Micro-grid compensation control method and device based on risk avoidance and storage medium

Abstract

The invention provides a micro-grid compensation control method and device based on risk avoidance and a storage medium, and relates to the field of power system safety. The method comprises the following steps: establishing a risk measurement constraint of a micro-grid system; the risk measurement constraint is used for avoiding the influence of a risk event on the micro-grid system performance, and the risk event is determined according to the occurrence probability and the loss degree of the event; establishing a micro-grid compensation control model by taking the risk measurement constraint as a model constraint condition and taking the minimum sum of the reasonability of power distribution of the micro-grid system, the regulation amplitude of the voltage frequency and the closeness degree of the voltage frequency and a standard value as a model target; obtaining measurement data of the voltage frequency of the micro-grid system; and based on the measurement data, solving the micro-grid compensation control model to obtain a compensation regulation and control strategy of the voltage frequency of the micro-grid system, and performing compensation regulation and control on the micro-grid system based on the compensation regulation and control strategy. Risk measurement constraints are introduced into micro-grid system control, so that the system can avoid risks and operate stably.

Description

Technical Field

[0001] The present invention relates to the field of power system safety technology, and in particular to a microgrid compensation control method, device and storage medium based on risk avoidance. Background Art

[0002] With the rapid development of the global economy and the acceleration of the industrialization process, the demand for energy has increased year by year, and new energy distributed generation technologies such as solar energy and wind energy have received widespread attention. Microgrids, as a small power distribution system that integrates distributed generation, loads, energy storage and other equipment, have achieved extensive integration of renewable energy sources such as wind and solar energy. However, the extensive integration of renewable energy has also brought new challenges to microgrids. For example, under risk factors such as extreme weather (such as strong winds, heavy rainfall, etc.), the supply of renewable energy may be interrupted, resulting in sudden disconnection of distributed power sources, which in turn causes serious line failure problems, causing significant fluctuations in line power supply quality, and even grid collapse. However, the existing microgrid control strategies cannot fully cope with the challenges of the above risks. Therefore, it is crucial to design a control strategy that can effectively mitigate these risk interferences. Summary of the invention

[0003] The present invention provides a microgrid compensation control method, device and storage medium based on risk avoidance, which are used to solve the defect that the existing microgrid control strategy cannot avoid the influence of risk factors and realize risk avoidance control of the microgrid.

[0004] The present invention provides a microgrid compensation control method based on risk avoidance, comprising the following steps.

[0005] Establishing risk measurement constraints for the microgrid system; the risk measurement constraints are used to avoid the impact of risk events on the performance of the microgrid system, and the risk events are determined based on the probability of occurrence of the event and the degree of loss; Taking the risk measurement constraint as the model constraint condition, taking the rationality of the power distribution of the microgrid system, the regulation amplitude of the voltage and frequency, and the minimum sum of the proximity between the voltage and frequency and the standard value as the model objective, a microgrid compensation control model is established; Obtaining measurement data of voltage and frequency of microgrid system; Based on the measurement data, solving the microgrid compensation control model to obtain a compensation control strategy for the voltage and frequency of the microgrid system; The microgrid system is compensated and regulated based on the compensation and regulation strategy.

[0006] According to a microgrid compensation control method based on risk avoidance provided by the present invention, solving the microgrid compensation control model includes: The risk measurement constraints are transformed into constraints on the mean and variance of voltage and frequency of multiple DG units in the microgrid system, and a solvable risk measurement constraint is obtained.

[0007] According to a microgrid compensation control method based on risk avoidance provided by the present invention, the compensation regulation strategy includes a multi-step compensation regulation sequence of voltage and frequency in the time dimension.

[0008] According to a microgrid compensation control method based on risk aversion provided by the present invention, the risk measurement constraint is established based on an exponential risk measurement method.

[0009] According to a microgrid compensation control method based on risk avoidance provided by the present invention, the microgrid compensation control model is established on the basis of a droop control method in combination with a quadratic deviation compensation control method.

[0010] According to a microgrid compensation control method based on risk avoidance provided by the present invention, the secondary deviation compensation control method adopts a distributed secondary control method.

