A multi-type energy complementary island microgrid coordination control method and system

Abstract

The application discloses a kind of multi-type energy complementary island microgrid coordination control method and system, it is related to energy coordination control technical field, including collecting island microgrid structure and scheduled forecast time zone carry out historical data analysis;Energy coordination control scheme is carried out based on island microgrid energy coordination control;Simulation tool is carried out simulation evaluation.The multi-type energy complementary island microgrid coordination control method provided by the application collects island microgrid structure and scheduled forecast time zone carries out historical data analysis, improves the accuracy and consistency of data analysis, according to the actual power consumption condition and management demand of island, sets different power consumption level, arranges data according to time sequence, improves the reliability and efficiency of power supply, uses the power generation prediction based on prediction model, improves the foresight and accuracy of energy management, the application achieves more good effect in the reliability of power supply, the accuracy of power generation prediction and efficiency.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of energy coordination control, in particular to a multi-type energy complementary island microgrid coordination control method and system. BACKGROUND

[0002] An island microgrid system is a local power grid for independent power supply, mainly applied to remote geographical locations, difficult power grid coverage or unable to access large-scale power networks in island areas. Due to the unique environment of islands, there are often abundant renewable energy resources such as wind energy, solar energy, wave energy, etc. Therefore, the island microgrid system usually adopts multiple renewable energy power generation methods to realize sustainable utilization and stable supply of energy. Floating wind power system, photovoltaic power generation system and wave energy power generation system are typical representatives. These power generation systems can effectively utilize the abundant natural resources around the island to provide reliable power supply for island residents and infrastructure.

[0003] However, in the prior art, various power generation systems often run independently, lacking unified coordination and management. Specifically, the operation and control strategies of wind power, photovoltaic and wave energy power generation systems are not effectively integrated, resulting in a lack of synergy between systems. For example, the wind power system can efficiently generate power when the wind is sufficient, while the photovoltaic system relies on the intensity of sunlight, and the wave energy power generation is closely related to the height and period of the sea waves. This independent running mode leads to the fact that in some cases, a certain type of power generation system may be in an efficient running state, while other systems fail to fully utilize their power generation potential, resulting in low resource utilization. In addition, the volatility and instability of a single type of power generation system cannot be balanced and optimized through the complementation of other systems, affecting the stability and reliability of the overall system. SUMMARY

[0004] In view of the above problems, the present application is proposed.

[0005] Therefore, the technical problem solved by the present application is that the existing energy coordination control method has the problems of poor power supply stability, low reliability, low resource utilization, and lack of synergy between systems.

[0006] To solve the above technical problems, the present application provides the following technical scheme: a multi-type energy complementary island microgrid coordination control method, comprising collecting island microgrid structure and predetermined prediction time zone for historical data analysis; performing energy coordination control of island microgrid based on energy coordination control scheme; and simulating and evaluating by simulation tool.

[0007] As a preferred scheme of the multi-type energy complementary island microgrid coordination control method according to the present application, wherein: the collecting island microgrid structure and predetermined prediction time zone for historical data analysis comprises collecting island microgrid structure;

[0008] The island micro-grid structure includes a power generation unit and a power consumption unit.

[0009] The power generation unit includes multiple types of power generation systems.

[0010] The overall architecture of the island micro-grid is determined, including the power generation unit and the power consumption unit.

[0011] The predetermined prediction time zone is collected, and the historical power generation data and the historical power consumption data are retrieved as constraints.

[0012] The historical power consumption data is analyzed for trends, and the predicted power consumption trend of the power consumption unit is generated based on the trend analysis results.

[0013] According to the management requirements of the island micro-grid, the time range of the prediction is determined.

[0014] From the data recording system of the power generation unit, the historical power generation data of the historical time zone in the predetermined prediction time zone is retrieved.

[0015] From the monitoring system of the power consumption unit, the historical power consumption data of the corresponding historical time zone in the predetermined prediction time zone is retrieved.

[0016] The historical power consumption data is standardized to eliminate the influence of different data sources and magnitudes, and the key features are extracted from the standardized historical data.

[0017] The historical power consumption data is analyzed using time series analysis method to identify the power consumption mode and seasonal trend, and the predicted power consumption trend of the power consumption unit is generated.

[0018] Time series analysis analyzes time series data, which is a numerical data recorded in chronological order, identifies patterns and trends in the data, and makes predictions.

[0019] As a preferred scheme of the multi-type energy complementary island micro-grid coordinated control method, the historical data analysis of the island micro-grid structure and the predetermined prediction time zone includes power consumption classification identification of the predicted power consumption trend, and a plurality of classification power consumption curves are obtained according to the power consumption classification identification results.

[0020] The power consumption classification standard is defined, different power consumption levels are set according to the actual power consumption situation and management requirements of the island, and the power consumption levels are set as key load, important load and general load according to the load type, residents, business and industry, and each power consumption level has a power consumption priority.

[0021] The data of the predicted electricity trend is arranged in time series, the electricity data of each time point is graded and identified according to the set electricity grading standard, and the graded electricity curve is output according to the grading identification result, each curve representing the electricity trend of the electricity grade;

[0022] The predicted meteorological data of the predetermined prediction time zone is collected, and the predicted power generation trend of the power generation unit is output combined with the historical power generation data;

[0023] The meteorological data of the predetermined prediction time zone is collected, including wind speed, solar radiation intensity, cloud cover, temperature, and sea wave height.

[0024] As a preferred scheme of the multi-type energy complementary island microgrid coordinated control method, the energy coordinated control of the island microgrid based on the energy coordinated control scheme includes activating the power generation prediction model, including the wind power prediction model based on wind speed, the photovoltaic power generation prediction based on solar radiation intensity, and the wave energy power generation prediction based on sea wave height and wave period.

[0025] Based on the historical power generation data and corresponding meteorological data, each type of power generation prediction model is trained, and the model parameters are adjusted to improve the prediction accuracy.

[0026] The wind power prediction model is used to input the wind speed data of the future period to generate the predicted power generation curve of the floating wind power system.

[0027] The photovoltaic power generation prediction model is used to input the solar radiation intensity, temperature and cloud cover data of the future period to generate the predicted power generation curve of the photovoltaic power generation system.

[0028] The wave energy power generation prediction model is used to input the sea wave height and wave period data of the future period to generate the predicted power generation curve of the wave energy power generation system.

[0029] The predicted power generation curves of various types of power generation systems are integrated.

