axis;

[0251] Then, the mechanical torque is obtained by calculating the output of the virtual asynchronous machine converter, the real-time input power of the AC side, and the virtual rotor speed compensation amount ;

[0252] The electromagnetic torque and the mechanical torque are subtracted, and then the virtual rotor angular velocity compensation amount is calculated through an adaptive inertia link , and then the synchronous speed is calculated for adjusting the mechanical torque , and at the same time, the rated angular velocity of the microgrid is obtained through subtraction calculation , and then the electrical angle of the asynchronous motor is obtained through an integral link .

[0253] The control method of the virtual asynchronous machine based on the coupled time-scale model of the dynamic responses of electric energy and thermal energy for the real-time power balance control on the electric energy side and improving the frequency dynamic response when the power demand on the AC side changes is as follows:

[0254] By collecting the voltage and current signals on the AC side, the input power of the AC side is calculated in real time ;

[0255] The power signal is controlled through a power outer loop and a current inner loop to generate the reference values of the AC electromotive force on the dq-axis and ,

[0256] The reference values of the AC electromotive force and , and then the reference value of the AC electromotive force in the abc reference frame of the asynchronous motor is obtained through inverse Park transformation ;

[0257] The AC electromotive force reference value of the asynchronous motor under the abc reference frame is modulated by PWM to generate the switch trigger signal of the rectifier, realizing the control of the virtual asynchronous machine converter, and then realizing the real-time power balance control on the power side, improving the frequency dynamic response when the power demand on the AC side changes. In addition, the electrical angle used in Park transformation Output by virtual asynchronous machine control method, such as Figure 7 Through this control structure, the virtual asynchronous machine can simulate the dynamic behavior of the traditional asynchronous generator and enhance the stability of the system.

[0258] Furthermore, the method includes a process of verifying the stability of the method by using a virtual asynchronous machine small signal modeling method.

[0259] The process of the virtual asynchronous machine small signal modeling method is as follows:

[0260] The small signal equation of the virtual asynchronous machine (VAM) is as follows:

[0261]

[0262]

[0263]

[0264] Where:

[0265] , , , ,

[0266] , , ,

[0267] , , , ,

[0268] , ,

[0269] In the formula, , , , is the stator current and voltage variation under dq axis, and are the steady-state values ​​of the stator current under the d-axis and q-axis respectively. To describe the stator current variation Change from rated angular velocity The relationship matrix between them. To describe the relationship matrix of the change in stator current ; To describe the relationship matrix of the change in stator current and the change in rotor d - axis magnetic flux as well as the change in stator current and the change in rotor angular velocity ; To describe the relationship matrix of the change in stator current and the change in stator voltage ; To describe the relationship matrix of the change in stator current and the change in stator voltage ; To describe the relationship matrix of the change in rotor d - axis magnetic flux and the change in stator current ; To describe the relationship matrix of the change in rotor d - axis magnetic flux ; To describe the relationship matrix of the change in rotor angular velocity and the change in rated angular velocity ; To describe the relationship matrix of the change in rotor angular velocity and the change in stator current ; To describe the relationship matrix of the change in rotor angular velocity and the change in rotor d - axis magnetic flux ; To describe the relationship matrix of the change in rotor angular velocity ;

[0270] Matrix is composed of the stator q - axis current and the stator d - axis current at the rated operating point. In matrix , is the rotational speed at the rated operating point, and are the stator and rotor resistances respectively, , and are the rotor leakage inductance, stator leakage inductance and magnetizing inductance respectively. Similarly, matrix is also formed by the system structure parameters and the angular velocity at the rated operating point through operations. In matrix , is the rotor d - axis magnetic flux at the rated operating point, . is the inertia coefficient, is the active power ratio coefficient, is the damping coefficient.

[0271] The small-signal equation between and the amplitude of the inverter output voltage is expressed as follows:

[0272]

[0273] Here:

[0274] , ,

[0275] In the formula, is the change in stator voltage, is the relationship matrix of the change in stator voltage with respect to the change in inverter voltage ; is the relationship matrix of the change in stator voltage with respect to the change in phase angle ; , are respectively the steady-state values of the power angle and voltage of the m th inverter, diag indicates that this matrix is a diagonal matrix.

