Regulation and control method and device for independent micro-grid system in agricultural region

Abstract

The invention provides a regulation and control method and device for an independent micro-grid system in an agricultural region, and the method comprises the steps: determining a system inertia demand constraint based on a virtual inertia support effect of a fan and energy storage on the independent micro-grid system; based on the characteristic difference of the load peak and valley periods, determining the fan flexible standby constraint based on the wind curtailment level; determining an agricultural light supplement load transfer constraint based on illumination demand characteristics in a crop growth process; and constructing a target function, and carrying out optimal scheduling on the independent micro-grid system. The method can effectively improve the rotational kinetic energy level of the system, enhance the power disturbance resistance of the system, and can effectively utilize the adjustment space generated by passive wind curtailment, thereby reducing the total operation cost of the system, improving the wind power utilization rate, and achieving adjustable and controllable agricultural light supplement load energy consumption transfer. Source load output can be fully coordinated on the premise that healthy growth of crops is guaranteed, new energy is fully and effectively consumed, and the total operation cost of the system is reduced.

Description

Technical Field

[0001] The present invention relates to the field of power systems, and particularly to a regulation method and device for an independent microgrid system in agricultural areas. Background Art

[0002] The energy demand in agricultural areas of our country is growing rapidly. However, due to the lack of reasonable energy management methods and regulation means, the problem of mismatched and unbalanced energy supply and demand in agricultural areas has become increasingly prominent.

[0003] The upgrading and innovation of modern agriculture such as "plant factories" and "facility agriculture" have promoted the continuous growth of load demand and distributed power generation scale in agricultural areas. At the same time, considering the high cost of main grid extension, locally consuming wind and light resources has gradually become the preferred energy supply method for remote mountainous areas and independent bases. At present, renewable energy local area networks should be built according to local conditions, and the construction of agricultural power grids in remote areas has been continuously strengthened. Against this background, independent microgrids provide a promising solution for the energy supply in remote agricultural areas in a low-cost manner.

[0004] Locally consuming new energy helps village- and county-level microgrids achieve self-sufficient production goals, and at the same time can improve the electrification level of terminal energy use. However, new energy units usually exhibit low inertia characteristics, and are prone to inertia shortage problems when a high proportion is incorporated into the power grid, which seriously weakens the system's ability to resist power disturbances. To address this problem, some scholars have strengthened the frequency stability of the power grid by introducing frequency security constraints into the dispatching plan. In addition, some scholars have pointed out that when the system inertia reserve is insufficient, by reducing the output limit of the unit, the impact power on the system during the occurrence of disturbances can be effectively reduced. However, the above research mainly relies on traditional resources to enhance system inertia, and fails to fully explore the potential of new energy units in inertia support to reduce the burden of system frequency modulation.

[0005] Considering that the response speed of new energy units is significantly better than that of traditional units, in addition to inertia support, existing research has also widely explored the possibility of new energy units providing primary frequency modulation services. Some scholars considered pre-unloading of wind turbines to provide frequency modulation reserve and proposed a wind turbine unloading strategy under wind-storage coordinated frequency modulation. However, the fixed proportion of wind turbine unloading method limits the flexibility of its strategy, and this strategy does not fully consider the impact of wind turbine unloading frequency modulation on the wind power consumption rate. Therefore, some scholars have also deeply explored the mechanism of wind turbines and conventional units participating in system frequency modulation together, and proposed an intraday rolling dispatching model with steady-state and transient coordinated optimization. However, the processing of wind power unloading constraints in this model is relatively brief, and there is still room for improvement in its wind power consumption rate.

[0006] Therefore, in view of the above existing problems, it is particularly necessary to propose an agricultural independent microgrid regulation method for agricultural production loads that better reflects agricultural characteristics. Summary of the Invention

[0007] In view of the problems in the prior art, embodiments of the present invention provide a method and a system for regulating an independent microgrid system in agricultural areas, so as to solve the problem that the agricultural production load in the regulation of the existing agricultural independent microgrid cannot better reflect the agricultural characteristics.

[0008] Specifically, the embodiments of the present invention provide the following technical solutions:

[0009] In a first aspect, embodiments of the present invention provide a method for regulating an independent microgrid system in agricultural areas, including:

[0010] Based on the virtual inertia support of the independent microgrid system by the wind turbines and energy storage, determining the system inertia demand constraint;

[0011] Based on the characteristic differences during the peak and valley periods of the load, determining the flexible reserve constraint of the wind turbines based on the wind curtailment level;

[0012] Based on the lighting demand characteristics during the crop growth process, determining the agricultural supplementary lighting load transfer constraint;

[0013] Taking the sum of at least one of the power generation cost, frequency regulation reserve cost, wind curtailment and negative frequency regulation reserve cost, and load transfer cost of the independent microgrid system as the minimum, constructing an objective function; and

[0014] According to the system inertia demand constraint, the flexible reserve constraint of the wind turbines, the agricultural supplementary lighting load transfer constraint, and the objective function, optimizing the dispatching of the independent microgrid system.

[0015] In a possible implementation manner, the optimizing the dispatching of the independent microgrid system according to the system inertia demand constraint, the flexible reserve constraint of the wind turbines, the agricultural supplementary lighting load transfer constraint, and the objective function includes:

[0016] Solving the objective function under the system inertia demand constraint, the flexible reserve constraint of the wind turbines, and the agricultural supplementary lighting load transfer constraint to obtain an optimal solution;

[0017] Based on the optimal solution, optimizing the dispatching of the independent microgrid system.

[0018] In a possible implementation manner, the determining the system inertia demand constraint based on the virtual inertia support of the independent microgrid system by the wind turbines and energy storage includes:

[0019] Based on the rotational kinetic energy of the diesel engine, the rotational kinetic energy of the wind turbine rotor, and the energy reserve of the energy storage device, calculating the total rotational kinetic energy E of the independent microgrid system at time t sys，t , t≥0,

[0020] Obtain the minimum rotational kinetic energy E required for the independent microgrid system under the maximum frequency change rate threshold lim ;

[0021] According to E lim and E sys，t , determine that the system inertia demand constraint satisfies the following formula:

[0022] E sys,t ≥E lim .

[0023] In a possible implementation manner, calculate the total rotational kinetic energy E of the independent microgrid system at time t based on the rotational kinetic energy of the diesel engine, the rotational kinetic energy of the fan rotor, and the energy reserve of the energy storage device sys，t , including:

[0024] Calculate E according to the following expression sys，t :

[0025]

[0026] where E sys,t is the total rotational kinetic energy of the independent microgrid system at time t, t≥0; represents the rotational kinetic energy of the diesel engine, represents the rotational kinetic energy of the fan rotor, represents the energy reserve of the energy storage device, H g , H w , H s,t are respectively the inertia time constant of the gth diesel engine, the equivalent inertia time constant of the wth fan, and the equivalent inertia time constant of the sth energy storage device at time t, where g = 1...N G , w = 1...N W , s = 1...N S , where N G , N W , N S are respectively the numbers of diesel engines, fans, and energy storage devices, N G , N W , N S are respectively positive integers greater than 0; are respectively the rated power of the gth diesel engine, the maximum power prediction value of the wth fan at time t, and the rated power of the sth energy storage device.

