A photoelectric storage and charging microgrid energy management system and method

Abstract

The present invention relates to the field of microgrid management technology, specifically to a photovoltaic storage and charging microgrid energy management system and method, the system includes a photovoltaic output adjustment module, an energy storage allocation module, a load management and optimization module, and an energy efficiency and resource optimization module. In the present invention, by adjusting the photovoltaic panel angle and operating frequency in real time, photovoltaic power generation is more efficient in an environment with unstable sunlight, greatly improving the utilization rate of solar energy resources, intelligently adjusting the charging and discharging cycle of the energy storage device to match the real-time sunlight changes and energy demand, effectively utilizing the energy storage system, reducing energy waste and balancing supply and demand, real-time load management optimizes power distribution, dynamically adjusts the power grid to respond to load changes, and reduces the energy consumption of non-critical loads. This comprehensive energy management improves the energy efficiency and economy of the microgrid, enhances the adaptability to external interference and system resilience, and ensures energy self-sufficiency in emergency situations.

Description

Technical Field

[0001] The present invention relates to the technical field of microgrid management, and in particular to a photovoltaic storage and charging microgrid energy management system and method. Background Art

[0002] The field of microgrid management technology involves the design, monitoring and optimization of local power grids (microgrids). The power grid can operate independently when disconnected and connected to the main power grid. The technology includes the coordination of energy generation (such as solar photovoltaics), energy storage (such as battery energy storage systems) and energy consumption. The core purpose of microgrid management is to improve energy utilization efficiency, ensure the reliability of energy supply, reduce environmental impact, and enhance the system's resilience to external interference. Technological advances in the field also include advanced algorithms and control strategies for real-time data monitoring, forecasting energy demand, automatic adjustment of energy flow and maintenance of grid stability.

[0003] Among them, the photovoltaic storage and charging microgrid energy management system is an integrated system that combines solar power generation, energy storage and energy charging management. The system is mainly used in microgrids to ensure the effective use of electricity and the reliability of power supply through intelligent control and management of photovoltaic power generation, storage process and subsequent power distribution. The purpose of this system is to maximize the utilization of solar energy resources, solve the intermittent problem of solar power generation through energy storage, optimize the supply and demand of electricity, improve the energy efficiency and economy of the entire microgrid, and support energy self-sufficiency in disaster emergency situations, and enhance the independent operation capability of the microgrid.

[0004] Although existing microgrid management technologies support independent operation and connection or disconnection with the main grid, they are still limited in terms of dynamic matching and real-time optimization of energy output and consumption. In particular, in the use of solar photovoltaic power generation, existing technologies fail to adjust power generation strategies in real time to cope with sudden weather conditions, resulting in a significant drop in solar power generation efficiency on cloudy or rainy days. The management of energy storage equipment mostly relies on preset charging and discharging cycles and lacks the ability to adjust flexibly, which can easily lead to insufficient or excessive energy supply when power demand fluctuates greatly. The load management in existing technologies is also relatively fixed and fails to make full use of real-time data for optimization, resulting in the risk of insufficient power supply during peak periods of power demand, limiting the overall performance and efficiency of microgrids, increasing operating costs and affecting the system's ability to respond to emergencies. Summary of the invention

[0005] The purpose of the present invention is to solve the shortcomings of the prior art and to propose a photovoltaic storage and charging microgrid energy management system and method.

[0006] In order to achieve the above-mentioned purpose, the present invention adopts the following technical scheme: A photovoltaic storage and charging microgrid energy management system comprises:

[0007] 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;

[0008] 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;

[0009] 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;

[0010] 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.

[0011] As a further solution of the present invention, the step of obtaining the photovoltaic power generation efficiency is specifically as follows:

[0012] Based on the real-time data of photovoltaic power generation, the current and voltage of the photovoltaic panel are measured using the formula:

[0013] ;

[0014] The real-time power generation is obtained by calculating the measured values, where: represents the current, Indicates voltage, Indicates real-time power generation;

[0015] 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:

[0016] ;

[0017] 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;

[0018] 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:

[0019] ;

[0020] 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.