[0276] Ignoring energy losses, according to the power balance on both sides of the AC-DC integrated circuit, we have:

[0277]

[0278] , , , are respectively the stator d-axis voltage, stator q-axis voltage, stator d-axis current, and stator q-axis current; , are the DC-side voltage and current; is the DC-side capacitance value, is the time rate of change of the DC-side voltage, is the output current of the DC side.

[0279] Then, the change in the DC-side voltage is written as the small-signal model:

[0280]

[0281] Here:

[0282] , , ,

[0283] In the formula, represents the change in DC-side voltage, , , , respectively represent the relationship matrices of the change in DC-side voltage with respect to the change in stator current , the change in stator voltage , itself, and the change in DC-side output current . and are the steady-state values of the stator voltage under the d-axis and q-axis respectively, C is the value of the DC-side capacitor. , are the steady-state values of the DC-side voltage and output current respectively. and are the steady-state values of the stator current under the d-axis and q-axis respectively.

[0284] The electric boiler is simulated as a fixed resistor , which changes with the load condition and is described as follows:

[0285]

[0286] Therefore, the small-signal state space of the electric boiler is:

[0287]

[0288] Here:

[0289]

[0290] In the formula, is the admittance matrix reflecting the relationship between the change in DC-side voltage and the DC-side output current .

[0291] The small-signal state space equation of the virtual asynchronous machine converter is expressed as follows:

[0292]

[0293] In the formula, is the state variable of the interconnection converter, is its derivative with respect to time, is the state variable of the AC side and the state variable of the interconnection converter ; is the relationship matrix reflecting the relationship between the state variables of the interconnection converter.

[0294] Here:

[0295]

[0296] , ,

[0297] ;

[0298] Wherein, is the power angle change amount, is the angular velocity change amount, is the voltage change amount, , are the line and load current change amounts on the AC side respectively, is the selection matrix.

[0299] The complete small-signal model of the AC side is written as:

[0300]

[0301] Wherein, is the relationship matrix reflecting the relationship between the state variables on the AC side, is the state variable of the interconnection converter and the relationship matrix between the state variables on the AC side .

[0302] Here:

[0303]

[0304] ,

[0305] ,

[0306] , ,

[0307]

[0308] Wherein, is M×M the identity matrix of size, is M×1 the column vector with all elements equal to 1 of size, M is the number of inverters, is the angular velocity change amount and the relationship matrix between the dq-axis current change amounts of the inverters , is the inverter voltage change amount and the relationship matrix between the dq-axis current change amounts of the inverters The relationship matrix between is the change in the angular velocity of the inverter and the change in the inverter voltage The relationship matrix between is the change in the inverter voltage The relationship matrix of its own relationship is the m voltage steady-state operating point of the -th inverter. and m are the active and reactive droop coefficients of the -th inverter respectively, is the power angle relationship matrix of multiple inverters, which is composed of the power angle relationship matrix of a single inverter through diagonalization, is determined by and , is the steady-state value of the power angle of the m -th inverter. is the line incident matrix in the DC section. In each row, the column elements corresponding to the line input or output are 1 or 1, and other elements are 0;

[0309] , ,

[0310] , ,

[0311] ,

[0312] In the formula, is used to reflect the relationship between the output current of the inverter under the dq axis and the power angle, and is composed of the matrix through diagonalization, is determined by the , and of a single inverter and . They are the steady-state values of the output current under the d axis and q axis of the m -th inverter and the sine and cosine values of the power angle respectively. The matrix is used to reflect the angular velocity relationship. It is a diagonal matrix, and all the diagonals of the matrix are .

[0313] Finally, by combining the above formulas, the small-signal model of the regional integrated electric and thermal system is obtained.

[0314] The small-signal model is expressed as follows:

[0315]

[0316] Here, is the overall system matrix formed by combination, reflecting all the relationships of the system, are all the state variables of the system.

[0317] Here there is:

[0318] , .

[0319] Composed of the AC-side state variables and the interconnection converter state variables , Composed of the relationship matrix reflecting the AC-side relationship , the relationship matrix reflecting the interconnection converter relationship , the reflecting the coupling relationship between the AC side and the interconnection converter side and combined to form.

[0320] Finally, it should be noted that: the above embodiments are only used to illustrate the technical solutions of the present invention, rather than limiting it; although the present invention has been described in detail with reference to the foregoing embodiments, those of ordinary skill in the art should understand that: they can still modify the technical solutions recorded in the foregoing embodiments, or perform equivalent replacements on some or all of the technical features; and these modifications or replacements do not make the essence of the corresponding technical solutions deviate from the scope of the technical solutions of the embodiments of the present invention.