[0027] In a possible implementation manner, the obtaining of the minimum rotational kinetic energy E required for the independent microgrid system under the maximum frequency change rate threshold lim , including:

[0028] Calculate E according to the following expression lim :

[0029]

[0030] where ΔP N-1 is the maximum power disturbance suffered by the independent microgrid system when N - 1 faults occur; f 0 is the reference frequency of the independent microgrid system; is the threshold of the maximum frequency change rate of the independent microgrid system.

[0031] In a possible implementation manner, determining the flexible reserve constraint of the wind turbine based on the curtailment level based on the characteristic differences during the peak and valley periods of the load includes:

[0032] Determine the flexible reserve constraint of the wind turbine based on the curtailment level at least according to the load reduction rule of the wind turbine;

[0033] The load reduction rule of the wind turbine includes:

[0034] During the valley period of the load, adjust the positive frequency regulation reserve capacity of the wind turbine to the curtailment level;

[0035] During the peak period of the load, reduce the pre - load reduction ratio of the wind turbine;

[0036] The rated output of the wind turbine minus the sum of the positive and negative reserves is greater than or equal to the safety load reduction limit value.

[0037] In a possible implementation manner, the flexible reserve constraint of the wind turbine satisfies:

[0038]

[0039] where are the positive and negative frequency regulation reserves of the w - th wind turbine at time t respectively; d max is the maximum load reduction ratio of the wind turbine under the premise of stable operation; P w,t is the planned output of the w - th wind turbine at time t, is the maximum power prediction value of the w - th wind turbine at time t, t ≥ 0, w = 1...N W N W is the number of wind turbines, and w is an integer greater than 0.

[0040] In a possible implementation manner, the light demand characteristics during the crop growth process include light demand conditions;

[0041] Determining the agricultural supplementary lighting load transfer constraint based on the light demand characteristics during the crop growth process includes:

[0042] Determine the agricultural supplementary lighting load transfer constraint based on the light demand conditions,

[0043] Among them, the light requirement conditions include at least one of the following:

[0044] Ensure that the photosynthetically active radiation level absorbed by the crops during the time period t reaches the expected value of the photosynthetically active radiation date that meets the growth requirements of the crops;

[0045] Ensure that the photosynthetically active radiation absorbed by the crops during the time period t is between the light saturation point and the light compensation point;

[0046] Ensure that the photosynthetic photon flux density provided by artificial light supplementation is within a predetermined range.

[0047] In a possible implementation manner, the agricultural light supplementation load transfer constraint satisfies at least one of Constraint 1, Constraint 2, and Constraint 3:

[0048] Constraint 1 is satisfied:

[0049]

[0050] Among them, R target is the expected value of the photosynthetically active radiation date that meets the growth requirements of the crops, and R PAR，t is the sum of the photosynthetically active radiation levels absorbed from natural light and artificial light supplementation during the time period t, is the transfer amount of the photosynthetically active radiation provided by artificial light supplementation during the time period t;

[0051] Constraint 2 is satisfied:

[0052]

[0053] Among them, are the photosynthetically active radiation levels absorbed by the crops at the light saturation point and the light compensation point respectively;

[0054] Constraint 3 is satisfied:

[0055]

[0056] Among them, is the upper limit of the photosynthetic photon flux density that can be provided by the greenhouse, is the transfer amount of the artificial light supplementation light intensity during the time period t, and η hps-PAR is the proportion of the photosynthetically active radiation in the artificial light supplementation spectrum, and R hps,t is the light intensity of the artificial light supplementation during the time period t.

[0057] In a second aspect, an embodiment of the present invention provides a control device for an independent microgrid system for an agricultural area, including:

[0058] A system inertia demand constraint determination module, configured to determine a system inertia demand constraint based on the virtual inertia support effect of the fan and the energy storage on the independent microgrid system;

[0059] A wind turbine flexible reserve constraint determination module, configured to determine a wind turbine flexible reserve constraint based on the curtailment level according to the characteristic differences during peak and valley load periods.

[0060] An agricultural supplementary lighting load transfer constraint determination module, configured to determine an agricultural supplementary lighting load transfer constraint according to the lighting demand characteristics during the growth process of crops.

[0061] An objective function construction module, configured to construct an objective function based on minimizing at least one of the power generation cost, frequency regulation reserve cost, wind turbine curtailment and negative frequency regulation reserve cost, and load transfer cost of the independent microgrid system; and

[0062] An optimal scheduling module, configured to perform optimal scheduling on the independent microgrid system according to the system inertia demand constraint, the wind turbine flexible reserve constraint, the agricultural supplementary lighting load transfer constraint, and the objective function.

[0063] The regulation method for an independent microgrid system in an agricultural area provided by an embodiment of the present invention determines a system inertia demand constraint based on the virtual inertia support of the wind turbine and energy storage for the independent microgrid system; determines a wind turbine flexible reserve constraint based on the curtailment level according to the characteristic differences during peak and valley load periods; determines an agricultural supplementary lighting load transfer constraint according to the lighting demand characteristics during the growth process of crops; constructs an objective function based on minimizing at least one of the power generation cost, frequency regulation reserve cost, wind turbine curtailment and negative frequency regulation reserve cost, and load transfer cost of the independent microgrid system; and performs optimal scheduling on the independent microgrid system according to the system inertia demand constraint, the wind turbine flexible reserve constraint, the agricultural supplementary lighting load transfer constraint, and the objective function. Among them, in the embodiment of the present invention, by using the wind turbine and energy storage device to support the system through virtual inertia, the system rotational kinetic energy level can be effectively improved, and its ability to resist power disturbances can be enhanced. Moreover, the wind turbine provides frequency regulation reserve through flexible reserve, which can effectively utilize the regulation space generated by passive curtailment, thereby reducing the total system operation cost and improving the wind power utilization rate. In addition, the controllable energy consumption transfer of the agricultural supplementary lighting load can fully coordinate the source-load output on the premise of ensuring the healthy growth of crops, thereby fully and effectively consuming new energy and reducing the total system operation cost. Thus, the independent frequency regulation ability and energy utilization efficiency of the agricultural power system are enhanced, so that the agricultural independent microgrid regulation better reflects the agricultural production load with agricultural characteristics. Description of the Drawings

[0064] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the following will briefly introduce the drawings required for the description of the embodiments or the prior art. Obviously, the drawings in the following description are some embodiments of the present invention. For those of ordinary skill in the art, without creative efforts, other drawings can also be obtained based on these drawings.

