Microgrid Energy Scheduling Method, System and Storage Medium Based on Energy Characteristics

Abstract

The present invention belongs to the field of microgrid scheduling, and particularly relates to a microgrid energy scheduling method, system and storage medium based on energy characteristics. The method first preprocesses the microgrid operation status, weather, gas consumption and load demand data, constructs a microgrid balance equation and predicts the load demand. Secondly, in combination with the microgrid status and the predicted load, the compensation demand is determined, and the wind-solar power output is predicted based on the weather. Thirdly, according to the compensation demand, the predicted wind-solar power output value and the energy cost, the output sequence of various types of energy is determined through an optimal output configuration model; finally, the priority is fed back to the microgrid control subsystem, and the energy devices are scheduled in real time by using a reinforcement scheduling control model to ensure that the microgrid remains balanced in real time. By introducing an optimized scheduling strategy based on energy characteristics, the present invention improves the utilization efficiency of the multi-energy system, enhances the stability and reliability of the microgrid, and reduces energy waste and pollutant emissions.

Description

Technical Field

[0001] The present invention belongs to the field of microgrid scheduling, and particularly relates to a microgrid energy scheduling method, system and storage medium based on energy characteristics. Background Art

[0002] As an important part of modern power systems, microgrids usually integrate multiple energy sources, such as solar energy, wind energy, energy storage devices, gas power generation, etc., to make up for the deficiencies in the power generation process of the main power generation energy in the microgrid. These energy sources have their own unique power generation characteristics. For example, solar energy is significantly affected by day-night changes, wind energy is greatly affected by wind speed changes, and gas power generation is stable but has high pollution and high cost. The differences in these energy characteristics increase the complexity of energy scheduling. How to effectively utilize the characteristics of different energy sources to optimize energy supply and maximize the efficiency and stability of the system has become a key issue in the field of microgrid energy scheduling.

[0003] For example, the patent with the publication number CN113300400A discloses a distributed microgrid scheduling method. First, it analyzes the structural composition of the microgrid and the economic and environmental requirements of each unit. Secondly, it establishes a microgrid energy management model based on the equal-cost incremental rate criterion, including the objective function and constraint conditions of microgrid energy management.

[0004] For example, the patent with the authorization publication number CN117318056B discloses a method and device for a virtual power plant participating in ancillary service regulation based on an interconnected microgrid. The method includes: considering the operating characteristics of distributed generation units, photovoltaic systems and energy storage systems, taking the minimum total operating cost of the day-ahead as the goal, establishing a day-ahead scheduling model for the virtual power plant to obtain the time-sharing reference electricity consumption and adjustable capacity of the virtual power plant; according to the real-time operating conditions, the power grid issues a regulation signal to the virtual power plant, and the virtual power plant distributes the regulation signal to the microgrid with the goal of minimizing the real-time total electricity cost; based on the distributed regulation signal, the microgrid takes the minimum total operating cost including the regulation deviation assessment cost, the power generation operating cost of distributed generation units and the operating cost of energy storage systems within the prediction time domain as the goal, establishes a real-time energy rolling optimization model for the microgrid, and obtains the optimal scheduling scheme for distributed generation units and energy storage systems.

[0005] The above existing technologies have the following problems: Most of the existing technologies only consider the grid scheduling balance, but do not give effective solutions to the scheduling and configuration problems of different types of supplementary energy under different working environments and electricity demands. Therefore, the present invention provides a microgrid energy scheduling method, system and storage medium based on energy characteristics. Summary of the Invention

[0006] In view of the deficiencies of the prior art, the present invention proposes a microgrid energy scheduling method, system and storage medium based on energy characteristics. The method first preprocesses the microgrid operation status, weather, gas consumption and load demand data, constructs a microgrid balance equation and predicts the load demand. Secondly, in combination with the microgrid status and the predicted load, the compensation demand is determined, and the wind-solar power output is predicted based on the weather. Thirdly, according to the compensation demand, the predicted wind-solar power output value and the energy cost, the output order of various types of energy is determined through an optimal output configuration model; finally, the priority is fed back to the microgrid control subsystem, and the energy device is scheduled in real time by using a reinforcement scheduling control model to ensure the balance of the microgrid while minimizing the total output cost; by introducing an optimized scheduling strategy based on energy characteristics, the present invention improves the utilization efficiency of the multi-energy system, enhances the stability and reliability of the microgrid, and reduces energy waste and pollution emissions.

[0007] To achieve the above object, the present invention provides the following technical solutions:

[0008] A microgrid energy scheduling method based on energy characteristics, the steps include:

[0009] S1. Obtain and preprocess historical microgrid operation status data, weather status data, gas consumption data and load demand data, use the preprocessed microgrid operation status data to construct a microgrid balance equation, and at the same time use the historical load demand data through a demand prediction model to obtain the predicted load demand;

[0010] S2. According to the microgrid operation status data, the microgrid balance equation and the predicted load demand, obtain the microgrid compensation demand, and at the same time use the obtained weather status data and the corresponding light energy and wind energy power generation data to obtain the wind-solar power output prediction values under different weather conditions through the constructed wind-solar power output prediction model;

[0011] S3. According to the obtained microgrid compensation demand, the wind-solar power output prediction value and the output costs corresponding to wind-solar-gas-storage, obtain the output priorities of different types of energy through the constructed optimal output configuration model;

[0012] The process of obtaining the output priorities of different types of energy is to judge whether wind power generation or solar power generation is in the optimal power generation interval according to the wind force level and radiation intensity, so as to decide whether to enable the wind or solar power generation device; when the wind force level and radiation intensity are in the optimal power generation interval, give priority to using wind or solar power generation, and switch or stop the power generation device in a timely manner according to the actual situation;

[0013] When the condition of the non-optimal power generation interval is met, by comprehensively considering the cost-benefit ratio and output power of wind power, solar power, energy storage devices and gas power generation, an optimal power generation combination is intelligently selected to meet the real-time needs of the microgrid;

[0014] S4. Feed the obtained output priorities of different types of energy back into the enhanced scheduling control model built in the microgrid control subsystem. According to the real-time microgrid compensation demand and the output priorities of different types of energy, dispatch the corresponding power generation devices to generate electricity so that the microgrid remains balanced in real time.

[0015] Specifically, the microgrid balance equation is specifically as follows:

[0016] ;

[0017] Among them, represents the load demand data at the current time t, represents the supply power value corresponding to the main output energy at the current time t, represents the power generation value corresponding to the wind power generation device configured in the microgrid at the current time t, represents the power generation value corresponding to the solar power generation device configured in the microgrid at the current time t, represents the power generation value corresponding to the gas power generation device configured in the microgrid at the current time t, The power value of the remaining power of the energy storage device configured in the microgrid at the current time t, is the microgrid compensation demand corresponding to the current time t.

