Microgrid control method and electronic equipment

Abstract

The embodiment of the invention provides a micro-grid control method and electronic equipment. The method comprises the following steps: obtaining the active marginal cost of active power output by a distributed power supply in a micro-grid, the reactive marginal cost of reactive power output by the distributed power supply, a first cost coefficient and a second cost coefficient; according to the active marginal cost of the active power output by the distributed power supply in the micro-grid, the reactive marginal cost of the reactive power output by the distributed power supply and the first cost coefficient, obtaining an adjustment voltage; according to the active marginal cost of the active power output by the distributed power supply in the micro-grid, the reactive marginal cost of the reactive power output by the distributed power supply and the second cost coefficient, obtaining an adjustment frequency; generating a control signal according to the adjusting voltage and the adjusting frequency; and adjusting the output voltage and the output frequency of the distributed power supply according to the control signal. The method is used for improving the control and use effect of the micro-grid.

Description

Technical Field

[0001] This application relates to the field of microgrid technology, and in particular to a microgrid control method and electronic equipment. Background Art

[0002] With the transformation of energy structure and the rapid development of renewable energy technologies, microgrids, as an important form of integrating multiple distributed generation sources (DGs), play a crucial role in improving energy utilization efficiency, enhancing power supply reliability, and achieving energy localization. Common distributed generation sources in microgrids include photovoltaics, wind power, micro gas turbines, and energy storage systems, which differ significantly in terms of generation costs, response characteristics, and operating efficiency. Therefore, in microgrid operation and control, how to rationally allocate power output among different power sources while balancing system stability and economy has become a research hotspot in the field of smart power distribution systems. Related technologies mainly involve multiple interdisciplinary directions such as power electronic conversion, distributed control strategies, and energy management systems.

[0003] Currently, existing methods utilize traditional droop control strategies to allocate active power based on the rated capacity ratio of each distributed power source, simulating the primary frequency regulation characteristics of a synchronous generator and achieving autonomous power regulation without a central controller. This method is simple in structure, has a fast response speed, and is suitable for scenarios with multiple inverters operating in parallel. However, existing methods still suffer from poor control performance when facing the complex and diverse operational needs of microgrids. Summary of the Invention

[0004] This application provides a microgrid control method and electronic equipment to address the problem of poor control performance of microgrids.

[0005] In a first aspect, embodiments of this application provide a microgrid control method, the method comprising:

[0006] Obtain the active marginal cost of active power output by distributed power sources in a microgrid, the reactive marginal cost of reactive power, and the first cost coefficient and the second cost coefficient that characterize the impact of changes in active power on reactive power cost.

[0007] The adjustment voltage is obtained based on the active marginal cost of active power output by distributed power sources in the microgrid, the reactive marginal cost of reactive power, and the first cost coefficient characterizing the impact of changes in active power on reactive power cost.

[0008] The adjustment frequency is obtained based on the active marginal cost of active power output by distributed power sources in the microgrid, the reactive marginal cost of reactive power, and the second cost coefficient characterizing the impact of changes in active power on reactive power cost.

[0009] Control signals are generated based on the adjusted voltage and frequency;

[0010] Adjust the output voltage and frequency of the distributed power supply according to the control signal.

[0011] Optionally, the adjustment voltage is obtained based on the active marginal cost of active power output by distributed power sources in the microgrid, the reactive marginal cost of reactive power, and a first cost coefficient characterizing the impact of changes in active power on reactive power cost, including:

[0012] The first coupling cost is obtained based on the first cost coefficient and the reactive marginal cost;

[0013] Based on the first coupling cost and the active marginal cost, the first marginal cost of distributed power generation is obtained.

[0014] The voltage regulation coefficient is obtained based on the first marginal cost, the first sensitivity coefficient of active power marginal cost, and the active power droop economic coefficient.

[0015] The adjusted voltage is obtained based on the allowable output voltage and voltage adjustment coefficient of the distributed power source.

[0016] Optionally, the voltage adjustment satisfies:

[0017]

[0018] Among them, U max U is the maximum permissible output voltage among the permissible output voltages. min The minimum permissible output voltage among the permissible output voltages;

[0019] λ L，P The effective downward economic coefficient;

[0020] is the first sensitivity coefficient of distributed source i;

[0021] k PQ The effective downward economic coefficient;

[0022] L i (P i P is the active power output by distributed power source i. i The marginal cost of active power, L i (Q i Q is the reactive power output by distributed power source i. i The marginal cost of reactive power.

[0023] Optionally, the method further includes:

[0024] The first sensitivity coefficient for active marginal cost is determined based on the rate of change of active marginal cost, the maximum active power output, and the maximum active marginal cost of distributed power sources.

[0025] Optionally, the method further includes:

[0026] The active power droop economic coefficient is determined based on the maximum allowable voltage deviation of the distributed power source, the first marginal cost, and the first sensitivity coefficient of the active power marginal cost.

[0027] Optionally, the adjustment frequency is obtained based on the active marginal cost of active power output by distributed power sources in the microgrid, the reactive marginal cost of reactive power, and a second cost coefficient characterizing the impact of changes in active power on reactive power cost, including:

[0028] The second coupling cost is obtained based on the second cost coefficient and the active marginal cost;

[0029] Based on the second coupling cost and the reactive marginal cost, the second marginal cost of distributed power generation is obtained;

[0030] The frequency adjustment coefficient is obtained based on the second marginal cost, the second sensitivity coefficient of reactive power marginal cost, and the reactive power droop economic coefficient.

[0031] The adjustment frequency is obtained based on the rated frequency and frequency adjustment coefficient of the distributed power source.

[0032] Optionally, the control frequency satisfies:

[0033]

[0034] Among them, f n The rated frequency of distributed power source i;

[0035] λ L，Q The reactive power drooping economic coefficient;

[0036] The second sensitivity coefficient of distributed source i;

[0037] k QP The effective downward economic coefficient;

[0038] L i (P i P is the active power output by distributed power source i. i The marginal cost of active power, L i (Q i Q is the reactive power output by distributed power source i. i The marginal cost of reactive power.

[0039] Optionally, the method further includes:

[0040] The second sensitivity coefficient for active marginal cost is determined based on the rate of change of reactive marginal cost, the maximum reactive power output, and the maximum reactive marginal cost of distributed power sources.

[0041] Optionally, the method further includes:

[0042] The reactive power droop economic coefficient is determined based on the maximum permissible frequency deviation of the distributed power source, the second marginal cost, and the second sensitivity coefficient of the reactive power marginal cost.