[0030] The wind power prediction model is represented as:

[0031]

[0032] Wherein, v represents the wind speed, v cut-in represents the starting wind speed of the wind turbine, v rated represents the rated wind speed of the wind turbine, v cut-out represents the shutdown wind speed of the wind turbine, η(v) is the efficiency coefficient at wind speed v, indicating the efficiency change of the wind turbine at different wind speeds, C p is the power coefficient, indicating the wind energy utilization rate of the wind turbine, ρ(v) represents the air density at wind speed v, ρ0 represents the air density at sea level, h represents the altitude, H represents the atmospheric pressure height, P ratedrepresents the rated power of the wind turbine;

[0033] The photovoltaic power generation prediction model is constructed as follows:

[0034] P pv (G,T,θ,α)=G·A·η pv (θ)·[1-β(T c -T ref )]·cos(α)

[0035] η pv (θ)=η0(1-k θ (θ-θ opt ) 2 )

[0036]

[0037] wherein G represents the solar radiation intensity, T represents the ambient temperature, θ represents the inclination angle of the photovoltaic module, α represents the angle between the inclination angle of the photovoltaic module and the incident angle of the sunlight, η pv (θ) represents the efficiency of the photovoltaic module at the angle θ, η0 represents the basic efficiency of the photovoltaic module, k θ represents the angle influence coefficient, θ opt represents the optimal angle of the photovoltaic module, β represents the temperature coefficient of the photovoltaic module, T c represents the working temperature of the photovoltaic module, T a represents the working temperature of the photovoltaic module, T a represents the ambient temperature, NOCT represents the nominal working temperature of the photovoltaic module, which is 45℃, v ref represents the reference wind speed, which is 1m / s;

[0038] The wave energy generation prediction matrix model is constructed as follows:

[0039]

[0040] wherein P w (H,T) represents the output power matrix of the wave energy generation system at different time points and locations, H represents the sea wave height matrix, which is an n×m matrix, wherein n is the number of time points, m is the number of locations, H s represents the effective wave height matrix, T represents the energy period matrix, represents the Hadamard product, η is the wave energy conversion efficiency matrix, which represents the efficiency of converting wave energy into electric energy, ρ represents the seawater density, and g represents the gravitational acceleration.

[0041] As a preferred scheme of the multi-type energy complementary island microgrid coordination control method, the energy coordination control scheme is used to perform energy coordination control of the island microgrid, which includes aligning the predicted power consumption trend and the predicted power generation trend.

[0042] Based on the multiple predicted power generation curves and the multiple hierarchical power consumption curves, energy coordination control analysis is performed to generate an energy coordination control scheme.

[0043] Based on the energy coordination control scheme, energy coordination control of the island microgrid is performed.

[0044] Aligning the predicted power consumption trend and the predicted power generation trend allows direct comparison and analysis of power consumption and power generation data at the same time point, and the predicted power consumption and the predicted power generation at each time point are compared to output the supply-demand difference.

[0045] When the predicted power consumption is greater than the predicted power generation, unnecessary loads are preferentially reduced to maintain the supply-demand balance.

[0046] When the predicted power generation is greater than the predicted power consumption, the power generation plan is adjusted to reduce power generation.

[0047] According to the energy coordination control scheme, the parameters of the microgrid control system are configured, including the operation instructions of the power generation equipment, the energy storage system, and the load management system.

[0048] As a preferred scheme of the multi-type energy complementary island microgrid coordination control method, the energy coordination control scheme is used to perform energy coordination control of the island microgrid, which includes aligning the predicted power consumption trend and the predicted power generation trend, generating a predicted energy storage trend, and identifying the presence of positive and negative trends.

[0049] Based on the predicted energy storage trend and the energy coordination control scheme, an energy storage scheme is generated.

[0050] According to the energy storage scheme, energy storage control of the energy storage unit is performed.

[0051] Aligning the predicted power consumption trend and the predicted power generation trend allows comparison and analysis of power consumption and power generation data at the same time point, and at each time point, the energy storage demand and the predicted power generation minus the predicted power consumption are output.

[0052] When the energy storage demand is positive, it indicates that there is electrical energy storage, which is positive.

[0053] When the energy storage demand is negative, it indicates that electrical energy needs to be extracted from the energy storage system, which is negative.

[0054] According to the result of the energy storage demand, the energy storage trend is identified to generate a predicted energy storage trend.

[0055] According to the positive data in the energy storage trend, a charging plan is formulated, including the charging time period and the charging power;

[0056] According to the negative data in the energy storage trend, a discharging plan is formulated, including the discharging time period and the discharging power;

[0057] The energy storage plan is combined with the energy coordination control scheme to generate an energy storage scheme;

[0058] According to the energy storage scheme, the operation parameters of the energy storage system are configured, including the time period, power setting of charging and discharging, and the charging and discharging operations are performed;

[0059] The preset time interval is collected, and when the predicted energy storage trend is positive in the preset time interval, an electric energy distribution instruction is generated;

[0060] Based on the electric energy distribution instruction, electric energy distribution to the external power grid is performed;

[0061] According to the operation characteristics and management requirements of the island microgrid, the preset time interval is determined, and the predicted energy storage trend data in the preset time interval is checked slidingly, to determine whether the energy storage trend in the preset time interval is all positive. If so, it indicates that the system has excess electric energy in the time period, and an electric energy distribution instruction is generated;

[0062] In the predetermined time interval, according to the electric energy distribution instruction, the microgrid control system is used to deliver electric energy to the external power grid;

[0063] Based on the predicted power generation curve and the hierarchical power consumption curve, energy coordination control analysis is performed to generate an energy coordination control scheme;

[0064] When the predicted power consumption trend is greater than the predicted power generation trend, load reduction is performed based on multiple hierarchical power consumption curves to generate a power consumption coordination control scheme;

[0065] The power consumption coordination control scheme is added to the energy coordination control scheme;

[0066] The predicted power consumption trend and the predicted power generation trend at each time point are compared, and the time period in which the power consumption is greater than the power generation is identified. The supply-demand difference at each time point is output, and the priority of each type of power consumption load is determined based on the hierarchical power consumption curve, and the low-priority load is preferentially reduced;

[0067] The low-priority load is reduced, and if the low-priority load is reduced and still cannot meet the balance requirement, the medium-priority load is reduced;

[0068] According to the load reduction strategy, a power consumption coordination control scheme is formulated to clearly specify the reduction amount and execution time of each type of load;

[0069] When the predicted power consumption trend is less than the predicted power generation trend, power generation scheduling is performed based on the predicted power generation curve to generate a power generation coordination control scheme;

[0070] The power generation coordination control scheme is added to the energy coordination control scheme;

[0071] The predicted power consumption trend and the predicted power generation trend at each time point are compared, and a time period in which the power consumption is less than the power generation is identified. The supply-demand difference at each time point is output. According to the supply-demand difference, the operation state and output power of various types of power generation equipment are adjusted to reduce power generation;

[0072] The scheduling priority of various types of power generation equipment is determined, and a detailed power generation coordination control scheme is formulated according to the power generation scheduling strategy, and the scheduling plan of various types of power generation equipment and the charging plan of the energy storage system are specified;

[0073] A simulation model of the island microgrid is constructed;

[0074] The simulation model of the island microgrid is simulated to generate a simulation data set;

[0075] The simulation data set is evaluated for energy coordination control to generate an energy coordination control evaluation coefficient;

[0076] A preset energy coordination control evaluation coefficient threshold is obtained, and it is determined whether the energy coordination control evaluation coefficient meets the preset energy coordination control evaluation coefficient threshold;

[0077] If it meets, a call instruction is generated, and the energy coordination control scheme is invoked to control the energy coordination of the island microgrid.

