Control method and device of optical storage system and storage medium

Abstract

The application discloses a control method and device of a light storage system and a storage medium, relates to the technical field of new energy, and comprises the following steps: in the grid-connected mode of the light storage system, determining the standby power demand of different hierarchical loads in each period according to the standby time of the different hierarchical loads in each period; determining the lower limit value of the SOC of the energy storage battery corresponding to each period based on the standby power demand, constructing the SOC constraint condition of the energy storage battery based on the lower limit value of the SOC of the energy storage battery, and optimizing the output plan of each energy equipment in the light storage system with the maximum economic benefit as the target; and obtaining a first output plan containing the output of each energy equipment corresponding to each period based on the first optimization result, so as to control each energy equipment in each period based on the first output plan. Through the scheme of the application, the emergency standby capacity reservation demand and the daily power economic efficiency can be considered at the same time in the grid-connected operation stage of the light storage system.

Description

Technical Field

[0001] This application relates to the field of new energy technology, and in particular to control methods, devices and storage media for photovoltaic energy storage systems. Background Technology

[0002] Currently, the grid-connected scheduling of photovoltaic (PV) and energy storage (ESS) systems mainly adopts a fixed lower limit for energy storage SOC to reserve capacity uniformly, and optimizes the output plan of each energy device in the PV-ESS system with the goal of maximizing economic benefits. This one-size-fits-all approach of reserving backup capacity with a fixed lower limit for energy storage SOC has several drawbacks. During periods of high power generation, too much backup capacity is reserved, resulting in surplus power that cannot be fed into the grid or used internally, leading to wasted economic benefits. Conversely, during periods of insufficient power supply and high load, the reserved backup capacity is insufficient, and critical loads cannot support the preset backup duration after a sudden power outage, resulting in emergency protection failure. In other words, the existing backup capacity reservation method has the defect of not being able to simultaneously consider backup power demand and electricity economy during the grid-connected operation of PV-ESS systems. Summary of the Invention

[0003] The main purpose of this application is to provide a control method, device and storage medium for a photovoltaic energy storage system, which aims to solve the technical problem of how to simultaneously consider the reserve of backup power demand and the economic efficiency of electricity consumption when the photovoltaic energy storage system is connected to the grid.

[0004] To achieve the above objectives, this application proposes a control method for a photovoltaic energy storage system, comprising: In the grid-connected mode of the photovoltaic-storage system, the backup power demand corresponding to different levels of load in each time period is determined according to the backup power duration corresponding to different levels of load in each time period. Based on the backup power demand, the lower limit of the SOC of the energy storage battery for each time period is determined, and the SOC constraint conditions of the energy storage battery are constructed based on the lower limit of the SOC of the energy storage battery. Based on the SOC constraint of the energy storage battery and with the goal of maximizing economic benefits, the output plan of each energy device in the photovoltaic-storage system is optimized. Based on the first optimization result, a first output plan is obtained, which includes the output of each energy device in each time period, so as to control each energy device accordingly in each time period based on the first output plan.

[0005] In one embodiment, determining the backup power demand corresponding to different load levels in each time period, based on the backup power duration corresponding to different load levels in each time period, includes: Obtain the backup power duration corresponding to different load levels in different time periods. The importance of different load levels varies, and the backup power duration is positively correlated with the importance of the load level. For a single time period, the backup power demand for each load level is determined by comparing the backup power duration for each load level within that time period with the duration of the single time period.

[0006] In one embodiment, determining the backup power demand for each load level in a single time period, based on a comparison between the backup power duration corresponding to each load level in a single time period and the duration of the single time period, includes: For a single tiered load, if the duration of a single time period is less than or equal to the backup power duration, the backup power requirement for the single tiered load is determined based on the rated power of all loads under the single tiered load. If the duration of a single time period is greater than the backup power duration, the preset value will be used as the backup power demand for a single tiered load, where the preset value is zero.

[0007] In one embodiment, determining the backup power demand for each load level in a single time period, based on a comparison between the backup power duration corresponding to each load level in a single time period and the duration of the single time period, includes: For a single tiered load, if the duration of a single time period is less than or equal to the backup power duration, the backup power demand corresponding to the single tiered load can be predicted based on the historical data of the single tiered load. If the duration of a single time period is greater than the backup power duration, the preset value will be used as the backup power demand for a single tiered load, where the preset value is zero.