[0021] As a further solution of the present invention, the steps for obtaining the optimal sunlight utilization plan are specifically as follows:

[0022] 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:

[0023] ;

[0024] 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;

[0025] Using the adjusted energy output data, compare to the forecasted energy demand using the formula:

[0026] ;

[0027] 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;

[0028] According to the sunlight utilization and light adjustment parameters, the photovoltaic panel angle is optimized using the formula:

[0029] ;

[0030] Generate the optimal daylight utilization plan, where represents the daylight utilization rate, Represents the lighting angle, Represents the optimal daylight utilization solution.

[0031] As a further solution of the present invention, the steps for obtaining the optimized energy storage scheduling strategy are specifically as follows:

[0032] 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:

[0033] ;

[0034] Generate a preliminary charging strategy, where represents the optimal daylight utilization scheme, Indicates the current weather condition percentage, Indicates the preliminary charging strategy;

[0035] According to the preliminary charging strategy, combined with the predicted energy demand and the state of the energy storage device, the formula is adopted:

[0036] ;

[0037] 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;

[0038] Using the preliminary energy storage scheduling plan and market energy prices, the charging and discharging strategy is optimized using the formula:

[0039] ;

[0040] 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.

[0041] As a further solution of the present invention, the step of acquiring the load adjustment execution record is specifically as follows:

[0042] 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.

[0043] ;

[0044] 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;

[0045] Using the adjusted run time, reference the equipment response time to perform dynamic load adjustment, applying the formula:

[0046] ;

[0047] 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;

[0048] 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:

[0049] ;

[0050] Generates a load adjustment execution record, where represents the load adjustment scheme, is a constant to avoid values ​​that are too small. It is the load adjustment execution record.

[0051] As a further solution of the present invention, the steps of obtaining the load management optimization measures are specifically as follows:

[0052] According to the load adjustment execution record and real-time load data, the formula is used:

[0053] ;

[0054] 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;

[0055] According to the preliminary load response evaluation results and the set response threshold, the demand to be adjusted is determined using the formula:

[0056] ;

[0057] 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;

[0058] Using the customized adjustment strategy described above, combined with the equipment operating constraints, determine and implement optimization measures using the formula:

[0059] ;

[0060] 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.

[0061] As a further solution of the present invention, the steps for obtaining the solar energy storage and charging adjustment solution are specifically as follows:

[0062] 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:

[0063] ;

[0064] 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;

[0065] Based on the preliminary energy efficiency assessment results and combined with energy usage trends, the formula is used:

[0066] ;

[0067] 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;

[0068] Using the adjusted energy efficiency optimization scheme, fine-tune the charging and discharging plan of the energy storage equipment, using the formula:

[0069] ;

[0070] 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.

[0071] A method for managing energy in a photovoltaic storage and charging microgrid is provided, wherein the method is implemented based on the photovoltaic storage and charging microgrid energy management system, and comprises the following steps:

[0072] S1: 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;

[0073] S2: 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;

[0074] S3: using the energy storage scheduling optimization solution, 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;

[0075] S4: 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 an energy efficiency optimization strategy by refining and adjusting the charging and discharging plan of the energy storage device;

[0076] S5: Based on the energy efficiency optimization strategy, adjust the energy allocation of the microgrid, refer to the photovoltaic output and energy storage equipment performance data, implement energy allocation operations, and build a photovoltaic storage and charging energy adjustment plan.

[0077] Compared with the prior art, the advantages and positive effects of the present invention are:

[0078] In the present invention, by adjusting the angle and operating frequency of the photovoltaic panel to adapt to real-time light and weather changes, the dynamic optimization of power output is achieved, making photovoltaic power generation more efficient, especially in an environment with unstable sunlight, every ray of sunlight can be effectively utilized, greatly improving the utilization rate of solar energy resources. By intelligently adjusting the charging and discharging cycle of the energy storage device to match the real-time sunlight changes and energy demand, the energy storage system is fully utilized, energy waste is reduced and supply and demand are balanced. The power distribution is optimized through real-time load management, and the power grid is dynamically adjusted according to the load adjustment record, so that non-critical loads can reduce energy consumption when demand is low, and the overall energy efficiency and economy of the system are improved. Comprehensive energy management not only improves the energy efficiency of the microgrid, but also enhances the system's adaptability and resilience to external interference, especially in emergency situations, it can maintain energy self-sufficiency. BRIEF DESCRIPTION OF THE DRAWINGS