[0018] Specifically, the wind-solar output prediction model includes a wind power output sub-model and a solar power output sub-model; the steps for constructing the wind power output sub-model include:

[0019] A1. Set the feasible interval of wind power levels corresponding to wind power generation according to the attribute parameters of the wind power generation device [ f c ， f d ] , obtain the power generation power per unit time corresponding to the wind power levels within the interval through the feasible interval of wind power levels, and preprocess the obtained data, where represents the lowest wind power level corresponding to the startup of the wind power generation device, is the maximum safe wind power level after the operation of the wind power generation device;

[0020] A2. Use the preprocessed wind power levels and the corresponding power generation power per unit time to construct a wind power level-power curve graph, and obtain the wind power supply-demand state change interval according to the wind power level-power curve graph, specifically:

[0021] { ∇ p t 1 ≥ 0 ， f t ∈ A ∇ p t 1 < 0 ， f t ∈ B A 、 B ∈ [ f c ， f d ] ;

[0022] Among them, represents the wind power level corresponding to the current time t, It represents the difference between the wind power generation power at the current moment \(t\) and the microgrid compensation demand corresponding to the current moment \(t\). \(A\) represents the wind force level interval that satisfies ; \(B\) represents the wind force level interval that satisfies ;

[0023] A3. Obtain the electricity price at the current moment and the cost consumed by the operating wind power generation device per unit time at each wind force level. Using the obtained electricity price at the current moment, the power generation power per unit time, and the cost consumed per unit time, obtain the wind force level intervals under different wind power generation profit deviations [ f a ， f b ] , specifically:

[0024] ∇ q 1 = p ¯ f × q t − q ¯ f { ∇ q 1 > 0 ， f t ∈ [ f a ， f b ] ⊆ [ f c ， f d ] ∇ q 1 ≤ 0 ， f t ∉ [ f a ， f b ] ⊆ [ f c ， f d ] Shutdown, f t ∉ [ f c ， f d ] ;

[0025] Among them, represents the wind power generation profit deviation value at the current moment, represents the average power of wind power generation per unit time at the same wind force level, represents the electricity price corresponding to the current moment \(t\), represents the consumption cost corresponding to the wind power generation device at the \(f\)-th wind force level per unit time, and represent the lower limit and upper limit of the wind force level interval corresponding to the positive wind power generation profit deviation in sequence;

[0026] A4. Align the variable with the wind force level as the horizontal axis, and map the obtained to the corresponding coordinate axes of the wind force level - power curve graph through a double Y-axis line graph, and obtain the wind force level - wind power generation profit deviation curve and the optimal wind power generation level interval that simultaneously satisfies , where C = A ∩ [ f a ， f b ] represents the intersection symbol, and & represents the "and" symbol;

[0027] A5. Obtain the electricity price and wind force level in real time to update the wind force level - wind power generation profit deviation curve and the optimal level power generation interval in real time, and obtain the wind power generation output power value at the current moment, and the wind force level intervals under different power generation profit deviations from the updated double Y-axis line graph including the wind force level - power curve and the wind force level - wind power generation profit deviation curve.

[0028] Specifically, the construction steps of the solar power output sub-model include:

[0029] B1. Obtain the solar radiation intensity and the corresponding power generation power data, and segment the obtained data with a two-hour segment interval;

[0030] B2. Construct a radiation intensity-power fluctuation curve based on the segmented radiation intensity and the corresponding power generation, and at the same time, use the radiation intensity and the corresponding power generation to obtain a radiation intensity-power fitting function through a support vector machine, and map the fitting function onto the radiation intensity-power fluctuation curve;

[0031] B3. According to the radiation intensity-power fitting function and the radiation intensity-power fluctuation curve, obtain the radiation supply-demand intervals D and E corresponding to the radiation intensity-power through the process of obtaining the power state change interval in A2, where D represents the radiation intensity interval corresponding to when satisfied, and E represents the radiation intensity interval corresponding to when satisfied; where represents the difference between the solar power generation at the current time t and the compensation demand of the microgrid at the current time t;

[0032] B4. According to the power value at the corresponding time on the radiation intensity-power fluctuation curve and the consumption cost corresponding to the solar power generation device per unit time, obtain the current solar power generation output power value, the radiation intensity level interval under different solar power generation profit deviations, the radiation intensity-solar power generation profit deviation curve, and the corresponding optimal solar power generation radiation intensity interval through the same process as in A3 - A5 where is the solar power generation profit deviation value at the current time. Among them, the radiation intensity interval under the solar power generation profit deviation is specifically:

[0033] ∇ q 2 = p ¯ g × q t − q 0 { ∇ q 2 > 0 ， g t > g 2 ∇ q 2 ≤ 0 ， g t ∈ [ g 1 ， g 2 ] Shutdown, g t < g 1 ;

[0034] Among them, represents the solar power generation profit deviation value at the current time, represents the average power of solar power generation per unit time under the same radiation intensity, represents the radiation intensity corresponding to the current time t, represents the cost consumed by the operation of the solar power generation device per unit time, represents the minimum radiation intensity required to start the solar power generation device, represents the corresponding radiation intensity;

[0035] B5. Based on the same process as in B3 and B4, obtain the output power corresponding to the gas and energy storage devices per unit time and and the power generation profit deviation value , represents the power value output corresponding to the gas power generation process per unit time, represents the power value output by the energy storage device per unit time, It indicates the profit deviation value corresponding to the gas power generation process per unit time.

[0036] Specifically, the steps of obtaining the output priorities of different types of energy include:

[0037] C1. According to the microgrid compensation demand, wind level and radiation intensity obtained at the current moment, if the wind level and radiation intensity at the current moment are both in the corresponding optimal wind power generation level interval and optimal solar power generation radiation intensity interval, then according to the obtained wind level-power curve and wind level-wind power generation profit deviation curve and radiation intensity-power fluctuation curve and radiation intensity-solar power generation profit deviation curve, obtain the duration of the optimal wind power generation level interval and the optimal solar power generation radiation intensity interval corresponding to the wind power generation and solar power generation at the current moment. and ,in Indicates the duration of the optimal wind power generation level interval. Indicates the duration of the optimal solar power generation radiation intensity interval;

[0038] C2. If , only wind power generation equipment is selected for supplementary power generation, and the wind power generation meets the requirements according to the wind level-power curve. The corresponding time point , and according to the radiation intensity-power fluctuation curve, the arrival The power generation interval state of solar energy at the moment, if the interval state of solar energy at the current moment satisfies , then stop the wind power generation device and directly call on the solar power generation device for supplementary power generation;

[0039] C3. If the interval state corresponding to the solar energy at the current moment satisfies , then when arriving At this moment, the solar power generation device is directly dispatched to make up for the power shortage of the wind power generation device at the current moment, until the wind power generation device meets the demand again. When the solar power generation device is stopped, represents the wind power value at the current time t, Indicates the solar power generation value at the current time t.