[0065] Figure 1 Flowchart of an exemplary regulation method for an independent microgrid system in an agricultural area provided by an embodiment of the present invention;

[0066] Figure 2 Flowchart of an exemplary regulation method for an independent microgrid system in an agricultural area provided by another embodiment of the present invention;

[0067] Figure 3 Energy structure of an agricultural independent microgrid provided by an embodiment of the present invention; and

[0068] Figure 4 Block diagram of a regulation device for an independent microgrid system in an agricultural area provided by an embodiment of the present invention. Detailed implementation manners

[0069] To make the objectives, technical solutions, and advantages of the embodiments of the present invention clearer, the following will clearly and completely describe the technical solutions in the embodiments of the present invention with reference to the drawings in the embodiments of the present invention. Obviously, the described embodiments are some, but not all, of the embodiments of the present invention. Based on the embodiments of the present invention, all other embodiments obtained by those of ordinary skill in the art without creative efforts belong to the scope of protection of the present invention.

[0070] With the advancement of the rural revitalization strategy, the energy demand in agricultural areas (rural areas) of our country has grown rapidly. However, due to the lack of reasonable energy management methods and regulation means, the problem of unbalanced energy supply and demand in agricultural areas has become increasingly prominent. Considering that the response speed of new energy units is significantly better than that of traditional units, in addition to inertia support, existing research has also widely explored the possibility of new energy units providing primary frequency regulation services. Some scholars considered pre-unloading of wind turbines to provide frequency regulation reserve and proposed a wind turbine unloading strategy under wind-storage coordinated frequency regulation. However, the fixed-ratio wind turbine unloading method limits the flexibility of its strategy, and this strategy does not fully consider the impact of wind turbine unloading for frequency regulation on the wind power consumption rate. Therefore, some scholars have also deeply explored the mechanism of wind turbines and conventional units participating in system frequency regulation together and proposed an intraday rolling scheduling model with steady-state and transient coordinated optimization. However, the handling of wind power unloading constraints in this model is relatively brief, and there is still room for improvement in its wind power consumption rate. However, existing research rarely considers agricultural production loads that can better reflect agricultural characteristics.

[0071] Aiming at the problem of agricultural production load in the prior art that cannot better reflect agricultural characteristics, the control method of the independent microgrid system for agricultural areas in the embodiments of the present application constructs an optimized dispatching model for the agricultural independent microgrid by setting up wind turbines and energy storage for the virtual inertia support ability of the system, the flexible reserve ability of wind turbines, and the adjustable characteristics of agricultural supplementary lighting load. Using wind turbines and energy storage devices to support the system through virtual inertia can effectively improve the level of the system's rotational kinetic energy and enhance its ability to resist power disturbances. The wind turbines provide frequency regulation reserve through flexible reserve constraints, which can effectively utilize the adjustment space generated by passive wind curtailment, thereby reducing the total operating cost of the system and improving the utilization rate of wind power. Based on the energy consumption transfer constraint of the agricultural supplementary lighting load established in this paper, it is possible to fully coordinate the power output of the source and load on the premise of ensuring the healthy growth of crops, thereby fully and effectively accommodating new energy and reducing the total operating cost of the system.

[0072] First, refer to Figure 1 , which shows the flowchart of the control method for the independent microgrid system for agricultural areas provided by an exemplary embodiment of the present invention. As Figure 1 shown, the control method for the independent microgrid system for agricultural areas provided by the embodiments of the present invention includes the following steps:

[0073] Step 110: Determine the system inertia demand constraint based on the virtual inertia support of the independent microgrid system by wind turbines and energy storage.

[0074] In one example, determining the system inertia demand constraint based on the virtual inertia support of the independent microgrid system by wind turbines and energy storage includes:

[0075] Based on the rotational kinetic energy of the diesel engine, the rotational kinetic energy of the wind turbine rotor, and the energy reserve of the energy storage device, calculate the total rotational kinetic energy E of the independent microgrid system at time t sys,t , t≥0;

[0076] Obtain the minimum rotational kinetic energy E required for the independent microgrid system under the maximum frequency change rate threshold lim ;

[0077] According to E lim and E sys，t , determine that the system inertia demand constraint satisfies the following formula:

[0078] E sys,t ≥E lim .

[0079] In one example, based on the rotational kinetic energy of the diesel engine, the rotational kinetic energy of the wind turbine rotor, and the energy reserve of the energy storage device, calculate the total rotational kinetic energy E of the independent microgrid system at time t sys，t , including:

[0080] Calculate E according to the following expression sys，t :

[0081]

[0082] where E sys,t is the total rotational kinetic energy of the independent microgrid system at time t, t ≥ 0; represents the rotational kinetic energy of the diesel engine, represents the rotational kinetic energy of the wind turbine rotor, represents the energy reserve of the energy storage device, H g 、H w 、H s,t are the inertia time constant of the g-th diesel engine, the equivalent inertia time constant of the w-th wind turbine, and the equivalent inertia time constant of the s-th energy storage device at time t, respectively, where g = 1...N G , w = 1...N W , s = 1...N S , where N G 、N W 、N S are the numbers of diesel engines, wind turbines, and energy storage devices respectively, N G 、N W 、N S are all positive integers greater than 0; are the rated power of the g-th diesel engine, the predicted maximum power value of the w-th wind turbine at time t, and the rated power of the s-th energy storage device respectively.

[0083] In one example, obtaining the minimum rotational kinetic energy E that the independent microgrid system needs to possess under the maximum frequency change rate threshold lim , includes:

[0084] Calculate E according to the following expression lim :

[0085]

[0086] where ΔP N-1 is the maximum power disturbance received by the independent microgrid system when an N-1 fault occurs; f 0 is the base frequency of the independent microgrid system; is the maximum frequency change rate threshold of the independent microgrid system.

[0087] The N-1 fault means that in a system, when any component (such as a line, generator, transformer, etc.) fails or disconnects, the remaining components should be able to continue to operate normally, ensuring the stable operation of the system and continuous power supply, rather than causing the collapse of the entire system due to the failure of a single component. In the power system, the N-1 principle is an important technical requirement to ensure that under normal operating conditions, when any component has no fault or is disconnected due to a fault, other components are not overloaded, and the voltage and frequency are within the allowable range. This is crucial for ensuring the stability and safety of the power grid. Especially in the application of critical users or important loads, the reliability of the power supply system is particularly important. When designing the power supply and distribution system, the N-1 principle should be fully considered to ensure that even when a power supply line or related equipment fails or is under maintenance, the remaining lines and equipment can still ensure the normal power supply of first-level and second-level loads.

[0088] In this embodiment, by using the fan and the energy storage device to support the system through virtual inertia, the rotational kinetic energy level of the system can be effectively improved, and its ability to resist power disturbances can be enhanced.

[0089] Step 120: Based on the characteristic differences between the peak and valley periods of the load, determine the flexible reserve constraint of the fan based on the wind curtailment level.