[0079] Figure 1 is a system flow chart of the present invention;

[0080] Figure 2 It is a flow chart of photovoltaic power generation efficiency in the present invention;

[0081] Figure 3 This is a flow chart of the optimal sunlight utilization scheme in the present invention;

[0082] Figure 4 This is a flow chart of the optimized energy storage scheduling strategy in the present invention;

[0083] Figure 5 A flow chart of a load adjustment execution record in the present invention;

[0084] Figure 6 A flow chart of load management optimization measures in the present invention;

[0085] Figure 7 It is a flow chart of the solar energy storage and charging adjustment scheme in the present invention. DETAILED DESCRIPTION

[0086] In order to make the purpose, technical solution and advantages of the present invention more clearly understood, the present invention is further described in detail below in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present invention and are not intended to limit the present invention.

[0087] In the description of the present invention, it should be understood that the terms "length", "width", "up", "down", "front", "back", "left", "right", "vertical", "horizontal", "top", "bottom", "inside", "outside" and the like indicate positions or positional relationships based on the positions or positional relationships shown in the drawings, and are only for the convenience of describing the present invention and simplifying the description, rather than indicating or implying that the device or element referred to must have a specific orientation, be constructed and operated in a specific orientation, and therefore cannot be understood as limiting the present invention. In addition, in the description of the present invention, "multiple" means two or more, unless otherwise clearly and specifically defined.

[0088] See also Figure 1 The present invention provides a technical solution: a photovoltaic storage and charging microgrid energy management system comprising:

[0089] 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;

[0090] The energy storage dispatch 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, combined with energy consumption trends and predicted demand, to establish an optimized energy storage dispatch strategy;

[0091] The load management and optimization module implements dynamic load management according to the optimized energy storage scheduling strategy, adjusts the operating time 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;

[0092] The energy efficiency and resource optimization module monitors and analyzes the energy consumption and output of the photovoltaic storage and charging microgrid based on load management optimization measures, adjusts energy distribution and optimizes energy utilization, obtains the 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.

[0093] Photovoltaic power generation efficiency includes angle optimization, frequency optimization, and weather adaptability. The optimal sunlight utilization plan includes angle optimization, frequency matching, and demand response capability. Energy storage efficiency data includes charging efficiency, discharge efficiency, and supply and demand balance indicators. The optimized energy storage scheduling strategy includes charging strategy fine-tuning, discharge strategy fine-tuning, and demand forecast matching. Load adjustment execution records include time period adjustment details, data adjustment response, and improved operating efficiency. Load management optimization measures include refinement of management strategies, improved response speed, and enhanced load adaptability. The initial energy efficiency optimization plan includes consumption reduction measures, output efficiency improvement, and distribution efficiency optimization. The light storage and charging energy adjustment plan includes power generation scheduling optimization, energy storage scheduling fine-tuning, and utilization maximization.

[0094] See also Figure 2 , the specific steps for obtaining photovoltaic power generation efficiency are:

[0095] Based on the real-time data of photovoltaic power generation, the current and voltage of the photovoltaic panel are measured using the formula:

[0096] ;

[0097] The real-time power generation is obtained by calculating the measured values, where: represents the current, Indicates voltage, Indicates real-time power generation;

[0098] 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:

[0099] ;

[0100] 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;

[0101] 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:

[0102] ;

[0103] 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.

[0104] Real-time power generation formula:

[0105] ;

[0106] : Current, in amperes (A), assumed to be measured by a sensor;

[0107] : Voltage, in volts (V), assumed to be measured by a sensor;

[0108] Assuming current A, assuming voltage V;

[0109] calculate :

[0110] ;

[0111] here W represents the real-time power generation which is 60 watts.

[0112] Adjusted power generation formula:

[0113] ;

[0114] : Environmental impact coefficient, assuming that factors such as temperature and humidity are taken into account;

[0115] : Light angle, obtained through the light angle sensor;

[0116] : Light intensity, in lumens (Im), obtained through the light intensity sensor;

[0117] Assumptions , assuming , assuming ;

[0118] calculate :

[0119] ;

[0120] here W means the adjusted power generation is 2.33 watts.