[0040] Specifically, the step of obtaining the output priorities of different types of energy also includes:

[0041] C4, if satisfied When the microgrid compensation demand is met, the corresponding output power of the energy storage device and the gas-fired power generation is judged. , stop the wind power generation device and the solar power generation device, and directly dispatch the energy storage device to supplement the missing part of the power;

[0042] C5. If or at this time, stop the solar power generation device, and directly dispatch the energy storage device to supplement the missing part of the power of the wind power generation device;

[0043] C6. If and at this time, then judge whether the gas power generation at the current moment meets the condition. If it meets, stop the wind power and solar power generation devices, and directly dispatch the gas power generation device to supplement the microgrid compensation demand;

[0044] C7. If it does not meet, make a secondary judgment. If the gas power generation device meets and but does not meet at this time, stop the solar power generation device, and dispatch the gas power generation device to supplement the missing part of the power of the wind power generation device.

[0045] Specifically, the steps of obtaining the output priority of different types of energy also include:

[0046] C8. When the gas power generation device does not meet , then judge the output power status of the wind power, solar power and energy storage devices according to the process of C2-C5, and dispatch a single or hybrid energy power generation device to supplement the missing part of the microgrid compensation demand. If the output powers of the wind power, solar power and energy storage devices at the current moment cannot meet the microgrid compensation demand at the same time, then dispatch the gas power generation device to supplement the power jointly missing by the wind power, solar power and energy storage devices;

[0047] C9. When the sum of the output powers of the wind power, solar power, energy storage device and gas power generation device is greater than the microgrid compensation demand after the gas power generation device is started, then make a combination according to the obtained at the current moment, so that the sum of the profit deviations after the combination is minimized while meeting the microgrid compensation demand, and turn off the power generation devices corresponding to the uncombined ones.

[0048] Specifically, the steps of obtaining the output priority of different types of energy also include:

[0049] C10. If , then determine the dispatch priority corresponding to each power generation device according to the same process of C2-C9;

[0050] C11. If , then according to the and Compare. If then give priority to scheduling the wind power generation device. Otherwise, give priority to scheduling the solar power generation device, and determine the scheduling priorities of the remaining power generation devices according to the same process of C2 - C9;

[0051] C12. If only wind power generation is in the optimal wind power generation level range or solar energy is in the optimal solar power generation radiation intensity range at the current moment, then select the energy corresponding to the optimal range to supplement the missing compensation demand of the microgrid, and repeat the same process of C2 - C9 to schedule the power generation devices corresponding to the remaining energy types;

[0052] C13. When neither wind power generation nor solar power generation is in the corresponding optimal wind power generation level range and optimal solar power generation radiation intensity range, then combine according to the corresponding to wind power generation, solar power generation and gas power generation, and minimize the sum of profit deviations after combination while meeting the microgrid compensation demand. If the sum of the output powers of wind power generation, solar power generation and gas power generation is less than the microgrid compensation demand, then schedule the energy storage device to make up for the common missing power of wind power generation, solar power generation and gas power generation, so that the microgrid can satisfy the microgrid balance equation in real time.

[0053] The microgrid energy scheduling system based on energy characteristics includes: a data processing module, an output analysis module, a configuration optimization module and an energy scheduling module;

[0054] The data processing module is used to obtain the microgrid operation status data, weather status data, gas consumption data and load demand data, and preprocess the obtained data;

[0055] The output analysis module includes a balance equation unit, a load demand prediction unit and a power prediction unit;

[0056] The balance equation unit is used to construct the microgrid balance equation by using the preprocessed microgrid operation status data;

[0057] The load demand prediction unit is used to obtain the predicted load demand prediction value through the demand prediction model according to the historical load demand data, and obtain the microgrid compensation demand corresponding to the current moment by using the constructed microgrid balance equation;

[0058] The power prediction unit is used to obtain the wind - light output prediction values under different weather conditions by using the obtained weather status data and the corresponding light and wind power generation data through the constructed wind - light output prediction model;

[0059] The configuration optimization module obtains the output priorities of different types of energy through the optimal output configuration model according to the microgrid compensation demand, wind - light output prediction values and the output costs of different energy types;

[0060] The process of obtaining the output priority of different types of energy is to determine whether wind power generation or solar power generation is in the optimal power generation range based on the wind level and radiation intensity, so as to decide whether to activate the wind or solar power generation device; when the wind level and radiation intensity are in the optimal power generation range, wind or solar power is preferentially utilized, and the power generation device is switched or stopped in a timely manner according to the actual situation;

[0061] When the condition of the non-optimal power generation range is met, by comprehensively considering the cost-benefit ratio and output power of wind power, solar power, energy storage devices and gas power generation, the optimal power generation combination is intelligently selected to meet the real-time demand of the microgrid;

[0062] The energy scheduling module is used to, according to the obtained compensation demand quantity and the output priority of different types of energy, through the built-in enhanced scheduling control model, schedule the corresponding power generation device to generate power so that the microgrid remains balanced in real time.

[0063] A computer-readable storage medium, characterized in that computer instructions are stored thereon, and when the computer instructions run, the microgrid energy scheduling method based on energy characteristics is executed.