[0011] According to a microgrid compensation control method based on risk avoidance provided by the present invention, the objective function is as follows: in, Indicates DG unit exist The objective function at time, t Indicates time, k Indicates the time number. represents the predicted time domain of voltage frequency, represents the number of control steps in the prediction time domain, Indicates the rated standard value of frequency, Indicates the rated voltage value. Indicates local i The equivalent frequency, Indicates local i The equivalent voltage, local i Including DG units And with DG unit Connected DG units, λ represents the weight coefficient, represents the control time domain of voltage frequency, Indicates the compensation control amplitude, Indicates the number of the DG unit. x represents the number of DG units, Indicates DG unit With DG unit connectivity, P Indicates active power, Q Represents reactive power,S Indicates power, Indicates DG unit To DG unit communication delay.

[0012] According to a microgrid compensation control method based on risk avoidance provided by the present invention, the solvable risk measurement constraint is as follows: in, Indicates local i The equivalent frequency, Indicates local i The equivalent voltage, local i Including DG units And with DG unit Connected DG units, represents the predicted frequency, V represents the predicted voltage, t Indicates time, k Indicates the time number. n represents the number of control steps, j Indicates the DG unit number, express Time DG unit With DG unit connectivity, Indicates DG unit To DG unit The communication delay, x represents the number of DG units, express Time DG unit The square of the difference between the frequency and the expected standard value of each unit frequency, express Time DG unit The square of the difference between the frequency and the expected standard value of each unit frequency, express Time DG unit The square of the difference between the voltage and the expected standard value of each unit voltage, express Time DG unit The square of the difference between the voltage and the expected standard value of each unit voltage, K represents the risk factor.

[0013] The present invention also provides a microgrid compensation control device based on risk avoidance, comprising the following modules: A risk measurement constraint building module is used to establish risk measurement constraints for the microgrid system; the risk measurement constraints are used to avoid the impact of risk events on the performance of the microgrid system, and the risk events are determined based on the probability of occurrence of the event and the degree of loss; A compensation control model building module is used to establish a microgrid compensation control model with the risk measurement constraint as a model constraint condition and the rationality of microgrid system power distribution, the voltage and frequency regulation amplitude, and the minimum sum of the proximity between the voltage and frequency and the standard value as the model objective; A data acquisition module, used to obtain measurement data of voltage and frequency of the microgrid system; A model solving module, used to solve the microgrid compensation control model based on the measurement data to obtain a compensation control strategy for the voltage and frequency of the microgrid system; A compensation control module is used to perform compensation control on the microgrid system based on the compensation control strategy.

[0014] The present invention also provides an electronic device, comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein when the processor executes the program, a microgrid compensation control method based on risk avoidance as described above is implemented.

[0015] The present invention also provides a non-transitory computer-readable storage medium having a computer program stored thereon, and when the computer program is executed by a processor, the microgrid compensation control method based on risk avoidance as described in any one of the above is implemented.

[0016] The present invention also provides a computer program product, comprising a computer program, wherein when the computer program is executed by a processor, the computer program implements any of the risk avoidance-based microgrid compensation control methods described above.

[0017] The risk-avoidance-based microgrid compensation control method, device and storage medium provided by the present invention introduce risk measurement constraints into the microgrid compensation control model, and take the rationality of the power distribution of the microgrid system, the voltage-frequency regulation amplitude and the minimum sum of the proximity of the voltage-frequency to the standard value as the goal to calculate the compensation control strategy of the microgrid voltage-frequency. Therefore, when a line fault occurs in the microgrid system due to risk factors, the above compensation control strategy can avoid the impact of the fault on the microgrid system and ensure the stable operation of the microgrid system. BRIEF DESCRIPTION OF THE DRAWINGS

[0018] In order to more clearly illustrate the technical solutions in the present invention or the prior art, the following briefly introduces the drawings required for use in the embodiments or the description of the prior art. Obviously, the drawings described below are some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0019] Figure 1 It is a flow chart of a microgrid compensation control method based on risk avoidance provided in an embodiment of the present invention.

[0020] Figure 2 It is a simplified equivalent circuit diagram of multiple DG units operating in parallel in an island mode provided by an embodiment of the present invention.

[0021] Figure 3 It is a predictive control structure diagram of the model predictive control (MPC) provided in an embodiment of the present invention.

[0022] Figure 4 It is a diagram of a risk measurement method provided by an embodiment of the present invention.

[0023] Figure 5 It is a compensation control flow chart based on the risk-avoidance MPC algorithm provided by an embodiment of the present invention.

[0024] Figure 6 It is a structural diagram of a microgrid compensation control device based on risk avoidance provided in an embodiment of the present invention.