[0121] Photovoltaic power generation efficiency formula:

[0122] ;

[0123] : Equipment efficiency adjustment parameters, taking into account the maintenance status and aging of the equipment;

[0124] : solar radiation intensity, in watts per square meter (W / m²);

[0125] : Equipment efficiency, including power factor;

[0126] : Influence of weather conditions, such as shadows, cloud cover, etc.;

[0127] Assumptions , assuming W / , assuming W, assuming units;

[0128] calculate :

[0129] ;

[0130] here It means that the efficiency of photovoltaic power generation is very low, either because of poor lighting conditions or low equipment efficiency.

[0131] See also Figure 3 , the specific steps for obtaining the optimal daylight utilization plan are:

[0132] 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:

[0133] ;

[0134] 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;

[0135] Use the adjusted energy output data to compare the forecasted energy demand using the formula:

[0136] ;

[0137] 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;

[0138] Adjust parameters according to sunlight utilization and illumination, optimize the photovoltaic panel angle, and use the formula:

[0139] ;

[0140] Generate the optimal daylight utilization plan, where represents the daylight utilization rate, Represents the lighting angle, Represents the optimal daylight utilization solution.

[0141] Adjusted energy output data formula:

[0142] ;

[0143] : The output power of the photovoltaic panel, assuming it is read directly by an electric meter, in kilowatts (kW);

[0144] : Weather conditions, assumed to be a simplified value representing the percentage of cloud cover;

[0145] : Light intensity, measured by a light sensor, in watts per square meter (W / m2);

[0146] : Sunlight adjustment factor, assumed to be , to avoid division by zero errors and simplify calculations;

[0147] Assumptions kW, assuming , assuming W / ;

[0148] calculate :

[0149] ;

[0150] ;

[0151] here kW represents the adjusted energy output of 49.4 kilowatts for a given light intensity and weather conditions.

[0152] The formula for daylight utilization is:

[0153] ;

[0154] : The adjusted energy output calculated in the previous step;

[0155] : predicted energy demand, assumed to be based on historical data and weather forecast models, in kilowatts (kW);

[0156] : Light intensity, mentioned in the previous step;

[0157] Assumed parameters: Use the parameters calculated in the previous step kW, assuming kW;

[0158] calculate :

[0159] ;

[0160] Indicates the current daylight utilization rate.

[0161] Optimal daylight utilization solution formula:

[0162] ;

[0163] : The daylight utilization rate calculated in the previous step;

[0164] : The illumination angle is assumed to be adjusted by the automatic tracking system to maximize the capture of sunlight, and the angle value is 30 degrees;

[0165] Assumed parameters: Use step 2 , assuming ;

[0166] Calculation process:

[0167] ;

[0168] ;

[0169] Represents the score of the optimal daylight utilization plan. The larger the value, the more effective the daylight utilization.

[0170] See also Figure 4 , the specific steps for obtaining the optimized energy storage scheduling strategy are:

[0171] According to the optimal sunlight utilization plan and current weather conditions, adjust the charging plan of the energy storage equipment and apply the formula:

[0172] ;

[0173] Generate a preliminary charging strategy, where represents the optimal daylight utilization scheme, Indicates the current weather condition percentage, Indicates the preliminary charging strategy;

[0174] According to the preliminary charging strategy, combined with the predicted energy demand and the status of the energy storage device, the formula is adopted:

[0175] ;

[0176] 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;

[0177] Using the preliminary energy storage dispatch plan and market energy prices, the charging and discharging strategy is optimized using the formula:

[0178] ;

[0179] 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.

[0180] Preliminary charging strategy formula:

[0181] ;

[0182] : The efficiency of the optimal sunlight utilization scheme, assumed to be obtained from the real-time monitoring data of the photovoltaic system;

[0183] : Weather condition percentage, assumed to be obtained through the weather forecast API;

[0184] Assumption parameters: Assumptions (75% efficiency), assuming (%);

[0185] calculate :

[0186] ;

[0187] This result It means that under the current weather conditions, the initial charging strategy adjusted based on the optimal sunlight utilization plan has a charging efficiency of 90%.