[0078] As a preferred scheme of the multi-type energy complementary island microgrid coordination control method, the simulation tool is used to establish a floating wind power, photovoltaic power generation, and wave energy power generation model, and set the operating parameters;

[0079] A model of the power consumption equipment is established, and the power consumption mode and demand characteristics are set;

[0080] A model of the microgrid control system is established, including load management, power generation scheduling, energy storage control, and electric energy distribution control logic;

[0081] The models of each unit are integrated into a unified island microgrid simulation model to ensure that each module can work cooperatively;

[0082] The island microgrid simulation model is run in the simulation tool to execute the energy coordination control scheme. During the simulation process, the operating data of each unit, including power generation, power consumption, energy storage state, and load reduction, are continuously collected to generate system operating data at different time points and integrate the simulation data set.

[0083] According to the target of the energy coordination control, an evaluation index is selected, an evaluation value at each time point is output according to the set evaluation index, each evaluation index is weighted and summed, and a comprehensive energy coordination control evaluation coefficient is output;

[0084] According to the system performance target and management requirements, an energy coordination control evaluation coefficient threshold is set, the energy coordination control evaluation coefficient is compared with the set energy coordination control evaluation coefficient threshold, if the evaluation coefficient is greater than or equal to the preset threshold, it indicates that the system performance meets the requirements, otherwise, the system performance does not meet the expectations;

[0085] When the evaluation coefficient is greater than or equal to the preset threshold, a call instruction is generated, and the energy coordination control scheme is started and executed.

[0086] Another object of the present application is to provide a multi-type energy complementary island microgrid coordination control system which can perform energy coordination control of the island microgrid through the energy coordination control scheme, and solve the problem of poor power supply stability in the current energy coordination control method.

[0087] As a preferred scheme of the multi-type energy complementary island microgrid coordination control system, it comprises a data acquisition and prediction module, an energy coordination control module, and a simulation and evaluation module; the path planning module is used to acquire the island microgrid structure and historical data, and determine the predetermined prediction time zone; the energy coordination control module is used to generate the energy coordination control scheme to coordinate the energy storage system; and the simulation and evaluation module is used to simulate and collect data.

[0088] A computer device comprises a memory and a processor, the memory stores a computer program, and the processor executes the computer program to realize the steps of the multi-type energy complementary island microgrid coordination control method.

[0089] A computer readable storage medium stores a computer program, and the computer program is executed by a processor to realize the steps of the multi-type energy complementary island microgrid coordination control method.

[0090] The beneficial effects of the present application: the multi-type energy complementary island microgrid coordination control method provided by the present application collects the island microgrid structure and the historical data analysis of the predetermined prediction time zone, improves the accuracy and consistency of data analysis, provides a reliable data basis for subsequent energy coordination control, sets different power consumption levels according to the actual power consumption situation and management requirements of the island, arranges the data in time sequence, and performs hierarchical identification, generates a hierarchical power consumption curve, improves the reliability and efficiency of power supply, collects the predicted meteorological data of the predetermined prediction time zone, improves the accuracy of power generation prediction, ensures the stable operation of the power generation system under different weather conditions, uses the wind speed-based wind power prediction model, the solar radiation intensity-based photovoltaic power prediction model, and the wave height and wave period-based wave energy prediction model to perform power generation prediction, improve the forward-looking and accuracy of energy management, align the predicted power consumption trend and the predicted power generation trend, perform energy coordination control analysis, generate an energy coordination control scheme, optimize the use of energy through the adjustment of the energy storage system, and improve the strain capacity and reliability of the system. The present application achieves better results in terms of power supply reliability, power generation prediction accuracy and efficiency. BRIEF DESCRIPTION OF DRAWINGS

[0091] In order to more clearly illustrate the technical solutions of the embodiments of the present application, the drawings needed in the embodiment description will be briefly introduced. Obviously, the drawings in the following description are only some embodiments of the present application, and other drawings can be obtained by those skilled in the art without creative labor.

[0092] Figure 1 The overall flowchart of a multi-type energy complementary island microgrid coordination control method provided for the first embodiment of the present application.

[0093] Figure 2 The flowchart of a multi-type energy complementary island microgrid coordination control method provided for the first embodiment of the present application.

[0094] Figure 3 The energy storage control flowchart of a multi-type energy complementary island microgrid coordination control method provided for the first embodiment of the present application.

[0095] Figure 4 The overall flowchart of a multi-type energy complementary island microgrid coordination control system provided for the third embodiment of the present application. DETAILED DESCRIPTION

[0096] In order to make the above objectives, characteristics and advantages of the present application more obvious and easy to understand, the specific embodiments of the present application will be described in detail below with reference to the accompanying drawings. Obviously, the described embodiments are part of the embodiments of the present application, rather than all the embodiments. Based on the embodiments in the present application, all other embodiments obtained by those skilled in the art without creative labor should fall within the scope of protection of the present application.

[0097] Embodiment 1, refer to Figures 1-3 For an embodiment of the present application, a multi-type energy complementary island microgrid coordination control method is provided, comprising:

[0098] S1: Collecting island microgrid structure and predetermined prediction time zone for historical data analysis.

[0099] Further, the island microgrid structure is obtained, wherein the island microgrid structure comprises a power generation unit and a power consumption unit, wherein the power generation unit comprises a multi-type power generation system;

[0100] The overall architecture of the island microgrid is determined, including the power generation unit and the power consumption unit, wherein the power generation unit is a wind-solar-wave-storage system dominated by floating wind power, including various types of power generation systems, such as floating wind power system, photovoltaic power generation system, wave energy power generation system, energy storage system, etc., wherein the floating wind power system is one of the main power generation systems of the island, which is a wind turbine installed on a floating platform, using the offshore wind energy around the island to generate electricity; the wind-solar-wave-storage system is a power generation system that comprehensively utilizes wind energy, solar energy, wave energy and energy storage technology, which realizes efficient utilization and stable power supply of energy by integrating various renewable energy sources and energy storage systems. The power consumption unit includes various types of power consumption equipment and loads on the island, such as various types of residents, commercial, industrial loads, etc.

[0101] A predetermined prediction time zone is obtained, and historical power generation data and historical power consumption data are retrieved based on the predetermined prediction time zone as a constraint; trend analysis is performed on the historical power consumption data, and a predicted power consumption trend of the power consumption unit is generated based on the trend analysis result;

[0102] According to the management requirements of the island microgrid, the time range of the prediction is determined, such as hourly prediction every day, daily prediction every week, weekly prediction every month, etc., and the predetermined prediction time zone is determined. From the data recording system of the power generation unit, the historical power generation data of the corresponding historical time zone of the predetermined prediction time zone is retrieved, which includes the power generation data records of floating wind power, photovoltaic power generation, wave energy power generation and energy storage system. From the monitoring system or smart meter of the power consumption unit, the historical power consumption data of the corresponding historical time zone of the predetermined prediction time zone is retrieved, which includes the power consumption data records of different types of loads.

[0103] The historical electricity consumption data is standardized to eliminate the influence of different data sources and magnitudes, facilitate unified analysis, extract key features from the standardized historical data, such as daily, weekly, monthly electricity consumption patterns, holiday effects, and the influence of climate change on electricity consumption, etc. The historical electricity consumption data is analyzed using time series analysis method to identify electricity consumption patterns and seasonal trends, and to generate predicted electricity consumption trends of the electricity consumption unit, wherein the time series analysis is a statistical method that identifies patterns and trends in data and makes predictions by analyzing time series data, i.e. numerical data recorded in chronological order.

