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CN118889572B - Energy management system and method for optical storage and charging micro-grid - Google Patents

Energy management system and method for optical storage and charging micro-grid Download PDF

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Publication number
CN118889572B
CN118889572B CN202411336648.6A CN202411336648A CN118889572B CN 118889572 B CN118889572 B CN 118889572B CN 202411336648 A CN202411336648 A CN 202411336648A CN 118889572 B CN118889572 B CN 118889572B
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energy
adjustment
load
time
adjusted
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CN118889572A (en
Inventor
崔新友
文涛
袁成
余鹏
罗乃好
李文慧
喻定海
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Wuhan Fiberhome Fuhua Electric Co ltd
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Wuhan Fiberhome Fuhua Electric Co ltd
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    • H—ELECTRICITY
    • H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
    • H02J—CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
    • H02J3/00—Circuit arrangements for AC mains or AC distribution networks
    • H02J3/38—Arrangements for parallely feeding a single network by two or more generators, converters or transformers
    • H02J3/46—Controlling of the sharing of output between the generators, converters, or transformers
    • H02J3/466—Scheduling the operation of the generators, e.g. connecting or disconnecting generators to meet a given demand
    • H—ELECTRICITY
    • H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
    • H02J—CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
    • H02J3/00—Circuit arrangements for AC mains or AC distribution networks
    • H02J3/12—Circuit arrangements for AC mains or AC distribution networks for adjusting voltage in AC networks by changing a characteristic of the network load
    • H02J3/14—Circuit arrangements for AC mains or AC distribution networks for adjusting voltage in AC networks by changing a characteristic of the network load by switching loads on to, or off from, network, e.g. progressively balanced loading
    • H02J3/144—Demand-response operation of the power transmission or distribution network
    • H—ELECTRICITY
    • H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
    • H02J—CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
    • H02J3/00—Circuit arrangements for AC mains or AC distribution networks
    • H02J3/28—Arrangements for balancing of the load in a network by storage of energy
    • H02J3/32—Arrangements for balancing of the load in a network by storage of energy using batteries with converting means
    • H—ELECTRICITY
    • H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
    • H02J—CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
    • H02J2300/00—Systems for supplying or distributing electric power characterised by decentralized, dispersed, or local generation
    • H02J2300/20—The dispersed energy generation being of renewable origin
    • H02J2300/22—The renewable source being solar energy
    • H02J2300/24—The renewable source being solar energy of photovoltaic origin
    • H—ELECTRICITY
    • H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
    • H02J—CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
    • H02J2310/00—The network for supplying or distributing electric power characterised by its spatial reach or by the load
    • H02J2310/50—The network for supplying or distributing electric power characterised by its spatial reach or by the load for selectively controlling the operation of the loads
    • H02J2310/56—The network for supplying or distributing electric power characterised by its spatial reach or by the load for selectively controlling the operation of the loads characterised by the condition upon which the selective controlling is based
    • H02J2310/58—The condition being electrical

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  • Engineering & Computer Science (AREA)
  • Power Engineering (AREA)
  • Charge And Discharge Circuits For Batteries Or The Like (AREA)

Abstract

The invention relates to the technical field of micro-grid management, in particular to an energy management system and method for an optical storage and charging micro-grid. According to the invention, the angle and the operating frequency of the photovoltaic panel are adjusted in real time, photovoltaic power generation is more efficient in an unstable sunlight environment, the utilization rate of solar resources is greatly improved, the charge and discharge period of the energy storage device is intelligently adjusted to match real-time sunlight change and energy demand, an energy storage system is effectively utilized, energy waste is reduced, supply and demand are balanced, real-time load management optimizes electric energy distribution, a power grid is dynamically adjusted to respond to load change, and energy consumption of non-critical loads is reduced.

Description

Energy management system and method for optical storage and charging micro-grid
Technical Field
The invention relates to the technical field of micro-grid management, in particular to an optical storage and charging micro-grid energy management system and method.
Background
The technical field of micro-grid management relates to design, monitoring and optimizing operation on a local power grid (micro-grid), wherein the power grid can independently operate in a state of disconnecting and connecting a main power grid, the technology comprises coordination of energy generation (such as solar photovoltaic), energy storage (such as a battery energy storage system) and energy consumption, the core purpose of micro-grid management is to improve the energy utilization efficiency, ensure the reliability of energy supply, reduce environmental impact and improve the toughness of the system to external interference, and the technical progress in the field also comprises advanced algorithms and control strategies for monitoring real-time data, predicting energy requirements, automatically regulating energy sources and maintaining the stability of the power grid.
The optical storage and charging micro-grid energy management system is a comprehensive system combining solar power generation, electric energy storage and electric energy charging management. The system is mainly used in micro-grids, and effective use of electric energy and reliability of power supply are ensured through intelligent control and management of electric energy generated by photovoltaic, a storage process and subsequent electric energy distribution. The system aims to maximize the utilization of solar energy resources, solve the intermittent problem of solar power generation through electric energy storage, optimize the supply and the demand of electric energy, improve the energy efficiency and the economy of the whole micro-grid, and also support the self-supply of energy under the disaster emergency condition and enhance the independent operation capability of the micro-grid.
The existing micro-grid management technology supports independent operation and connection or disconnection with a main grid, but has limitation in dynamic matching and real-time optimization of energy output and consumption, particularly in the utilization of solar photovoltaic power generation, the existing technology fails to adjust a power generation strategy in real time to cope with abrupt weather conditions, so that the solar power generation efficiency is greatly reduced in cloudy or rainy days, the management of energy storage equipment is mostly dependent on a preset charge and discharge period, and the capability of flexible adjustment is lacking, so that insufficient or excessive energy supply is easily caused under the condition of large fluctuation of power demand. Load management in the prior art is also relatively fixed, real-time data cannot be fully utilized for optimization, so that the risk of insufficient power supply occurs in the peak period of electric energy demand, the overall performance and efficiency of the micro-grid are limited, the running cost is increased, and the response capability of the system to emergency is influenced.
Disclosure of Invention
The invention aims to solve the defects in the prior art, and provides an energy management system and method for an optical storage and charging micro-grid.