[0090] In an example, based on the characteristic differences between the peak and valley periods of the load, determining the flexible reserve constraint of the fan based on the wind curtailment level includes:

[0091] Determine the flexible reserve constraint of the fan based on the wind curtailment level at least according to the load reduction rule of the fan;

[0092] The load reduction rules of the fan include:

[0093] In the load valley period, adjust the positive frequency regulation reserve capacity of the fan to the wind curtailment level;

[0094] In the load peak period, reduce the pre-load reduction ratio of the fan;

[0095] The rated output of the fan minus the sum of the positive and negative reserves is greater than or equal to the safety load reduction limit value.

[0096] In an example, the flexible reserve constraint of the fan satisfies:

[0097]

[0098] Among them, are the positive and negative frequency regulation reserves of the wth fan at time t respectively; d max is the maximum load reduction ratio of the fan under the premise of stable operation; P w,t is the planned output of the wth fan at time t, is the maximum power prediction value of the wth fan at time t, t≥0, w = 1...NW , N W is the number of fans, and w is an integer greater than 0.

[0099] In this embodiment, the fans provide frequency regulation reserve through flexible reserve constraints, which can effectively utilize the regulation space generated by passive curtailment of wind power, thereby reducing the total system operation cost and improving the utilization rate of wind power.

[0100] Step 130: Determine the agricultural supplementary lighting load transfer constraint based on the lighting demand characteristics during the crop growth process.

[0101] In one example, the lighting demand characteristics during the crop growth process include lighting demand conditions;

[0102] Determining the agricultural supplementary lighting load transfer constraint based on the lighting demand characteristics during the crop growth process includes:

[0103] Determine the agricultural supplementary lighting load transfer constraint based on the lighting demand conditions,

[0104] where the lighting demand conditions include at least one of the following:

[0105] Ensure that the photosynthetically active radiation level absorbed by the crops during the t period reaches the expected value of the photosynthetically active radiation date that meets the crop growth requirements;

[0106] Ensure that the photosynthetically active radiation absorbed by the crops during the t period is between the light saturation point and the light compensation point;

[0107] Ensure that the photosynthetic photon flux density provided by artificial supplementary lighting is within a predetermined range.

[0108] In one example, the agricultural supplementary lighting load transfer constraint satisfies at least one of Constraint 1, Constraint 2, and Constraint 3:

[0109] Constraint 1 is satisfied:

[0110]

[0111] where R target is the expected value of the photosynthetically active radiation date that meets the crop growth requirements, and R PAR，t is the sum of the photosynthetically active radiation levels absorbed from natural lighting and artificial supplementary lighting during the t period, is the transfer amount of the photosynthetically active radiation provided by artificial supplementary lighting during the t period.

[0112] Constraint 2 is satisfied:

[0113]

[0114] where, are the photosynthetically active radiation levels absorbed by the crops at the light saturation point and the light compensation point, respectively;

[0115] Constraint 3 is satisfied:

[0116]

[0117] wherein, is the upper limit of the photosynthetic photon flux density that the greenhouse can provide, is the transfer amount of the artificial supplementary lighting intensity in the t period, η hps-PAR is the proportion of photosynthetically active radiation in the artificial supplementary lighting spectrum, R hps,t is the lighting intensity of the artificial supplementary lighting in the t period.

[0118] In this embodiment, by satisfying the expected value of the photosynthetically active radiation date required for crop growth, ensuring that the photosynthetically active radiation absorbed by the crops in each period is between the light saturation point and the light compensation point, and ensuring that the photosynthetic photon flux density provided by the artificial supplementary lighting is within a predetermined range, it is possible to fully coordinate the source-load output on the premise of ensuring the healthy growth of the crops, and then fully and effectively absorb new energy and reduce the total system operation cost.

[0119] Step 140: Based on the sum of at least one of the power generation cost, frequency modulation reserve cost, wind turbine curtailment and negative frequency modulation reserve cost, and load transfer cost of the independent microgrid system being minimized, construct an objective function.

[0120] Objective function:

[0121] min{W e +W r +W w +W tl}

[0122]

[0123] In the formula: W e 、W r 、W w 、W tl are the power generation cost, frequency modulation reserve cost, wind turbine curtailment and negative frequency modulation reserve cost, and load transfer cost respectively; P g,t 、P v,t are the planned output of the gth diesel engine and the vth photovoltaic unit at time t; is the load transfer power; are the positive and negative frequency modulation reserves of the gth diesel engine at time t respectively; are the positive and negative frequency modulation reserves of the sth energy storage device at time t respectively; Times is the total number of scheduling plan times; N V is the number of photovoltaic units.

[0124] In this embodiment, a target function is constructed based on the sum of at least one of the power generation cost, frequency regulation reserve cost, wind curtailment and negative frequency regulation reserve cost, and load transfer cost of the independent microgrid system, fully considering various costs in the system and reducing the total operating cost of the system.

[0125] Step 150: Optimally dispatch the independent microgrid system according to the system inertia demand constraint, the flexible reserve constraint of the wind turbines, the agricultural supplementary lighting load transfer constraint, and the target function.

[0126] In an example, optimally dispatching the independent microgrid system according to the system inertia demand constraint, the flexible reserve constraint of the wind turbines, the agricultural supplementary lighting load transfer constraint, and the target function includes: solving the target function under the system inertia demand constraint, the flexible reserve constraint of the wind turbines, and the agricultural supplementary lighting load transfer constraint to obtain an optimal solution; and based on the optimal solution, optimally dispatching the independent microgrid system.

[0127] In an example, before solving the target function under the system inertia demand constraint, the flexible reserve constraint of the wind turbines, and the agricultural supplementary lighting load transfer constraint to obtain an optimal solution, it further includes: obtaining the system power balance constraint, the system frequency regulation reserve constraint, the diesel engine output limit constraint, the diesel engine frequency regulation reserve limit constraint, the wind turbine output limit constraint, the photovoltaic output limit constraint, the energy storage operation state constraint, the energy storage output limit constraint, the energy storage SOC constraint, and the energy storage frequency regulation reserve limit constraint corresponding to the independent microgrid system.

[0128] In an example, solving the target function under the system inertia demand constraint, the flexible reserve constraint of the wind turbines, and the agricultural supplementary lighting load transfer constraint to obtain an optimal solution includes: solving the target function under the system inertia demand constraint, the flexible reserve constraint of the wind turbines, the agricultural supplementary lighting load transfer constraint, as well as the system power balance constraint, the system frequency regulation reserve constraint, the diesel engine output limit constraint, the diesel engine frequency regulation reserve limit constraint, the wind turbine output limit constraint, the photovoltaic output limit constraint, the energy storage operation state constraint, the energy storage output limit constraint, the energy storage SOC constraint, and the energy storage frequency regulation reserve limit constraint to obtain an optimal solution.

[0129] In this embodiment, not only the system inertia demand constraint, the flexible reserve constraint of the wind turbines, and the agricultural supplementary lighting load transfer constraint are considered, but also the system power balance constraint, the system frequency regulation reserve constraint, the diesel engine output limit constraint, the diesel engine frequency regulation reserve limit constraint, the wind turbine output limit constraint, the photovoltaic output limit constraint, the energy storage operation state constraint, the energy storage output limit constraint, the energy storage SOC constraint, and the energy storage frequency regulation reserve limit constraint are further considered. Furthermore, based on the above constraints, the objective function is solved to obtain the optimal solution that satisfies the above constraints. Thus, based on the optimal solution that satisfies the above constraints, the independent microgrid system is optimized and dispatched, which can improve the stability of the system operation, optimize the resource utilization rate, ensure various load demands, extend the service life of equipment, etc.