[0188] Preliminary energy storage dispatch plan formula:

[0189] ;

[0190] : The preliminary charging strategy calculated in the previous step;

[0191] : Status indication of the energy storage device, assuming this is obtained from the device's health monitoring system;

[0192] : Forecasted energy demand, assumed to be calculated through historical data analysis and future demand forecasting models;

[0193] Assumption parameters: Use the parameters obtained in the previous step , assuming (95% device health), assuming (kW demand);

[0194] calculate :

[0195] ;

[0196] This result This indicates that the current actual energy storage scheduling plan is very inefficient, which reflects the impact of equipment health or the challenge of energy consumption demand.

[0197] Optimized energy storage scheduling strategy formula:

[0198] ;

[0199] : The actual energy storage dispatch plan obtained from the previous step;

[0200] : Market energy price, assumed to be obtained through real-time data from the energy market;

[0201] Assumption parameters: Use the parameters obtained in the previous step , assuming (%);

[0202] calculate :

[0203] ;

[0204] This result It represents the efficiency of the final optimized energy storage dispatch strategy, adjusted to the response after changes in market energy prices.

[0205] See also Figure 5 , the specific steps for obtaining the load adjustment execution record are:

[0206] Extract key data from the optimized energy storage scheduling strategy, combine it with the current real-time energy supply situation, and calculate the time window for adjusting non-critical loads.

[0207] ;

[0208] 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;

[0209] Using the adjusted run time, refer to the equipment response time for dynamic load adjustment, applying the formula:

[0210] ;

[0211] 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;

[0212] According to the dynamic load adjustment scheme and real-time operation data, calculate and record the execution effect of load adjustment, using the formula:

[0213] ;

[0214] Generates a load adjustment execution record, where represents the load adjustment scheme, is a constant to avoid values ​​that are too small. It is the load adjustment execution record.

[0215] The formula for adjusted run time is:

[0216] ;

[0217] : The efficiency of the optimized energy storage dispatch strategy is obtained through the analysis tools of the energy management system;

[0218] : The current energy supply status is obtained in real time through the monitoring equipment of the energy supply system;

[0219] : Adjustment coefficient, determined based on historical data and forecasting models, used to adjust load time to adapt to changes in energy supply;

[0220] : Adjust constants to increase the flexibility of the formula to handle unexpected or extreme situations;

[0221] Assume the parameter values ​​are: (80% efficiency), (Unit: kilowatt), (Adjustment coefficient), (Adjustment constant);

[0222] calculate :

[0223] ;

[0224] This result It means that under the given supply and scheduling strategy, the ideal operating time of non-critical load is 0.001067 unit time.

[0225] Dynamic load adjustment scheme formula:

[0226] ;

[0227] : The load running time calculated in the previous step;

[0228] : The response time of the device, obtained from the device specifications and operation records;

[0229] : A multiplier used to enhance adjustment accuracy, set according to device performance and operating environment;

[0230] Assume that the parameter value is: Use the value calculated in the previous step , (Unit: seconds), ;

[0231] calculate :

[0232] ;

[0233] This result A detailed load adjustment scheme needs to consider the impact of equipment response time and adjustment multiplier.

[0234] Load adjustment execution record formula:

[0235] ;

[0236] : The load adjustment solution obtained in the previous step;

[0237] : In order to avoid the value being too small to be handled, the added constant is usually set to 1 or a smaller positive number to keep the value stable;

[0238] Assume that the parameter value is: Use the value calculated in the previous step , ;

[0239] calculate :

[0240] ;

[0241] This result The value of the execution record is displayed, indicating the effective record of the adjustment execution.

[0242] See also Figure 6 , the steps for obtaining load management optimization measures are as follows:

[0243] Based on the load adjustment execution record and real-time load data, the formula is used:

[0244] ;

[0245] 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;

[0246] Based on the preliminary load response assessment results and the set response threshold, determine the demand that needs to be adjusted using the formula:

[0247] ;

[0248] 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;

[0249] Use a customized tuning strategy to identify and implement optimization measures in conjunction with equipment operating constraints, using the formula:

[0250] ;

[0251] 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.

[0252] The formula for the preliminary load response assessment result is:

[0253] ;

[0254] : Load adjustment execution record, actual record obtained from the energy management system;

[0255] : Real-time load data, collected in real time through sensors and monitoring systems;

[0256] : A small positive number, used to prevent division by zero errors, set to 0.01;

[0257] : A variable adjusted based on historical data, reflecting the effect of past treatments on similar situations, set to an empirical value of 1.5;

[0258] : Weight coefficient, adjusted to adapt to different load changes, determined through simulation and optimization process, here set ;

[0259] Assumptions ;

[0260] Calculation process:

[0261] ;

[0262] This suggests that given the real-time data and historical experience, an initial estimate of the load response is approximately 0.375.