In order to achieve the purpose, the invention adopts the following technical scheme that the energy management system of the optical storage and charging micro-grid comprises:
The photovoltaic output adjusting module is used for adjusting the angle and the operating frequency of the photovoltaic panel based on real-time data generated in real time by photovoltaic power generation to obtain photovoltaic power generation efficiency, adjusting output and matching energy requirements by combining real-time weather changes and illumination conditions, and generating an optimal sunlight utilization scheme;
The energy storage allocation module adjusts the charge and discharge period of the energy storage equipment by utilizing the optimal sunlight utilization scheme, matches sunlight changes, balances the peak value of real-time energy supply and demand, acquires energy storage efficiency data, adjusts the charge and discharge strategy by combining the energy consumption trend and the predicted demand through the energy storage efficiency data, and establishes an optimized energy storage scheduling strategy;
the load management and optimization module carries out dynamic load management according to the optimized energy storage scheduling strategy, adjusts the operation period of non-critical load to obtain a load adjustment execution record, adjusts load response according to the load adjustment execution record and generates load management optimization measures according to real-time load data;
and the energy efficiency and resource optimization module monitors and analyzes the energy consumption and output of the optical storage and charging micro-grid based on the load management optimization measures, adjusts energy distribution and optimizes energy utilization rate to obtain an initial energy efficiency optimization scheme, and finely adjusts a charging and discharging plan of the energy storage equipment to generate an optical storage and charging energy adjustment scheme.
As a further aspect of the present invention, the step of obtaining the photovoltaic power generation efficiency specifically includes:
based on real-time data generated in real time by photovoltaic power generation, measuring current and voltage of a photovoltaic panel, and adopting the formula:
;
The real-time generated power is obtained through measurement value calculation, wherein, The current is represented by a value representing the current,The voltage is represented by a voltage value,Representing real-time generation power;
According to the real-time power generation power and the illumination angle obtained from the illumination intensity sensor, the angle of the photovoltaic panel is adjusted, the generated energy is optimized, the environmental influence coefficient and the illumination intensity are redesigned and added, and the following formula is adopted:
;
Generating an adjusted generated power, wherein, Is the angle of illumination, the light is emitted,Is a coefficient of influence of the environment,Is the intensity of the light to be irradiated,Indicating the generated power after the adjustment,Representing real-time generation power;
and calculating the power generation efficiency by combining the adjusted power generation power, the current weather data, the solar radiation intensity and the total efficiency of the equipment, and using the formula:
;
The photovoltaic power generation efficiency is obtained, wherein, Is the data of the weather, and is the data of the weather,Is the intensity of the solar radiation and,Is the efficiency of the device and is based on the fact that,Is an adjustment parameter for the efficiency of the device,The efficiency of the photovoltaic power generation is represented,Indicating the adjusted generated power.
As a further aspect of the present invention, the obtaining step of the optimal sunlight utilization scheme specifically includes:
Based on the photovoltaic power generation efficiency, real-time illumination intensity and current weather conditions are measured through an illumination intensity sensor, and the sunlight adjustment factor is calculated by combining output data of a photovoltaic panel, and the formula is adopted:
;
generating adjusted energy output data, wherein, Representing the output power of the photovoltaic panel,Indicating the condition of the weather and,The intensity of the light is indicated and,Representing the adjusted energy output data,Representing a solar adjustment factor;
and comparing the predicted energy demand by using the adjusted energy output data, and adopting the formula:
;
the solar utilization is calculated and generated, wherein, Is the energy output data after adjustment,Is a predicted energy requirement for the utility model,Is the intensity of the light to be irradiated,Is the sunlight utilization rate;
according to the sunlight utilization rate and the illumination adjustment parameters, optimizing the angle of the photovoltaic panel, and using the formula:
;
An optimal daylight utilization solution is generated, wherein, Representing the utilization rate of sunlight, the sunlight is utilized,Representing the angle of illumination of the light,Representing an optimal daylight usage regimen.
As a further scheme of the present invention, the steps of obtaining the optimized energy storage scheduling policy specifically include:
According to the optimal sunlight utilization scheme and the current weather condition, adjusting a charging plan of the energy storage equipment, and applying the formula:
;
a preliminary charging strategy is generated, wherein, Indicating an optimal daylight utilization solution,Indicating the percentage of the current weather condition,Representing a preliminary charging strategy;
According to the preliminary charging strategy, the predicted energy demand and the state of the energy storage device are combined, and the formula is adopted:
;
a preliminary stored energy scheduling plan is generated, wherein, Is a preliminary charging strategy that is set up to the user,Is an indication of the state of the energy storage device,Is a function of predicting the energy demand of the plant,Is a preliminary energy storage scheduling plan;
Optimizing a charging and discharging strategy by using the preliminary energy storage scheduling plan and the market energy price, and applying the formula:
;
Generating an optimized energy storage scheduling strategy, wherein, Representing a preliminary stored energy dispatch plan,Representing the price of the energy source in the market,And representing the optimized energy storage scheduling strategy.
As a further aspect of the present invention, the step of obtaining the load adjustment execution record specifically includes:
Extracting key data from the optimized energy storage scheduling strategy, and calculating a time window of an adjustable non-key load by combining the current real-time energy supply condition through the formula:
;
An adjusted run time is generated, wherein, Representing the energy storage scheduling strategy after optimization,Representing the current state of energy supply,Represents the adjustment coefficient of the device,Indicating the adjustment constant(s),Representing the adjusted run time;
and performing dynamic load adjustment by using the adjusted running time and referring to the response time of the equipment, and applying the formula:
;
a dynamic load adjustment scheme is generated, wherein, Is the running time after the adjustment of the running time,Is the response time of the device and,Is a multiplier that enhances the accuracy of the adjustment,Is a dynamic load adjustment scheme;
According to the dynamic load adjustment scheme and the real-time operation data, calculating and recording the execution effect of load adjustment, and adopting the formula:
;
A load adjustment execution record is generated, wherein, Representing a load regulation scheme that is used to regulate the load,Is a constant that avoids too small a value,Is a load adjustment execution record.
As a further aspect of the present invention, the step of obtaining the load management optimization measure specifically includes:
Recording and real-time load data are executed according to the load adjustment, and the following formula is adopted:
;
evaluating the current load response effectiveness, generating a preliminary load response evaluation result, wherein, A load adjustment execution record is indicated,Representing the real-time load data,Is a small positive number added to avoid dividing by zero,Is a variable defined based on historical data,Is a preliminary load response assessment result,Is a weight coefficient;
according to the preliminary load response evaluation result and the set response threshold, determining the requirement to be adjusted, and adopting the formula:
;
a customized adjustment strategy is generated, wherein, Is a preliminary load response assessment result,Is a response threshold value that is set to be a response threshold value,Is a customized adjustment strategy that is to be used,AndIs a newly introduced adjustment coefficient;
Using the customized adjustment strategy, in combination with the device operation limits, determining and implementing optimization measures, adopting the formula:
;
load management optimization measures are generated, wherein, Is a customized adjustment strategy that is to be used,Is a device operation limit that is set to be limited,The coefficient of use is represented by a coefficient of use,Is a measure of load management optimization and is characterized by that,AndRepresenting the sensitivity and extensibility of the adjustment formula.