Claims

1. A real-time control method for an electric thermal energy system based on a virtual asynchronous machine, characterized in that: include: Establish a coupled time scale model of the dynamic response of electric and thermal energy in a regional electric-thermal coupled energy system based on different time scales; A virtual asynchronous machine control method based on a coupled time scale model of the dynamic response of electric energy and thermal energy is used to achieve real-time power balance control on the electric energy side and improve the frequency dynamic response when the power demand on the DC side changes. The virtual asynchronous machine control method based on the electric energy and thermal energy dynamic response coupling time scale model is as follows: Based on the three-phase current abc of the asynchronous motor, the dq axis current is obtained through park transformation; Then the electromagnetic torque is calculated by the current in the dq axis respectively and angular velocity compensation ; The mechanical torque is then calculated by calculating the virtual asynchronous machine converter output, the real-time input power on the AC side, and the virtual rotor speed compensation. ; Electromagnetic torque and mechanical torque After the subtraction operation, the virtual rotor angular velocity compensation is calculated through the adaptive inertia link. , and then calculate the synchronous speed To adjust the mechanical torque , and the rated angular velocity of the microgrid is obtained by subtracting , and then the electrical angle of the asynchronous motor is obtained through the integral link ; Based on the real-time temperature in the building, the inertia coefficient of temperature change is used to adjust the temperature response of the thermal energy side to achieve real-time control of the electric thermal energy system; The virtual rotor angular velocity compensation The expression is as follows: Where: J represents the inertia coefficient of the temperature change of the electric thermal energy system, D represents the friction damping coefficient, T L is the rotor mechanical torque, Electromagnetic torque; The virtual asynchronous machine control method based on the coupled time scale model of the dynamic response of electric energy and thermal energy controls the real-time power balance on the electric energy side and improves the dynamic frequency response when the power demand on the AC side changes as follows: By collecting the voltage and current signals on the AC side, the input power on the AC side is calculated in real time ; The power signal is controlled by the power outer loop and the current inner loop to generate the AC electromotive force reference values ​​on the d-axis and q-axis respectively. and , AC electromotive force reference value and , and then the AC electromotive force reference value of the asynchronous motor in the abc reference system is obtained through Park transformation ; The AC electromotive force reference value of the asynchronous motor under the abc reference system is modulated by PWM to generate the switch trigger signal of the rectifier, so as to realize the control of the virtual asynchronous machine converter, and then realize the real-time power balance control on the electric energy side, and improve the frequency dynamic response when the power demand on the AC side changes; The process of using the virtual asynchronous machine small signal modeling method to verify the stability of the real-time control method is as follows: The small signal equation of the virtual asynchronous machine is as follows: Where: ， ， ， ， ， ， ， ， ， ， ， ， ， In the formula, , , , is the stator current and voltage variation under dq axis, and are the steady-state values ​​of the stator current under the d-axis and q-axis respectively, To describe the stator current variation Change from rated angular velocity The relationship matrix between To describe the stator current variation The relationship matrix of To describe the stator current variation The change of the rotor d-axis magnetic flux And stator current change Rotor angular velocity change The relationship matrix between them; To describe the stator current variation The stator voltage change The relationship matrix between them; To describe the stator current variation The stator voltage change The relationship matrix between them; To describe the change in the rotor d-axis magnetic flux The stator current variation The relationship matrix between them; To describe the change in the rotor d-axis magnetic flux The relationship matrix of To describe the change in rotor angular velocity Change from rated angular velocity The relationship matrix between them; To describe the change in rotor angular velocity The stator current variation The relationship matrix between them; To describe the change in rotor angular velocity The change in the rotor d-axis magnetic flux The relationship matrix between them; To describe the change in rotor angular velocity The relationship matrix of matrix The stator q-axis current at the rated operating point is and stator d-axis current Composition, Matrix In is the speed at the rated operating point, and are the stator and rotor resistances, respectively, , and are the rotor leakage inductance, stator leakage inductance and magnetizing inductance respectively. Similarly, the matrix Also determined by the system structure parameters and the angular velocity at the rated operating point After calculation, the matrix In is the rotor d-axis magnetic flux at the rated operating point, , is the inertia coefficient, is the active proportional coefficient, is the damping coefficient; The