[0130] The control method for the independent microgrid system in agricultural areas of this embodiment can effectively improve the system's rotational kinetic energy level and enhance its ability to resist power disturbances by using the wind turbines and energy storage devices to support the system through virtual inertia. The wind turbines provide frequency regulation reserve through flexible reserve, which can effectively utilize the adjustment space generated by passive wind curtailment, thereby reducing the total system operation cost and increasing the utilization rate of wind power. The controllable agricultural supplementary lighting load energy consumption transfer can fully coordinate the source-load output on the premise of ensuring the healthy growth of crops, thereby fully and effectively consuming new energy and reducing the total system operation cost. Thus, the independent frequency regulation ability and energy utilization efficiency of the agricultural power system are enhanced.

[0131] The following is another exemplary embodiment of the present application. Refer to Figure 2 , the following embodiments of the present invention provide a control method for an independent microgrid system in agricultural areas, including:

[0132] Step A: Considering the virtual inertia support of the wind turbines and energy storage for the system, determine the corresponding system inertia demand constraint.

[0133] Step B: According to the characteristic differences during the peak and valley periods of the load, determine the flexible reserve constraint of the wind turbines based on the wind curtailment level.

[0134] Step C: Combining the lighting demand characteristics during the crop growth process, determine the agricultural supplementary lighting load energy consumption transfer constraint;

[0135] Step D: Combining the system inertia demand constraint, the flexible reserve constraint of the wind turbines, and the agricultural supplementary lighting load transfer constraint, construct an optimization dispatch model for the agricultural independent microgrid.

[0136] In step A, by setting the minimum rotational kinetic energy required by the system under the maximum frequency change rate threshold, the system rotational inertia demand is characterized.

[0137]

[0138] Similarly, the total rotational kinetic energy of the independent microgrid system at the current moment is set to characterize the inertia of the independent microgrid system. The total rotational kinetic energy mainly comes from the rotational kinetic energy of the diesel engine, the wind turbine rotor, and the energy storage of the energy storage device.

[0139] Based on the rotational kinetic energy of the diesel engine, the rotational kinetic energy of the wind turbine rotor, and the energy storage of the energy storage device, the total rotational kinetic energy E of the independent microgrid system at time t is calculated sys，t , specifically, E is calculated according to the following expression sys，t :

[0140]

[0141] Among them, the above formula (2) contains three inertia time constants: H g is a fixed parameter, reflecting the mechanical inertia provided by the diesel engine; H w is an adjustable parameter of the control unit, characterizing the virtual inertia provided by the wind turbine; H s,t characterizes the virtual inertia provided by the energy storage device, and its value is determined according to the current energy state of the energy storage, as shown in the following formula (3).

[0142]

[0143] In the above formula: SOC s,t is the state of charge of the s-th energy storage device at time t; is the maximum charge / discharge rate of the energy storage; S 0 is the unit reference power.

[0144] In summary, to ensure that the independent microgrid system has sufficient inertia support, the following formula needs to be satisfied:

[0145] E sys,t ≥E lim (4)

[0146] In this embodiment, by using the wind turbine and the energy storage device to support the system through virtual inertia, the rotational kinetic energy level of the system can be effectively improved, and its ability to resist power disturbances can be enhanced.

[0147] In step B, in view of the problem of the increasing proportion of new energy access and the increasingly serious phenomenon of wind curtailment, this embodiment establishes a flexible reserve constraint of the wind turbine based on the wind curtailment level. This flexible reserve constraint of the wind turbine allows the system to flexibly adjust the positive and negative frequency modulation reserve capacities of the wind turbine within the safe load reduction range based on the wind curtailment characteristics during the peak and valley periods of the load.

[0148] The load reduction rules for the flexible reserve constraint of the wind turbine based on the wind curtailment level are as follows:

[0149] 1) During periods with severe curtailment of wind power, such as during low load periods, the positive frequency regulation reserve capacity of the wind turbines can be adjusted to the curtailment level, so as to make full use of the regulation capacity of the wind turbines generated by curtailment.

[0150] 2) During periods with high power supply pressure and no curtailment of wind power, such as during peak load periods, the pre - load reduction ratio of the wind turbines should be appropriately reduced, that is, the positive frequency regulation reserve capacity should be reduced, and instead, the power generation output should be increased preferentially to ensure the stable power supply of clean energy.

[0151] 3) When the wind turbines provide negative reserve, long - term pre - load reduction is not required. When participating in downward frequency regulation, the output power needs to be reduced. The sum of the positive and negative reserves provided by the wind turbines shall not be lower than the safe load reduction range. That is, the rated output of the wind turbines minus the sum of the positive and negative reserves is greater than or equal to the safe load reduction limit value.

[0152] Combining the above statements, according to the load reduction rules of the wind turbines to determine the flexible reserve constraints of the wind turbines based on the curtailment level, the constraint conditions of the flexible reserve constraints of the wind turbines established in this embodiment are as follows:

[0153]

[0154]

[0155]

[0156] In the formula: are the positive and negative frequency regulation reserves of the w - th wind turbine at time t, respectively; d max is the maximum load reduction ratio of the wind turbine under the premise of stable operation; P w,t is the planned output of the w - th wind turbine at time t.

[0157] Through the above flexible reserve constraints of the wind turbines based on the curtailment level, this embodiment can not only effectively utilize the regulation capacity of the wind turbines provided by passive curtailment, but also avoid the unnecessary curtailment problems caused by the traditional fixed - ratio load reduction reserve method. The wind turbines provide frequency regulation reserve through flexible reserve constraints, which can effectively utilize the regulation space generated by passive curtailment, thereby reducing the total system operation cost and improving the utilization rate of wind power.

[0158] In step C, taking the lighting load with high power consumption in agricultural production as the incentive - type demand response, combined with the lighting demand characteristics in the process of crop growth, an energy consumption transfer constraint for agricultural lighting load is constructed.

[0159] (1) The lighting intensity required for crop growth

[0160] The growth of crops requires sufficient Photosynthetically Active Radiation (PAR). In the field of agricultural engineering, high-pressure sodium lamps (HPS) are often used for artificial supplementary lighting when natural light is insufficient. Of course, other types of lamps can also be used, and the specific type of lamp cannot be used as a limitation to the present invention. The PAR level R absorbed by crops during the t period PAR,t As shown in Equation (8):

[0161] R PAR,t = R sun-PAR,t + R hps-PAR,t (8)

[0162] In the formula: R sun-PAR,t is the PAR level absorbed from natural light during the t period, and R hps-PAR,t is the PAR level absorbed from artificial supplementary lighting during the t period.