[0025] Figure 7 It is a schematic diagram of the structure of an electronic device provided by an embodiment of the present invention. DETAILED DESCRIPTION

[0026] In order to make the purpose, technical solution and advantages of the present invention clearer, the technical solution of the present invention will be clearly and completely described below in conjunction with the drawings of the present invention. Obviously, the described embodiments are part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0027] Aiming at the current situation that the existing microgrid control schemes are unable to cope with risk events (such as microgrid line failures and DG disconnection caused by extremely bad weather), this paper proposes a microgrid secondary dynamic compensation control strategy based on risk avoidance. By predicting and compensating the mitigation response that the microgrid system should make when it is disturbed by risk events, the impact of risk events on the microgrid system is avoided, thereby ensuring the safe and stable operation of the microgrid.

[0028] Combine the following Figure 1-Figure 5The present invention describes a microgrid compensation control method based on risk avoidance.

[0029] Figure 1 is one of the flow charts of the microgrid compensation control method based on risk avoidance provided by an embodiment of the present invention, such as Figure 1 As shown, the microgrid compensation control method based on risk avoidance includes the following steps: Step 101: Establish risk measurement constraints for a microgrid system; the risk measurement constraints are used to avoid the impact of risk events on the performance of the microgrid system, and the risk events are determined based on the probability of occurrence of the event and the degree of loss.

[0030] Step 102: Establish a microgrid compensation control model with the risk measurement constraint as the model constraint and the rationality of microgrid system power distribution, the voltage and frequency regulation amplitude, and the minimum sum of the proximity between the voltage and frequency and the standard value as the model objective.

[0031] Step 103: Acquire the measurement data of the voltage and frequency of the microgrid system.

[0032] Step 104: Solve the microgrid compensation control model based on the measurement data to obtain a compensation control strategy for the voltage and frequency of the microgrid system; Step 105: Perform compensation regulation on the microgrid system based on the compensation regulation strategy.

[0033] In some embodiments of the present invention, considering that variables such as frequency, voltage, active power and reactive power are coupled in a microgrid, a microgrid compensation control model is constructed based on the concept of droop control.

[0034] In the primary control of the microgrid, droop control is usually used to adjust the frequency and voltage of the microgrid system to ensure the uniform distribution of power among multiple DG units and achieve the decoupling of active and reactive power. The basic principle of droop control can be described by the equivalent circuit of a voltage source inverter connected to the AC bus. Figure 2 It is a simplified equivalent circuit diagram of multiple DG units operating in parallel in island mode.

[0035] Figure 2 middle E i For DG i The output voltage amplitude, V pcc is the voltage at the common coupling point, Z i is the sum of the voltage source inverter output impedance and the line impedance, S i is the power transmitted by the voltage source inverter to the common AC bus, which can be expressed as: (1) Separate the real and imaginary parts of equation (1) and consider that in the microgrid, the impedance Z i It is mainly inductive impedance. The resistance part is significantly smaller than the inductance part. The active power output of each DG unit is obtained. P i and reactive power Q i They are: (2) In the above formula, , L i is the coupled inductance in the line, coupled inductance L i The phase angle deviation caused Defined by formula (3): (3) From formula (2), we can see that the output active power of DG is mainly affected by the power angle δ The output reactive power mainly depends on the output voltage of DG. δ The droop control equation can be derived as follows: (4) In the above formula, and Respectively represent the frequency and voltage amplitude of the distributed DG unit output under initial conditions, and They are the frequency droop coefficient and the voltage droop coefficient respectively.

[0036] In an embodiment of the present invention, when the system adopts droop control to control steady-state operation, the system voltage and frequency deviate from the rated value, and due to the influence of line impedance, the active and reactive power output by each DG unit cannot be accurately distributed. Therefore, it is necessary to introduce secondary control and superimpose its output on the droop control to compensate for the frequency and voltage deviations caused by the droop control, so that its droop characteristic curve is shifted in parallel. Existing secondary control methods can be divided into centralized, decentralized and distributed. The centralized control strategy requires each DG unit to communicate with the central controller and receive control instructions. This control method is highly dependent on high-bandwidth communication links, but once any communication link fails, the operation of the controlled unit may become disordered, thereby threatening the stable operation of the microgrid. The decentralized control strategy only requires local information of the DG unit, but due to the lack of global information, it is impossible to achieve coordinated control and global state consistency of the DG units in the microgrid. Distributed control comprehensively coordinates the advantages and disadvantages of centralized control and decentralized control. Based on the principle of sparse communication network, the DG units in distributed control only receive information from their neighbors or root nodes, reducing the communication burden and coordinating the global states of all DG units in the microgrid to remain consistent. Based on this, the secondary control method of the embodiment of the present invention uses a distributed control method.