inverter output voltage amplitude The small signal equation between is expressed as follows: Where: ， ， In the formula, is the stator voltage change, is the stator voltage change relative to the inverter voltage change The relationship matrix of is the stator voltage change relative to the phase angle change Relationship Matrix , Respectively m The steady-state values ​​of the power angle and voltage of each inverter, diag Indicates that the matrix is ​​a diagonal matrix; Ignoring energy loss, according to the power balance on both sides of the AC / DC integrated circuit, we have: , , , They are stator d-axis voltage, stator q-axis voltage, stator d-axis current, and stator q-axis current respectively; , is the DC side voltage and current; is the DC side capacitance value, is the time rate of change of the DC side voltage, is the output current on the DC side; Then, the change in DC side voltage is The small signal model of is written as: Where: ， ， ， In the formula, Indicates the change in DC side voltage, , , , Respectively represent the DC side voltage change relative to the stator current change , stator voltage change , itself and DC side output current The relationship matrix of the variation, and are the steady-state values ​​of the stator voltage on the d-axis and q-axis respectively, C is the DC side capacitance value, , are the steady-state values ​​of DC side voltage and output current respectively, and are the steady-state values ​​of the stator current on the d-axis and q-axis respectively; The electric boiler is modeled as a fixed resistor , varies with load conditions and is described as follows: Therefore, the small signal state space of the electric boiler is: Where: In the formula, To reflect the change of DC side voltage The DC output current Admittance matrix of the relation; The small signal state space equation of the virtual asynchronous machine converter is expressed as follows: In the formula, is the state variable of the interconnect converter, is its derivative with respect to time, is the state variable on the AC side State variables of interconnected converters The relationship matrix between them; is a relation matrix reflecting the relationship between the state variables of the interconnected converters; Where: ， ， ； In the formula, is the power angle change, is the change in angular velocity, is the voltage change, , are the line and load current changes on the AC side, is the selection matrix; The complete AC side small signal model is written as: In the formula, To reflect the relationship matrix between the state variables of the AC measurement, is the interconnect converter state variable and AC side state variables The relationship matrix between them; Where: ， ， ， ， In the formula, for M×M The identity matrix of size, for M×1 A column vector whose size is all 1. M is the number of inverters, is the angular velocity change The change of inverter dq axis current The relationship matrix between is the inverter voltage change The change of inverter dq axis current The relationship matrix between is the inverter angular velocity change The inverter voltage change The relationship matrix between is the inverter voltage change The relationship matrix of its own relationship, For the m The voltage steady-state operating point of the inverter is , Respectively m Active and reactive droop coefficients of each inverter, is the inverter angular velocity, is the power angle relationship matrix of multiple inverters, which is composed of the power angle relationship matrix of a single inverter Diagonal composition, Depend on and Decide, For the m The inverter power angle steady-state value, is the line incident matrix of the DC section, and the column elements corresponding to the line input or output in each row are 1 or 1, other elements are 0; ， ， ， ， ， In the formula, It is used to reflect the relationship between the output current and power angle of the inverter under the dq axis, which is represented by the matrix Diagonal composition, From a single inverter , and and Decision, which are m The steady-state value of the output current of the inverter under the d-axis and q-axis and the sine and cosine values ​​of the power angle, the matrix It is used to reflect the angular velocity relationship. It is a diagonal matrix, and the diagonals of the matrix are ; Finally, combining the above formulas, the small signal model of the regional electric and thermal integrated system is obtained: The small signal model is expressed as follows: Here, The system matrix is ​​composed of a combination of the system matrix, which reflects all the relationships of the system. are all the state variables of the system; Here are: ， ， The state variables of the AC side and interconnect converter state variables composition, The relationship matrix reflecting the communication side relationship , the relationship matrix reflecting the relationship between interconnected converters , reflecting the coupling relationship between the AC side and the interconnected converter side and Combination formation.

2. According to claim 1, a real-time control method for an electric thermal energy system based on a virtual asynchronous machine is characterized in that: The expression of the temperature-varying inertia coefficient J is as follows: in: , is the positive inertia compensation coefficient, T indoor is the indoor temperature, T norm Set the temperature for the indoor temperature, T max and T min are the maximum and minimum values ​​of the indoor temperature, J0 is the initial inertia coefficient, is the indoor temperature relative to time The rate of change.

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