[0104] The predicted electricity consumption trend is identified by electricity consumption classification, and a plurality of classification electricity consumption curves are obtained according to the electricity consumption classification result.

[0105] The electricity consumption classification standard is defined, specifically, different electricity consumption levels are set according to the actual electricity consumption and management requirements of the island, for example, different electricity consumption levels are set according to the load type, such as residential, commercial, and industrial, such as critical load, important load, and general load, and each electricity consumption level has a power consumption priority.

[0106] The data of the predicted electricity consumption trend is arranged in chronological order, and the electricity consumption data at each time point is classified according to the set electricity consumption classification standard, and a plurality of classification electricity consumption curves are generated according to the classification result, each curve representing the electricity consumption trend of an electricity consumption level, for example, critical load electricity consumption curve, important load electricity consumption curve and general load electricity consumption curve.

[0107] The predicted meteorological data of the predetermined prediction time zone is obtained, and the predicted electricity generation trend of the electricity generation unit is generated combined with the historical electricity generation data, wherein the predicted electricity generation trend includes a plurality of predicted electricity generation curves of the plurality of types of electricity generation systems.

[0108] Meteorological data of the predetermined prediction time zone is obtained from meteorological agencies, which includes wind speed, solar radiation intensity, cloud cover, temperature, sea wave height, etc. The electricity generation prediction model is activated, which includes wind power prediction model based on wind speed, such as wind speed power curve model, photovoltaic power generation prediction based on solar radiation intensity, such as photovoltaic power curve model, wave energy power generation prediction based on sea wave height and wave period, etc. Based on historical electricity generation data and corresponding meteorological data, various electricity generation prediction models are trained, and model parameters are adjusted to improve prediction accuracy.

[0109] S2: Energy coordination control of island microgrid based on energy coordination control scheme.

[0110] Further, a wind power prediction model is used to input wind speed data of a future period to generate a predicted power generation curve of the floating wind power system; a photovoltaic power generation prediction model is used to input data such as solar radiation intensity, temperature and cloud cover of the future period to generate a predicted power generation curve of the photovoltaic power generation system; and a wave power generation prediction model is used to input sea wave height and wave period data of the future period to generate a predicted power generation curve of the wave power generation system. The predicted power generation curves of various power generation systems are integrated together to form a comprehensive predicted power generation trend.

[0111] The predicted power consumption trend and the predicted power generation trend are aligned, energy coordination control analysis is performed based on the plurality of predicted power generation curves and the plurality of hierarchical power consumption curves to generate an energy coordination control scheme, and energy coordination control of the island microgrid is performed based on the energy coordination control scheme.

[0112] The predicted power consumption trend and the predicted power generation trend are aligned, so that power consumption and power generation data at the same time point can be directly compared and analyzed. The predicted power consumption and the predicted power generation at each time point are compared, and the supply-demand difference is calculated. When the predicted power consumption is greater than the predicted power generation, unnecessary loads are preferentially reduced to maintain the supply-demand balance. When the predicted power generation is greater than the predicted power consumption, the power generation plan is adjusted to reduce unnecessary power generation. The above strategies are integrated to develop a detailed energy coordination control scheme.

[0113] According to the energy coordination control scheme, the parameters of the microgrid control system are configured, including specific operation instructions of the power generation equipment, the energy storage system and the load management system. Specifically, according to the control scheme, load reduction is implemented to ensure that the supply-demand balance is maintained during the power consumption peak period; or the output power of the power generation equipment is adjusted to ensure that the power generation capacity matches the power consumption. Through the above steps, the energy coordination control of the island microgrid can be effectively performed, and the overall operation efficiency and stability of the system can be improved.

[0114] It should be noted that the wind power prediction model is represented as:

[0115]

[0116] wherein v represents the wind speed, v cut-in represents the starting wind speed of the wind turbine, v rated represents the rated wind speed of the wind turbine, v cut-out represents the shutdown wind speed of the wind turbine, η(v) is the efficiency coefficient at the wind speed v, indicating the efficiency change of the wind turbine at different wind speeds, C p is the power coefficient, indicating the wind energy utilization rate of the wind turbine, ρ(v) represents the air density at the wind speed v, ρ0 represents the air density at sea level, h represents the altitude, H represents the atmospheric pressure height, P rated represents the rated power of the wind turbine;

[0117] The photovoltaic power generation prediction model is represented as:

[0118] P pv (G,T,θ,α)=G·A·η pv (θ)·[1-β(T c -T ref )]·cos(α)

[0119] η pv (θ)=η0(1-k θ (θ-θ opt ) 2 )

[0120]

[0121] wherein G represents the solar radiation intensity, T represents the ambient temperature, θ represents the tilt angle of the photovoltaic module, α represents the angle of incidence of the photovoltaic module with the sunlight, η pv (θ) represents the efficiency of the photovoltaic module at angle θ, η0 represents the basic efficiency of the photovoltaic module, k θ represents the angle influence coefficient, θ opt represents the optimal angle of the photovoltaic module, β represents the temperature coefficient of the photovoltaic module, T c represents the working temperature of the photovoltaic module, T a represents the working temperature of the photovoltaic module, T a represents the ambient temperature, NOCT represents the nominal working temperature of the photovoltaic module, which is 45℃, v ref represents the reference wind speed, which is 1m / s;

[0122] The wave energy generation prediction matrix model is represented as:

[0123]

[0124] wherein P w (H,T) represents the output power matrix of the wave energy generation system at different time points and locations, H represents the sea wave height matrix, which is an n×m matrix, wherein n is the number of time points, m is the number of locations, H s represents the effective wave height matrix, T represents the energy period matrix, represents the Hadamard product, η is the wave energy conversion efficiency matrix, which represents the efficiency of converting wave energy into electric energy, ρ represents the seawater density, and g represents the gravitational acceleration.

[0125] It should also be noted that the predicted power consumption trend, the predicted power generation trend, and the predicted energy storage trend are aligned, wherein the predicted energy storage trend is identified as positive or negative;

[0126] Based on the predicted energy storage trend, an energy storage scheme is generated in combination with the energy coordination control scheme.

[0127] According to the energy storage scheme, energy storage control of the energy storage unit is performed.

[0128] The predicted power consumption trend and the predicted power generation trend are aligned so that power consumption and power generation data at the same time point can be directly compared and analyzed. At each time point, the energy storage demand, i.e., the predicted power generation minus the predicted power consumption, is calculated. When the energy storage demand is positive, it indicates that there is excess power that can be stored, and when the energy storage demand is negative, it indicates that power needs to be extracted from the energy storage system. According to the calculation result of the energy storage demand, the energy storage trend is identified, and a predicted energy storage trend is generated.

[0129] According to the positive data in the energy storage trend, a charging plan is developed, including specific charging time periods and charging power; and according to the negative data in the energy storage trend, a discharging plan is developed, including specific discharging time periods and discharging power. The energy storage plan is combined with the energy coordination control scheme to generate an energy storage scheme, ensuring the balance of supply and demand and optimal operation of the overall system.