As a further aspect of the present invention, the step of obtaining the optical storage and charging energy adjustment scheme specifically includes:
According to the load management optimization measures, capturing real-time energy consumption and energy output of the optical storage and charging micro-grid, and applying the formula:
;
generating a preliminary energy efficiency evaluation result, wherein, Is a small positive number, the number of which is,AndIs a weight factor that is used to determine the weight of the object,Represents the energy consumption of the power plant,Represents the output of energy sources,Is a preliminary energy efficiency evaluation result;
based on the preliminary energy efficiency evaluation result, the energy use trend is combined, and the formula is adopted:
;
generating an adjusted energy efficiency optimization scheme, wherein, Is the coefficient of adjustment of the degree of reaction,Is the result of the preliminary energy efficiency evaluation,The energy use trend is indicated,The energy efficiency is optimized;
and fine-tuning a charge and discharge plan of the energy storage equipment by using the adjusted energy efficiency optimization scheme, and applying the formula:
;
Obtaining an optical storage energy source adjusting scheme, wherein, Is an adjustment factor that is used to adjust the position of the device,Is the prediction error of the demand and,Is an energy-efficiency optimization scheme, and is characterized in that,Is an optical storage energy source adjusting scheme.
The light storage and charging micro-grid energy management method is executed based on the light storage and charging micro-grid energy management system and comprises the following steps of:
S1, analyzing current illumination intensity and weather conditions based on real-time data produced in real time by photovoltaic power generation, controlling and adjusting the angle of a panel through a motor, adjusting the operating frequency through a frequency converter, and calculating to obtain an optimized sunlight utilization strategy;
S2, according to the optimized sunlight utilization strategy, adopting a current regulation technology to adjust the charging period of the energy storage equipment, adopting a voltage regulation technology to adjust the discharging period, and implementing dynamic energy balance by combining the real-time change of sunlight and the predicted energy demand to obtain an energy storage dispatching optimization scheme;
S3, utilizing the energy storage dispatching optimization scheme, adopting a load management controller to adjust the running time of a non-critical load, recording the adjusted execution condition, updating a load response strategy, and obtaining an optimized load management record;
S4, extracting energy consumption data from the optimized load management record, monitoring the energy output condition of the micro-grid through real-time monitoring configuration, adjusting energy distribution according to the energy consumption data, and generating an energy efficiency optimization strategy by finely adjusting a charge and discharge plan of the energy storage equipment;
And S5, adjusting energy allocation of the micro-grid based on the energy efficiency optimization strategy, and referring to performance data of the photovoltaic output and the energy storage equipment, implementing energy allocation operation, and constructing an optical storage energy adjustment scheme.
Compared with the prior art, the invention has the advantages and positive effects that:
According to the invention, the angle and the operating frequency of the photovoltaic panel are adjusted to adapt to real-time illumination and weather changes, so that dynamic optimization of electric energy output is realized, the photovoltaic power generation is more efficient, each sunlight can be effectively utilized particularly in an unstable sunlight environment, and the utilization rate of solar energy resources is greatly improved. Real-time sunlight change and energy demand are matched through intelligent adjustment of charge and discharge cycles of energy storage equipment, an energy storage system is fully utilized, energy waste is reduced, supply and demand are balanced, electric energy distribution is optimized through real-time load management, a power grid is dynamically adjusted according to load adjustment records, energy consumption is reduced when demand is low by non-critical loads, overall energy efficiency and economy of the system are improved, overall energy management not only improves energy efficiency of a micro-grid, but also adaptability and toughness of the system to external interference are enhanced, and self-sufficiency of energy can be maintained especially under emergency conditions.
Drawings
FIG. 1 is a system flow diagram of the present invention;
FIG. 2 is a flow chart of photovoltaic power generation efficiency in the present invention;
FIG. 3 is a flow chart of an optimal daylight utilization solution in the present invention;
FIG. 4 is a flow chart of an optimized energy storage scheduling strategy according to the present invention;
FIG. 5 is a flowchart of a load adjustment execution record according to the present invention;
FIG. 6 is a flow chart of the load management optimization measure of the present invention;
fig. 7 is a flowchart of an embodiment of the present invention.
Detailed Description
The present invention will be described in further detail with reference to the drawings and examples, in order to make the objects, technical solutions and advantages of the present invention more apparent. It should be understood that the specific embodiments described herein are for purposes of illustration only and are not intended to limit the scope of the invention.
In the description of the present invention, it should be understood that the terms "length," "width," "upper," "lower," "front," "rear," "left," "right," "vertical," "horizontal," "top," "bottom," "inner," "outer," and the like indicate orientations or positional relationships based on the orientation or positional relationships shown in the drawings, merely to facilitate describing the present invention and simplify the description, and do not indicate or imply that the devices or elements referred to must have a specific orientation, be configured and operated in a specific orientation, and therefore should not be construed as limiting the present invention. Furthermore, in the description of the present invention, the meaning of "a plurality" is two or more, unless explicitly defined otherwise.
Referring to fig. 1, the present invention provides a technical solution, an optical storage and charging micro-grid energy management system includes:
The photovoltaic output adjusting module is used for adjusting the angle and the operating frequency of the photovoltaic panel based on real-time data generated in real time by photovoltaic power generation to obtain photovoltaic power generation efficiency, adjusting output and matching energy requirements by combining real-time weather changes and illumination conditions, and generating an optimal sunlight utilization scheme;
The energy storage allocation module adjusts the charge and discharge period of the energy storage equipment by utilizing an optimal sunlight utilization scheme, matches sunlight changes, balances the peak value of real-time energy supply and demand, acquires energy storage efficiency data, adjusts the charge and discharge strategy by combining the energy consumption trend and the predicted demand through the energy storage efficiency data, and establishes an optimized energy storage scheduling strategy;
The load management and optimization module carries out dynamic load management according to the optimized energy storage scheduling strategy, adjusts the operation period of the non-critical load to obtain a load adjustment execution record, adjusts load response according to the load adjustment execution record through real-time load data, and generates load management optimization measures;
The energy efficiency and resource optimization module monitors and analyzes the energy consumption and output of the optical storage and charging micro-grid based on load management optimization measures, adjusts energy distribution and optimizes energy utilization rate to obtain an initial energy efficiency optimization scheme, and finely adjusts a charging and discharging plan of the energy storage device to generate an optical storage and charging energy adjustment scheme.