[0037] The compensation methods for droop control in distributed control are divided into general compensation method and optimization compensation method. The general compensation method uses classical control theory to compensate for the deviation values ​​of physical quantities such as voltage and current through the regulator, or changes the droop coefficient through the change value of the associated physical quantity, thereby compensating the droop curve. On the basis of the general compensation method, the optimization compensation method calculates the compensation amount through various optimization algorithms to achieve the optimization of the control target. At present, the most widely used optimization compensation method is the distributed secondary control strategy based on the consistency algorithm. Model predictive control (MPC), which can be applied to more complex systems and has better control performance, has been widely used in distributed secondary control strategies. Its predictive control structure diagram is shown in the figure below. Figure 3 As shown. MPC predicts the future operating state of the microgrid and designs online rolling optimization of the value function with multiple objectives and constraints. It has a natural advantage in solving complex microgrid optimization control problems, and by combining predictive control with distributed solutions, the system has plug-and-play (PnP) functions. Based on this, the microgrid compensation control model of this embodiment adopts a secondary distributed control strategy based on MPC.

[0038] This embodiment adopts a distributed control strategy based on model predictive control to incorporate the compensation value of the secondary control into the traditional droop control equation, and its droop characteristic can be expressed as: (5) In the above formula, the relationship between frequency-active power and voltage-reactive power is defined respectively, wherem i and n i They represent the droop coefficients of active power and reactive power respectively, ω 0 and V 0 Respectively represent the frequency rated standard value and voltage rated standard value. In the formula, and Indicates the frequency compensation value and voltage compensation value introduced by secondary control.

[0039] As mentioned above, distributed control is based on the principle of sparse communication network. DG units only receive information from their neighbors or root nodes and coordinate the global state of all DG units in the microgrid to keep consistent. For the communication model of distributed control, DG units i and j The bidirectional links between a ij and delayed items The adjacency term indicates the connectivity between two DG units. The DG units received in each sampling period i The function of information is shown in formula (6).

[0040] (6) In the embodiment of the present invention, the distributed microgrid communication delay problem is also considered, and the delay term ( ). Delayed Items ( ≥1) measured within the sampling period, indicating DG i and DG j The time required for the sending and receiving process between. Since the communication is full-duplex, that is, the communication parties can send and receive information at the same time, the information interaction method satisfies the equation τ ij = τ ji and a ij = a ji That's it.

[0041] In an embodiment of the present invention, the output of the above-mentioned model predictive control algorithm is a multi-step compensation regulation sequence of voltage and frequency in the time dimension, and the specific implementation method can be as follows.

[0042] By performing Taylor expansion transformation on equations (2), (3) and (5) to simplify the optimization problem, we can obtain the prediction model and determine t k+n The behavior of the DG unit at . The equation is as follows: (7) In the formula, For local measurement information; , is the coupling inductance in the line; ,in The sampling period used for secondary control. and It is defined as follows by formula (8): (8) Understandably, n For the compensation control steps, the predicted compensation control sequence of the frequency is , the predicted compensation control sequence of voltage is The reason why the embodiment of the present invention performs multi-step compensation for power and voltage instead of one-time compensation is to avoid one-time compensation causing excessive fluctuation and impact on the system, thereby affecting the stability of the system.

[0043] The objective function of the embodiment of the present invention is introduced below.

[0044] In the embodiment of the present invention, as shown in formula (9), the objective function is composed of a six-item weighted matrix machine, where each item represents a control target in the microgrid. The establishment of the first two items is to make the frequency and voltage Close to the reference standard value; the third and fourth items minimize the control operations required to achieve the control target, so that the control effect is not too large and affects the stability of the entire system; the last two items reach a consensus on the contribution of active and reactive power of adjacent DGs, thereby achieving a reasonable distribution of active and reactive power. The specific objective function is as follows: (9) in, Indicates DG unit exist The objective function at time, t Indicates time, k Indicates the time number. Represents the predicted time domain of voltage frequency (for objects ), represents the number of control steps in the prediction time domain, Indicates the rated standard value of frequency, Indicates the rated voltage value. Indicates local i The equivalent frequency, Indicates local i The equivalent voltage, local i Including DG unit And with DG unit The connected DG units, λ represents the weight coefficient, Indicates the control time domain of voltage frequency (for objects ), Indicates the compensation control amplitude, Indicates the number of the DG unit. x represents the number of DG units, Indicates DG unit With DG unit connectivity, P Indicates active power, Q Represents reactive power, S Indicates power, Indicates DG unit To DG unit communication delay.