[0130] According to the energy storage scheme, the operating parameters of the energy storage system are configured, including the time periods and power settings for charging and discharging, and specific charging and discharging operations are performed to ensure that the system operates in an efficient and stable state.

[0131] Further, the method further includes:

[0132] A preset time interval is obtained, and when the predicted energy storage trend is positive within the preset time interval, an electric energy distribution instruction is generated;

[0133] Based on the electric energy distribution instruction, electric energy distribution to an external power grid is performed.

[0134] According to the operation characteristics and management requirements of the island microgrid, a preset time interval is determined, such as any 6 hours, 12 hours, 24 hours, etc. The predicted energy storage trend data within the preset time interval is checked, and it is determined whether the energy storage trend within the preset time interval is all positive. If so, it indicates that there is excess power in the system during this time period, and an electric energy distribution instruction is generated.

[0135] Within the predetermined time interval, the excess electric energy is transported to an external power grid, such as an island or a coastal area with weak power supply capacity around the island, through the microgrid control system according to the electric energy distribution instruction, to maximize economic benefits.

[0136] Further, the method of performing energy coordination control analysis based on the plurality of predicted power generation curves and the plurality of hierarchical power consumption curves to generate an energy coordination control scheme includes:

[0137] when the predicted power consumption trend is greater than the predicted power generation trend, performing load shedding based on the plurality of hierarchical power consumption curves to generate a power consumption coordination control scheme;

[0138] adding the power consumption coordination control scheme to the energy coordination control scheme.

[0139] comparing the predicted power consumption trend and the predicted power generation trend at each time point, identifying time periods in which power consumption is greater than power generation, calculating the supply-demand difference at each time point, determining the priority of each type of power consumption load in combination with the hierarchical power consumption curves, and preferentially shedding low-priority loads, specifically, first shedding low-priority loads such as certain commercial lighting and non-critical industrial equipment, and if the balance of demand cannot be met after shedding low-priority loads, further shedding medium-priority loads such as some household appliances and office equipment to ensure system stability. According to the load shedding strategy, a detailed power consumption coordination control scheme is developed, specifying the amount of load shedding and the specific execution time for each type of load.

[0140] Further, the energy coordination control analysis based on the plurality of predicted power generation curves and the plurality of hierarchical power consumption curves to generate an energy coordination control scheme includes:

[0141] when the predicted power consumption trend is less than the predicted power generation trend, performing power generation scheduling based on the plurality of predicted power generation curves to generate a power generation coordination control scheme;

[0142] adding the power generation coordination control scheme to the energy coordination control scheme.

[0143] comparing the predicted power consumption trend and the predicted power generation trend at each time point, identifying time periods in which power consumption is less than power generation, calculating the supply-demand difference at each time point, and adjusting the operating state and output power of each type of power generation equipment according to the supply-demand difference to reduce excess power generation, specifically, determining the scheduling priority of each type of power generation equipment, and preferentially scheduling power generation equipment with high energy utilization rate and low power generation cost. According to the power generation scheduling strategy, a detailed power generation coordination control scheme is developed, specifying the scheduling plan for each type of power generation equipment and the charging plan for the energy storage system.

[0144] Further, the generation of the energy coordination control scheme further includes:

[0145] constructing an island microgrid simulation model;

[0146] performing simulation and modeling of the energy coordination control scheme through the island microgrid simulation model to generate a simulation data set;

[0147] performing energy coordination control evaluation on the simulation data set to generate an energy coordination control evaluation coefficient;

[0148] obtaining a preset energy coordination control evaluation coefficient threshold, and judging whether the energy coordination control evaluation coefficient meets the preset energy coordination control evaluation coefficient threshold;

[0149] If yes, generating a calling instruction, and calling the energy coordination control scheme to perform energy coordination control of the island microgrid based on the calling instruction.

[0150] S3: Simulation evaluation is performed by a simulation tool.

[0151] Further, a simulation tool such as MATLAB / Simulink is used to establish models of multiple types of power generation systems such as floating wind power, photovoltaic power generation, wave power generation, and the like, and set operation parameters thereof; models of various types of power consumption equipment are established, and power consumption modes and demand characteristics are set; a model of a microgrid control system is established, including control logics such as load management, power generation scheduling, energy storage control, and power distribution. The models of various units are integrated into a unified island microgrid simulation model to ensure that the modules can work cooperatively.

[0152] The island microgrid simulation model is run in the simulation tool to execute the energy coordination control scheme. In the simulation process, operation data of various units are continuously collected, including power generation, power consumption, energy storage state, load reduction, and the like, to generate operation data of the system at different time points, and simulation data sets are obtained by integration.

[0153] According to the target of energy coordination control, appropriate evaluation indexes such as power supply continuity, resource utilization rate, system stability, economic benefit, and the like are selected, evaluation values at various time points are calculated according to the set evaluation indexes, the evaluation values are weighted and summed to generate a comprehensive energy coordination control evaluation coefficient, and the operation effect of the overall system is reflected.

[0154] According to the system performance target and management requirement, an energy coordination control evaluation coefficient threshold is set, the energy coordination control evaluation coefficient is compared with the set energy coordination control evaluation coefficient threshold, and if the evaluation coefficient is greater than or equal to the preset threshold, it is indicated that the system performance meets the requirement; otherwise, the system performance does not meet the expectation. When the evaluation coefficient is greater than or equal to the preset threshold, a calling instruction is generated to start and execute the energy coordination control scheme.

[0155] It should be noted that if not, an optimization instruction is generated;

[0156] The energy coordination control scheme is optimized according to the optimization instruction.

[0157] When the energy coordination control evaluation coefficient does not reach the preset threshold, detailed analysis is required to determine the reasons for not meeting the requirements, which may include insufficient power generation, excessive power consumption, low efficiency of the energy storage system, etc. Through detailed analysis of the evaluation data, the specific links and problem points of the system performance are identified, and according to the analysis results, the specific content of the optimization instruction is determined, including the system parameters that need to be optimized, the adjustment direction of the control strategy, the adjustment of resource allocation, etc.

[0158] According to the optimization instruction, the key parameters in the control system are adjusted, such as the operating parameters of the power generation equipment, the charging and discharging strategy of the energy storage system, and the load reduction plan, so as to redevelop or adjust the energy coordination control strategy and obtain the optimized control scheme.

[0159] Further, the method for performing energy coordination control evaluation on the simulation data set to generate an energy coordination control evaluation coefficient includes:

[0160] Based on the simulation data set, power supply continuity evaluation is performed to generate a power supply continuity evaluation coefficient;

[0161] Based on the simulation data set, resource utilization rate evaluation is performed to generate a resource utilization rate evaluation coefficient;

[0162] The power supply continuity evaluation coefficient and the resource utilization rate evaluation coefficient are weighted and summed to generate the energy coordination control evaluation coefficient.