[0008] In one embodiment, determining the lower limit of the SOC of the energy storage battery for each time period based on the backup power demand includes: For a single time period, the minimum remaining power of the energy storage battery is determined based on the backup power demand corresponding to each level of load. The lower limit of SOC of the energy storage battery for a single time period is determined based on the minimum remaining charge of the energy storage battery, the installed capacity of the energy storage battery, and the safe lower boundary value of the SOC of the energy storage battery.

[0009] In one embodiment, the method further includes: In the off-grid mode of the photovoltaic-storage system, the remaining backup power duration for each level of load is determined based on the backup power duration corresponding to each level of load, the status corresponding to each level of load, and the off-grid time of the photovoltaic-storage system. With the goal of maximizing the remaining backup power duration, the output of each energy device in the photovoltaic-storage system and the power outage plan of each graded load are optimized to obtain the second optimization result. Based on the second optimization result, the second output plan of each energy device and the power outage plan of each graded load are obtained, so as to control each energy device accordingly based on the second output plan and control each load accordingly based on the power outage plan.

[0010] In one embodiment, determining the remaining backup power duration for each tiered load based on the backup power duration corresponding to each tiered load, the status corresponding to each tiered load, and the off-grid time of the photovoltaic-storage system includes: For a single tiered load, if the state corresponding to the single tiered load is the power supply state, the remaining backup power duration corresponding to the single tiered load is obtained based on the time difference between the backup power duration corresponding to the single tiered load and the off-grid time of the photovoltaic and energy storage system.

[0011] In one embodiment, the energy equipment includes photovoltaics, energy storage batteries, and batteries for electric vehicles; the second power output plan includes: Photovoltaics are used to supply power to the load. If the photovoltaic output is insufficient, energy storage batteries are used to supplement the power supply. Alternatively, if there is surplus electricity after the photovoltaic system meets the load's power demand, the surplus electricity can be used to charge the energy storage battery. If the energy storage battery is fully charged, the surplus electricity can be used to charge the battery of the electric vehicle. Alternatively, if neither photovoltaic nor energy storage batteries can meet the power supply needs of the load, the batteries of electric vehicles can be used to supply power to the critical load.

[0012] In addition, to achieve the above objectives, this application also proposes a control device for an optical storage system, comprising: a memory, a processor, and a computer program stored in the memory and executable on the processor, the computer program being configured to implement the steps of the control method for the optical storage system as described above.

[0013] In addition, to achieve the above objectives, this application also proposes a storage medium, which is a computer-readable storage medium, on which a computer program is stored, and when the computer program is executed by a processor, it implements the steps of the control method of the optical storage system described above.

[0014] The one or more technical solutions proposed in this application have at least the following technical effects: This solution first calculates the backup power demand corresponding to each time period based on the differentiated backup power duration of different load levels, and then calculates the lower limit of the SOC of the energy storage battery for the backup power demand corresponding to each time period and converts it into a constraint condition. Unlike the traditional fixed SOC reservation value mode, this solution can accurately match the corresponding minimum backup power capacity according to the fluctuation of the backup power demand of different loads, avoiding the economic loss caused by the ineffective accumulation of energy storage capacity when the power supply is surplus and the defect of insufficient backup power capacity when the power supply is insufficient. Subsequently, based on the energy storage battery SOC constraint condition and with the goal of maximizing economic benefits, the output optimization is carried out, and finally the output plan that takes into account both the minimum backup power capacity constraint and economic benefits is output. Thus, during the grid-connected operation of the photovoltaic-energy storage system, it can simultaneously take into account the emergency backup power capacity reservation requirements and the economic efficiency of daily electricity use. Attached Figure Description

[0015] The accompanying drawings, which are incorporated in and form part of this specification, illustrate embodiments consistent with this application and, together with the description, serve to explain the principles of this application.

[0016] To more clearly illustrate the technical solutions in the embodiments of this application or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, for those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0017] Figure 1 A flowchart illustrating the control method for the photovoltaic energy storage system of this application in the first embodiment; Figure 2 A flowchart illustrating the second embodiment of the control method for the photovoltaic energy storage system of this application; Figure 3 This is a schematic diagram of the overall flow of the control method for the photovoltaic energy storage system of this application; Figure 4 This is a schematic diagram of the control device of the photovoltaic energy storage system of this application.