[0045] The risk measurement constraints in the embodiments of the present invention are introduced below.

[0046] Microgrid is a typical random hybrid system. At present, the control methods for random hybrid systems mainly include risk measurement methods based on mathematical expectation and methods based on Min-Max thinking. The risk measurement method based on mathematical expectation does not consider the impact of "low probability, high loss" events on the control results when designing controllers. The method based on Min-Max thinking easily leads to the conservatism of control strategies, such as Figure 4 Therefore, in order to simultaneously consider the probability and severity of risk events, ensure the control effect under normal conditions, and effectively avoid the impact of extreme events on system performance, the embodiment of the present invention adopts an exponential risk measurement method (which is more sensitive to uncertainty and fluctuation) and applies it to the constraints of the microgrid compensation control model, as shown in formula (10), which can ensure the stability of the system while increasing the anti-disturbance performance of the system.

[0047] (10) Where E is the expectation, exp is the exponential function, is a risk-sensitive parameter.

[0048] By establishing the objective function, the problem to be optimized is clarified. By adding the risk measurement idea into the microgrid compensation control model of the controller, the designed controller can have better stability when facing risk events.

[0049] However, the established risk measurement constraint (exponential risk measurement method) cannot be directly solved when the objective function is added, so it is derived and transformed for subsequent solution. The derivation and transformation process is as follows: (11) It can be seen that, ignoring the high order, It can be considered as a linear combination of mean and variance. This conclusion can help design solvable system constraints.

[0050] When θ approaches 0 Equivalent to E(J), it is risk neutral; when θ<0, it indicates risk aversion (conservative); when θ>0, it indicates risk preference (risk taking). Ignoring the higher order, It can be considered as a linear function of mean plus variance.

[0051] Based on the above objective function and risk constraint equivalence ideas, the embodiment of the present invention establishes a system operation constraint consisting of a set of frequency and voltage mean and variance of multiple DG units. The design of the constraint condition mainly defines the mean equation of the output frequency and voltage of each DG droop control. At the same time, the mean equation of the output frequency and voltage variance of each DG unit is added to the mean equation of the output frequency and voltage. The final steady-state operation result can reach the rated value, so that the voltage and frequency return to the standard value. This set of constraints is defined as follows: (12a) (12b) (12c) (12d) (12e) (12f) in, Indicates local i The equivalent frequency, Indicates local i The equivalent voltage, local i Including DG unit And with DG unit Connected DG units, represents the predicted frequency, V represents the predicted voltage, t Indicates time, k Indicates the number, n represents the number of control steps, j Indicates the DG unit number, express Time DG unit With DG unit connectivity, Indicates DG unit To DG unit The communication delay, x represents the number of DG units, express Time DG unit The square of the difference between the frequency and the expected standard value of each unit frequency, express Time DG unit The square of the difference between the frequency and the expected standard value of each unit frequency, express Time DG unit The square of the difference between the voltage and the expected standard value of each unit voltage, express Time DG unit The square of the difference between the voltage and the expected standard value of each unit voltage. K represents the risk factor. Adjusting the size of K is to adjust the risk preference of the compensation control model of the present invention. The effect is the same. By adjusting the size of K, the properties of the compensation control model can be adjusted between conservative and risky. It can be understood that the compensation control strategy based on the conservative compensation control model will make the probability of stable operation of the microgrid higher than that based on the risky compensation control model.

[0052] Equations (12a) and (12b) contain the parameters and . The parameters integrate the received information into the calculation of the equation mean, thus ensuring stability in the event of communication failure or DG off-grid data loss. represents the delay estimate during the communication process, which is used to compensate for the network delay on the predicted mean. Equations (12c) and (12d) ensure that the frequency and voltage values ​​at the end of the prediction range converge to the rated standard values. To ensure that the optimization problem has a feasible solution, equations (12e) and (12f) ensure that the system voltage and DG power are within a reasonable and specific range.

[0053] At this point, based on the conditional constraints, the objective function is minimized and the quadratic programming problem is solved to obtain the frequency and voltage compensation control sequence. The specific algorithm flow chart is as follows: Figure 5 .