[0043] Optionally, a control signal is generated based on the adjusted voltage and adjusted frequency, including:

[0044] The voltage and frequency are adjusted and input to the voltage-current dual-loop controller to obtain the modulation ratio signal;

[0045] The modulation ratio signal is input to the PWM modulator to obtain the control signal.

[0046] Secondly, embodiments of this application provide a microgrid control device, comprising:

[0047] The acquisition module is used to acquire the active marginal cost of active power output by distributed power sources in the microgrid, the reactive marginal cost of reactive power, and the first cost coefficient and the second cost coefficient that characterize the impact of changes in active power on reactive power cost.

[0048] The first obtaining module is used to obtain the adjustment voltage based on the active marginal cost of active power output by distributed power sources in the microgrid, the reactive marginal cost of reactive power, and a first cost coefficient characterizing the degree of influence of changes in active power on reactive power cost.

[0049] The second module is used to obtain the adjustment frequency based on the active marginal cost of active power output by distributed power sources in the microgrid, the reactive marginal cost of reactive power, and a second cost coefficient that characterizes the degree of influence of changes in active power on reactive power cost.

[0050] The generation module is used to generate control signals based on the adjusted voltage and frequency;

[0051] The adjustment module is used to adjust the output voltage and output frequency of the distributed power supply according to the control signal.

[0052] Thirdly, embodiments of this application provide a microgrid control device, including: a memory and a processor;

[0053] The memory stores the instructions that the computer executes;

[0054] The processor executes computer execution instructions stored in memory, causing the processor to perform the first aspect and / or various possible implementations of the first aspect as described above.

[0055] Fourthly, embodiments of this application provide a computer-readable storage medium storing computer-executable instructions, which, when executed by a processor, are used to implement the first aspect and / or various possible implementations of the first aspect.

[0056] Fifthly, embodiments of this application provide a computer program product, including a computer program that, when executed by a processor, implements the first aspect and / or various possible implementations of the first aspect.

[0057] The microgrid control method and electronic equipment provided in this application obtain the active marginal cost of active power output by distributed power sources in the microgrid, the reactive marginal cost of reactive power, a first cost coefficient characterizing the impact of changes in active power on reactive power cost, and a second cost coefficient characterizing the impact of changes in reactive power on active power cost. Based on the active marginal cost of active power output by distributed power sources in the microgrid, the reactive marginal cost of reactive power, and the first cost coefficient characterizing the impact of changes in active power on reactive power cost, an adjustment voltage is obtained. Based on the active marginal cost of active power output by distributed power sources in the microgrid, the reactive marginal cost of reactive power, and the first cost coefficient characterizing the impact of changes in active power on reactive power cost, an adjustment voltage is obtained. A second cost coefficient, reflecting the impact of reactive power costs, is used to determine the adjustment frequency. Based on the adjusted voltage and frequency, a control signal is generated. The output voltage and frequency of the distributed generation are adjusted according to the control signal. This method comprehensively considers the active marginal cost and reactive marginal cost of the active power output by the distributed generation in the microgrid, introducing a first cost coefficient to reflect the impact of active power changes on reactive power costs, and a second cost coefficient to reflect the impact of reactive power changes on active power costs, thus constructing a more accurate economic evaluation model. Based on this, the adjustment amounts for voltage and frequency are calculated based on the above parameters, generating corresponding control signals, and then dynamically adjusting the output voltage and frequency of the distributed generation. This improves upon the limitations of traditional droop control, which only allocates power according to rated capacity, achieving a tilt towards low-cost, high-efficiency power sources while ensuring stable system operation. This effectively reduces the overall system operating cost and enhances the economy and control flexibility of the microgrid. Attached Figure Description

[0058] The accompanying drawings, which are incorporated in and form part of this specification, illustrate embodiments consistent with this application and, together with the description, serve to explain the principles of this application.

[0059] Figure 1 A schematic diagram of a microgrid scenario provided for this application;

[0060] Figure 2 Flowchart of the microgrid control method provided in this application Figure 1 ;

[0061] Figure 3 Flowchart of the microgrid control method provided in this application Figure 2 ;

[0062] Figure 4 A schematic diagram of the control device for the microgrid provided in this application;

[0063] Figure 5 A schematic diagram of the structure of the control equipment for the microgrid provided in this application.

[0064] The above drawings illustrate specific embodiments of the present application, which will be described in more detail below. These drawings and the textual description are not intended to limit the scope of the present application in any way, but rather to illustrate the concepts of the present application to those skilled in the art by reference to specific embodiments. Detailed Implementation

[0065] Exemplary embodiments will now be described in detail, examples of which are illustrated in the accompanying drawings. When the following description relates to the drawings, unless otherwise indicated, the same numbers in different drawings denote the same or similar elements. The embodiments described in the following exemplary embodiments do not represent all embodiments consistent with this application. Rather, they are merely examples of apparatuses and methods consistent with some aspects of this application as detailed in the appended claims.

[0066] First, let me explain the terms used in this application:

[0067] A microgrid can refer to a small power generation and consumption system composed of distributed power sources (such as photovoltaic, wind power, energy storage systems, etc.), loads, energy management systems and control devices, which can operate in grid-connected or islanded modes.

[0068] Distributed power sources can refer to small and medium-sized power generation systems that are directly installed at or near load centers. They can operate independently or be connected to the grid to provide electricity to users.

[0069] Existing microgrids contain a wide variety of distributed power sources, including solar photovoltaic, wind power, micro gas turbines, and fuel cells, each with varying operating costs and efficiencies. Traditional droop control strategies typically allocate power based on the rated capacity of each power source, without fully considering the actual differences in generation costs among them. This can easily lead to higher overall system operating costs.

[0070] The microgrid control method provided in this application introduces the marginal costs of active and reactive power and their cross-cost coefficients, thereby constructing a more refined control strategy. This effectively solves the problem of low operating efficiency caused by traditional droop control neglecting the differences in generation costs and the coupling cost of active and reactive power output, thus improving the control and utilization effect of the microgrid.

[0071] Figure 1 The schematic diagram of the microgrid scenario provided in this application is as follows: Figure 1 As shown, the specific application scenario of this application is a microgrid control system, which includes: a power measurement element, a voltage adjustment acquisition element, a frequency adjustment acquisition element, a voltage and current dual-loop controller, a PWM modulator, a distributed power supply, and a filter.