[0018] The purpose, features, and advantages of this application will be further explained in conjunction with the embodiments and with reference to the accompanying drawings. Detailed Implementation

[0019] It should be understood that the specific embodiments described herein are merely illustrative of the technical solutions of this application and are not intended to limit this application.

[0020] To better understand the technical solution of this application, a detailed description will be provided below in conjunction with the accompanying drawings and specific implementation methods.

[0021] In related technologies, the one-size-fits-all backup capacity reservation method with a fixed lower limit of the energy storage SOC has the following drawbacks: when the power generation is high, too much backup capacity is reserved, and the surplus power cannot be connected to the grid or used by the user, resulting in a waste of economic benefits; when the power supply is insufficient and the load is high, the reserved backup capacity is insufficient, and after a sudden power outage, important loads cannot support the preset backup power duration, and emergency protection fails. In other words, the existing backup capacity reservation method has the defect that it cannot simultaneously take into account the backup power demand and the economic efficiency of electricity use when the photovoltaic and energy storage system is connected to the grid.

[0022] To address the aforementioned shortcomings, this application proposes a control method for a photovoltaic-storage system. The main technical solution includes: in the grid-connected mode of the photovoltaic-storage system, determining the backup power demand corresponding to different load levels in each time period based on the backup power duration corresponding to different load levels in each time period; determining the lower limit of the state of charge (SOC) of the energy storage battery corresponding to each time period based on the backup power demand; constructing SOC constraints for the energy storage battery based on the lower limit of the SOC; optimizing the output plan of each energy device in the photovoltaic-storage system based on the energy storage battery SOC constraints and with the goal of maximizing economic benefits; obtaining a first output plan containing the output of each energy device in each time period based on the first optimization result, and controlling each energy device accordingly in each time period based on the first output plan.

[0023] This solution first calculates the backup power demand for each time period based on the differentiated backup power duration of different load levels. Then, it converts the backup power demand for each time period into the lower limit of the SOC of the energy storage battery and transforms it into a constraint condition. Unlike the traditional one-size-fits-all approach with a fixed SOC reserve value, this solution can accurately match the corresponding minimum backup power capacity according to the fluctuation of backup power demand of different loads. This avoids the economic losses caused by the ineffective accumulation of energy storage capacity during surplus power supply and the defects of insufficient backup power capacity when power supply is insufficient. Subsequently, based on the energy storage battery SOC constraint condition and with the goal of maximizing economic benefits, the output optimization is carried out, and finally the output plan that takes into account both the minimum backup power capacity constraint and economic benefits is output. Thus, during the grid-connected operation of the photovoltaic-energy storage system, it can simultaneously take into account the emergency backup power capacity reserve requirement and the economic efficiency of daily electricity use.

[0024] It should be noted that the executing entity in this embodiment can be a computing service device with data processing, network communication, and program execution functions, such as a tablet computer, personal computer, or mobile phone, or an electronic device capable of performing the above functions, such as a control device for a photoelectric storage system. The following description uses a control device for a photoelectric storage system as an example to illustrate this embodiment and the subsequent embodiments.

[0025] Based on this, embodiments of this application provide a control method for a photovoltaic energy storage system, referring to... Figure 1 , Figure 1 This is a flowchart illustrating the first embodiment of the control method for the photovoltaic storage system of this application. In this embodiment, the control method for the photovoltaic storage system includes steps S10 to S40: Step S10: In the grid-connected mode of the photovoltaic-storage system, determine the backup power demand corresponding to different levels of load in each time period based on the backup power duration corresponding to different levels of load in each time period.

[0026] The operation mode of a photovoltaic-storage system can be grid-connected, off-grid, or a combination of both. This embodiment focuses on how to determine the output plan of energy equipment in grid-connected mode. Grid-connected mode refers to the operation mode in which the photovoltaic-storage system maintains an electrical connection with the public power grid and can perform bidirectional power exchange with the grid. Its function is to rely on the grid as a power buffer, drawing power from the grid when photovoltaic output or energy storage capacity is insufficient, and feeding power back to the grid when photovoltaic output is surplus or energy storage needs to discharge, thus ensuring the stability of the system's power supply and participating in electricity price arbitrage.