[0054] Based on the objective function and system operation constraints, the matrix vector [A i , B i , H, F, Ae, Be] to construct the quadratic programming (QP) problem for each DG in the microgrid, as defined in (13). The optimal solution is a solution that contains the prediction range Predicted values ​​and control limits on A vector of control sequences on , providing a sequence of control actions, but only applying the first element, solving the optimization problem again in the next sampling period.

[0055] (13) The controller updates the matrix [A i ,B i , H, F, Ae, Be], and the controller output vector Y is obtained by solving the QP problem i ={Y pi ,Y Δi}, the output vector contains the predicted range Predicted values ​​and control ranges within The control sequence in Eq. (14) defines the predictor variable set Y pi and the optimal control sequence Y Δi , as shown below: (14) It should be noted that stable predictive control requires a feasible solution to the optimization problem, so if the QP problem obtains an infeasible solution, then and Set to zero.

[0056] It should be noted that, since the embodiment of the present invention adopts distributed control, each DG unit is applicable to the above compensation control model. For any DG unit, it collects its own power and voltage in each sampling period. When the actual collected power and voltage deviate from the rated power standard value and voltage standard value, the actual collected power and voltage are input into the above compensation control model to solve the model, and a frequency and voltage control sequence containing multiple-step compensation values ​​is obtained, and then the frequency and voltage of the DG unit can be compensated and controlled according to the control sequence. The compensation control here is divided into multiple steps. For example, taking 5 steps as an example (the number of steps can be determined according to actual conditions), the voltage compensation control sequence {3,2,2,3,1} means that the voltage compensation is 3V in the first step, 2V in the second step, 2V in the third step, 3V in the fourth step, and 1V in the fifth step, until the last step is adjusted to restore the frequency and voltage of the DG unit to the rated standard value.

[0057] It should be further explained that while the compensation control sequence is being calculated, the frequency and voltage of the DG unit are also being collected in real time. Once it is determined that the frequency or voltage has changed significantly based on the collected data, the collected frequency and voltage data are re-entered into the compensation control model for re-solution, and then compensation control is performed based on the updated compensation control sequence. The relatively large frequency and voltage fluctuations here may be caused by a DG unit exiting (or joining) the grid or a load joining (or exiting) the grid.

[0058] The distributed voltage frequency quadratic dynamic compensation control strategy based on the model predictive control algorithm in the embodiment of the present invention uses the droop control equation, phase angle deviation equation and power transmission equation as prediction models, takes communication connection and delay into consideration, designs system constraint items based on risk constraints, and obtains the quadratic control compensation amount of frequency voltage by solving the objective function. and , the compensation amount is added to the droop control to compensate for the parameter drop of the system. Since the present invention takes risk constraints into consideration when solving the compensation amount of frequency voltage, the microgrid control based on the present invention can cope with the interference caused by risk factors and achieve stable operation of the system.

[0059] The microgrid prediction control device based on risk avoidance provided by the present invention is described below. The microgrid prediction control device based on risk avoidance described below and the microgrid compensation control method based on risk avoidance described above can be referenced to each other. Figure 6 The structure diagram of the microgrid compensation control device based on risk avoidance provided by the embodiment of the present invention is as follows: Figure 6 As shown, the device includes the following modules: The risk measurement constraint building module 601 is used to establish the risk measurement constraint of the microgrid system; the risk measurement constraint is used to avoid the impact of risk events on the performance of the microgrid system, and the risk event is determined according to the probability of occurrence of the event and the degree of loss; The compensation control model building module 602 is used to establish a microgrid compensation control model with the risk measurement constraint as the model constraint condition and the rationality of the power distribution of the microgrid system, the regulation amplitude of the voltage and frequency, and the minimum sum of the proximity between the voltage and frequency and the standard value as the model target; The data acquisition module 603 is used to obtain the measurement data of the voltage and frequency of the microgrid system; The model solving module 604 is used to solve the microgrid compensation control model based on the measurement data to obtain a compensation control strategy for the voltage and frequency of the microgrid system.

[0060] The compensation control module 605 is used to perform compensation control on the microgrid system based on the compensation control strategy.

[0061] The specific working of each module in the device can be cross-referenced with the risk avoidance-based microgrid compensation control method described above, and will not be described in detail here.