[0072] The distributed power source's AC bus is connected to the outside via a filter. Power measurement elements are connected to the AC bus to obtain the active and reactive power of the distributed power source. The voltage adjustment element calculates the adjustment voltage based on the active and reactive power, and the frequency adjustment element calculates the adjustment frequency based on the active and reactive power. The voltage and current dual-loop controller obtains the modulation ratio signal through the adjustment voltage and frequency, and sends the modulation ratio signal to the PWM modulator to obtain the control signal. The PWM modulator then sends the control signal to the distributed power source for control.

[0073] The following specific embodiments describe in detail the technical solution of the present application and how the technical solution of the present application solves the above-mentioned technical problems. The following specific embodiments can be combined with each other, and the same or similar concepts or processes may not be repeated in some embodiments. The embodiments of the present application will be described below in conjunction with the accompanying drawings.

[0074] Figure 2 Flowchart of the microgrid control method provided in this application Figure 1 ,like Figure 2 As shown, the method includes:

[0075] S201. Obtain the active marginal cost of active power output by distributed power sources in the microgrid, the reactive marginal cost of reactive power, and the first cost coefficient characterizing the impact of changes in active power on reactive power cost and the second cost coefficient characterizing the impact of changes in reactive power on active power cost.

[0076] The active power output by the distributed generation source refers to the actual electrical energy supplied by the distributed generation source to the microgrid for performing work. This electrical energy can be used to measure its generation capacity and its ability to meet load demand. In this embodiment, the active power output by the distributed generation source can be collected in real time by sensors or smart meters, combined with monitoring data on the operating status of the distributed generation source in the microgrid management system. Furthermore, a predictive model can be established based on the generation type of the distributed generation source (such as photovoltaic, wind power, etc.) and current environmental conditions (such as sunlight intensity and wind speed) to estimate its active power within a specific time period.

[0077] The marginal cost of active power can refer to the generation cost resulting from a unit increase in active power output. In the embodiments of this application, the marginal cost of active power can be calculated based on the generation characteristics of distributed power sources and their operating cost functions. For example, the cost change per unit increase in power generation for diesel generators can be derived from the fuel consumption curve; for renewable energy sources, it can be determined based on their maintenance costs or opportunity costs. In some embodiments, for different types of power sources, piecewise linear or nonlinear cost models can be established, and parameters can be fitted using historical operating data to ultimately obtain a mathematical expression reflecting their marginal generation cost.

[0078] The reactive power output of a distributed generation source can refer to the auxiliary power support provided by the distributed generation source to maintain the voltage stability of the microgrid. This auxiliary power support does not directly participate in energy work. In the embodiments of this application, the reactive power output of the distributed generation source can be determined by the inverter, that is, it can be obtained in real time by measuring the voltage and current signals at the inverter output terminal and calculating them through dq transformation or FFT analysis.

[0079] In this embodiment of the application, the active power generation cost function of distributed power source i satisfies:

[0080] C i (P i )=α i,P P i 2 +β i,P P i +γ i,P ;

[0081] The marginal cost of active power is then:

[0082]

[0083] Where, α i，P Let β be the rate of increase in the losses of distributed source i when the active power of distributed source i increases. i，P γ represents the basic cost loss per unit active power of distributed power source i. i，PThis refers to the standby power loss in distributed power source i that is independent of active power.

[0084] The reactive marginal cost of reactive power refers to the additional cost incurred by a unit increase in reactive power output. This cost may involve equipment losses, capacity limitations, and the opportunity cost of reduced active power capacity due to providing reactive power support. This cost reflects the resource cost of distributed generation when providing voltage support. In the embodiments of this application, the reactive marginal cost of reactive power can be determined based on the opportunity cost of distributed generation providing reactive power support, equipment losses, and the capacity loss that may affect active power output. For example, inverters used to provide reactive power support will occupy a portion of apparent power capacity, thereby limiting the capacity available for active power output. This cost can be estimated by establishing a cost optimization model under apparent power constraints, or by setting an empirical coefficient based on performance parameters provided by equipment manufacturers.

[0085] In this embodiment of the application, the reactive power generation cost function of distributed power source i satisfies:

[0086] C i (Q i )=α i,Q Q i +β i,Q ;

[0087] The marginal cost of reactive power is:

[0088]

[0089] Where, α i，Q β represents the basic cost loss per unit reactive power of distributed power source i; i，Q This refers to the standby loss in distributed power source i that is independent of reactive power.

[0090] The first cost coefficient, characterizing the impact of changes in active power on reactive power costs, can refer to a parameter used to reflect how fluctuations in active power cause reactive power regulation demand and corresponding cost changes. In the embodiments of this application, the first cost coefficient can be determined according to the power type of the distributed power source; for example, it can be 0.1-0.3 for micro gas turbines and 0.05-0.2 for fuel cells.

[0091] The second cost coefficient, characterizing the impact of reactive power changes on active power costs, can refer to a parameter used to reflect the impact of reactive power adjustments on active power output capacity and corresponding generation costs. In the embodiments of this application, the second cost coefficient can be determined according to the power type of the distributed power source. The second cost coefficient corresponds to the first cost coefficient; for example, it can be 0.08-0.25 for micro gas turbines and 0.03-0.15 for fuel cells.

[0092] S202. Based on the active marginal cost of active power output by distributed power sources in the microgrid, the reactive marginal cost of reactive power, and the first cost coefficient characterizing the degree of influence of changes in active power on reactive power cost, the adjustment voltage is obtained.

[0093] In this context, voltage adjustment refers to the process of calculating an optimal voltage regulation value that considers both economic efficiency and system constraints during the operation of a microgrid, based on the active marginal cost of the active power output of each distributed power source, the reactive marginal cost of the reactive power output, and the first cost coefficient reflecting the coupling relationship between active and reactive power. This voltage value not only reflects the differences in operating costs of each power source under the current system, but also reflects the impact of changes in active power output on reactive power regulation requirements. It can be used to guide the inverters or controllers of distributed power sources to dynamically adjust the output voltage, thereby achieving voltage stability, improving power quality, and reducing the overall operating cost of the system while meeting operational constraints, thus achieving the goal of coordinated optimization of economic efficiency and safety.

[0094] In this embodiment of the application, the adjustment voltage is obtained based on the active marginal cost of active power output by distributed power sources in the microgrid, the reactive marginal cost of reactive power, and a first cost coefficient characterizing the impact of changes in active power on reactive power cost, including:

[0095] The first coupling cost is obtained based on the first cost coefficient and the reactive marginal cost;

[0096] Based on the first coupling cost and the active marginal cost, the first marginal cost of distributed power generation is obtained.