[0027] The photovoltaic-storage system includes multiple energy devices, which refer to the equipment units in the photovoltaic-storage system that can output electrical energy to the load. In the embodiments of this application, the energy devices may include, but are not limited to, photovoltaic power generation units, energy storage battery units, electric vehicle battery units, charging piles, etc.

[0028] The electricity generated by the energy devices in this photovoltaic-storage system can power the operation of the loads. These loads can be categorized into different levels based on their importance, with varying power supply priorities for each level. By classifying the loads, priority can be given to powering higher-level loads during grid outages and other backup power scenarios, thus rationally allocating limited energy storage capacity and improving the utilization efficiency of backup power resources.

[0029] The number of loads in different levels can be one or more. Different levels of loads, due to their varying importance, can be assigned different backup power durations. When there are two or more loads in the same level, the backup power duration for each load within that level can be set to the same or different, depending on the actual situation. Backup power duration refers to the length of time a load of the corresponding level needs continuous power supply in a scenario where the mains power supply is interrupted. Its purpose is to serve as the basis for calculating backup power capacity and backup power output, ensuring that energy equipment retains sufficient power to support the stable operation of the corresponding level of load within the set duration.

[0030] Backup power demand refers to the active power required to meet the continuous power supply needs of corresponding tiered loads in backup power scenarios. Its purpose is to quantify the backup power requirements of different load tiers at each time period and is a fundamental parameter for subsequently deriving the lower limit of the SOC (State of Charge) value of energy storage batteries. The unit of this backup power demand is kW (kilowatts).

[0031] In one alternative approach, a mapping relationship between the pre-set backup power duration and the pre-set backup power demand can be pre-set for each load level. In actual use, the backup power demand for each load level is obtained by matching the pre-set mapping relationship with the backup power duration corresponding to each load level.

[0032] Alternatively, the backup power demand for each load level can be obtained by summing the rated power of all loads under each load level in each time period. Or, the backup power demand for each load level can be predicted using a machine learning model or neural network model based on historical load data. The machine learning model or neural network module can be configured according to actual conditions.

[0033] Step S20: Based on the backup power demand, determine the lower limit of the SOC of the energy storage battery for each time period, and construct the SOC constraint conditions of the energy storage battery based on the lower limit of the SOC of the energy storage battery.

[0034] The State of Charge (SOC) lower limit for energy storage batteries refers to the minimum percentage of remaining capacity relative to the rated total capacity of the battery. It represents the minimum remaining charge that the battery cannot fall below during discharge. Its purpose is to limit the maximum depth of discharge, reserve sufficient charge to cope with sudden grid outages, and ensure backup power for tiered loads. For example, if the rated capacity of an energy storage battery is 500 kWh, and the SOC lower limit is set to 20% for a certain period, then the remaining charge after discharge during that period cannot be less than 100 kWh.

[0035] In one alternative approach, a mapping relationship can be pre-established between different pre-set power consumption requirements and a preset lower limit of the State of Charge (SOC) of the energy storage battery. During actual use, the lower limit of the SOC of the energy storage battery can be determined based on this mapping relationship.

[0036] In another alternative approach, the required backup power can be input into a calculation model for the lower limit of the energy storage battery's State of Charge (SOC). This model then calculates the lower limit of the energy storage battery's SOC. Specifically, based on the backup power required for each load level, the minimum remaining charge of the energy storage battery for a single time period can be determined. This minimum remaining charge is then input into the calculation model, which calculates the lower limit of the energy storage battery's SOC for that single time period.

[0037] After determining the lower limit of the SOC (State of Charge) of the energy storage battery, a SOC constraint condition can be constructed based on this lower limit. The SOC constraint condition refers to the constraint rule set for the remaining capacity of the energy storage battery during the power output optimization calculation of the photovoltaic-energy storage system. It requires that the SOC value of the energy storage battery in each time period must not be lower than the corresponding lower limit of the SOC value for that time period. Its function is to transform the backup power demand into a constraint in the optimization calculation, ensuring that the optimized power output plan does not excessively consume the energy storage capacity, always retaining the minimum amount of backup power required, so that sufficient power can be reserved to cope with sudden grid outages. The upper limit of the SOC of the energy storage battery under this constraint condition can be a fixed value. This SOC constraint condition can be expressed as: .in, This indicates the lower limit of the SOC (State of Charge) of the energy storage battery. This indicates the upper limit of the SOC (State of Charge) of the energy storage battery.