[0163] Specific indicators for power supply continuity evaluation are set, such as power supply time percentage, power supply interruption frequency, and power supply interruption duration, etc. Data related to power supply continuity is extracted from the simulation data set, such as power supply state in each time period, power supply interruption events, etc. According to the extracted data, the evaluation indicators such as power supply time percentage, power supply interruption frequency and power supply interruption duration are calculated. The weighted sum method is used to weight and process each indicator to obtain the power supply continuity evaluation coefficient.

[0164] Specific indicators for resource utilization rate evaluation are set, such as power generation equipment utilization rate, energy storage system utilization rate, and energy conversion efficiency, etc. Data related to resource utilization rate is extracted from the simulation data set, such as actual power generation of each power generation equipment, usage of the energy storage system, energy conversion process, etc. According to the extracted data, the evaluation indicators such as power generation equipment utilization rate, energy storage system utilization rate and energy conversion efficiency are calculated. The weighted sum method is used to weight and process each indicator to obtain the resource utilization rate evaluation coefficient.

[0165] According to the system performance target and management requirement, weights of the power supply continuity evaluation coefficient and the resource utilization evaluation coefficient are set, the weight values should reflect the importance of each index to the overall performance of the system, and the power supply continuity evaluation coefficient and the resource utilization evaluation coefficient are weighted and summed based on the weights to calculate the comprehensive energy coordination control evaluation coefficient.

[0166] Embodiment 2, one embodiment of the application, provides a multi-type energy complementary island microgrid coordination control method, in order to verify the beneficial effects of the application, through economic benefit calculation and simulation experiment for scientific demonstration.

[0167] First of all, the experiment is divided into experimental group and control group, the experimental group uses the method of the application, and the control group uses the prior art.

[0168] The island microgrid structure used in the experiment includes floating wind power, photovoltaic power generation and wave energy generation system, as well as different types of power consumption units (residents, businesses, industries). Collect the historical power generation data and power consumption data of each power generation unit and power consumption unit in the island microgrid structure, and the prediction time zone is predetermined as the past 24 months. Collect the historical data of wind speed, solar radiation intensity, cloud cover, temperature and sea wave height. Standardize the historical power consumption data to eliminate the influence of different data sources and magnitudes, and extract the key features. Use time series analysis method to identify the patterns and seasonal trends in the historical data, and generate the predicted power consumption trend. Activate the power generation prediction model, including the prediction model of wind power, photovoltaic power generation and wave energy generation, input the meteorological data of the future period, and generate the predicted power generation curve of each type of power generation system.

[0169] The historical power generation data is retrieved from the data recording system of the power generation unit, and the historical power consumption data is retrieved from the monitoring system of the power consumption unit. These data are standardized and the key features are extracted. The historical power consumption data is analyzed using time series analysis method to identify the power consumption patterns and seasonal trends, and the predicted power consumption trend of the power consumption unit is generated. Based on the historical power generation data and the corresponding meteorological data, the wind power, photovoltaic power generation and wave energy generation prediction models are trained, and the model parameters are adjusted to improve the prediction accuracy. The wind power prediction model is used to input the wind speed data of the future period to generate the predicted power generation curve of the floating wind power system; the photovoltaic power generation prediction model is used to input the solar radiation intensity, temperature and cloud cover data of the future period to generate the predicted power generation curve of the photovoltaic power generation system; the wave energy generation prediction model is used to input the sea wave height and wave period data of the future period to generate the predicted power generation curve of the wave energy generation system. The predicted power generation curves of various types of power generation systems are integrated to form comprehensive power generation prediction data.

[0170] Based on the predicted power consumption trend and the predicted power generation trend, an energy coordination control analysis is performed to generate an energy coordination control scheme, including a load reduction strategy and a power generation scheduling plan. The parameters of the microgrid control system are configured, including the operation instructions of the power generation equipment, the energy storage system and the load management system, to implement load reduction and power generation scheduling. According to the predicted energy storage trend, a charging and discharging plan is made, the operation parameters of the energy storage system are configured, and specific charging and discharging operations are performed to ensure that the system operates in an efficient and stable state.

[0171] A simulation tool is used to establish a floating wind power, photovoltaic power generation and wave power generation model, set operation parameters, establish a model of power consumption equipment and a microgrid control system, and integrate the models of each unit into a unified island microgrid simulation model.

[0172] The simulation model is run in the simulation tool to execute the energy coordination control scheme, continuously collect operation data of each unit, generate operation data of the system at different time points, and integrate the output simulation data set.

[0173] According to the target of energy coordination control, evaluation indexes are selected, evaluation values at each time point are output, and a comprehensive energy coordination control evaluation coefficient is output by weighted summation of each evaluation index.

[0174] Table 1 Experimental data table

[0175]

[0176] The error between the predicted power generation and the actual power generation in the experimental group is small, with an average error of about 2.5%. The error between the predicted power generation and the actual power generation in the control group is large, with an average error of about 8.3%. The difference between the power consumption and the predicted power generation and the actual power generation in the experimental group is small, with an average difference of about 1.8%. The difference between the power consumption and the predicted power generation and the actual power generation in the control group is large, with an average difference of about 6.1%. The power supply at different time points in the experimental group is relatively stable with small fluctuations, while the power supply in the control group fluctuates greatly with obvious peaks and troughs.

[0177] In summary, the present application achieves better results in terms of power supply reliability, power generation prediction accuracy and efficiency.

[0178] Example 3, refer to Figure 4 As an embodiment of the present application, a multi-type energy complementary island microgrid coordination control system is provided, which includes a data acquisition and prediction module, an energy coordination control module, and a simulation and evaluation module.

[0179] The path planning module is used for collecting island micro-grid structure and historical data, and determining a predetermined prediction time zone; the energy coordination control module is used for generating an energy coordination control scheme to coordinate the energy storage system; and the simulation and evaluation module is used for simulation and data collection.

[0180] If the functions are implemented in the form of software function units and sold or used as independent products, they can be stored in a computer readable storage medium. Based on this understanding, the technical solutions of the present application or the parts of the present application that essentially contribute to the prior art or the parts of the technical solutions can be embodied in the form of a software product stored in a storage medium, including a plurality of instructions for causing a computer device (which can be a personal computer, a server, or a network device, etc.) to execute all or part of the steps of the embodiments of the present application. The aforementioned storage medium includes a U disk, a mobile hard disk, a read-only memory (ROM), a random access memory (RAM), a magnetic disk or an optical disk, and various media that can store program codes.

[0181] The logic and / or steps represented in the flowchart or otherwise described herein, for example, can be considered a list of executable instructions for implementing logic functions, and can be specifically embodied in any computer-readable medium for use by or in connection with an instruction execution system, apparatus, or device, such as a computer-based system, a system including a processor, or other system that can fetch the instructions from the instruction execution system, apparatus, or device and execute the instructions. For the purposes of this specification, a "computer-readable medium" can be any device that can contain, store, communicate, propagate, or transport the program for use by or in connection with the instruction execution system, apparatus, or device or in conjunction with these instruction execution systems, apparatuses, or devices. For the purposes of this specification, a "computer-readable medium" can be any device that can contain, store, communicate, propagate, or transport the program for use by or in connection with the instruction execution system, apparatus, or device or in conjunction with these instruction execution systems, apparatuses, or devices.