The photovoltaic power generation efficiency comprises angle optimization, frequency optimization and weather adaptability, the optimal sunlight utilization scheme comprises angle optimization, frequency matching degree and demand response capability, energy storage efficiency data comprises charging efficiency, discharging efficiency and supply and demand balance indexes, an optimized energy storage scheduling strategy comprises charging strategy fine adjustment, discharging strategy fine adjustment and demand prediction matching, load adjustment execution records comprise time period adjustment details, data adjustment response and operation efficiency improvement, load management optimization measures comprise management strategy refinement, response speed improvement and load adaptability improvement, an initial energy efficiency optimization scheme comprises consumption reduction measures, output efficiency improvement and distribution efficiency optimization, and a light storage and charging energy adjustment scheme comprises power generation scheduling optimization, energy storage scheduling fine adjustment and utilization rate maximization.
Referring to fig. 2, the photovoltaic power generation efficiency is obtained by the steps of:
based on real-time data generated in real time by photovoltaic power generation, measuring current and voltage of a photovoltaic panel, and adopting the formula:
;
The real-time generated power is obtained through measurement value calculation, wherein, The current is represented by a value representing the current,The voltage is represented by a voltage value,Representing real-time generation power;
According to the real-time power generation and the illumination angle obtained from the illumination intensity sensor, the angle of the photovoltaic panel is adjusted, the generated energy is optimized, the environmental influence coefficient and the illumination intensity are redesigned and added, and the following formula is adopted:
;
Generating an adjusted generated power, wherein, Is the angle of illumination, the light is emitted,Is a coefficient of influence of the environment,Is the intensity of the light to be irradiated,Indicating the generated power after the adjustment,Representing real-time generation power;
And (3) calculating the power generation efficiency by combining the adjusted power generation power, current weather data, solar radiation intensity and total efficiency of the equipment, and using the formula:
;
The photovoltaic power generation efficiency is obtained, wherein, Is the data of the weather, and is the data of the weather,Is the intensity of the solar radiation and,Is the efficiency of the device and is based on the fact that,Is an adjustment parameter for the efficiency of the device,The efficiency of the photovoltaic power generation is represented,Indicating the adjusted generated power.
The real-time generation power formula:
;
Current in amperes (A), assumed to be measured by a sensor;
Voltage in volts (V), assumed to be measured by the sensor;
Assuming current A, assume voltageV;
Calculation of:
;
Here, theW represents that the real-time generated power is 60 watts.
The adjusted generation power formula:
;
environmental impact coefficient, supposing that factors such as temperature, humidity and the like are considered;
The illumination angle is obtained by an illumination angle sensor;
The illumination intensity is expressed in lumens (Im) and is obtained by an illumination intensity sensor;
Assume that Assume thatAssume that;
Calculation of:
;
Here, theW indicates that the regulated generated power is 2.33 watts.
Photovoltaic power generation efficiency formula:
;
the equipment efficiency adjusting parameters take the maintenance state and aging of the equipment into consideration;
Solar radiation intensity in watts per square meter (W/m 2);
device performance, including power factor;
weather conditions effects such as shadows, clouds, etc.;
Assume that Assume thatW/Assume thatW, assumingunits;
Calculation of:
;
Here, theThe photovoltaic power generation efficiency is very low because of poor lighting conditions or poor equipment efficiency.
Referring to fig. 3, the obtaining steps of the optimal sunlight utilization scheme specifically include:
Based on photovoltaic power generation efficiency, real-time illumination intensity and current weather conditions are measured through an illumination intensity sensor, sunlight adjustment factors are calculated by combining output data of a photovoltaic panel, and the formula is adopted:
;
generating adjusted energy output data, wherein, Representing the output power of the photovoltaic panel,Indicating the condition of the weather and,The intensity of the light is indicated and,Representing the adjusted energy output data,Representing a solar adjustment factor;
and comparing the predicted energy demand by using the adjusted energy output data, and adopting the formula:
;
the solar utilization is calculated and generated, wherein, Is the energy output data after adjustment,Is a predicted energy requirement for the utility model,Is the intensity of the light to be irradiated,Is the sunlight utilization rate;
according to the sunlight utilization rate and the illumination adjustment parameters, the angle of the photovoltaic panel is optimized, and the following formula is used:
;
An optimal daylight utilization solution is generated, wherein, Representing the utilization rate of sunlight, the sunlight is utilized,Representing the angle of illumination of the light,Representing an optimal daylight usage regimen.
The adjusted energy output data formula:
;
The output power of the photovoltaic panel is assumed to be directly read through an ammeter and is expressed in kilowatts (kW);
weather conditions, assumed to be a simplified value, represent percent cloud cover;
The illumination intensity is measured by an illumination sensor and is expressed in watts per square meter (W/m 2);
sunlight adjustment factor, assumed to be To avoid zero removal errors and to simplify the calculation;
Assume that KW, let us assumeAssume thatW/;
Calculation of:
;
;
Here, theKW stands for the adjusted energy output of 49.4 kW for a given light intensity and weather conditions.
The formula of sunlight utilization rate:
;
the energy output after adjustment calculated in the previous step;
predicted energy demand, in kilowatts (kW), is assumed to be based on historical data and weather prediction models;
The intensity of the illumination is mentioned in the previous step;
assume parameters calculated in the previous step KW, let us assumekW;
Calculation of:
;
Indicating the current daylight utilization.
The optimal sunlight utilization scheme formula:
;
The sunlight utilization rate calculated in the previous step;
the illumination angle is assumed to be adjusted by an automatic tracking system to maximize sunlight capture, and the angle value is 30 degrees;
Assume parameters using step2 Assume that;
The calculation process comprises the following steps:
;
;
A larger number represents a score for the optimal daylight usage regimen, indicating more efficient daylight usage.
Referring to fig. 4, the steps for obtaining the optimized energy storage scheduling policy specifically include:
according to the optimal sunlight utilization scheme and the current weather condition, the charging plan of the energy storage equipment is adjusted, and the formula is applied:
;
a preliminary charging strategy is generated, wherein, Indicating an optimal daylight utilization solution,Indicating the percentage of the current weather condition,Representing a preliminary charging strategy;
according to the preliminary charging strategy, the predicted energy demand and the state of the energy storage equipment are combined, and the formula is adopted:
;
a preliminary stored energy scheduling plan is generated, wherein, Is a preliminary charging strategy that is set up to the user,Is an indication of the state of the energy storage device,Is a function of predicting the energy demand of the plant,Is a preliminary energy storage scheduling plan;
Optimizing a charging and discharging strategy by utilizing a preliminary energy storage scheduling plan and a market energy price, and applying the formula:
;
Generating an optimized energy storage scheduling strategy, wherein, Representing a preliminary stored energy dispatch plan,Representing the price of the energy source in the market,And representing the optimized energy storage scheduling strategy.