[0064] Compared with the prior art, the beneficial effects of the present invention are:

[0065] In view of the deficiencies of the prior art, by comprehensively analyzing the historical operating state of the microgrid, weather state, gas consumption and load demand data, the present invention not only constructs a microgrid balance equation, but also obtains the predicted load demand quantity by using a demand prediction model. Among them, through a wind-solar output prediction model, the output values of wind energy and light energy are predicted under different weather conditions, and combined with the output costs of wind-light-gas-storage, an optimal output configuration model is constructed, so as to determine the output priority of different types of energy; finally, the output priority is fed back to the enhanced scheduling control model of the microgrid control subsystem, and the power generation device is scheduled according to the real-time compensation demand quantity and output priority, realizing the real-time balance and the lowest output cost of the microgrid; in summary, the present invention provides an effective solution for the supplementary energy scheduling configuration under different working environments and power consumption demands, improving the operation efficiency and economy of the microgrid. BRIEF DESCRIPTION OF THE DRAWINGS

[0066] Figure 1 It is a flowchart of the microgrid energy scheduling method based on energy characteristics according to Embodiment 1 of the present invention;

[0067] Figure 2 It is a module diagram of the microgrid energy scheduling system based on energy characteristics according to Embodiment 2 of the present invention. DETAILED DESCRIPTION OF THE INVENTION

[0068] Embodiment 1

[0069] Please refer to Figure 1 , an embodiment provided by the present invention: a microgrid energy scheduling method based on energy characteristics, the steps include:

[0070] S1. Obtain and preprocess historical microgrid operation status data, weather status data, gas consumption data and load demand data, construct a microgrid balance equation using the preprocessed microgrid operation status data, and at the same time obtain the predicted load demand through a demand prediction model using historical load demand data;

[0071] Furthermore, the microgrid balance equation in this embodiment is specifically:

[0072] ;

[0073] Wherein, represents the load demand data at the current time t, represents the supply power value corresponding to the main output energy at the current time t. Here, the main output energy corresponds to the supply of the main power grid for the load demand, such as an external power generation network; represents the power generation value corresponding to the wind power generation device configured in the microgrid at the current time t, represents the power generation value corresponding to the solar power generation device configured in the microgrid at the current time t, represents the power generation value corresponding to the gas power generation device configured in the microgrid at the current time t, The power value of the remaining power of the energy storage device configured in the microgrid at the current time t.

[0074] Furthermore, the demand prediction model in this embodiment is obtained by constructing through the random forest algorithm;

[0075] The specific steps for obtaining the predicted load demand include:

[0076] S101. Obtain historical load demand data with a time length of one year and preprocess the obtained data;

[0077] S102. Obtain the load demand change rate according to the obtained historical load demand data, input the obtained load demand change rate into the clustering algorithm to obtain the months with the same demand change trend, and use the average value of the load demand change rates corresponding to the months with the same demand change trend as the seasonal factor for the months with the same demand change trend;

[0078] S103. Input the obtained historical load demand data and the obtained seasonal factor into the demand prediction model for training to obtain the trained demand prediction model;

[0079] S104. Obtain the historical load demand data corresponding to the 15 days before the prediction day, and input the obtained historical load demand data into the trained demand prediction model to obtain the load demand corresponding to the next 12 hours.

[0080] S2. Obtain the microgrid compensation demand according to the microgrid operation state data, the microgrid balance equation, and the predicted load demand. At the same time, use the obtained weather state data and the corresponding light energy and wind energy generation data, and through the constructed wind-light output prediction model, obtain the wind-light output prediction values under different weather states;

[0081] Furthermore, the microgrid compensation demand in this embodiment is , which is the microgrid compensation demand corresponding to the current moment t;

[0082] Furthermore, the wind-light output prediction model in this embodiment includes a wind power output sub-model and a solar power output sub-model; among them, the steps for constructing the wind power output sub-model include:

[0083] A1. Set the feasible interval of wind levels corresponding to wind power generation according to the attribute parameters of the wind power generation device [ f c ， f d ] , obtain the power generation power per unit time corresponding to the wind levels within the interval through the feasible interval of wind levels, and preprocess the obtained data, where represents the lowest wind level corresponding to the startup of the wind power generation device, is the maximum safe wind level corresponding after the wind power generation device operates;

[0084] Furthermore, the lowest wind level corresponding to the startup of the wind power generation device and the maximum safe wind level corresponding after the wind power generation device operates in this embodiment are specifically set by those skilled in the art according to the attribute parameters of the corresponding wind power generation device.

[0085] A2. Use the preprocessed wind levels and the corresponding power generation power per unit time to construct a wind level-power curve graph, and according to the wind level-power curve graph, obtain the wind supply-demand state change interval, specifically:

[0086] { ∇ p t 1 ≥ 0 ， f t ∈ A ∇ p t 1 < 0 ， f t ∈ B A 、 B ∈ [ f c ， f d ] ;

[0087] Among them, represents the wind level corresponding to the current moment t, represents the difference between the wind power generation power at the current moment t and the microgrid compensation demand corresponding to the current moment t, and A represents satisfying The wind force level range, that is, the power generation power corresponding to the wind force level at the current moment can meet the compensation demand of the corresponding microgrid at the current moment; B represents meeting The wind force level range; that is, the power generation power corresponding to the wind force level at the current moment cannot meet the compensation demand of the corresponding microgrid at the current moment;

[0088] A3. Obtain the electricity price at the current moment and the cost consumed by the wind power generation device per unit time at each wind force level. Using the obtained electricity price at the current moment, the power generation power per unit time, and the cost consumed per unit time, obtain the wind force level range under different wind power generation profit deviations [ f a ， f b ] , specifically:

[0089] ∇ q 1 = p ¯ f × q t − q ¯ f { ∇ q 1 > 0 ， f t ∈ [ f a ， f b ] ⊆ [ f c ， f d ] ∇ q 1 ≤ 0 ， f t ∉ [ f a ， f b ] ⊆ [ f c ， f d ] Shutdown, f t ∉ [ f c ， f d ] ;

[0090] Among them, represents the wind power generation profit deviation value at the current moment, represents the average power of wind power generation per unit time at the same wind force level, represents the electricity price corresponding to the current t moment, represents the consumption cost corresponding to the wind power generation device at the f-th wind force level per unit time, and respectively represent the lower limit and upper limit of the wind force level range corresponding to the positive wind power generation profit deviation; represents the symbol of inclusion;

[0091] A4. Align the variable with the wind force level as the horizontal axis, and map the obtained to the coordinate axis corresponding to the wind force level-power curve through a double Y-axis line graph, and obtain the wind force level-wind power generation profit deviation curve and the optimal wind power generation level range that simultaneously meet C = A ∩ [ f a ， f b ] , where represents the intersection symbol, and & represents the "and" symbol;

[0092] A5. Obtain the electricity price and wind force level in real time to update the wind force level-wind power generation profit deviation curve and the optimal level power generation range in real time, and obtain the wind power generation output power value at the current moment from the updated double Y-axis line graph including the wind force level-power curve and the wind force level-wind power generation profit deviation curve, and the wind force level range under different power generation profit deviations.

[0093] Furthermore, the construction steps of the solar power output sub-model include:

[0094] B1. Obtain the solar radiation intensity and corresponding power generation data, and segment the obtained data with a two-hour interval as the segmentation range.