[0182] More specific examples (a non-exhaustive list) of the computer-readable medium include the following: an electrical connection having one or more wires (electrical devices), a portable computer diskette (magnetic devices), a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber device, and a portable compact disc read-only memory (CDROM). In addition, the computer-readable medium can even be paper or other suitable medium on which the program can be printed, because the program can be electronically obtained, for example, by optical scanning of the paper or other medium, followed by electronic conversion, interpretation, or processing, if necessary, in other suitable ways, and then stored in a computer memory.

[0183] It should be understood that portions of the present application can be implemented with hardware, software, firmware, or a combination thereof. In the above embodiments, multiple steps or methods can be implemented with software or firmware stored in memory and executed by a suitable instruction execution system. For example, if implemented in hardware, as in another embodiment, implementation can be with any or a combination of the following technologies, which are all well known in the art: a discrete logic circuit having logic gates for implementing logic functions upon an application of data signals, an application specific integrated circuit having appropriate combinational logic gates, a programmable gate array (PGA), a field programmable gate array (FPGA), etc. It should be understood that the foregoing embodiments are merely illustrative of the present application and are not to be used to limit the present application. Although the present application has been described in detail with reference to the preferred embodiments, it will be apparent to those skilled in the art that various changes and modifications can be contributed to the present application without departing from the spirit and scope of the present application, and such changes and modifications should be encompassed within the scope of the appended claims.

[0184] It should be understood that the foregoing embodiments are merely illustrative of the present application and are not to be used to limit the present application. Although the present application has been described in detail with reference to the preferred embodiments, it will be apparent to those skilled in the art that various changes and modifications can be contributed to the present application without departing from the spirit and scope of the present application, and such changes and modifications should be encompassed within the scope of the appended claims.

Claims

1. A multi-type energy complementary island microgrid coordination control method, characterized in that, The application relates to a method for energy coordination control of an island micro-grid, and belongs to the technical field of island micro-grid energy coordination control. The method comprises the following steps: Collecting historical data of island micro-grid structure and a predetermined prediction time zone; Performing energy coordination control of the island micro-grid based on an energy coordination control scheme; Simulating and evaluating through a simulation tool; The collecting historical data of island micro-grid structure and a predetermined prediction time zone comprises the following steps: Identifying power consumption classification of a predicted power consumption trend; Obtaining a plurality of classification power consumption curves according to the power consumption classification identification result; Defining power consumption classification standards, setting different power consumption levels according to actual power consumption conditions and management requirements of the island, setting power consumption levels of key loads, important loads and general loads according to load types, and setting power consumption priorities for each power consumption level; Arranging data of the predicted power consumption trend in time sequence, classifying and identifying power consumption data of each time point according to the set power consumption classification standards, outputting classification power consumption curves according to the classification identification result, and each curve representing a power consumption trend of a power consumption level; wherein, represents the output power matrix of the wave energy generation system at different time points and locations, represents the significant wave height matrix, which is an n x m matrix, where n is the number of time points and m is the number of locations, represents the energy period matrix, represents the Hadamard product, is the wave energy conversion efficiency matrix, representing the efficiency of the conversion of wave energy into electrical energy, represents the seawater density, represents the gravitational acceleration; Collecting meteorological data of the predetermined prediction time zone, including wind speed, solar radiation intensity, cloud cover, temperature and sea wave height; Outputting a predicted power generation trend of a power generation unit based on the meteorological data and in combination with historical power generation data; Constructing a wave energy power generation prediction matrix model, which is expressed as: The performing energy coordination control of the island micro-grid based on the energy coordination control scheme comprises the following steps: Aligning the predicted power consumption trend and the predicted power generation trend; Performing energy coordination control analysis based on a plurality of predicted power generation curves and a plurality of classification power consumption curves, and generating an energy coordination control scheme; Performing energy coordination control of the island micro-grid based on the energy coordination control scheme; 2. The multi-type energy complementary island microgrid coordination control method of claim 1, wherein: Aligning the predicted power consumption trend and the predicted power generation trend, directly comparing and analyzing power consumption and power generation data at the same time point, comparing predicted power consumption and predicted power generation at each time point, and outputting supply-demand differences; When the predicted power consumption is greater than the predicted power generation, unnecessary loads are preferentially reduced to maintain supply-demand balance; When the predicted power generation is greater than the predicted power consumption, power generation is reduced by adjusting a power generation plan; According to the energy coordination control scheme, parameters of a micro-grid control system are configured, including operation instructions of power generation equipment, energy storage systems and load management systems. The collecting historical data of island micro-grid structure and a predetermined prediction time zone comprises the following steps: Collecting the island micro-grid structure; The island micro-grid structure comprises a power generation unit and a power consumption unit; The power generation unit comprises a plurality of types of power generation systems; The overall architecture of the island micro-grid is determined, including the power generation unit and the power consumption unit; The predetermined prediction time zone is collected, and historical power generation data and historical power consumption data are called in the predetermined prediction time zone as constraints; Trend analysis is performed on the historical power consumption data, and a predicted power consumption trend of the power consumption unit is generated based on the trend analysis result; According to management requirements of the island micro-grid, a time range of prediction is determined; The historical power generation data of the historical time zone of the predetermined prediction time zone are called from a data recording system of the power generation unit; The historical power consumption data of the corresponding historical time zone of the predetermined prediction time zone are called from a monitoring system of the power consumption unit; Standardization processing is performed on the historical power consumption data, and influences of different data sources and magnitudes are eliminated, and key features are extracted from the standardization-processed historical data; Using time series analysis method, the historical power consumption data is analyzed to identify the power consumption mode and seasonal trend, and the predicted power consumption trend of the power consumption unit is generated; Time series analysis analyzes time series data, numerical data recorded in chronological order, identifies patterns and trends in the data, and makes predictions.