Preliminary charging strategy formula:
;
the efficiency of the optimal sunlight utilization scheme is assumed to be obtained from real-time monitoring data of the photovoltaic system;
the weather condition percentage is assumed to be obtained through a weather forecast API;
Hypothesis parameters, hypothesis (75% Efficiency), assuming that(%);
Calculation of:
;
This resultIndicating a charge efficiency of 90% for the preliminary charge strategy adjusted based on the optimal daylight usage solution under the current weather conditions.
Preliminary energy storage scheduling formula:
;
The preliminary charging strategy calculated in the previous step;
an indication of the state of the energy storage device, assuming that this is obtained from the health monitoring system of the device;
Predicted energy demand is calculated by historical data analysis and a future demand prediction model;
Assume parameters using the parameters obtained in the previous step Assume that(95% Of device health), assuming that(KW demand);
Calculation of :
;
This resultIt is explained that the current actual energy storage dispatch plans are very inefficient, reflecting challenges of the impact of equipment health or energy consumption requirements.
The energy storage scheduling strategy formula after optimization:
;
the actual energy storage scheduling plan obtained from the previous step;
market energy prices, assuming real-time data acquisition through an energy market;
Assume parameters using the parameters obtained in the previous step Assume that(%);
Calculation of:
;
This resultAnd the efficiency of the finally optimized energy storage scheduling strategy is represented, and the energy storage scheduling strategy is adjusted to the response after the market energy price is changed.
Referring to fig. 5, the load adjustment execution record obtaining step specifically includes:
extracting key data from the optimized energy storage scheduling strategy, and calculating a time window of an adjustable non-key load by combining the current real-time energy supply condition through the formula:
;
An adjusted run time is generated, wherein, Representing the energy storage scheduling strategy after optimization,Representing the current state of energy supply,Represents the adjustment coefficient of the device,Indicating that the adjustment constant is to be made,Representing the adjusted run time;
and (3) performing dynamic load adjustment by using the adjusted running time and referring to the response time of the equipment, and applying the formula:
;
a dynamic load adjustment scheme is generated, wherein, Is the running time after the adjustment of the running time,Is the response time of the device and,Is a multiplier that enhances the accuracy of the adjustment,Is a dynamic load adjustment scheme;
according to the dynamic load adjustment scheme and the real-time operation data, calculating and recording the execution effect of the load adjustment, and adopting the formula:
;
A load adjustment execution record is generated, wherein, Representing a load regulation scheme that is used to regulate the load,Is a constant that avoids too small a value,Is a load adjustment execution record.
The adjusted run time formula:
;
the efficiency of the energy storage scheduling strategy after optimization is obtained through an analysis tool of an energy management system;
the current energy supply state is obtained in real time through monitoring equipment of an energy supply system;
the adjustment coefficient is determined according to the historical data and the prediction model and is used for adjusting the load time to adapt to the energy supply change;
adjusting constants, and increasing the flexibility of formulas to handle unexpected or extreme cases;
Assume that the parameter values are: (80% efficiency), (In kilowatts),(Adjustment coefficient),(Adjusting the constant);
Calculation of :
;
This resultIndicating that the ideal run time for a non-critical load is 0.001067 units of time given the supply and scheduling strategy.
Dynamic load adjustment scheme formula:
;
load operation time calculated in the previous step;
the response time of the equipment is obtained from the equipment specification and the operation record;
A multiplier for enhancing the adjustment precision is set according to the equipment performance and the running environment;
Assuming that the parameter value is calculated in the previous step ,(Unit: seconds),;
Calculation of:
;
This resultRepresenting a detailed load adjustment scheme requires consideration of the effects of device response time and adjustment multipliers.
Load adjustment execution record formula:
;
the load adjustment scheme obtained in the previous step;
to avoid values that are too small to handle, the added constants are typically set to positive numbers of 1 or less to keep the values stable;
Assuming that the parameter value is calculated in the previous step ,;
Calculation of:
;
This resultThe value of the execution record is displayed, representing the effective record of the adjustment execution.
Referring to fig. 6, the load management optimization measure is obtained specifically by:
recording and real-time load data according to load adjustment, and adopting the formula:
;
evaluating the current load response effectiveness, generating a preliminary load response evaluation result, wherein, A load adjustment execution record is indicated,Representing the real-time load data,Is a small positive number added to avoid dividing by zero,Is a variable defined based on historical data,Is a preliminary load response assessment result,Is a weight coefficient;
According to the preliminary load response evaluation result and the set response threshold, determining the requirement to be adjusted, and adopting the formula:
;
a customized adjustment strategy is generated, wherein, Is a preliminary load response assessment result,Is a response threshold value that is set to be a response threshold value,Is a customized adjustment strategy that is to be used,AndIs a newly introduced adjustment coefficient;
using a custom adjustment strategy, in combination with equipment operation constraints, determining and implementing optimization measures, employing the formula:
;
load management optimization measures are generated, wherein, Is a customized adjustment strategy that is to be used,Is a device operation limit that is set to be limited,The coefficient of use is represented by a coefficient of use,Is a measure of load management optimization and is characterized by that,AndRepresenting the sensitivity and extensibility of the adjustment formula.
The preliminary load response assessment results are formulated:
;
Load adjustment execution records, actual records obtained from an energy management system;
Real-time load data is acquired in real time through a sensor and a monitoring system;
a tiny positive number, which is used for preventing zero removal errors and is set to be 0.01;
according to the variable adjusted by the historical data, reflecting the processing effect of the similar situation in the past, and setting the experience value to be 1.5;
The weight coefficient is adjusted to adapt to different load change conditions, and is determined by simulation and optimization process, and is set ;
Assume that;
The calculation process comprises the following steps:
;
this shows that the initial evaluation of the load response is about 0.375 given the real-time data and historical experience.
The formula of the customized adjustment strategy:
;
load response evaluation calculated in the previous step;
a preset response threshold value is set to be 0.5 based on a history effect and safety standard setting;
Gain coefficient, adjust response sensitivity, set as 2;
Enhancing the nonlinear effect of adjustment to be 1.5;
Assume that the parameter value is that using the above Value of;
Calculation of:
;
This indicates that the need for further adjustment is reduced by the adjustment factor and the threshold.
Load management optimization measure formula:
;
the adjustment scheme generated in the previous step;
The device operation limit is determined according to the device performance parameter and is set to 200;
The practical coefficient is adjusted according to the operation experience and is set to be 0.8;
Sensitivity and expansibility for adjusting formulas, set ;
Using the aboveValue 0.218;
Calculation of :
;
This means that the final optimization measure value is very small, indicating that the adjustment measure has a light impact on the current load, and that it is necessary to evaluate whether it is sufficient to affect the system performance.