[0097] The voltage regulation coefficient is obtained based on the first marginal cost, the first sensitivity coefficient of active power marginal cost, and the active power droop economic coefficient.

[0098] The adjusted voltage is obtained based on the allowable output voltage and voltage adjustment coefficient of the distributed power source.

[0099] Among them, the first coupling cost, calculated by the first cost coefficient and the reactive marginal cost, can reflect the additional economic impact of active power changes on reactive power regulation, thus reflecting the coupling relationship between active and reactive power.

[0100] Then, by combining the first coupling cost with the active marginal cost, the first marginal cost of the distributed power source is obtained, which is the actual adjustment cost after comprehensively considering active and reactive power and their mutual influence.

[0101] Finally, using the first marginal cost, the first sensitivity coefficient corresponding to the active power marginal cost, and the preset active power droop economic coefficient, a voltage adjustment coefficient for voltage regulation is calculated. Given the current operating conditions, how should the voltage be adjusted to achieve economic optimization?

[0102] In this embodiment of the application, the voltage adjustment satisfies:

[0103]

[0104] Among them, U max U is the maximum permissible output voltage among the permissible output voltages. min The minimum permissible output voltage among the permissible output voltages;

[0105] λ L，P The effective downward economic coefficient;

[0106] is the first sensitivity coefficient of distributed source i;

[0107] k PQ The effective downward economic coefficient;

[0108] L i (P i P is the active power output by distributed power source i. i The marginal cost of active power, L i (Q i Q is the reactive power output by distributed power source i. i The marginal cost of reactive power.

[0109] Among them, (U) max +U min ) / 2 is the average value of the allowable output voltage, which can be used as a reference voltage level. It can reflect the degree of influence of distributed power sources on system voltage when providing active and reactive power, so as to dynamically adjust the reference voltage level, thereby compensating for voltage deviations caused by load changes, power output fluctuations and other factors, and ensuring that the actual voltage always operates stably around the reference value.

[0110] In this embodiment of the application, the method further includes:

[0111] The first sensitivity coefficient for active marginal cost is determined based on the rate of change of active marginal cost, the maximum active power output, and the maximum active marginal cost of distributed power sources.

[0112] The first sensitivity coefficient satisfies:

[0113]

[0114] in, P is the rate of change of the marginal cost of active power. i，max L represents the maximum active power output. i,pmax Let be the maximum active marginal cost of distributed power source i.

[0115] In this embodiment of the application, the method further includes:

[0116] The active power droop economic coefficient is determined based on the maximum allowable voltage deviation of the distributed power source, the first marginal cost, and the first sensitivity coefficient of the active power marginal cost.

[0117] Among them, the active power downward economic coefficient satisfies:

[0118]

[0119] Wherein, ΔU max This represents the maximum permissible voltage deviation of distributed power source i. In this embodiment, this value can be set to 5% of the rated voltage of the bus in distributed power source i. The maximum first sensitivity coefficient is represented. In the embodiments of this application, when there are multiple distributed power sources, if one of them λ L，P If the value increases, then the λ of other distributed power sources... L，P Reduce to ensure λ for all distributed power sources L，P The total value remains constant.

[0120] S203. The adjustment frequency is obtained based on the active marginal cost of active power output by distributed power sources in the microgrid, the reactive marginal cost of reactive power, and the second cost coefficient characterizing the degree of influence of changes in active power on reactive power cost.

[0121] Frequency adjustment can refer to dynamically adjusting the system frequency based on the marginal cost of active power output, the marginal cost of reactive power output, and the second cost coefficient (characterizing the impact of active power changes on reactive power cost) of distributed power sources in the microgrid. Specifically, it involves calculating a cost item reflecting the interaction between the two using the second cost coefficient and the reactive power marginal cost, then combining this with the active power marginal cost to determine a comprehensive cost index, and finally deriving the frequency adjustment amount based on the relationship between this cost index and the system frequency deviation.

[0122] In this embodiment of the application, the adjustment frequency is obtained based on the active marginal cost of active power output by distributed power sources in the microgrid, the reactive marginal cost of reactive power, and a second cost coefficient characterizing the impact of changes in active power on reactive power cost, including:

[0123] The second coupling cost is obtained based on the second cost coefficient and the active marginal cost;

[0124] Based on the second coupling cost and the reactive marginal cost, the second marginal cost of distributed power generation is obtained;

[0125] The frequency adjustment coefficient is obtained based on the second marginal cost, the second sensitivity coefficient of reactive power marginal cost, and the reactive power droop economic coefficient.

[0126] The adjustment frequency is obtained based on the rated frequency and frequency adjustment coefficient of the distributed power source.

[0127] First, the second coupling cost, calculated by multiplying the second cost coefficient by the active power marginal cost, is used to quantify the reverse impact of reactive power changes on active power regulation costs, thus reflecting the economic coupling relationship between active and reactive power. Next, this coupling cost is combined with the reactive power marginal cost to obtain the second marginal cost of the distributed power source, which characterizes the actual regulation cost after comprehensively reflecting the impact of reactive power regulation on active power operation costs.

[0128] Subsequently, based on the second marginal cost, the second sensitivity coefficient corresponding to the reactive marginal cost, and the reactive droop economic coefficient, the frequency adjustment coefficient is calculated, so that the frequency control not only responds to load changes, but also reflects the economic characteristics of each power source in the reactive dimension, forming a control signal that takes into account both stability and economy.

[0129] Finally, by combining the rated frequency of the distributed power source with its adjustment coefficient, an adjustment frequency is dynamically generated to achieve adaptive optimization of frequency regulation. Thus, by introducing economic indicators to drive frequency control, the microgrid's frequency stability is ensured while simultaneously approaching a low-cost operating state, thereby improving overall operating efficiency and energy utilization.

[0130] In this embodiment of the application, the control frequency satisfies:

[0131]

[0132] Among them, f n The rated frequency of distributed power source i;

[0133] λ L，Q The reactive power drooping economic coefficient;

[0134] The second sensitivity coefficient of distributed source i;

[0135] k QP The effective downward economic coefficient;

[0136] L i (P i P is the active power output by distributed power source i. i The marginal cost of active power, L i (Q i Q is the reactive power output by distributed power source i. i The marginal cost of reactive power.

[0137] in, Feedback gain can be used to stabilize the system, suppress noise, and improve dynamic response. Therefore, to achieve closed-loop negative feedback control, the control input is continuously adjusted by comparing the deviation between the reference input and the actual output, making the system output closer to the desired value, thereby enhancing the anti-interference capability and stability during use.