[0095] B2. Based on the segmented radiation intensity and corresponding power generation, construct a radiation intensity-power fluctuation curve. At the same time, use the radiation intensity and corresponding power generation, through the support vector machine, obtain a radiation intensity-power fitting function, and map the fitting function to the radiation intensity-power fluctuation curve.

[0096] B3. According to the radiation intensity-power fitting function and the radiation intensity-power fluctuation curve, through the process of obtaining the power state change interval in A2, obtain the radiation supply-demand intervals D and E corresponding to the radiation intensity-power, where D represents the radiation intensity interval corresponding to when satisfied, and E represents the radiation intensity interval corresponding to when satisfied; where represents the difference between the solar power generation at the current t moment and the compensation demand of the microgrid at the current t moment.

[0097] B4. According to the power value at the corresponding moment on the radiation intensity-power fluctuation curve and the consumption cost corresponding to the solar power generation device per unit time, through the same process as A3 - A5, obtain the current solar power generation output power value, the radiation intensity level intervals under different solar power generation profit deviations, the radiation intensity-solar power generation profit deviation curve, and the corresponding optimal solar power generation radiation intensity interval where is the solar power generation profit deviation value at the current moment. Among them, the radiation intensity interval under the solar power generation profit deviation is specifically:

[0098] ∇ q 2 = p ¯ g × q t − q 0 { ∇ q 2 > 0 ， g t > g 2 ∇ q 2 ≤ 0 ， g t ∈ [ g 1 ， g 2 ] Shutdown, g t < g 1 ;

[0099] Among them, represents the solar power generation profit deviation value at the current moment, represents the average power of solar power generation per unit time under the same radiation intensity, represents the radiation intensity corresponding to the current t moment, represents the cost consumed by the operation of the solar power generation device per unit time, represents the minimum radiation intensity required to start the solar power generation device, represents the corresponding radiation intensity;

[0100] B5. Based on the same process as B3 and B4, obtain the corresponding output power per unit time of the gas and energy storage devices and the power generation profit deviation value , It represents the power value corresponding to the power generation process of the gas per unit time. It represents the power value output by the energy storage device per unit time. It represents the profit deviation value corresponding to the power generation process of the gas per unit time.

[0101] The wind power output sub-model of this process pre-defines the optimal operating range of wind power generation by setting the feasible interval of wind power levels and combining the attribute parameters of wind power generation devices. Secondly, by using the wind power level-power curve, it can clearly show the power generation capacity under different wind power levels, and further optimize the power generation strategy through the wind power level-wind power generation profit deviation curve to ensure the maximization of economic benefits while meeting the compensation requirements of the microgrid. At the same time, the solar power output sub-model processes the radiation intensity data in segments, uses the support vector machine technology to fit the relationship between the radiation intensity and the power generation power, and can also predict the solar power generation according to the radiation intensity, and determine the optimal power generation plan through the profit deviation analysis; during the whole process, by real-time updating parameters such as electricity price, wind power level and radiation intensity, the system can dynamically adjust the power generation strategy to ensure that the cost-effective optimal energy combination can be found under various conditions; in addition, this method also considers the output power and profit deviation of the gas and the energy storage device, enabling the entire microgrid system to comprehensively consider various energy forms, realize more flexible and efficient energy scheduling and management, and thus improve the overall operating efficiency and economy of the microgrid.

[0102] S3. According to the obtained microgrid compensation demand, wind-solar power output prediction values and the output costs corresponding to wind-solar-gas-energy storage, through the constructed optimal output configuration model, obtain the output priorities of different types of energy.

[0103] Furthermore, the steps of obtaining the output priorities of different types of energy in this embodiment include:

[0104] C1. According to the microgrid compensation demand, wind power level and radiation intensity obtained at the current moment, if the wind power level and radiation intensity at the current moment are both in the corresponding optimal wind power generation level interval and the optimal solar power generation radiation intensity interval, then according to the obtained wind power level-power curve, wind power level-wind power generation profit deviation curve, radiation intensity-power fluctuation curve and radiation intensity-solar power generation profit deviation curve, obtain the duration corresponding to the current moment of wind power generation and solar power generation in the corresponding optimal wind power generation level interval and the optimal solar power generation radiation intensity interval and , where represents the duration corresponding to the optimal wind power generation level interval, represents the duration corresponding to the optimal solar power generation radiation intensity interval;;

[0105] C2. If , only the wind power generation device is selected for supplementary power generation. At the same time, according to the wind power level-power curve, the time point corresponding to when the wind power generation meets is obtained. , and according to the radiation intensity-power fluctuation curve, the power generation interval state corresponding to solar energy at the moment is obtained. If the interval state corresponding to solar energy at the current moment meets , the wind power generation device is stopped, and the solar power generation device is directly called for supplementary power generation;

[0106] C3. If the interval state corresponding to solar energy at the current moment meets , then when reaching the moment, the solar power generation device is directly dispatched to make up the power shortage of the wind power generation device at the current moment until the wind power generation device meets again, and the solar power generation device is stopped; where represents the wind power generation power value at the current t moment, represents the solar power generation power value at the current t moment;

[0107] C4. If it meets when, then the microgrid compensation demand is judged against the power output corresponding to the energy storage device and the gas power generation. If it meets , the wind power generation device and the solar power generation device are stopped, and the energy storage device is directly dispatched to make up the missing part of the power;

[0108] C5. If or when, then the solar power generation device is stopped, and the energy storage device is directly dispatched to make up the missing part of the power of the wind power generation device;

[0109] C6. If and when, then it is judged whether the gas power generation at the current moment meets condition. If it meets, the wind and solar power generation devices are stopped, and the gas power generation device is directly dispatched to supplement the microgrid compensation demand;

[0110] C7. If it does not meet, a secondary judgment is made. If the gas power generation device meets and but does not meet , the solar power generation device is stopped, and the gas power generation device is dispatched to make up the missing part of the power of the wind power generation device;

[0111] C8. When the gas power generation device does not meet , then judge the output power status of wind power, solar energy and energy storage devices according to the C2-C5 process, and dispatch single or hybrid energy generation devices to make up for the shortage of the compensation demand of the microgrid. If the output powers of wind power, solar energy and energy storage devices cannot meet the compensation demand of the microgrid at the current moment, dispatch the gas power generation device to supplement the power jointly missing by wind power, solar energy and energy storage devices, so that the microgrid remains balanced in real time;