Referring to fig. 7, the steps of obtaining the optical storage and charging energy adjustment scheme specifically include:
according to load management optimization measures, capturing real-time energy consumption and energy output of the optical storage and charging micro-grid, and applying the formula:
;
generating a preliminary energy efficiency evaluation result, wherein, Is a small positive number, the number of which is,AndIs a weight factor that is used to determine the weight of the object,Represents the energy consumption of the power plant,Represents the output of energy sources,Is a preliminary energy efficiency evaluation result;
based on the preliminary energy efficiency evaluation result, the energy use trend is combined, and the formula is adopted:
;
generating an adjusted energy efficiency optimization scheme, wherein, Is the coefficient of adjustment of the degree of reaction,Is the result of the preliminary energy efficiency evaluation,The energy use trend is indicated,The energy efficiency is optimized;
and (3) fine-tuning the charge and discharge plans of the energy storage equipment by utilizing the adjusted energy efficiency optimization scheme, and applying the formula:
;
Obtaining an optical storage energy source adjusting scheme, wherein, Is an adjustment factor that is used to adjust the position of the device,Is the prediction error of the demand and,Is an energy-efficiency optimization scheme, and is characterized in that,Is an optical storage energy source adjusting scheme.
Preliminary energy efficiency evaluation result formula:
;
energy output (such as photovoltaic power generation);
Energy consumption (e.g., energy consumption);
tiny constant, avoiding zero error, general taking ;
Adjusting the coefficient to influence the weight of output and consumption;
assume that in a photovoltaic system, the total energy output in a day 500KWh, energy consumptionFor 450kWh, set,,;
Calculation of:
;
;
;
This means that the energy efficiency ratio is about 5.905, and the high energy efficiency ratio reflects a good energy utilization efficiency.
The energy efficiency optimization scheme formula after adjustment:
;
preliminary energy efficiency evaluation results obtained from the previous step;
The energy use trend percentage;
Trend reaction adjustment coefficient;
assuming energy usage trends Is 5%, regulating coefficient;
Calculation of:
;
;
;
The optimized energy efficiency scheme obtained hereIncreasing to 6.121 shows an increase in energy efficiency with the trend.
The formula of the light storage and energy charging energy adjustment scheme is as follows:
;
The energy efficiency optimization scheme after the adjustment obtained from the previous step;
A demand prediction error adjustment factor;
predicting the percentage of demand errors;
Assuming prediction error Is 2%, adjustment factor;
Calculation of:
;
;
Final light storage and charge energy adjustment schemeThe adjustment is 5.773, and the error of demand prediction is considered.
The light storage and charging micro-grid energy management method is executed based on the light storage and charging micro-grid energy management system and comprises the following steps of:
S1, analyzing current illumination intensity and weather conditions based on real-time data produced in real time by photovoltaic power generation, controlling and adjusting the angle of a panel through a motor, adjusting the operating frequency through a frequency converter, and calculating to obtain an optimized sunlight utilization strategy;
S2, according to the optimized sunlight utilization strategy, adopting a current regulation technology to adjust the charging period of the energy storage equipment, adopting a voltage regulation technology to adjust the discharging period, and combining the sunlight real-time change and the predicted energy demand to implement dynamic energy balance to obtain an energy storage dispatching optimization scheme;
s3, utilizing an energy storage dispatching optimization scheme, adopting a load management controller to adjust the running time of a non-critical load, recording the adjusted execution condition, updating a load response strategy, and obtaining an optimized load management record;
s4, extracting energy consumption data from the optimized load management record, monitoring the energy output condition of the micro-grid through real-time monitoring configuration, adjusting energy distribution according to the energy consumption data, and generating an energy efficiency optimization strategy by finely adjusting a charge and discharge plan of the energy storage equipment;
And S5, adjusting energy allocation of the micro-grid based on an energy efficiency optimization strategy, and referring to performance data of the photovoltaic output and the energy storage equipment, implementing energy allocation operation and constructing an optical storage energy adjustment scheme.
The present invention is not limited to the above embodiments, and any equivalent embodiments which can be changed or modified by the technical disclosure described above can be applied to other fields, but any simple modification, equivalent changes and modification made to the above embodiments according to the technical matter of the present invention will still fall within the scope of the technical disclosure.

Claims (5)

1.一种光储充微电网能源管理系统，其特征在于，所述系统包括：1. A photovoltaic storage and charging microgrid energy management system, characterized in that the system includes: 光伏产出调整模块基于光伏发电实时产出的实时数据，调整光伏面板角度和操作频率，得到光伏发电效率，并结合实时天气变化和光照条件，调整输出并匹配能源需求，生成最优日光利用方案；The photovoltaic output adjustment module adjusts the photovoltaic panel angle and operating frequency based on the real-time data of photovoltaic power generation, obtains the photovoltaic power generation efficiency, and adjusts the output and matches the energy demand in combination with the real-time weather changes and light conditions to generate the optimal sunlight utilization plan; 储能调配模块利用所述最优日光利用方案，调整储能设备的充放电周期并匹配日光变化，平衡实时能源供应与需求峰值，获取储能效率数据，通过所述储能效率数据，并结合能源消耗趋势和预测需求，调整充放电策略，建立优化后的储能调度策略；The energy storage dispatching module uses the optimal sunlight utilization plan to adjust the charge and discharge cycle of the energy storage equipment and match the sunlight changes, balance the real-time energy supply and demand peak, obtain energy storage efficiency data, and adjust the charge and discharge strategy through the energy storage efficiency data and combined with the energy consumption trend and predicted demand to establish an optimized energy storage dispatching strategy; 负载管理与优化模块根据所述优化后的储能调度策略，实施动态负载管理，调整非关键负载的运行时段，得到负载调整执行记录，根据所述负载调整执行记录，通过实时负载数据调整负载响应，生成负载管理优化措施；The load management and