[0062] Figure 7 An example of a physical structure diagram of an electronic device is shown in FIG. Figure 7As shown, the electronic device may include: a processor 810, a communication interface 820, a memory 830 and a communication bus 840, wherein the processor 810, the communication interface 820 and the memory 830 communicate with each other through the communication bus 840. The processor 810 may call the logic instructions in the memory 830 to execute the microgrid compensation control method based on risk avoidance, the method comprising: establishing a risk measurement constraint of the microgrid system; the risk measurement constraint is used to avoid the impact of risk events on the performance of the microgrid system, and the risk event is determined according to the probability and severity of the event; taking the microgrid system constraint as the model constraint condition, taking the rationality of the power distribution of the microgrid system, the voltage frequency regulation amplitude and the minimum sum of the proximity of the voltage frequency to the standard value as the model target, establishing a microgrid prediction control model; the microgrid system constraint includes the risk measurement constraint; obtaining the measurement data of the voltage frequency of the microgrid system; solving the microgrid prediction control model based on the measurement data to obtain the regulation strategy of the voltage frequency of the microgrid system. As for a more specific method, reference may be made to the microgrid compensation control method based on risk avoidance described above, which will not be repeated here.

[0063] In addition, the logic instructions in the above-mentioned memory 830 can be implemented in the form of a software functional unit and can be stored in a computer-readable storage medium when it is sold or used as an independent product. Based on this understanding, the technical solution of the present invention is essentially or the part that contributes to the prior art or the part of the technical solution can be embodied in the form of a software product, and the computer software product is stored in a storage medium, including a number of instructions to enable a computer device (which can be a personal computer, a server, or a network device, etc.) to perform all or part of the steps of the method described in each embodiment of the present invention. The aforementioned storage medium includes: U disk, mobile hard disk, read-only memory (ROM, Read-Only Memory), random access memory (RAM, Random Access Memory), disk or optical disk and other media that can store program codes.

[0064] On the other hand, the present invention also provides a computer program product, which includes a computer program, which can be stored on a non-transitory computer-readable storage medium. When the computer program is executed by a processor, the computer can execute the microgrid compensation control method based on risk avoidance provided by the above methods, which includes: establishing a risk measurement constraint for the microgrid system; the risk measurement constraint is used to avoid the impact of risk events on the performance of the microgrid system, and the risk event is determined according to the probability of occurrence of the event and the degree of loss; using the risk measurement constraint as a model constraint condition, and taking the rationality of the power distribution of the microgrid system, the voltage frequency regulation amplitude, and the minimum sum of the proximity of the voltage frequency to the standard value as the model target, to establish a microgrid compensation control model; obtaining the measurement data of the voltage frequency of the microgrid system; based on the measurement data, solving the microgrid compensation control model to obtain the compensation control strategy of the voltage frequency of the microgrid system; and compensating and controlling the microgrid system based on the compensation control strategy. As for a more specific method, reference can be made to the microgrid compensation control method based on risk avoidance described above, which will not be repeated here.

[0065] On the other hand, the present invention also provides a non-transitory computer-readable storage medium, on which a computer program is stored, and when the computer program is executed by the processor, it is implemented to execute the microgrid compensation control method based on risk avoidance provided by the above methods, the method comprising: establishing a risk measurement constraint for the microgrid system; the risk measurement constraint is used to avoid the impact of risk events on the performance of the microgrid system, and the risk event is determined according to the probability of occurrence of the event and the degree of loss; using the risk measurement constraint as a model constraint condition, and taking the rationality of the power distribution of the microgrid system, the regulation amplitude of the voltage frequency, and the minimum sum of the proximity of the voltage frequency to the standard value as the model target, a microgrid compensation control model is established; the measurement data of the voltage frequency of the microgrid system is obtained; based on the measurement data, the microgrid compensation control model is solved to obtain the compensation control strategy of the voltage frequency of the microgrid system; based on the compensation control strategy, the microgrid system is compensated and regulated. As for a more specific method, reference can be made to the microgrid compensation control method based on risk avoidance described above, which will not be repeated here.

[0066] The device embodiments described above are merely illustrative, wherein the units described as separate components may or may not be physically separated, and the components displayed as units may or may not be physical units, that is, they may be located in one place, or they may be distributed on multiple network units. Some or all of the modules may be selected according to actual needs to achieve the purpose of the scheme of this embodiment. Ordinary technicians in this field can understand and implement it without paying creative labor.