3. The coordinated control method of multi-type energy complementary island microgrid according to claim 2, characterized in that: The energy coordination control scheme based on the energy coordination control scheme for the island microgrid includes activating the power generation prediction model, including the wind power prediction model based on wind speed, the photovoltaic power generation prediction based on solar radiation intensity, and the wave energy power generation prediction based on sea wave height and wave period; Based on historical power generation data and corresponding meteorological data, train various types of power generation prediction models, and adjust model parameters to improve prediction accuracy; Using the wind power prediction model, input the wind speed data of the future period, and generate the predicted power generation curve of the floating wind power system; Using the photovoltaic power generation prediction model, input the solar radiation intensity, temperature and cloud cover data of the future period, and generate the predicted power generation curve of the photovoltaic power generation system; Using the wave energy power generation prediction model, input the sea wave height and wave period data of the future period, and generate the predicted power generation curve of the wave energy power generation system; Integrate the predicted power generation curves of various types of power generation systems; The wind power prediction model is represented as: wherein represents the wind speed, represents the cut-in wind speed of the wind turbine, represents the rated wind speed of the wind turbine, represents the cut-out wind speed of the wind turbine, is the efficiency coefficient at wind speed v, representing the efficiency change of the wind turbine at different wind speeds, is the power coefficient, representing the wind energy utilization rate of the wind turbine, represents the air density at wind speed v, represents the air density at sea level, represents the altitude, represents the atmospheric pressure height, represents the rated power of the wind turbine; The photovoltaic power generation prediction model is represented as: wherein, represents the solar radiation intensity, represents the ambient temperature, represents the tilt angle of the photovoltaic module, represents the tilt angle of the photovoltaic module and the angle of incidence of the sunlight, represents the efficiency of the photovoltaic module at an angle represents the base efficiency of the photovoltaic module, represents the angle impact factor, represents the optimal angle of the photovoltaic module, represents the temperature coefficient of the photovoltaic module, represents the operating temperature of the photovoltaic module, represents the ambient temperature, represents the nominal operating temperature of the photovoltaic module, which is 45°C, represents the reference wind speed, which is 1 m / s.​ 4. The multi-type energy complementary island microgrid coordination control method of claim 3, wherein: The energy coordination control scheme based on the energy coordination control scheme for the island microgrid includes aligning the predicted power consumption trend, the predicted power generation trend, generating the predicted energy storage trend, and identifying the positive and negative directions of the predicted energy storage trend; Based on the predicted energy storage trend, combine the energy coordination control scheme to generate the energy storage scheme; According to the energy storage scheme, perform energy storage control of the energy storage unit; Align the predicted power consumption trend and the predicted power generation trend to compare and analyze the power consumption and power generation data at the same time point. At each time point, the predicted power generation is reduced by the predicted power consumption to output the energy storage demand; When the energy storage demand is positive, it means that there is energy storage, which is positive; When the energy storage demand is negative, it means that energy needs to be extracted from the energy storage system, which is negative; According to the result of the energy storage demand, identify the energy storage trend to generate the predicted energy storage trend; According to the positive data in the energy storage trend, develop a charging plan, including the charging time period and the charging power; According to the negative data in the energy storage trend, develop a discharging plan, including the discharging time period and the discharging power; Combine the energy storage plan with the energy coordination control scheme to generate the energy storage scheme; According to the energy storage scheme, configure the operation parameters of the energy storage system, including the time period, power setting of charging and discharging, and perform charging and discharging operations; Collect the preset time interval, and when the predicted energy storage trend is positive in the preset time interval, generate the energy distribution instruction; Based on the energy distribution instruction, perform energy distribution to the external power grid; According to the operation characteristics and management requirements of the island microgrid, determine the preset time interval, any 6 hours, 12 hours or 24 hours, and perform sliding check on the predicted energy storage trend data in the preset time interval to determine whether the energy storage trend in the preset time interval is all positive. If so, it means that the system has excess energy in the time period, and an energy distribution instruction is generated. In a predetermined time interval, according to the electric energy distribution instruction, the electric energy is delivered to the external power grid through the micro-grid control system; Based on the predicted power generation curve and the hierarchical power consumption curve, energy coordination control analysis is performed to generate an energy coordination control scheme; When the predicted power consumption trend is greater than the predicted power generation trend, load reduction is performed based on multiple hierarchical power consumption curves to generate a power consumption coordination control scheme; The power consumption coordination control scheme is added to the energy coordination control scheme; The predicted power consumption trend and the predicted power generation trend at each time point are compared to identify time periods in which power consumption is greater than power generation, and the supply-demand difference at each time point is output. In combination with the hierarchical power consumption curve, the priority of each type of power consumption load is determined, and low-priority loads are preferentially reduced; If the low-priority load reduction still cannot meet the balance demand, the medium-priority load is reduced; According to the load reduction strategy, a power consumption coordination control scheme is developed to clearly specify the reduction amount and execution time of each type of load; When the predicted power consumption trend is less than the predicted power generation trend, power generation scheduling is performed based on the predicted power generation curve to generate a power generation coordination control scheme; The power generation coordination control scheme is added to the energy coordination control scheme; The predicted power consumption trend and the predicted power generation trend at each time point are compared to identify time periods in which power consumption is less than power generation, and the supply-demand difference at each time point is output. Based on the supply-demand difference, the operating state and output power of each type of power generation equipment are adjusted to reduce power generation; The scheduling priority of each type of power generation equipment is determined, and a detailed power generation coordination control scheme is developed according to the power generation scheduling strategy to clearly specify the scheduling plan of each type of power generation equipment and the charging plan of the energy storage system; A simulation model of the island micro-grid is constructed; Simulation simulation of the energy coordination control scheme is performed through the island micro-grid simulation model to generate a simulation data set; Energy coordination control evaluation is performed on the simulation data set to generate an energy coordination control evaluation coefficient; A preset energy coordination control evaluation coefficient threshold is obtained, and it is determined whether the energy coordination control evaluation coefficient meets the preset energy coordination control evaluation coefficient threshold; If it meets, a call instruction is generated, and the energy coordination control scheme is invoked to perform energy coordination control of the island micro-grid based on the call instruction.

5. The coordinated control method of multi-type energy complementary island microgrid according to claim 4, characterized in that: The simulation evaluation through the simulation tool includes using the simulation tool to establish models of floating wind power, photovoltaic power generation, and wave energy generation, and setting operating parameters; A model of the power consumption equipment is established, and the power consumption mode and demand characteristics are set; A model of the micro-grid control system is established, including load management, power generation scheduling, energy storage control, and electric energy distribution control logic; The models of each unit are integrated into a unified island micro-grid simulation model to ensure that each module can work cooperatively; The island micro-grid simulation model is run in the simulation tool to execute the energy coordination control scheme. During the simulation process, the operating data of each unit, including power generation, power consumption, energy storage state, and load reduction amount, are continuously collected to generate the operating data of the system at different time points, and the simulation data set is integrated and output; According to the target of energy coordination control, an evaluation index is selected, and based on the set evaluation index, the evaluation value at each time point is output. The evaluation indexes are weighted and summed to output a comprehensive energy coordination control evaluation coefficient; According to the system performance target and management requirement, a threshold of the energy coordination control evaluation coefficient is set, the energy coordination control evaluation coefficient is compared with the set threshold of the energy coordination control evaluation coefficient, if the evaluation coefficient is greater than or equal to the preset threshold, it indicates that the system performance meets the requirement; otherwise, the system performance does not reach the expectation; When the evaluation coefficient is greater than or equal to the preset threshold, a calling instruction is generated, and the energy coordination control scheme is started and executed.

6. A system for coordinated control of a multi-type energy complementary island microgrid according to any one of claims 1-5, characterized in that: The method comprises a data acquisition and prediction module, an energy coordination control module, a simulation and evaluation module; The data acquisition and prediction module is used for acquiring island microgrid structure and historical data, and determining a predetermined prediction time zone; The energy coordination control module is used for generating an energy coordination control scheme to coordinate the energy storage system; The simulation and evaluation module is used for simulation and data acquisition. 7.A computer device, comprising a memory and a processor, wherein the memory stores a computer program, and the computer device is configured to perform the method according to any one of claims 1-6 when the computer program is executed by the processor. The processor executes the computer program to realize the steps of the multi-type energy complementary island microgrid coordination control method in any one of claims 1 to 5.

8. A computer-readable storage medium having stored thereon a computer program, characterized in that, The computer program is executed by the processor to realize the steps of the multi-type energy complementary island microgrid coordination control method in any one of claims 1 to 5.

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