[0138] In this embodiment of the application, the method further includes:

[0139] The second sensitivity coefficient for active marginal cost is determined based on the rate of change of reactive marginal cost, the maximum reactive power output, and the maximum reactive marginal cost of distributed power sources.

[0140] The second sensitivity coefficient satisfies:

[0141]

[0142] in, Q is the rate of change of the marginal cost of reactive power. i，max L is the maximum active power output of reactive power. i,Qmax Let be the maximum reactive marginal cost of distributed power source i.

[0143] In this embodiment of the application, the method further includes:

[0144] The reactive power droop economic coefficient is determined based on the maximum permissible frequency deviation of the distributed power source, the second marginal cost, and the second sensitivity coefficient of the reactive power marginal cost.

[0145] Among them, the reactive power droop economic coefficient satisfies:

[0146]

[0147] Where, Δf max This represents the maximum permissible frequency deviation of the distributed power source i. In this embodiment, this value can be 0.05Hz. Characterized by the maximum second sensitivity coefficient. In this embodiment, when there are multiple distributed power sources, if one of them λ L，Q If the value increases, then the λ of other distributed power sources... L，Q Reduce to ensure λ for all distributed power sources L，Q The total value remains constant.

[0148] S204. Generate control signals based on the adjusted voltage and frequency.

[0149] The process of generating control signals based on voltage and frequency adjustments can be achieved through internal voltage and frequency loop adjustment algorithms. For example, the current voltage deviation (the difference between the target voltage and the actual voltage) and frequency deviation (the difference between the target frequency and the actual frequency) can be used as inputs. Combined with preset control strategies (such as PI control, droop control, or economic optimization algorithms), the corresponding control quantities are calculated to adjust the inverter's modulation ratio or power output. This dynamically corrects the output voltage and frequency of the distributed power source, bringing them closer to the set target values ​​and ensuring the stable and efficient operation of the microgrid.

[0150] In this embodiment of the application, the control signal is generated based on the adjustment voltage and the adjustment frequency, including:

[0151] The voltage and frequency are adjusted and input to the voltage-current dual-loop controller to obtain the modulation ratio signal;

[0152] The modulation ratio signal is input to the PWM modulator to obtain the control signal.

[0153] The voltage-current dual-loop controller can consist of an outer voltage loop and an inner current loop. The voltage loop adjusts the current reference value based on the deviation between the voltage reference value and the actual output voltage, while the current loop responds quickly to and controls changes in the output current based on this reference value, thereby achieving precise regulation of the output voltage and frequency. Upon receiving the adjusted voltage and frequency, the modulation ratio signal is obtained.

[0154] A PWM modulator is used to receive a modulation ratio signal and generate a corresponding control signal based on the input modulation ratio signal. In some embodiments, the PWM modulator can compare the received modulation ratio signal with a high-frequency triangular wave to generate a pulse sequence (control signal) with a duty cycle that varies with the modulation wave, thereby controlling the on-time ratio of the power device and achieving precise control of the output voltage amplitude and waveform of the inverter in the distributed power supply.

[0155] In this embodiment, each distributed power source corresponds to a voltage and current dual-loop controller. The PWM modulator can receive modulation ratio signals output by multiple voltage and current dual-loop controllers and generate control signals to adjust the output voltage and output frequency of different distributed power sources based on multiple modulation ratio signals. This ensures the output cost of the distributed power source and improves its output efficiency.

[0156] S205. Adjust the output voltage and output frequency of the distributed power supply according to the control signal.

[0157] The microgrid control method provided in this application comprehensively considers the active marginal cost and reactive marginal cost of the active power output from distributed power sources in the microgrid. It introduces a first cost coefficient to reflect the impact of active power changes on reactive power costs, and a second cost coefficient to reflect the impact of reactive power changes on active power costs, thereby constructing a more accurate economic evaluation model. Based on this, adjustment amounts for voltage and frequency regulation are calculated based on the aforementioned parameters, generating corresponding control signals to dynamically adjust the output voltage and frequency of the distributed power sources. This overcomes the limitations of traditional droop control, which only allocates power according to rated capacity. It achieves tilted scheduling towards low-cost, high-efficiency power sources while ensuring stable system operation, effectively reducing the overall system operating cost and improving the economic efficiency and control flexibility of the microgrid.

[0158] In this embodiment of the application, in a multi-distributed-source microgrid:

[0159] For each distributed power source in the microgrid, independently calculate the active marginal cost of its current output active power, the reactive marginal cost of its reactive power, and the first cost coefficient (reflecting the impact of active power changes on reactive cost) and the second cost coefficient (reflecting the impact of reactive cost changes on active power) characterizing the interaction between active and reactive power outputs.

[0160] The reference value for adjusting the voltage for each distributed power source is calculated using the active marginal cost, reactive marginal cost, and first cost coefficient.

[0161] A reference value for adjusting the frequency is calculated for each distributed power source using the active marginal cost, reactive marginal cost, and a second cost coefficient.

[0162] Since multiple distributed power sources are involved, distributed consensus algorithms or other suitable information exchange mechanisms (such as average consensus protocols based on communication networks) can be used to enable each power source to share its respective regulation voltage and frequency reference values ​​and update them iteratively until consensus is reached.

[0163] Ultimately, based on unified adjustment voltage and frequency values, corresponding control signals are generated for each distributed power source. These signals are then used to regulate the output voltage and frequency of their respective inverters to achieve stable operation and economic optimization within the microgrid.

[0164] Figure 3 Flowchart of the microgrid control method provided in this application Figure 2 ,like Figure 3 As shown, the method includes:

[0165] S301, Real-time calculation of active marginal cost L i (Pi ) and reactive marginal cost L i (Q i );

[0166] S302. Dynamically adjust the cross-cost coefficient k according to the type of distributed power source. PQ and k QP .

[0167] For example, the k of a micro gas turbine PQ =0.2, k QP =0.15, k of fuel cell PQ =0.08, k QP =0.05.

[0168] S303. Calculate the sensitivity coefficient based on the marginal cost change rate. and

[0169] S304, according to ΔU max and Δf max Dynamic calculation of λ L，P and λ L，Q And ensure that the constraints are met.

[0170]

[0171] S305, Obtain the adjustment voltage.

[0172] For example, the process may include:

[0173] 1) Initialization parameters: Set the upper and lower voltage limits of the distributed power source: Umax = 400V, Umin = 380V, and the maximum allowable voltage deviation ΔU = 5% * 400V = 20V.