[0263] The formula for the customized adjustment strategy:

[0264] ;

[0265] : Evaluation of the load response calculated in the previous step;

[0266] : The preset response threshold is set to 0.5 based on historical effects and safety standards;

[0267] : Gain coefficient, adjust the sensitivity of the response, set to 2;

[0268] : Enhance the nonlinear effect of adjustment, set to 1.5;

[0269] Assume that the parameter value is: Using the above value ;

[0270] calculate :

[0271] ;

[0272] This suggests that the need for further adjustment is reduced by the adjustment factor and threshold.

[0273] Load management optimization measures formula:

[0274] ;

[0275] : The adjustment plan generated in the previous step;

[0276] : Equipment operation limit, determined according to equipment performance parameters, set to 200;

[0277] : Practical coefficient, adjusted according to operating experience, set to 0.8;

[0278] : Used to adjust the sensitivity and scalability of the formula. ;

[0279] Use the above Value 0.218;

[0280] calculate :

[0281] ;

[0282] This means that the final optimization measure value is very small, indicating that the adjustment measure has a slight impact on the current load and needs to be evaluated whether it has a sufficient impact on system performance.

[0283] See also Figure 7 , the specific steps for obtaining the solar storage and charging energy adjustment plan are:

[0284] 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:

[0285] ;

[0286] 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;

[0287] Based on the preliminary energy efficiency assessment results and combined with energy usage trends, the formula is used:

[0288] ;

[0289] 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;

[0290] Using the adjusted energy efficiency optimization plan, fine-tune the charging and discharging plan of the energy storage equipment, using the formula:

[0291] ;

[0292] 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.

[0293] Preliminary energy efficiency assessment result formula:

[0294] ;

[0295] : Energy output (e.g. photovoltaic power generation);

[0296] : Energy consumption (e.g. energy consumption);

[0297] : A small constant to avoid division by zero errors, usually ;

[0298] : Adjustment coefficient, the weight that affects output and consumption;

[0299] Assume that in a photovoltaic system, the total energy output in a day is The energy consumption is 500kWh. For 450kWh, set , , ;

[0300] calculate :

[0301] ;

[0302] ;

[0303] ;

[0304] This means that the energy efficiency ratio is about 5.905, and a high energy efficiency ratio reflects better energy utilization efficiency.

[0305] Adjusted energy efficiency optimization solution formula:

[0306] ;

[0307] : The preliminary energy efficiency evaluation results obtained from the previous step;

[0308] : Energy use trend percentage;

[0309] : Trend response adjustment coefficient;

[0310] Assumed energy use trends It is 5%, the adjustment factor ;

[0311] calculate :

[0312] ;

[0313] ;

[0314] ;

[0315] The optimized energy efficiency solution obtained here It increases to 6.121, showing the improvement of energy efficiency as the trend increases.

[0316] The formula for adjusting the light storage and charging energy is as follows:

[0317] ;

[0318] : The adjusted energy efficiency optimization solution obtained from the previous step;

[0319] : Demand forecast error adjustment factor;

[0320] : Percentage of forecast demand error;

[0321] Assuming the prediction error The adjustment factor is 2%. ;

[0322] calculate :

[0323] ;

[0324] ;

[0325] The final solar energy storage and charging adjustment plan Adjusted to 5.773, taking into account the error in demand forecast.