[0112] C9. When the sum of the output powers of the wind power, solar energy, energy storage device and gas power generation device is greater than the compensation demand of the microgrid after the gas power generation device is started, then according to the obtained at the current moment for combination, while meeting the compensation demand of the microgrid, make the sum of the profit deviations after combination the smallest, and turn off the power generation devices corresponding to those not participating in the combination; for example, when the sum of the corresponding power outputs of the wind power and gas power generation devices meets the compensation demand of the microgrid and the corresponding sum is the smallest, then turn off the solar power generation device and the energy storage device;

[0113] C10. If , then according to the same process of C2-C9, determine the scheduling priority corresponding to each type of power generation device; that is, only select the solar power generation device for supplementary power generation, and at the same time obtain the time point corresponding to when the wind power generation meets according to the radiation intensity-power curve graph, and according to the wind power level-power fluctuation curve, obtain the power generation interval state corresponding to the wind power level at the moment of reaching . If the interval state corresponding to the wind power at the current moment meets , then stop the solar power generation device, directly call the wind power generation device for supplementary power generation, and judge and dispatch the remaining power generation devices through the C3-C9 process, so that the microgrid remains balanced in output in real time;

[0114] C11. If , then compare according to the and corresponding to the wind power generation and solar power generation at the current moment. If , then give priority to dispatching the wind power generation device, otherwise give priority to dispatching the solar power generation device, and determine the scheduling priority of the remaining power generation devices according to the same process of C2-C9;

[0115] C12. If only the wind power generation is in the optimal wind power generation level interval or the solar energy is in the optimal solar energy radiation intensity interval at the current moment, then select the energy corresponding to the optimal interval to make up for the shortage of the compensation demand of the microgrid, and repeat the same process of C2-C9 to dispatch the power generation devices corresponding to the remaining energy types;

[0116] ​C13. When neither wind power generation nor solar power generation is within the corresponding optimal wind power generation level range and the optimal solar power generation radiation intensity range, then according to the combinations are made to minimize the sum of profit deviations after combination while meeting the microgrid compensation demand. If the sum of the output powers of wind power generation, solar power generation, and gas power generation is less than the microgrid compensation demand, the energy storage device is dispatched to make up for the common missing power of wind power generation, solar power generation, and gas power generation, so that the microgrid always meets the microgrid balance equation.

[0117] In this process, by constructing an optimal output configuration model, the output priorities of different types of energy are refined, so as to effectively respond to the microgrid compensation demand; this process first judges whether it is in the optimal power generation interval according to the wind level and radiation intensity, so as to decide whether to activate the wind or solar power generation device; when the conditions are met, wind or solar power generation is preferentially used, and the power generation device is switched or stopped in a timely manner according to the actual situation to ensure the continuity and economy of power supply; for non-optimal power generation conditions, the system intelligently selects the most suitable power generation combination to meet the real-time needs of the microgrid by comprehensively considering the cost-benefit ratios of wind power, solar power, energy storage devices, and gas power generation; when gas power generation becomes necessary, the model will further evaluate the total profit deviation of the combination of gas power generation and other energy sources and select the plan with the best cost-benefit; finally, whether it is a single or hybrid energy power generation plan selection, it is committed to minimizing the overall power generation cost while meeting the microgrid compensation demand; this method not only optimizes the energy utilization efficiency, reduces unnecessary energy waste and pollution emissions caused by gas power generation, but also improves the stability and reliability of the microgrid operation, thus providing users with higher-quality and more stable power services.

[0118] S4. Feed back the obtained output priorities of different types of energy into the enhanced scheduling control model built in the microgrid control subsystem, and dispatch the corresponding power generation device to generate power according to the real-time microgrid compensation demand and the output priorities of different types of energy, so that the microgrid always maintains balance.

[0119] Furthermore, in this embodiment, the output priorities of different types of energy are determined according to the scheduling process of the corresponding power generation device in the C1-C13 process; for example, from the C1-C9 process, it can be obtained that the scheduling priority of the wind power generation device is the highest, and the scheduling priorities of the solar energy, energy storage device, and gas device are specifically scheduled according to the corresponding discrimination conditions, which will not be elaborated here.

[0120] Embodiment 2

[0121] Please refer to Figure 2, Another embodiment provided by the present invention: A microgrid energy scheduling system based on energy characteristics, comprising: a data processing module, an output analysis module, a configuration optimization module, and an energy scheduling module;

[0122] The data processing module is used to obtain the microgrid operation status data, weather status data, gas consumption data, and load demand data, and preprocess the obtained data;

[0123] The output analysis module is used to construct a microgrid balance equation and obtain the load demand prediction value and the output prediction value of wind-solar power generation through prediction; The output analysis module includes a balance equation unit, a load demand prediction unit, and a power prediction unit; The balance equation unit is used to construct a microgrid balance equation by using the preprocessed microgrid operation status data; The load demand prediction unit is used to obtain the predicted load demand value for the next 12 hours through a demand prediction model based on historical load demand data, and obtain the microgrid compensation demand corresponding to the current moment by using the constructed microgrid balance equation;

[0124] The power prediction unit is used to obtain the wind-solar output prediction value under different weather conditions by using the obtained weather status data and the corresponding solar and wind power generation data through the constructed wind-solar output prediction model;

[0125] The configuration optimization module, according to the microgrid compensation demand, the wind-solar output prediction value, and the output cost of different energy types, obtains the output priority of different types of energy through an optimal output configuration model;

[0126] The energy scheduling module is used to dispatch the corresponding power generation device to generate electricity according to the compensation demand and the output priority of different types of energy through the built-in enhanced scheduling control model, so that the microgrid remains balanced in real time.

[0127] Embodiment 3

[0128] A computer-readable storage medium, on which computer instructions are stored, and when the computer instructions run, they execute the microgrid energy scheduling method based on energy characteristics.

[0129] An electronic device, comprising a memory and a processor, the memory stores a computer program, and when the processor executes the computer program, it implements the microgrid energy scheduling method based on energy characteristics.

[0130] The embodiments of the present invention have been described above in conjunction with the accompanying drawings. However, the present invention is not limited to the above specific embodiments. The above specific embodiments are merely illustrative and not restrictive. Under the inspiration of the present invention, those of ordinary skill in the art can also make changes, modifications, substitutions, and variations to the above embodiments without departing from the spirit of the present invention and the scope protected by the claims. All of these fall within the protection scope of the present invention.