[0038] Step S30: Based on the SOC constraint of the energy storage battery and with the goal of maximizing economic benefits, optimize the output plan of each energy device in the photovoltaic-storage system.

[0039] The purpose of optimization is to find the optimal output scheme from all feasible output schemes within the set constraints and according to the specified optimization objective.

[0040] Economic benefits refer to the net revenue generated by the photovoltaic and energy storage system during its operating cycle. As the objective function for output optimization, it guides the system's output allocation towards maximizing benefits and minimizing costs. Economic benefits are the sum of grid connection benefits and grid connection benefits, minus the energy storage discharge start-up cost and the SOC penalty cost when the electric vehicle leaves the grid. Grid connection benefits refer to the reduction in electricity costs paid to the grid, resulting in savings on electricity that would otherwise be purchased from the grid to meet household loads. This is a positive benefit. Grid connection benefits refer to the revenue generated when photovoltaic power output exceeds the household's real-time load and energy storage charging capacity, and the excess electricity is fed back to the public grid. The grid then settles the revenue with the user according to the agreed-upon grid connection price. This is also a positive benefit. Energy storage discharge start-up cost refers to the lifespan degradation cost incurred by the energy storage battery per unit of electricity discharged. It quantifies the irreversible capacity decay and cell aging losses caused by deep and frequent discharges. This is a cost deduction that reduces economic benefits. The SOC penalty cost when an electric vehicle leaves refers to the penalty cost used to constrain the charging scheduling of the electric vehicle. When the electric vehicle's battery SOC fails to reach the user's pre-set target charge level at the planned departure time, a fixed large penalty value is added to the economic benefit, which is a negative benefit and reduces economic returns. The objective function required for calculating economic benefits can be expressed as: .

[0041] Where Max is the maximization operator, representing the goal of maximizing the cumulative value over all time periods within the parentheses, i.e., pursuing the highest possible economic benefit for the system. t∈T indicates that the summation is performed over all time periods within the scheduling period, where T is the set of all time periods covered by this optimization, for example, a time series set consisting of 15-minute intervals over the next 24 hours. This represents the on-grid electricity price for time period t, expressed in yuan / kWh. It is the time-of-use electricity price applied when a user draws electricity from the grid, with higher values ​​during peak hours. This represents the power purchased from the grid during time period t. The power sign rule is negative, indicating that the system absorbs electricity from the municipal grid. The larger this power, the more electricity costs would normally be incurred. This represents the grid-connected electricity price for surplus photovoltaic power during time period t, expressed in yuan / kWh. It is the purchase price settled by the grid when surplus photovoltaic power is fed into the grid. This represents the power transmitted from photovoltaic cells to the grid during time period t. It is a positive value, indicating that the system generates revenue from selling electricity. This represents the unit discharge loss cost of energy storage, which is the cost of battery life degradation corresponding to every kilowatt-hour of electrical energy discharged by the energy storage. This represents the discharge power of the energy storage battery during time period t, which is a positive value, indicating that the energy storage battery outputs electrical energy to supply household loads. This represents a binary identifier variable ranging from 0 to 1. A value of 1 indicates that the battery SOC of the electric vehicle has reached the user-set target value at the planned departure time, while a value of 0 indicates that the battery charge has not reached the target. M is a fixed penalty coefficient, with a value higher than the benefits of normal system operation. It is used to amplify the losses caused by insufficient battery charge of the electric vehicle and force the optimization algorithm to prioritize the charging needs of the electric vehicle. Indicates the revenue generated from offline operations; Indicates revenue from internet access; This indicates the cost of starting up energy storage discharge. This represents the SOC (State of Charge) penalty cost when the electric vehicle leaves the station.

[0042] In one alternative approach, the output combinations of each energy device at different time periods are used as particle position codes, and economic benefit is used as the fitness function. Under the premise of satisfying the SOC constraint of the energy storage battery, the optimal output scheme is iteratively searched using a particle swarm optimization algorithm. In specific execution, multiple initial output schemes are first randomly generated as initial particle swarms. Each scheme is checked to see if it meets the SOC constraint of the energy storage battery. Schemes that violate the constraint have their fitness reduced directly. Then, the particle positions and velocities are updated according to the iterative rules of the particle swarm algorithm, continuously searching towards directions with higher fitness. After multiple iterations, the output scheme with the highest fitness is converged, which is the first optimal result.