[0163] Due to factors such as the attenuation of light in the plant canopy, only the photosynthetic radiation in the 400 - 700 nm band belongs to PAR, and the greenhouse covering material isolates part of the direct irradiation of natural light, only part of the natural light can be converted into PAR and absorbed by crops.

[0164] The PAR level R absorbed from natural light during the t period sun-PAR,t As shown in Equation (9):

[0165]

[0166] In the formula: k is the PAR extinction coefficient of the plant canopy, LAI is the leaf area index; 4.57 is the conversion coefficient for converting the unit W / m 2 to the unit μmol / (s·m 2 ); α sun-PAR is the absorption coefficient of crops for PAR of natural light, η sun-PAR is the proportion of PAR in the natural light spectrum; α r is the transmittance coefficient of the greenhouse covering material, and sr is the reflectance coefficient of the greenhouse covering material; R sun,t is the natural light intensity in the greenhouse during the t period, and I rad,t is the natural light intensity outside the greenhouse during the t period.

[0167] Similar to the above natural light, only part of the artificial supplementary light can be converted into PAR and absorbed by crops.

[0168] Among them, the PAR level R absorbed from artificial supplementary lighting during the t period hps-PAR,t As shown in Equation (10):

[0169] Rhps-PAR,t = (1 - e -k×LAI )(α hps-PAR × η hps-PAR × R hps,t )(10)

[0170] Where: α hps-PAR is the absorption coefficient of crops for PAR of artificial light, η hps-PAR is the proportion of PAR in the artificial supplementary light spectrum; R hps,t is the light intensity of artificial supplementary light in the t period.

[0171] (2) Power consumption of artificial supplementary light for crops

[0172] In this embodiment, taking a greenhouse as an example, in the greenhouse, the supplementary light power E per unit area in the t period AL,t depends on the current light intensity R of artificial supplementary light hps,t . When the intensity of artificial supplementary light in the greenhouse increases, the supplementary light power consumed per unit area also increases, as shown in Equation (11):

[0173]

[0174] Where: PE AL is the photosynthetic photon efficiency of high-pressure sodium lamps, that is, the photosynthetic photon flux of high-pressure sodium lamps per unit power; PPF AL is the photosynthetic photon flux, that is, the number of photosynthetic photons emitted by each high-pressure sodium lamp per second; E AL_r is the rated power of each high-pressure sodium lamp, η hps-PAR is the proportion of photosynthetically active radiation in the artificial supplementary light spectrum.

[0175] Thus, in this embodiment, the coverage area S of each high-pressure sodium lamp at the current (t moment) can be calculated AL,t . When the supplementary light power per unit area increases, the coverage area that a single high-pressure sodium lamp can cover decreases accordingly, as shown in Equation (12):

[0176]

[0177] Among them, E AL_r is the rated power of each high-pressure sodium lamp; E AL,t is the supplementary light power per unit area in the t period.

[0178] Finally, by calculating the number N of supplementary light lamps in the working state in the greenhouse hps,t , the supplementary light load power P of crops in the t period can be obtained hps,t , as shown in Equation (13):

[0179]

[0180] Where: A v is the area occupied by the greenhouse, F C is the proportion of the sown area of crops in the greenhouse area; E AL_r is the rated power of each HPS, S AL,t is the coverage area of each high-pressure sodium lamp at the current time (time t).

[0181] (3) Agricultural supplementary lighting load transfer constraint considering crop growth characteristics

[0182] After transferring the agricultural supplementary lighting load, the power system should still ensure that the PAR level absorbed by the crops reaches the standard during the day. The relevant mathematical expression is shown in Equation (14):

[0183]

[0184] Where: R target is the desired value of PAR per day to meet the growth requirements of the crops, is the transfer amount of the PAR level provided by artificial supplementary lighting in the t period, R PAR，t is the sum of the photosynthetically active radiation levels absorbed from natural light and artificial supplementary lighting in the t period.

[0185] In addition, considering characteristics such as the light saturation point and light compensation point, there are upper and lower limits for the PAR level absorbed by the crops in the t period. After transferring the agricultural supplementary lighting load, the power system should still ensure that the PAR absorbed by the crops in each period is between the light saturation point and the light compensation point, as shown in Equation (15):

[0186]

[0187] Where: are the PAR levels absorbed by the crops at the light saturation point and the light compensation point, respectively.

[0188] In addition, due to the design upper limit of the number of HPS in the greenhouse, the transferable photosynthetic photon flux density provided by artificial supplementary lighting in the t period is also restricted, as shown in Equation (16):

[0189]

[0190] Where: is the upper limit of the photosynthetic photon flux density that can be provided by the greenhouse, is the transfer amount of the artificial supplementary lighting intensity in the t period, η hps-PAR is the proportion of photosynthetically active radiation in the artificial supplementary lighting spectrum, R PAR，t is the sum of the photosynthetically active radiation levels absorbed from natural light and artificial supplementary lighting in the t period.

[0191] In this embodiment, by satisfying the expected value of photosynthetically active radiation date that meets the growth requirements of crops, ensuring that the photosynthetically active radiation absorbed by crops in each period is between the light saturation point and the light compensation point, and ensuring that the photosynthetic photon flux density provided by artificial supplementary lighting is within a predetermined range, it is possible to fully coordinate the source and load output on the premise of ensuring the healthy growth of crops, and then fully and effectively absorb new energy and reduce the total system operation cost.

[0192] In step D, according to the resource endowment of the agricultural microgrid, this embodiment constructs an optimal scheduling model for an independent agricultural microgrid considering the active frequency support of wind turbines and the load transfer of agricultural supplementary lighting. Its energy structure is as Figure 3 shown.

[0193] The energy structure of the agricultural microgrid includes not only power sources such as distributed wind turbines, rooftop photovoltaics, diesel engines, and energy storage devices, but also residential, agricultural, and industrial loads. Among them, the characteristics of agricultural residential and industrial loads are basically the same as those of urban residential and industrial loads. In this paper, they are classified as basic loads, and the agricultural loads that can better reflect agricultural characteristics, especially the supplementary lighting load with a relatively high proportion, are analyzed emphatically.

[0194] (1) Objective function

[0195] min{W e +W r +W w +W tl} (17)

[0196]

[0197] (2) Constraint conditions

[0198] In addition to the above system inertia demand constraint, the flexible reserve constraint of the wind turbine, and the load transfer constraint of the agricultural supplementary lighting, this embodiment further considers the following constraints:

[0199] 1) System power balance constraint

[0200]

[0201] In the formula: P g,t 、P w,t 、P v,t 、P s，t are the planned output of the gth diesel engine, the wth wind turbine, the vth photovoltaic unit, and the sth energy storage device at time t, respectively; P L,t is the basic load demand at time t; is the load transfer power.