[0174] The active power cost parameter α of the preset micro gas turbine i，P =0.02, β i，P =10, the reactive power cost parameter α of the fuel cell i，Q =0.05.

[0175] 2) Real-time calculation: Obtain the current P i =50kW, Q i =10KVar. Calculate the marginal cost of active power L. i (P i ) = 2 × 0.02 × 50 + 10 = 12 / kWh, reactive power marginal cost L i (Q i = 0.05 yuan / kVar. Calculate the comprehensive marginal cost item (L). i (P i )+k PQ *Li (Q i =12 + 0.2 × 0.05 = 12.01.

[0176] 3) Adjust the output voltage: Calculate the first sensitivity coefficient. (Assume P) i，max =100kW, L i,pmax =12 yuan / kWh). Dynamically adjust the downward economic coefficient λ. L，P =20 / (12.01×0.33)≈5.03.

[0177] Therefore, the voltage should be adjusted to (400+380) / 2-5.03×12.01×0.33≈385V.

[0178] S306, Obtain the adjustment frequency.

[0179] For example, the process may include:

[0180] 1) Initialization parameters: Set the rated frequency f n =50Hz, maximum permissible frequency deviation Δf max =0.5Hz. Preset reactive power cost α of the micro gas turbine. i，Q =0.03, the active power cost parameter α of the fuel cell i，P =0.01.

[0181] 2) Real-time calculation: Obtain the current Q i =15kVar, P i =60kW. Calculate the reactive power marginal cost L. i (Q i ) = 0.03 yuan / kVar, active marginal cost L i (P i )=2×0.01×60+8=9.2 yuan / kWh (assuming β i，P =8). Calculate the comprehensive marginal cost item (L). i (Q i )+k QP *L i (P i =0.03 + 0.15 × 9.2 = 1.41.

[0182] 3) Adjust the output frequency: Calculate the sensitivity coefficient (Assume Q i，max =30kVar, L i,Qmax =0.03 yuan / kVar). Dynamically adjust the downward economic coefficient λ. L，Q =0.5 / (1.41×2)≈0.177.

[0183] Therefore, according to the adjusted frequency fi =50-0.177×1.41×2≈49.5Hz.

[0184] S307. Based on the adjustment voltage and adjustment frequency, generate control signals and adjust the output voltage and output frequency of the distributed power supply.

[0185] In the embodiments of this application:

[0186] 1) Sensitivity coefficient update: The marginal cost change rate is updated every 50ms. and Recalculate and For example, when the active power of a micro gas turbine increases to 80kW,

[0187] 2) Adaptive adjustment of cross-cost coefficient: When a type switch of distributed power source is detected (e.g., from a micro gas turbine to a fuel cell), a command is sent to the cross-cost coefficient tuning module via the communication bus to adjust k. PQ Adjusted from 0.2 to 0.08, k QP The value was adjusted from 0.15 to 0.05.

[0188] 3) Multi-distributed power source collaborative control: Each distributed power source synchronizes and integrates marginal cost information through a consensus algorithm to ensure that the λ of all units is consistent. L，P and λ L，Q Consistent. For example, when a distributed power source experiences a change in load, λ... L，P When the droop coefficient is increased, other units adjust their droop coefficients synchronously to achieve economical power distribution.

[0189] The experimental verification and effects of the embodiments in this application are as follows:

[0190] 1) Test platform configuration: A low-voltage microgrid experimental platform was built, consisting of two micro gas turbines (50kW / 20kVar) and one fuel cell (30kW / 10kVar), with a line impedance of 0.1Ω (resistive dominance).

[0191] 2) Experimental results:

[0192] Traditional droop control: Active power is distributed according to rated capacity (25kW output from each micro gas turbine and 30kW output from each fuel cell), and the total operating cost of the system is 120 yuan / h.

[0193] The microgrid control method of this application embodiment: the micro gas turbine allocates active power according to marginal cost (outputting 28kW and 22kW respectively), the fuel cell outputs 30kW, and the total system operating cost is reduced to 112 yuan / h, a reduction of 6.7%.

[0194] Dynamic response: When the load suddenly increases by 20%, the voltage fluctuation amplitude decreases from ±15V to ±8V, and the frequency recovery time is shortened from 2s to 1.2s.

[0195] Therefore, the microgrid control method provided in this application embodiment is as follows:

[0196] Considering that active and reactive power outputs share costs at the equipment level (such as the mutual influence between inverter losses), by introducing a cross-marginal cost coupling term, the calculation of marginal costs can be made closer to the actual operating characteristics of the equipment, thereby reducing the total system operating cost by 5%-10%.

[0197] By introducing a sensitivity coefficient Quantify the rate of change of marginal cost of power sources (such as nonlinear power sources). Larger size corresponds to higher sensitivity; linear power supply Small size (corresponding to low sensitivity) transforms the physical characteristics of the power source (such as the nonlinear losses of a micro gas turbine and the linear efficiency of a fuel cell) into adjustable mathematical parameters. Its function is as follows: for power sources sensitive to marginal cost, high sensitivity allows for rapid response to power changes; for power sources with stable marginal cost, low sensitivity allows for smooth output; for power sources with reactive power regulation advantages (such as SVC), dedicated sensitivity enables them to keenly capture frequency (phase difference) changes, overcoming the "one-size-fits-all" bias of traditional unified control and achieving precise matching of "cost characteristics and control strategies" for various types of power sources.

[0198] By ensuring that the overall marginal cost of each distributed unit is consistent, and by combining voltage and frequency coordinated control strategies, the system's economy and stability are taken into account, enabling "plug-and-play" access and high-reliability operation of distributed power sources in the microgrid.

[0199] To address the resistance-dominated characteristics of low-voltage microgrids, the accuracy of power allocation is improved by introducing cross-marginal cost terms and sensitivity coefficients. This approach is particularly suitable for low-voltage distribution network scenarios with a high proportion of renewable energy access, enhancing the applicability and robustness of the control strategy.

[0200] Figure 4 A schematic diagram of the control device for the microgrid provided in this application is shown below. Figure 4 As shown, the microgrid control device 40 provided in this embodiment includes:

[0201] The acquisition module 401 is used to acquire the active marginal cost of active power output by distributed power sources in the microgrid, the reactive marginal cost of reactive power, and the first cost coefficient and the second cost coefficient that characterize the degree of influence of changes in active power on reactive power cost.