[0043] Step S40: Based on the first optimization result, a first output plan is obtained, which includes the output of each energy device in each time period, so as to control each energy device accordingly in each time period based on the first output plan.

[0044] The first optimization result refers to the optimal power output scheme output by the optimization calculation process, including the optimal power output of each energy device in each time period. For example, the first optimization result includes the photovoltaic power output value, energy storage charging and discharging power value, electric vehicle battery power value, and corresponding economic benefits for each time period of 24 hours. The first power output plan refers to the optimal arrangement scheme of the output power of each energy device according to the time period, specifying the output power value of each energy device in each time period. It is used to guide each energy device to output electrical energy according to the planned output power in the corresponding time period to meet the electricity demand of each level of load. For example, in the 24-hour power output plan, it is specified how many kilowatts of photovoltaic power output, how many kilowatts of energy storage battery discharge, and how many kilowatts of electricity to be purchased from the grid are specified each hour, and each energy device operates according to the power output plan in each time period.

[0045] In one alternative approach, during specific control, the output data for each time period in the first optimization result can be converted into a time-ordered sequence of output commands. Each time period includes photovoltaic power generation commands, energy storage charging and discharging commands, and grid interaction commands. The system controller updates the commands once every preset cycle and issues corresponding power commands to the photovoltaic inverter, energy storage converter, and grid-connected switch, respectively.

[0046] In another optional approach, an initial output plan is first generated based on the first optimization result. During actual operation, the current SOC value of the energy storage battery and the actual load power are verified after each time period. If the deviation is within the allowable range, the planned output for the next time period is executed directly. If the deviation exceeds the threshold, the plan for the remaining time periods is slightly modified based on the current state before execution. Specifically, the first optimization result is first converted into an output plan for each time period throughout the day. During operation, at each time period node, the current energy storage SOC, actual load power, and actual photovoltaic output data are collected and compared with the deviation of the planned values. When the deviation is less than the preset deviation, the planned output for the current time period is executed directly. When the deviation is greater than the preset deviation, the output plan for the remaining time periods is quickly recalculated and modified according to the original constraints and targets, starting from the current state, and then the modified output for the current time period is executed, ensuring that the actual operation always conforms to the optimal target and backup power constraints.

[0047] In this embodiment, the backup power demand for each time period is first calculated based on the differentiated backup power duration of different load levels. Then, the lower limit of the SOC of the energy storage battery is calculated and converted into a constraint condition based on the backup power demand for each time period. Unlike the traditional one-size-fits-all approach with a fixed SOC reserve value, this solution can accurately match the minimum backup power capacity corresponding to the fluctuation of backup power demand of different loads. This avoids the economic losses caused by the ineffective accumulation of energy storage capacity during surplus power supply and the defects of insufficient backup power capacity when power supply is insufficient. Subsequently, based on the energy storage battery SOC constraint condition and with the goal of maximizing economic benefits, the output optimization is performed, and finally, an output plan that takes into account both the minimum backup power capacity constraint and economic benefits is output. Thus, during the grid-connected operation phase of the photovoltaic-energy storage system, both the emergency backup power capacity reserve requirement and the daily electricity economy can be taken into account.

[0048] It should be noted that, in addition to optimization based on the SOC constraint of the energy storage battery, the embodiments of this application may also set the following constraints:

[0049] in, , Let represent the charging power and discharging power of the energy storage battery at time t, respectively. , These represent the home energy storage charging efficiency and discharge power, respectively. This indicates the initial state of energy storage (SOC) for a home. This represents the real-time SOC of the energy storage battery at time t; This represents the real-time SOC of the energy storage battery at time t-1. Indicates the rated capacity of the energy storage battery; This indicates the duration of a single scheduling step.