[0202] 2) System frequency regulation reserve constraint

[0203]

[0204] In the formula: are the positive and negative frequency regulation reserves of the g-th diesel engine at time t, respectively; are the positive and negative frequency regulation reserves of the w-th wind turbine at time t, respectively; are the positive and negative frequency regulation reserves of the s-th energy storage device at time t, respectively; are the positive and negative frequency regulation reserve limits of the system at time t, respectively.

[0205] 3) Constraint on the output limit of the diesel engine

[0206]

[0207] In the formula: P g,t is the planned output of the g-th diesel engine at time t, is the rated power of the g-th diesel engine.

[0208] 4) Constraint on the frequency regulation reserve limit of the diesel engine

[0209]

[0210] 5) Constraint on the output limit of the wind turbine

[0211]

[0212] Among them, P w,t is the planned output of the w-th wind turbine at time t; is the maximum power prediction value of the w-th wind turbine at time t.

[0213] 6) Constraint on the output limit of the photovoltaic

[0214]

[0215] In the formula: P v,t is the planned output of the v-th photovoltaic unit at time t; is the maximum power prediction value of the v-th photovoltaic unit at time t.

[0216] 7) Constraint on the operating state of the energy storage

[0217]

[0218] In the formula: is a binary variable representing the charge / discharge state of the energy storage device.

[0219] 8) Constraint on the output limit of the energy storage

[0220]

[0221]

[0222] Wherein: are respectively the discharging and charging powers of the s-th energy storage device at time t; for the convenience of expression, an intermediate variable P is defined s,t As shown in Equation (16), is the rated power of the s-th energy storage device.

[0223] 9) Energy storage SOC constraint

[0224]

[0225]

[0226] Wherein: E s,t , SOC s,t are respectively the current energy and state of charge of the s-th energy storage device at time t; E s is the rated capacity of the s-th energy storage device; are respectively the upper and lower limits of the state of charge of the s-th energy storage device; SOC s,0 , SOC s,END are respectively the initial and final states of charge of the s-th energy storage device; α and η are respectively the self-discharge rate and charge-discharge efficiency of the energy storage, is the discharging power of the s-th energy storage device at time t; is the charging power of the s-th energy storage device at time t.

[0227] 10) Energy storage frequency regulation reserve limit constraint

[0228]

[0229] Taking the independent microgrid of a certain village and town as the research background, simulation modeling and example analysis are carried out in the MATLAB development environment. The greenhouse crops studied in this embodiment are light-loving plants, tomatoes.

[0230] The following conclusions are obtained through analysis:

[0231] 1. By introducing the virtual inertia support of new energy and energy storage, the present application significantly improves the rotational kinetic energy level of the system. This strategy not only does not limit the adjustable range of the unit, but also can maintain a lower maximum frequency change rate in the face of a larger N-1 fault disturbance. It can be seen that using wind turbines and energy storage devices to support the system through virtual inertia can effectively improve the rotational kinetic energy level of the system and enhance its ability to resist power disturbances.

[0232] 2. During frequent periods of wind curtailment such as low load periods, the system in this application effectively shares the frequency regulation pressure of diesel engines by utilizing the regulating capacity of wind turbines generated by passive wind curtailment. This further promotes the consumption of wind power and reduces the operating cost during this period. At the same time, during non-essential wind curtailment periods such as peak load periods, the system preferentially arranges the output of wind turbines instead of active load shedding, avoiding the unreasonable curtailment of wind energy and effectively suppressing the increase in operating costs. It can be seen that by providing frequency regulation reserve through flexible reserve constraints of wind turbines, the regulating space generated by passive wind curtailment can be effectively utilized, thereby reducing the total operating cost of the system and improving the utilization rate of wind power.

[0233] 3. On the premise of ensuring the healthy growth of crops, the model established in this invention is used to optimize the transfer of agricultural supplementary lighting load in this application. It can be seen that based on the energy consumption transfer constraint of the agricultural supplementary lighting load established in this article, the output of the power source and load can be fully coordinated on the premise of ensuring the healthy growth of crops, thereby fully and effectively consuming new energy and reducing the total operating cost of the system.

[0234] As Figure 4 shown, the present invention also provides a control device 300 for an independent microgrid system in an agricultural area, including:

[0235] A system inertia demand constraint determination module 310, configured to determine system inertia demand constraints based on the virtual inertia support of wind turbines and energy storage for the independent microgrid system;

[0236] A wind turbine flexible reserve constraint determination module 320, configured to determine wind turbine flexible reserve constraints based on the difference in characteristics between peak and valley load periods;

[0237] An agricultural supplementary lighting load transfer constraint determination module 330, configured to determine agricultural supplementary lighting load transfer constraints based on the lighting demand characteristics during the growth process of crops;

[0238] A target function construction module 340, configured to construct a target function based on the minimum sum of at least one of the power generation cost, frequency regulation reserve cost, wind turbine curtailment and negative frequency regulation reserve cost, and load transfer cost of the independent microgrid system; and

[0239] An optimal scheduling module 350, configured to perform optimal scheduling of the independent microgrid system according to the system inertia demand constraints, the wind turbine flexible reserve constraints, the agricultural supplementary lighting load transfer constraints, and the target function.

[0240] In the above embodiments, the descriptions of the various embodiments have their own emphases. For parts not detailed or recorded in a certain embodiment, reference may be made to the relevant descriptions of other embodiments.

[0241] Those of ordinary skill in the art can realize that the templates, units, and algorithm steps of the examples described in combination with the embodiments disclosed herein can be implemented in electronic hardware or in combination with computer software and electronic hardware. Whether these functions are executed in a hardware or software manner depends on the specific application and design constraints of the technical solution. Professional technicians can use different methods for each specific application to implement the described functions, but such implementation should not be considered to exceed the scope of the present invention.

[0242] If the module / unit is implemented in the form of 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, to implement all or part of the processes in the above-described embodiment methods of the present invention, it can also be completed by instructing relevant hardware through a computer program. The computer program can be stored in a computer-readable storage medium. When the computer program is executed by a processor, it can implement the steps of the above-described embodiments of each independent microgrid system control method. Among them, the computer program includes computer program code, and the computer program code can be in the form of source code, object code, executable file, or some intermediate form, etc. The computer-readable medium can include: any entity or device capable of carrying the computer program code, recording medium, USB flash drive, mobile hard disk, magnetic disk, optical disc, computer memory, read-only memory, random access memory, electrical carrier signal, telecommunication signal, and software distribution medium, etc.

[0243] The above-described 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 foregoing embodiments, those of ordinary skill in the art should understand that they can still modify the technical solutions recorded in the foregoing embodiments, or perform equivalent replacements for some of the technical features; and these modifications or replacements do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the embodiments of the present invention, and should all be included in the protection scope of the present invention.