Claims

1. A microgrid energy dispatching method based on energy characteristics, characterized in that: include: S1. Obtain and preprocess historical microgrid operation status data, weather status data, gas consumption data and load demand data, use the preprocessed microgrid operation status data to build a microgrid balance equation, and use the historical load demand data through a demand forecasting model to obtain the predicted load demand; S2. According to the microgrid operation status data, the microgrid balance equation and the predicted load demand, the microgrid compensation demand is obtained. At the same time, the obtained weather status data and the corresponding solar and wind power generation data are used to obtain the wind-solar output prediction value under different weather conditions through the constructed wind-solar output prediction model; S3. Based on the obtained microgrid compensation demand, wind-solar output forecast value and the output cost corresponding to wind-solar-fuel-storage, the output priority of different types of energy is obtained through the constructed optimal output configuration model; The process of obtaining the output priority of different types of energy is to determine whether wind power generation or solar power generation is in the optimal power generation range based on the wind level and radiation intensity, so as to decide whether to enable the wind or solar power generation device; when the wind level and radiation intensity are in the optimal power generation range, wind power or solar power generation is used first, and the power generation device is switched or stopped in time according to the actual situation; When the power generation range is not optimal, the cost-effectiveness and output power of wind, solar, energy storage and gas-fired power generation are comprehensively considered to intelligently select the optimal power generation combination to meet the real-time needs of the microgrid. S4. Feedback the output priorities of different types of energy into the enhanced dispatching control model built into the microgrid control subsystem. According to the real-time microgrid compensation demand and the output priorities of different types of energy, dispatch the corresponding power generation devices to generate electricity so that the microgrid can maintain real-time balance.

2. The microgrid energy scheduling method based on energy characteristics according to claim 1, characterized in that: The microgrid balance equation is specifically: ； in, represents the load demand data at the current time t, Indicates the supply power value corresponding to the main output energy at the current time t, represents the power generation value corresponding to the wind power generation device configured in the microgrid at the current time t, It represents the power generation value corresponding to the solar power generation device configured in the microgrid at the current time t, It represents the power generation value corresponding to the gas power generation device configured in the microgrid at the current time t, The power value of the remaining power of the energy storage device configured in the microgrid at the current time t, is the microgrid compensation demand corresponding to the current time t.

3. The microgrid energy scheduling method based on energy characteristics as claimed in claim 2, characterized in that: The wind-solar output prediction model includes a wind output sub-model and a solar output sub-model; the steps of constructing the wind output sub-model include: A1. Set the feasible interval of wind power level corresponding to wind power generation according to the attribute parameters of the wind power generation device , the power generation per unit time corresponding to the wind force level in the feasible interval of the wind force level is obtained, and the obtained data is preprocessed, where Indicates the minimum wind speed level corresponding to the start of the wind power generation device. It is the maximum safe wind force level corresponding to the operation of the wind power generation device; A2. Use the pre-processed wind force level and the corresponding power generation per unit time to construct a wind force level-power curve. According to the wind force level-power curve, obtain the wind power supply-demand state change interval, specifically: ； in, Indicates the wind force level corresponding to the current time t, It represents the difference between the wind power generation at the current time t and the microgrid compensation demand corresponding to the current time t, and A represents the satisfaction Wind force level range; B means meeting Wind force level range; A3. Obtain the current electricity price and the cost of operating the wind power generation device per unit time at each wind power level. Use the current electricity price, power generation per unit time and cost per unit time to obtain the wind power level range under different wind power generation profit deviations. , specifically: ； in, Indicates the current wind power generation profit deviation value, It indicates the average power of wind power generation per unit time under the same wind force level. represents the electricity price corresponding to the current time t, It represents the consumption cost of the wind power generation device under the f-th wind force level per unit time, and They represent the lower and upper limits of the wind power level range corresponding to the positive wind power generation profit deviation; A4. Align the variable with wind force level as the horizontal axis and obtain By mapping the double Y-axis line graph to the coordinate axis corresponding to the wind power level-power curve graph, the wind level-wind power generation profit deviation curve and the simultaneous satisfaction are obtained. The optimal wind power generation level range ,in represents the intersection symbol, and & represents the "and" symbol; A5. Obtain electricity prices and wind power levels in real time to update the wind level-wind power generation profit deviation curve and the optimal level power generation range in real time, and obtain the wind power generation output power value at the current moment from the updated double Y-axis line chart containing the wind level-power curve and the wind level-wind power generation profit deviation curve. and wind power level ranges under different power generation profit deviations.

4. The microgrid energy scheduling method based on energy characteristics according to claim 3 is characterized in that: The solar power output sub-model construction steps include: B1. Obtain solar radiation intensity and corresponding power generation data, and process the acquired data in segments with two-hour intervals; B2. Based on the segmented radiation intensity and the corresponding power generation, a radiation intensity-power fluctuation curve is constructed. At the same time, the radiation intensity and the corresponding power generation are used to obtain a radiation intensity-power fitting function through a support vector machine, and the fitting function is mapped to the radiation intensity-power fluctuation curve; B3, according to the radiation intensity-power fitting function and the radiation intensity-power fluctuation curve, through the power state change interval acquisition process in A2, the radiation supply-demand intervals D and E corresponding to the radiation intensity-power are obtained, where D means that the radiation supply-demand intervals D and E corresponding to the radiation intensity-power are satisfied. The corresponding radiation intensity interval, E means satisfying When , the corresponding radiation intensity interval; It represents the difference between the solar power generation power at the current time t and the compensation demand of the microgrid at the current time t; B4. According to the power value at the corresponding moment on the radiation intensity-power fluctuation curve and the corresponding consumption cost of the solar power generation device per unit time, the same process as A3-A5 is used to obtain the current solar power generation output power value, the radiation intensity level range under different solar power generation profit deviations, the radiation intensity-solar power generation profit deviation curve and the corresponding optimal solar power generation radiation intensity range. ,in is the profit deviation value of solar power generation at the current moment, where the radiation intensity range under the profit deviation of solar power generation is specifically: ； in, Indicates the profit deviation value of solar power generation at the current moment, It represents the average power of solar power generation per unit time under the same radiation intensity. represents the radiation intensity corresponding to the current time t, It represents the cost of solar power generation device operation per unit time. Indicates the minimum radiation intensity required to start the solar power generation device. express The corresponding radiation intensity when B5. Based on the same process of B3 and B4, obtain the corresponding output power per unit time of gas and energy storage device and and power generation profit deviation , Indicates the power value corresponding to the output of the gas power generation process per unit time. Indicates the power value output per unit time by the energy storage device. It indicates the profit deviation value corresponding to the gas power generation process per unit time.