[0202] The first obtaining module 402 is used to obtain the adjustment voltage based on the active marginal cost of active power output by distributed power sources in the microgrid, the reactive marginal cost of reactive power, and a first cost coefficient characterizing the degree of influence of changes in active power on reactive power cost.

[0203] The second module 403 is used to obtain the adjustment frequency based on the active marginal cost of active power output by distributed power sources in the microgrid, the reactive marginal cost of reactive power, and a second cost coefficient characterizing the degree of influence of changes in active power on reactive power cost.

[0204] The generation module 404 is used to generate control signals based on the adjustment voltage and adjustment frequency;

[0205] The adjustment module 405 is used to adjust the output voltage and output frequency of the distributed power supply according to the control signal.

[0206] In one possible implementation, the first obtaining module 402 can also be used for:

[0207] The first coupling cost is obtained based on the first cost coefficient and the reactive marginal cost;

[0208] Based on the first coupling cost and the active marginal cost, the first marginal cost of distributed power generation is obtained.

[0209] The voltage regulation coefficient is obtained based on the first marginal cost, the first sensitivity coefficient of active power marginal cost, and the active power droop economic coefficient.

[0210] The adjusted voltage is obtained based on the allowable output voltage and voltage adjustment coefficient of the distributed power source.

[0211] In one possible implementation, the voltage adjustment in the first obtaining module 402 satisfies:

[0212]

[0213] Among them, U max U is the maximum permissible output voltage among the permissible output voltages. min The minimum permissible output voltage among the permissible output voltages;

[0214] λ L，P The effective downward economic coefficient;

[0215] is the first sensitivity coefficient of distributed source i;

[0216] k PQ The effective downward economic coefficient;

[0217] L i (P iP is the active power output by distributed power source i. i The marginal cost of active power, L i (Q i Q is the reactive power output by distributed power source i. i The marginal cost of reactive power.

[0218] In one possible implementation, the first obtaining module 402 can also be used for:

[0219] The first sensitivity coefficient for active marginal cost is determined based on the rate of change of active marginal cost, the maximum active power output, and the maximum active marginal cost of distributed power sources.

[0220] In one possible implementation, the first obtaining module 402 can also be used for:

[0221] The active power droop economic coefficient is determined based on the maximum allowable voltage deviation of the distributed power source, the first marginal cost, and the first sensitivity coefficient of the active power marginal cost.

[0222] In one possible implementation, the second obtaining module 403 can also be used for:

[0223] The second coupling cost is obtained based on the second cost coefficient and the active marginal cost;

[0224] Based on the second coupling cost and the reactive marginal cost, the second marginal cost of distributed power generation is obtained;

[0225] The frequency adjustment coefficient is obtained based on the second marginal cost, the second sensitivity coefficient of reactive power marginal cost, and the reactive power droop economic coefficient.

[0226] The adjustment frequency is obtained based on the rated frequency and frequency adjustment coefficient of the distributed power source.

[0227] In one possible implementation, the control frequency in the second module 403 satisfies:

[0228]

[0229] Among them, f n The rated frequency of distributed power source i;

[0230] λ L，Q The reactive power drooping economic coefficient;

[0231] The second sensitivity coefficient of distributed source i;

[0232] k QP The effective downward economic coefficient;

[0233] L i (Pi P is the active power output by distributed power source i. i The marginal cost of active power, L i (Q i Q is the reactive power output by distributed power source i. i The marginal cost of reactive power.

[0234] In one possible implementation, the second obtaining module 403 can also be used for:

[0235] The second sensitivity coefficient for active marginal cost is determined based on the rate of change of reactive marginal cost, the maximum reactive power output, and the maximum reactive marginal cost of distributed power sources.

[0236] In one possible implementation, the second obtaining module 403 can also be used for:

[0237] The reactive power droop economic coefficient is determined based on the maximum permissible frequency deviation of the distributed power source, the second marginal cost, and the second sensitivity coefficient of the reactive power marginal cost.

[0238] In one possible implementation, the generation module 404 can also be used for:

[0239] The voltage and frequency are adjusted and input to the voltage-current dual-loop controller to obtain the modulation ratio signal;

[0240] The modulation ratio signal is input to the PWM modulator to obtain the control signal.

[0241] The microgrid control device provided in this embodiment can execute the method provided in the above method embodiment. Its implementation principle and technical effect are similar, and will not be described in detail here.

[0242] Figure 5 This is a schematic diagram of the control equipment for the microgrid provided in this application. Figure 5 As shown, the microgrid control device 50 provided in this embodiment includes at least one processor 501 and a memory 502. Optionally, the device 50 further includes a communication component 503. The processor 501, memory 502, and communication component 503 are connected via a bus 504.

[0243] In a specific implementation, at least one processor 501 executes computer execution instructions stored in memory 502, causing at least one processor 501 to perform the above-described method.

[0244] The specific implementation process of processor 501 can be found in the above method embodiments, and its implementation principle and technical effect are similar. It will not be repeated here.

[0245] In the above embodiments, it should be understood that the processor can be a Central Processing Unit (CPU), or other general-purpose processors, digital signal processors (DSPs), application-specific integrated circuits (ASICs), etc. The general-purpose processor can be a microprocessor or any conventional processor. The steps of the method disclosed in this invention can be directly implemented by a hardware processor, or implemented by a combination of hardware and software modules within the processor.

[0246] The memory may include random access memory (RAM) and may also include non-volatile memory (NVM), such as at least one disk storage device.

[0247] The bus can be an Industry Standard Architecture (ISA) bus, a Peripheral Component Interconnect (PCI) bus, or an Extended Industry Standard Architecture (EISA) bus, etc. Buses can be categorized as address buses, data buses, control buses, etc. For ease of illustration, the buses shown in the accompanying drawings are not limited to a single bus or a single type of bus.

[0248] This application also provides a computer program product, including a computer program that, when executed by a processor, implements the above-described method.

[0249] This application also provides a computer-readable storage medium storing computer-executable instructions, which, when executed by a processor, implement the above-described method.

[0250] The aforementioned readable storage medium can be implemented by any type of volatile or non-volatile storage device or a combination thereof, such as static random access memory (SRAM), electrically erasable programmable read-only memory (EEPROM), erasable programmable read-only memory (EPROM), programmable read-only memory (PROM), read-only memory (ROM), magnetic storage, flash memory, magnetic disk, or optical disk. The readable storage medium can be any available medium accessible to a general-purpose or special-purpose computer.