Claims

1. A control method for an independent microgrid system in an agricultural area, characterized in that: include: Determining the system inertia demand constraint based on the virtual inertia support of the wind turbine and energy storage to the independent microgrid system; Based on the characteristics of load peak and valley periods, determine the flexible reserve constraints of wind turbines based on the wind abandonment level; Based on the characteristics of light demand during crop growth, determine the transfer constraints of agricultural lighting load; An objective function is constructed based on minimizing the sum of at least one of the power generation cost, the frequency regulation reserve cost, the wind turbine abandonment and negative frequency regulation reserve cost, and the load transfer cost of the independent microgrid system; as well as The independent microgrid system is optimally dispatched according to the system inertia demand constraint, the wind turbine flexible standby constraint, the agricultural supplementary lighting load transfer constraint and the objective function.

2. The control method for an independent microgrid system in an agricultural area according to claim 1, characterized in that: The optimizing and dispatching of the independent microgrid system according to the system inertia demand constraint, the wind turbine flexible standby constraint, the agricultural supplementary lighting load transfer constraint and the objective function includes: Under the constraints of the system inertia demand, the wind turbine flexible standby constraint and the agricultural lighting load transfer constraint, solving the objective function to obtain an optimal solution; Based on the optimal solution, the independent microgrid system is optimized and dispatched.

3. The control method for an independent microgrid system in an agricultural area according to claim 1, characterized in that: The determining of the system inertia demand constraint based on the virtual inertia support effect of the wind turbine and the energy storage on the independent microgrid system includes: Based on the rotational kinetic energy of the diesel engine, the rotational kinetic energy of the fan rotor and the energy reserve of the energy storage device, the total rotational kinetic energy E of the independent microgrid system at time t is calculated. sys，t , t≥0, Obtain the minimum rotational kinetic energy E required for the independent microgrid system under the maximum frequency change rate threshold lim ; According to E lim and E sys，t , determine that the system inertia requirement constraint satisfies the following formula: AND sys,t ≥E lim 。 4. The control method for an independent microgrid system in an agricultural area according to claim 3, characterized in that: The total rotational kinetic energy E of the independent microgrid system at time t is calculated based on the rotational kinetic energy of the diesel engine, the rotational kinetic energy of the fan rotor and the energy reserve of the energy storage device. sys，t ,include: E is calculated according to the following expression sys，t : Among them, E sys,t is the total rotational kinetic energy of the independent microgrid system at time t, t ≥ 0; represents the rotational kinetic energy of the diesel engine, represents the rotational kinetic energy of the fan rotor, Represents the energy reserve of the energy storage device, H g , H w , H s,t are the inertia time constant of the g-th diesel engine, the equivalent inertia time constant of the w-th fan, and the equivalent inertia time constant of the s-th energy storage device at time t, where g = 1...N G , w=1...N W , s=1...N S , where N G 、N W 、N S are the number of diesel engines, fans, and energy storage devices, respectively, N G 、N W 、N S are integers greater than 0 respectively; They are respectively the rated power of the g-th diesel engine, the maximum power prediction value of the w-th fan at time t, and the rated power of the s-th energy storage device.

5. The control method for an independent microgrid system in an agricultural area according to claim 3, characterized in that: The minimum rotational kinetic energy E required for the independent microgrid system to be obtained under the maximum frequency change rate threshold lim ,include: E is calculated according to the following expression lim : Among them, ΔP N-1 is the maximum power disturbance received by the independent microgrid system when N-1 fault occurs; f0 is the reference frequency of the independent microgrid system; It is the maximum frequency change rate threshold of the independent microgrid system.

6. The control method for an independent microgrid system in an agricultural area according to claim 1, characterized in that: The determination of the wind turbine flexible reserve constraint based on the wind abandonment level based on the characteristic difference of the load peak and valley periods includes: Determining the wind turbine flexible reserve constraint based on the wind abandonment level at least according to the load shedding rule of the wind turbine; The load reduction rules of the fan include: During the load trough period, the positive frequency regulation reserve capacity of the wind turbine is adjusted to the wind abandonment level; During peak load periods, reduce the pre-load reduction ratio of the fan; The sum of the fan rated output minus the positive and negative standby outputs is greater than or equal to the safe load reduction limit.

7. The control method for an independent microgrid system in an agricultural area according to claim 6, characterized in that: The wind turbine flexible standby constraint satisfies: in, are respectively the positive and negative frequency regulation standby of the wth wind turbine at time t; d max The maximum load reduction ratio of the fan under the premise of stable operation; P w,t For the planned output of the wth wind turbine at time t, is the predicted maximum power of the wth wind turbine at time t, t≥0, w=1...N W , N W is the number of fans, and w is an integer greater than 0.

8. The control method for an independent microgrid system in an agricultural area according to claim 1, characterized in that: The light requirement characteristics during the growth of the crop include light requirement conditions; The determination of agricultural lighting load transfer constraints based on the light demand characteristics during crop growth includes: Determine the agricultural lighting load transfer constraints based on the lighting demand conditions. The lighting requirement condition includes at least one of the following: Ensure that the level of photosynthetically active radiation absorbed by crops during period t reaches the expected daily value of photosynthetically active radiation that meets the growth requirements of crops; Ensure that the photosynthetically active radiation absorbed by crops during period t is between the light saturation point and the light compensation point; Ensure that the photosynthetic photon flux density provided by artificial lighting is within the predetermined range.

9. The control method for an independent microgrid system in an agricultural area according to claim 8, characterized in that: The agricultural lighting load transfer constraint satisfies at least one of constraint 1, constraint 2 and constraint 3: Constraint 1 satisfies: Among them, R target To meet the expected daily photosynthetic active radiation required for crop growth, R PAR，t is the sum of the photosynthetically active radiation levels absorbed from natural light and artificial supplementary light during period t, is the amount of photosynthetically active radiation transferred during period t provided by artificial supplementary lighting; Constraint 2 satisfies: in, are the levels of photosynthetically active radiation absorbed by crops at the light saturation point and light compensation point, respectively; Constraint 3 satisfies: in, is the upper limit of photosynthetic photon flux density that the greenhouse can provide, is the transfer amount of artificial lighting intensity during period t, η hps-PAR is the proportion of photosynthetically active radiation in the artificial light spectrum, R hps,t is the light intensity of artificial lighting during period t.

10. A control device for an independent microgrid system in an agricultural area, characterized in that: include: A system inertia demand constraint determination module is used to determine the system inertia demand constraint based on the virtual inertia support effect of the wind turbine and the energy storage on the independent microgrid system; A module for determining the flexible reserve constraint of wind turbines is used to determine the flexible reserve constraint of wind turbines based on the wind abandonment level based on the characteristic difference of load peak and valley periods; A module for determining agricultural supplementary lighting load transfer constraints is used to determine agricultural supplementary lighting load transfer constraints based on the characteristics of light demand during crop growth; Constructing an objective function module, for constructing an objective function based on minimizing the sum of at least one of the power generation cost, frequency regulation standby cost, wind turbine abandonment and negative frequency regulation standby cost, and load transfer cost of the independent microgrid system; as well as The optimization scheduling module is used to optimize the scheduling of the independent microgrid system according to the system inertia demand constraint, the wind turbine flexible standby constraint, the agricultural supplementary lighting load transfer constraint and the objective function.

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