optimization module implements dynamic load management according to the optimized energy storage scheduling strategy, adjusts the operating time period of non-critical loads, obtains load adjustment execution records, adjusts load response through real-time load data according to the load adjustment execution records, and generates load management optimization measures; 能效与资源优化模块基于所述负载管理优化措施，监测并分析光储充微电网的能源消耗与产出，调整能源分配并优化能源利用率，得到初始能效优化方案，并对储能设备的充放电计划进行微调，生成光储充能源调整方案；Based on the load management optimization measures, the energy efficiency and resource optimization module monitors and analyzes the energy consumption and output of the photovoltaic storage and charging microgrid, adjusts energy distribution and optimizes energy utilization, obtains an initial energy efficiency optimization plan, and fine-tunes the charging and discharging plan of the energy storage equipment to generate a photovoltaic storage and charging energy adjustment plan; 所述负载调整执行记录的获取步骤具体为：The steps of obtaining the load adjustment execution record are specifically as follows: 从所述优化后的储能调度策略中提取关键数据，结合当前实时能源供应状况，计算可调节非关键负载的时间窗口，通过公式：Extract key data from the optimized energy storage scheduling strategy, combine it with the current real-time energy supply status, and calculate the time window for adjusting non-critical loads. ； ; 生成调整后的运行时间，其中，代表优化后的储能调度策略，代表当前能源供应状态，表示调节系数，表示调节常数，表示调整后的运行时间；Generates the adjusted runtime where represents the optimized energy storage dispatch strategy, Represents the current energy supply status, represents the adjustment coefficient, represents the adjustment constant, represents the adjusted running time; 利用所述调整后的运行时间，参照设备响应时间，进行动态负载调整，应用公式：Using the adjusted run time, reference the equipment response time to perform dynamic load adjustment, applying the formula: ； ; 生成动态负载调整方案，其中，是调整后的运行时间，是设备的响应时间，是增强调整精度的乘数，是动态负载调整方案；Generate a dynamic load adjustment scheme where is the adjusted running time, is the response time of the device, is a multiplier that enhances the precision of the adjustment, It is a dynamic load adjustment scheme; 根据所述动态负载调整方案和实时运行数据，计算并记录负载调整的执行效果，采用公式：According to the dynamic load adjustment scheme and real-time operation data, the execution effect of the load adjustment is calculated and recorded, using the formula: ； ; 生成负载调整执行记录，其中，代表负载调整方案，是规避数值过小的常数，是负载调整执行记录；Generates a load adjustment execution record, where represents the load adjustment scheme, is a constant to avoid values that are too small. is the load adjustment execution record; 所述负载管理优化措施的获取步骤具体为：The steps for obtaining the load management optimization measures are specifically as follows: 根据所述负载调整执行记录和实时负载数据，采用公式：According to the load adjustment execution record and real-time load data, the formula is used: ； ; 评估当前的负载响应有效性，生成初步的负载响应评估结果，其中，表示负载调整执行记录，代表实时负载数据，是规避除零而加入的小正数，是根据历史数据定义的变量，是初步的负载响应评估结果，是权重系数；Evaluate the effectiveness of the current load response and generate preliminary load response evaluation results, including: Indicates the load adjustment execution record, Represents real-time load data, is a small positive number added to avoid division by zero, is a variable defined based on historical data. is the preliminary load response assessment result, is the weight coefficient; 根据所述初步的负载响应评估结果和设定的响应阈值，确定需调整的需求，采用公式：According to the preliminary load response evaluation results and the set response threshold, the demand to be adjusted is determined using the formula: ； ; 生成定制化调整策略，其中，是初步的负载响应评估结果，是响应阈值，是定制化调整策略，和是新引入的调节系数；Generate a customized adjustment strategy, where: is the preliminary load response assessment result, is the response threshold, It is a customized adjustment strategy. and is the newly introduced adjustment coefficient; 使用所述定制化调整策略，结合设备运行限制，确定并实施优化措施，采用公式：Using the customized adjustment strategy described above, combined with the equipment operating constraints, determine and implement optimization measures using the formula: ； ; 生成负载管理优化措施，其中，是定制化调整策略，是设备运行限制，表示实用系数，是负载管理优化措施，和表示调节公式的敏感度和扩展性；Generate load management optimization measures, where It is a customized adjustment strategy. It is the equipment operation limitation. represents the practical coefficient, is a load management optimization measure, and Indicates the sensitivity and scalability of the adjustment formula; 所述光储充能源调整方案的获取步骤具体为：The steps for obtaining the photovoltaic storage and charging energy adjustment plan are specifically as follows: 根据所述负载管理优化措施，捕捉光储充微电网的实时能源消耗和能源产出，应用公式：According to the load management optimization measures, the real-time energy consumption and energy output of the photovoltaic storage microgrid are captured, and the formula is applied: ； ; 生成初步能效评估结果，其中，是小正数，和是权重因子，代表能源消耗，代表能源产出，是初步能效评估结果；Generate preliminary energy efficiency assessment results, including: is a small positive number, and is the weight factor, represents energy consumption, Represents energy output, It is the result of the preliminary energy efficiency assessment; 基于所述初步能效评估结果，结合能源使用趋势，采用公式：Based on the preliminary energy efficiency assessment results and combined with energy usage trends, the formula is used: ； ; 生成调整后的能效优化方案，其中，是反应度调节系数，是初步能效评估结果，表示能源使用趋势，为调整后的能效优化方案；Generate an adjusted energy efficiency optimization plan, where: is the responsiveness adjustment coefficient, is the preliminary energy efficiency assessment result, Indicates energy usage trends, The energy efficiency optimization plan after adjustment; 利用所述调整后的能效优化方案，对储能设备的充放电计划进行微调，运用公式：Using the adjusted energy efficiency optimization scheme, fine-tune the charging and discharging plan of the energy storage equipment, using the formula: ； ; 得到光储充能源调整方案，其中，是调整因子，是需求预测误差，是能效优化方案，是光储充能源调整方案。Get the light storage and charging energy adjustment plan, where: is the adjustment factor, is the demand forecast error, It is an energy efficiency optimization solution. It is a solar storage and charging energy adjustment plan. 2.根据权利要求1所述的光储充微电网能源管理系统，其特征在于，所述光伏发电效率的获取步骤具体为：2. The photovoltaic storage and charging microgrid energy management system according to claim 1 is characterized in that the step of obtaining the photovoltaic power generation efficiency is specifically: 基于光伏发电实时产出的实时数据，测量光伏面板电流和电压，采用公式：Based on the real-time data of photovoltaic power generation, the current and voltage of the photovoltaic panel are measured using the formula: ； ; 通过测量值计算获取实时发电功率，其中，表示电流，表示电压，表示实时发电功率；The real-time power generation is obtained by calculating the measured values, where: represents the current, Indicates voltage, Indicates real-time power generation; 根据所述实时发电功率和从光照强度传感器中获取的光照角度，进行光伏面板角度的调整，优化发电量，重新设计并加入环境影响系数和光照强度，通过公式：According to the real-time power generation and the light angle obtained from the light intensity sensor, the angle of the photovoltaic panel is adjusted to optimize the power generation, and the environmental impact coefficient and light intensity are redesigned and added, through the formula: ； ; 生成调整后的发电功率，其中，是光照角度，是环境影响系数，是光照强度，表示调整后的发电功率，表示实时发电功率；Generates adjusted power generation, where is the lighting angle, is the environmental impact factor, is the light intensity, represents the adjusted power generation, Indicates real-time power generation; 结合所述调整后发电功率、当前天气数据、太阳辐射强度和设备总效能，进行发电效率的计算，使用公式：The power generation efficiency is calculated by combining the adjusted power generation, current weather data, solar radiation intensity and total equipment efficiency, using the formula: ； ; 得到光伏发电效率，其中，是天气数据，是太阳辐射强度，是设备效能，是设备效率调整参数，表示光伏发电效率，表示调整后的发电功率。