[0251] An exemplary readable storage medium is coupled to a processor, enabling the processor to read information from and write information to the readable storage medium. Of course, the readable storage medium can also be a component of the processor. The processor and the readable storage medium can reside in an Application Specific Integrated Circuit (ASIC). Alternatively, the processor and the readable storage medium can exist as discrete components in the device.

[0252] The division of units is merely a logical functional division; in actual implementation, there may be other division methods. For example, multiple units or components may be combined or integrated into another system, or some features may be ignored or not executed. Furthermore, the coupling or direct coupling or communication connection shown or discussed may be indirect coupling or communication connection through some interfaces, devices, or units, and may be electrical, mechanical, or other forms.

[0253] Units described as separate components may or may not be physically separate, and components shown as units may or may not be physical units, that is, they may be located in one place or distributed across multiple network units. Some or all of these units may be selected to achieve the purpose of this embodiment according to actual needs.

[0254] In addition, the functional units in the various embodiments of the present invention can be integrated into one processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit.

[0255] If a function is implemented as a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of this invention, or the part that contributes to the prior art, or a part of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute all or part of the steps of the methods of the various embodiments of this invention. The aforementioned storage medium includes various media capable of storing program code, such as USB flash drives, portable hard drives, read-only memory (ROM), random access memory (RAM), magnetic disks, or optical disks.

[0256] Those skilled in the art will understand that all or part of the steps of the above-described method embodiments can be implemented by hardware related to program instructions. The aforementioned program can be stored in a computer-readable storage medium. When executed, the program performs the steps of the above-described method embodiments; and the aforementioned storage medium includes various media capable of storing program code, such as ROM, RAM, magnetic disks, or optical disks.

[0257] Finally, it should be noted that other embodiments of the invention will readily occur to those skilled in the art upon consideration of the specification and practice of the invention disclosed herein. This invention is intended to cover any variations, uses, or adaptations of the invention that follow the general principles of the invention and include common knowledge or customary techniques in the art not disclosed herein, and is not limited to the precise structures described above and shown in the accompanying drawings, and various modifications and changes can be made without departing from its scope. The scope of the invention is limited only by the appended claims.

Claims

1. A control method for a microgrid, characterized in that, The method includes: The active marginal cost of active power output by distributed power sources in a microgrid, the reactive marginal cost of reactive power, a first cost coefficient characterizing the impact of changes in active power on the cost of reactive power, and a second cost coefficient characterizing the impact of changes in reactive power on the cost of active power are obtained. The adjustment voltage is obtained based on the active marginal cost of the active power output by the distributed power source in the microgrid, the reactive marginal cost of the reactive power, and a first cost coefficient characterizing the degree of influence of the change in active power on the cost of reactive power. The adjustment frequency is obtained based on the active marginal cost of the active power output by the distributed power sources in the microgrid, the reactive marginal cost of the reactive power, and a second cost coefficient that characterizes the degree of influence of changes in the active power on the reactive power cost. A control signal is generated based on the adjusted voltage and the adjusted frequency; The output voltage and output frequency of the distributed power supply are adjusted according to the control signal.

2. The method according to claim 1, characterized in that, The step of obtaining the adjustment voltage based on the active marginal cost of active power output by distributed power sources in the microgrid, the reactive marginal cost of reactive power, and a first cost coefficient characterizing the impact of changes in active power on the reactive power cost includes: The first coupling cost is obtained based on the first cost coefficient and the reactive marginal cost; The first marginal cost of the distributed power source is obtained based on the first coupling cost and the active marginal cost. The voltage regulation coefficient is obtained based on the first marginal cost, the first sensitivity coefficient of the active marginal cost, and the active droop economic coefficient. The adjusted voltage is obtained based on the allowable output voltage of the distributed power source and the voltage adjustment coefficient.

3. The method according to claim 2, characterized in that, The adjusted voltage satisfies: Wherein, the U max The maximum allowable output voltage among the allowable output voltages, U min The minimum allowable output voltage among the allowable output voltages; The λ L，P The active power droop economic coefficient is mentioned above; The This is the first sensitivity coefficient of the distributed power source i; The k PQ The active power droop economic coefficient is mentioned above; The L i (P i The active power P output by the distributed power source i is... i The active marginal cost, the L i (Q i ) represents the reactive power Q output by the distributed power source i. i The marginal cost of reactive power.

4. The method according to claim 3, characterized in that, The method further includes: A first sensitivity coefficient for the active marginal cost is determined based on the rate of change of the active marginal cost, the maximum active output of the active power, and the maximum active marginal cost of the distributed power source.

5. The method according to claim 3, characterized in that, The method further includes: The active power droop economic coefficient is determined based on the maximum allowable voltage deviation of the distributed power source, the first marginal cost, and the first sensitivity coefficient of the active power marginal cost.

6. The method according to claim 1, characterized in that, The step of obtaining the adjustment frequency based on the active marginal cost of active power output by distributed power sources in the microgrid, the reactive marginal cost of reactive power, and a second cost coefficient characterizing the impact of changes in active power on the reactive power cost, includes: The second coupling cost is obtained based on the second cost coefficient and the active marginal cost; The second marginal cost of the distributed power source is obtained based on the second coupling cost and the reactive power marginal cost. The frequency adjustment coefficient is obtained based on the second marginal cost, the second sensitivity coefficient of the reactive power marginal cost, and the reactive power droop economic coefficient. The adjustment frequency is obtained based on the rated frequency of the distributed power source and the frequency adjustment coefficient.

7. The method according to claim 5, characterized in that, The method further includes: A second sensitivity coefficient for the active marginal cost is determined based on the rate of change of the reactive marginal cost, the maximum reactive output of the reactive power, and the maximum reactive marginal cost of the distributed power source.

8. The method according to claim 5, characterized in that, The method further includes: The reactive power droop economic coefficient is determined based on the maximum permissible frequency deviation of the distributed power source, the second marginal cost, and the second sensitivity coefficient of the reactive power marginal cost.

9. The method according to any one of claims 1 to 8, characterized in that, The step of generating a control signal based on the adjusted voltage and the adjusted frequency includes: The adjustment voltage and the adjustment frequency are input to a voltage-current dual-loop controller to obtain a modulation ratio signal; The modulation ratio signal is input to the PWM modulator to obtain the control signal.

10. A control device for a microgrid, characterized in that, include: Memory, processor; The memory stores computer-executed instructions; The processor executes computer execution instructions stored in the memory, causing the processor to perform the method as described in any one of claims 1-9.

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