5. The microgrid energy scheduling method based on energy characteristics according to claim 4, characterized in that: The step of obtaining the output priorities of different types of energy includes: C1. According to the microgrid compensation demand, wind level and radiation intensity obtained at the current moment, if the wind level and radiation intensity at the current moment are both in the corresponding optimal wind power generation level interval and optimal solar power generation radiation intensity interval, then according to the obtained wind level-power curve and wind level-wind power generation profit deviation curve and radiation intensity-power fluctuation curve and radiation intensity-solar power generation profit deviation curve, obtain the duration of the optimal wind power generation level interval and the optimal solar power generation radiation intensity interval corresponding to the wind power generation and solar power generation at the current moment. and ,in Indicates the duration of the optimal wind power generation level interval. Indicates the duration of the optimal solar power generation radiation intensity interval; C2. If , only wind power generation equipment is selected for supplementary power generation, and the wind power generation meets the requirements according to the wind level-power curve. The corresponding time point , and according to the radiation intensity-power fluctuation curve, the arrival The power generation interval state of solar energy at the moment, if the interval state of solar energy at the current moment satisfies , then stop the wind power generation device and directly call on the solar power generation device for supplementary power generation; C3. If the interval state corresponding to the solar energy at the current moment satisfies , then when arriving At this moment, the solar power generation device is directly dispatched to make up for the power shortage of the wind power generation device at the current moment, until the wind power generation device meets the demand again. When the solar power generation device is stopped, represents the wind power value at the current time t, Indicates the solar power generation value at the current time t.

6. The microgrid energy dispatching method based on energy characteristics according to claim 5, characterized in that: The step of obtaining the output priorities of different types of energy also includes: C4, if satisfied When the microgrid compensation demand is met, the corresponding output power of the energy storage device and the gas-fired power generation is judged. , then stop the wind power generation device and solar power generation device, and directly dispatch the energy storage device to make up for the missing electricity; C5. If and When the wind power generation device is running low, the solar power generation device is stopped and the energy storage device is directly dispatched to make up for the missing electricity of the wind power generation device; C6. If and , it is determined whether the gas power generation at the current moment meets If the conditions are met, the wind and solar power generation devices are stopped, and the gas power generation devices are directly dispatched to supplement the microgrid compensation demand; C7, if not satisfied, then make a second judgment, if the gas power generation device meets and , but not satisfied When the solar power generation device is stopped, the gas power generation device is dispatched to make up for the missing electricity of the wind power generation device.

7. The microgrid energy dispatching method based on energy characteristics according to claim 6, characterized in that: The step of obtaining the output priorities of different types of energy also includes: C8. When the gas-fired power generation device does not meet , then the output power status of wind power, solar energy and energy storage devices is determined according to the C2-C5 process, and single or hybrid energy generation devices are dispatched to make up for the missing compensation demand of the microgrid. If the output power of wind power, solar energy and energy storage devices at the same time cannot meet the compensation demand of the microgrid at the current moment, the gas-fired generation device is dispatched to make up for the missing power of wind power, solar energy and energy storage devices; C9. When the sum of the output power of wind power, solar power, energy storage device and gas power generation device after the gas power generation device is turned on is greater than the compensation demand of the microgrid, then according to the current moment The combination is carried out to minimize the sum of the profit deviations after the combination while meeting the compensation demand of the microgrid, and the corresponding power generation devices that are not involved in the combination are shut down.

8. The microgrid energy dispatching method based on energy characteristics according to claim 7, characterized in that: The step of obtaining the output priorities of different types of energy also includes: C10, if , then according to the same process of C2-C9, determine the dispatch priority corresponding to each type of power generation device; C11. If , then according to the corresponding wind power generation and solar power generation at the current moment and For comparison, if Then the wind power generation device is dispatched first, otherwise the solar power generation device is dispatched first, and the dispatch priority of the remaining power generation devices is determined according to the same process of C2-C9; C12. If only wind power generation is in the optimal wind power generation level range or solar power generation is in the optimal solar power generation radiation intensity range at the current moment, then select the energy corresponding to the optimal range to supplement the microgrid compensation demand, and repeat the same process of C2-C9 to dispatch the power generation devices corresponding to the remaining energy types; C13. When neither wind power generation nor solar power generation is within the corresponding optimal wind power generation level range and optimal solar power generation radiation intensity range, the corresponding wind power generation, solar power generation and gas power generation The combination is carried out to minimize the sum of the profit deviations after the combination while meeting the compensation demand of the microgrid. If the sum of the power output of wind power generation, solar power generation and gas power generation is less than the compensation demand of the microgrid, the energy storage device is dispatched to make up for the missing power of wind power generation, solar power generation and gas power generation, so that the microgrid satisfies the microgrid balance equation in real time.

9. A microgrid energy dispatching system based on energy characteristics, which is used to implement the microgrid energy dispatching method based on energy characteristics as described in any one of claims 1 to 8, characterized in that: include: Data processing module, output analysis module, configuration optimization module and energy scheduling module; The data processing module is used to obtain microgrid operation status data, weather status data, gas consumption data and load demand data, and pre-process the obtained data; The output analysis module includes a balance equation unit, a load demand prediction unit, and a power prediction unit; The balance equation unit is used to construct a microgrid balance equation using the preprocessed microgrid operation status data; The load demand prediction unit is used to obtain a predicted load demand forecast value based on historical load demand data through a demand prediction model, and to obtain a microgrid compensation demand corresponding to the current moment using a constructed microgrid balance equation; The power prediction unit is used to obtain wind-solar output prediction values ​​under different weather conditions by using the acquired weather status data and the corresponding solar and wind power generation data and constructing a wind-solar output prediction model; The configuration optimization module obtains the output priority of different types of energy through the optimal output configuration model according to the microgrid compensation demand, wind-solar output forecast value and output cost of different energy types; The process of obtaining the output priority of different types of energy is to determine whether wind power generation or solar power generation is in the optimal power generation range based on the wind level and radiation intensity, so as to decide whether to enable the wind or solar power generation device; when the wind level and radiation intensity are in the optimal power generation range, wind power or solar power generation is used first, and the power generation device is switched or stopped in time according to the actual situation; When the power generation range is not optimal, the cost-effectiveness and output power of wind, solar, energy storage and gas-fired power generation are comprehensively considered to intelligently select the optimal power generation combination to meet the real-time needs of the microgrid. The energy scheduling module is used to schedule the corresponding power generation device to generate electricity based on the obtained compensation demand and the output priority of different types of energy through the built-in enhanced scheduling control model so that the microgrid can maintain real-time balance.

10. A computer-readable storage medium, characterized in that: Computer instructions are stored thereon, and when the computer instructions are executed, the microgrid energy scheduling method based on energy characteristics described in any one of claims 1-8 is executed.

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