The photovoltaic power generation efficiency is obtained, where It is weather data. is the solar radiation intensity, It is the equipment performance. is the equipment efficiency adjustment parameter, represents the photovoltaic power generation efficiency, Indicates the adjusted power generation. 3.根据权利要求2所述的光储充微电网能源管理系统，其特征在于，所述最优日光利用方案的获取步骤具体为：3. The photovoltaic storage and charging microgrid energy management system according to claim 2 is characterized in that the step of obtaining the optimal sunlight utilization plan is specifically: 基于所述光伏发电效率，通过光照强度传感器测量实时光照强度和当前天气状况，结合光伏面板的输出数据，计算日照调整因子，采用公式：Based on the photovoltaic power generation efficiency, the real-time light intensity and current weather conditions are measured by the light intensity sensor, combined with the output data of the photovoltaic panel, to calculate the sunshine adjustment factor using the formula: ； ; 生成调整后的能源输出数据，其中，表示光伏面板的输出功率，表示天气状况，表示光照强度，表示调整后的能源输出数据，表示日照调整因子；Generate adjusted energy output data where, Represents the output power of the photovoltaic panel, Indicates weather conditions. Indicates the light intensity, represents the adjusted energy output data, represents the sunshine adjustment factor; 使用所述调整后的能源输出数据，对比预测的能源需求，采用公式：Using the adjusted energy output data, compare to the forecasted energy demand using the formula: ； ; 计算并生成日光利用率，其中，是调整后的能源输出数据，是预测的能源需求，是光照强度，是日光利用率；Calculate and generate daylight utilization rate, where is the adjusted energy output data, is the predicted energy demand, is the light intensity, is the daylight utilization rate; 根据所述日光利用率和光照调整参数，优化光伏面板角度，使用公式：According to the sunlight utilization and light adjustment parameters, the photovoltaic panel angle is optimized using the formula: ； ; 生成最优日光利用方案，其中，代表日光利用率，代表光照角度，代表最优日光利用方案。Generate the optimal daylight utilization plan, where represents the daylight utilization rate, Represents the lighting angle, Represents the optimal daylight utilization solution. 4.根据权利要求3所述的光储充微电网能源管理系统，其特征在于，所述优化后的储能调度策略的获取步骤具体为：4. The photovoltaic storage and charging microgrid energy management system according to claim 3 is characterized in that the step of obtaining the optimized energy storage scheduling strategy is specifically: 根据所述最优日光利用方案和当前天气状况，调整储能设备的充电计划，应用公式：According to the optimal sunlight utilization plan and current weather conditions, the charging plan of the energy storage device is adjusted, and the formula is applied: ； ; 生成初步充电策略，其中，表示最优日光利用方案，表示当前的天气状况百分比，表示初步充电策略；Generate a preliminary charging strategy, where represents the optimal daylight utilization scheme, Indicates the current weather condition percentage, Indicates the preliminary charging strategy; 根据所述初步充电策略，结合预测的能源需求和储能设备的状态，采用公式：According to the preliminary charging strategy, combined with the predicted energy demand and the state of the energy storage device, the formula is adopted: ； ; 生成初步储能调度计划，其中，是初步充电策略，是储能设备的状态指示，是预测能源需求，是初步储能调度计划；Generate a preliminary energy storage dispatch plan, where: is the initial charging strategy, It is the status indicator of the energy storage device. is to predict energy demand, It is the preliminary energy storage dispatch plan; 利用所述初步储能调度计划和市场能源价格，优化充放电策略，运用公式：Using the preliminary energy storage scheduling plan and market energy prices, the charging and discharging strategy is optimized using the formula: ； ; 生成优化后的储能调度策略，其中，代表初步储能调度计划，代表市场能源价格，表示优化后的储能调度策略。Generate an optimized energy storage dispatch strategy, where: Represents the preliminary energy storage dispatch plan, represents the market energy price, Represents the optimized energy storage scheduling strategy. 5.一种光储充微电网能源管理方法，其特征在于，根据权利要求1-4任一项所述的光储充微电网能源管理系统执行，包括以下步骤：5. A method for managing energy in a photovoltaic storage and charging microgrid, characterized in that it is implemented according to the photovoltaic storage and charging microgrid energy management system according to any one of claims 1 to 4, comprising the following steps: 基于光伏发电实时产出的实时数据，分析当前光照强度和天气状况，通过电机控制调节面板角度，利用变频器调整操作频率，计算得出优化后的日光利用策略；Based on the real-time data of photovoltaic power generation, the current light intensity and weather conditions are analyzed, the panel angle is adjusted through motor control, the operating frequency is adjusted using the inverter, and the optimized daylight utilization strategy is calculated; 根据所述优化后的日光利用策略，采用电流调节技术调整储能设备的充电周期，使用电压调节技术调整放电周期，结合日光实时变化和预测能源需求，实施动态能源平衡，获取储能调度优化方案；According to the optimized sunlight utilization strategy, the charging cycle of the energy storage device is adjusted by using current regulation technology, and the discharge cycle is adjusted by using voltage regulation technology. In combination with the real-time changes of sunlight and the predicted energy demand, dynamic energy balance is implemented to obtain the energy storage scheduling optimization plan; 利用所述储能调度优化方案，采用负载管理控制器调整非关键负载的运行时间，记录调整后的执行情况，更新负载响应策略，获取优化负载管理记录；Utilizing the energy storage scheduling optimization scheme, using a load management controller to adjust the operating time of non-critical loads, recording the adjusted execution status, updating the load response strategy, and obtaining optimized load management records; 从所述优化负载管理记录中提取能源消耗数据，通过实时监控配置监控微电网能源产出情况，根据能源消耗数据调整能源分配，通过细化调整储能设备的充放电计划，生成能效优化策略；Extracting energy consumption data from the optimized load management record, monitoring the energy output of the microgrid through real-time monitoring configuration, adjusting energy distribution according to the energy consumption data, and generating energy efficiency optimization strategies by refining and adjusting the charging and discharging plans of the energy storage equipment; 基于所述能效优化策略，调整微电网的能源调配，参照光伏产出和储能设备性能数据，实施能源调配操作，构建光储充能源调整方案。Based on the energy efficiency optimization strategy, the energy allocation of the microgrid is adjusted, and the energy allocation operation is implemented with reference to the photovoltaic output and energy storage equipment performance data to build a photovoltaic storage and charging energy adjustment plan.
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