[0326] A method for managing energy in a photovoltaic storage and charging microgrid is provided. The method for managing energy in a photovoltaic storage and charging microgrid is implemented based on the photovoltaic storage and charging microgrid energy management system, and comprises the following steps:

[0327] S1: 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;

[0328] S2: Based on the optimized sunlight utilization strategy, current regulation technology is used to adjust the charging cycle of energy storage equipment, and voltage regulation technology is used to adjust the discharge cycle. Combined with the real-time changes in sunlight and predicted energy demand, dynamic energy balance is implemented to obtain an energy storage scheduling optimization plan;

[0329] S3: Using the energy storage scheduling optimization solution, the load management controller is used to adjust the operating time of non-critical loads, record the adjusted execution status, update the load response strategy, and obtain the optimized load management record;

[0330] S4: Extract energy consumption data from the optimized load management records, monitor the energy output of the microgrid through real-time monitoring configuration, adjust energy distribution according to energy consumption data, and generate energy efficiency optimization strategies by refining and adjusting the charging and discharging plans of energy storage devices;

[0331] S5: Based on the energy efficiency optimization strategy, adjust the energy allocation of the microgrid, refer to the photovoltaic output and energy storage equipment performance data, implement energy allocation operations, and build a photovoltaic storage and charging energy adjustment plan.

[0332] The above are only preferred embodiments of the present invention and are not intended to limit the present invention in other forms. Any technician familiar with the profession may use the technical contents disclosed above to change or modify them into equivalent embodiments with equivalent changes and apply them to other fields. However, any simple modification, equivalent change and modification made to the above embodiments based on the technical essence of the present invention without departing from the technical solution of the present invention still falls within the protection scope of the technical solution of the present invention.

Claims

1. A photovoltaic storage and charging microgrid energy management system, characterized in that: The system comprises: 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; 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; 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; 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; The steps of obtaining the load adjustment execution record are specifically as follows: 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. ； 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, Indicates the adjusted running time; Using the adjusted run time, reference the equipment response time to perform dynamic load adjustment, applying the formula: ； 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; 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: ； 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; The steps for obtaining the load management optimization measures are specifically as follows: According to the load adjustment execution record and real-time load data, the formula is used: ； 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; According to the preliminary load response evaluation results and the set response threshold, the demand to be adjusted is determined using the formula: ； 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; Using the customized adjustment strategy described above, combined with the equipment operating constraints, determine and implement optimization measures using the formula: ； 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; The steps for obtaining the photovoltaic storage and charging energy adjustment plan are specifically as follows: 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: ； 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 preliminary energy efficiency assessment result; Based on the preliminary energy efficiency assessment results and combined with energy usage trends, the formula is used: ； 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; Using the adjusted energy efficiency optimization scheme, fine-tune the charging and discharging plan of the energy storage equipment, using the formula: ； 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. The photovoltaic storage and charging microgrid energy management system according to claim 1 is characterized in that: The steps for obtaining the photovoltaic power generation efficiency are specifically as follows: Based on the real-time data of photovoltaic power generation, the current and voltage of the photovoltaic panel are measured using the formula: ； The real-time power generation is obtained by calculating the measured values, where: represents the current, Indicates voltage, Indicates real-time power generation; 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: ； 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; 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: ； 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. The photovoltaic storage and charging microgrid energy management system according to claim 2 is characterized in that: The steps for obtaining the optimal daylight utilization plan are specifically as follows: 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: ； 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; Using the adjusted energy output data, compare to the forecasted energy demand using the formula: ； 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; According to the sunlight utilization and light adjustment parameters, the photovoltaic panel angle is optimized using the formula: ； Generate the optimal daylight utilization plan, where represents the daylight utilization rate, Represents the lighting angle, Represents the optimal daylight utilization solution.

4. The photovoltaic storage and charging microgrid energy management system according to claim 3 is characterized in that: The steps for obtaining the optimized energy storage scheduling strategy are specifically as follows: 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: ； Generate a preliminary charging strategy, where represents the optimal daylight utilization scheme, Indicates the current weather condition percentage, Indicates the preliminary charging strategy; According to the preliminary charging strategy, combined with the predicted energy demand and the state of the energy storage device, the formula is adopted: ； 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; Using the preliminary energy storage scheduling plan and market energy prices, the charging and discharging strategy is optimized using the formula: ； 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. A method for energy management of a photovoltaic storage and charging microgrid, characterized in that: The photovoltaic storage and charging microgrid energy management system according to any one of claims 1 to 4 comprises the following steps: 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; According to the optimized sunlight utilization strategy, current regulation technology is used to adjust the charging cycle of the energy storage equipment, and voltage regulation technology is used to adjust the discharge cycle. In combination with real-time changes in sunlight and predicted energy demand, dynamic energy balance is implemented to obtain an energy storage scheduling optimization plan; 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; 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 plan of the energy storage device; 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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