[0067] Through the description of the above implementation methods, those skilled in the art can clearly understand that each implementation method can be implemented by means of software plus a necessary general hardware platform, and of course, can also be implemented by hardware. Based on this understanding, the above technical solution is essentially or the part that contributes to the prior art can be embodied in the form of a software product, and the computer software product can be stored in a computer-readable storage medium, such as ROM / RAM, a disk, an optical disk, etc., including a number of instructions for a computer device (which can be a personal computer, a server, or a network device, etc.) to execute the methods described in each embodiment or some parts of the embodiments.

[0068] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, rather than to limit it. Although the present invention has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that they can still modify the technical solutions described in the aforementioned embodiments, or make equivalent replacements for some of the technical features therein. However, these modifications or replacements do not deviate the essence of the corresponding technical solutions from the spirit and scope of the technical solutions of the embodiments of the present invention.

Claims

1. A microgrid compensation control method based on risk avoidance, characterized in that: include: Establish risk measurement constraints for microgrid systems; The risk measurement constraint is used to avoid the impact of risk events on the performance of the microgrid system, and the risk event is determined according to the probability of occurrence of the event and the degree of loss; Taking the risk measurement constraint as the model constraint condition, taking the rationality of the power distribution of the microgrid system, the regulation amplitude of the voltage and frequency, and the minimum sum of the proximity between the voltage and frequency and the standard value as the model objective, a microgrid compensation control model is established; Obtaining measurement data of voltage and frequency of microgrid system; Based on the measurement data, solving the microgrid compensation control model to obtain a compensation control strategy for the voltage and frequency of the microgrid system; The microgrid system is compensated and regulated based on the compensation and regulation strategy.

2. The microgrid compensation control method based on risk avoidance according to claim 1 is characterized in that: The solving of the microgrid compensation control model comprises: The risk measurement constraints are transformed into constraints on the mean and variance of voltage and frequency of multiple DG units in the microgrid system, and a solvable risk measurement constraint is obtained.

3. The microgrid compensation control method based on risk avoidance according to claim 1 is characterized in that: The compensation control strategy includes a multi-step compensation control sequence of voltage frequency in the time dimension.

4. The microgrid compensation control method based on risk avoidance according to claim 1 is characterized in that: The risk measurement constraint is established based on an exponential risk measurement method.

5. The microgrid compensation control method based on risk avoidance according to claim 1 is characterized in that: The microgrid compensation control model is established on the basis of the droop control method and combined with the quadratic deviation compensation control method.

6. The microgrid compensation control method based on risk avoidance according to claim 5 is characterized in that: The quadratic deviation compensation control method adopts a distributed quadratic control method.

7. The microgrid compensation control method based on risk avoidance according to any one of claims 1 to 6, characterized in that: The objective function is as follows: in, Indicates DG unit exist The objective function at time, t Indicates time, k Indicates the time number. represents the predicted time domain of voltage frequency, represents the number of control steps in the prediction time domain, Indicates the rated standard value of frequency, Indicates the rated voltage value. Indicates local i The equivalent frequency, Indicates local i The equivalent voltage, local i Including DG units And with DG unit The connected DG units, λ represents the weight coefficient, represents the control time domain of voltage frequency, Indicates the compensation control amplitude, Indicates the number of the DG unit. x represents the number of DG units, Indicates DG unit With DG unit connectivity, P Indicates active power, Q Represents reactive power, S Indicates power, Indicates DG unit To DG unit communication delay.

8. The microgrid compensation control method based on risk avoidance according to any one of claims 1 to 6, characterized in that: The solvable risk measurement constraints are as follows: in, Indicates local i The equivalent frequency, Indicates local i The equivalent voltage, local i Including DG units And with DG unit Connected DG units, represents the predicted frequency, V represents the predicted voltage, t Indicates time, k Indicates the time number. n represents the number of control steps, j Indicates the DG unit number, express Time DG unit With DG unit connectivity, Indicates DG unit To DG unit The communication delay, x represents the number of DG units, express Time DG unit The square of the difference between the frequency and the expected standard value of each unit frequency, express Time DG unit The square of the difference between the frequency and the expected standard value of each unit frequency, express Time DG unit The square of the difference between the voltage and the expected standard value of each unit voltage, express Time DG unit The square of the difference between the voltage and the expected standard value of each unit voltage, K represents the risk factor.

9. An electronic device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein: When the processor executes the program, the microgrid compensation control method based on risk avoidance as described in any one of claims 1 to 8 is implemented.

10. A non-transitory computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the risk avoidance-based microgrid compensation control method according to any one of claims 1 to 8 is implemented.

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