[0050] In grid-connected mode, the system does not actively use the electric vehicle's battery for power, but it will simultaneously consider economic efficiency and the electric vehicle's final state of charge (SOC) target value to rationally schedule the electric vehicle's charging. The corresponding constraints are as follows:

[0051] in, Charging power for electric vehicles, The initial SOC when the electric vehicle is connected. The target SOC value set for electric vehicles For the planned access time of electric vehicles, Planned departure time for electric vehicles; For electric vehicle charging efficiency; The rated capacity of the battery for electric vehicles. This indicates the minimum safe operating point of charge (SOC) of an electric vehicle's battery. This indicates the upper limit of the safe state of charge (SOC) of an electric vehicle's battery. This represents the state of charge (SOC) of the electric vehicle's battery at time t. Indicates the time when the electric vehicle is connected to the system; Indicates the planned departure time of the electric vehicle; This indicates the maximum charging power of the electric vehicle.

[0052] Introducing state variables This indicates whether the SOC target value was reached when the charging vehicle left. When the electric vehicle leaves, the battery SOC must reach or exceed the target SOC value. When the electric vehicle leaves, the battery SOC has not reached the target SOC value.

[0053] In addition, it may include system energy balance constraints, equipment output boundaries, system safety constraints, etc.

[0054]

[0055] in, This represents the power purchased from the grid during time period t. This represents the amount of electricity purchased by the power grid during time period t. This represents the DC power output of the photovoltaic system during time period t. This represents the total power consumption of all graded loads during time period t; This represents the charging power of the electric vehicle during time period t; The grid connection status is indicated by a binary flag of 0-1, where 1 represents that the system is in grid connection and 0 represents that it is off-grid. This indicates the maximum power that the system is allowed to purchase from the grid; The 0-1 binary flag indicates mutual exclusion between energy storage charging and discharging during time period t, where 1 represents that energy storage is allowed to charge and 0 represents that charging is prohibited. Indicates the maximum charging power of the energy storage; This indicates the maximum discharge power of the stored energy.

[0056] In one feasible implementation, determining the backup power demand corresponding to different load levels in each time period in step S10, based on the backup power duration corresponding to different load levels in each time period, may include: Step S11: Obtain the backup power duration corresponding to different load levels in each time period. The importance of different load levels varies, and the backup power duration is positively correlated with the importance of the load level.

[0057] The load levels here can be categorized into critical loads, general loads, and other loads based on actual conditions. Critical loads refer to those that maintain life and health, ensure data and property security, and provide necessary lighting and communication, requiring priority and uninterrupted power supply. Examples include ventilators, refrigerators, routers, and emergency lighting. General loads refer to loads that affect living comfort but are not essential for survival and can be interrupted briefly, such as air conditioners, kitchen appliances, and lighting in non-critical areas. Other loads refer to loads that should have their power cut off or abandoned first during power shortages, such as decorative lighting and electric vehicle charging loads.

[0058] Different load categories have different levels of importance. The more important the load category, the longer the required backup power duration, and vice versa. In other words, the backup power duration is positively correlated with the importance of the load category. For example, the backup power duration for important loads can be set to 2 hours, meaning that after a power outage, the energy equipment needs to maintain normal power supply to the important load for at least two consecutive hours; the backup power duration for general loads can be set to 1 hour, and the backup power duration for other loads can be set to 0 hours.

[0059] In one optional approach, a mapping relationship between different preset load types and preset backup power durations can be pre-set. During actual use, the backup power duration corresponding to each load type can be obtained based on this mapping relationship. The backup power durations differ for different load types, and the backup power durations for loads within the same load type can be the same or different, depending on the actual situation.

[0060] Step S12: For a single time period, determine the backup power demand corresponding to each level of load in the single time period based on the comparison between the backup power duration corresponding to each level of load in the single time period and the duration of the single time period.

[0061] In one optional approach, for a single tiered load, if the duration of a single time period is less than or equal to the backup power duration, the backup power demand corresponding to the single tiered load is determined based on the rated power of all loads under the single tiered load; if the duration of a single time period is greater than the backup power duration, a preset value is used as the backup power demand corresponding to the single tiered load, where the preset value is zero. The above determination of the backup power demand corresponding to a single tiered load based on the rated power of all loads under the single tiered load includes: obtaining the backup power demand corresponding to the single tiered load based on the sum of the rated power of all loads under the single tiered load. This can be expressed by the following formula: .

[0062] in, This represents the backup power demand of different load levels i during time period t. This represents the rated power of the j-th device in the i-th load during time period t. , Let be the total number of devices at the i-th load level, and let t take values ​​ranging from 1 to 2. ,in, These correspond to critical loads, general loads, and other loads, respectively.

[0063] In another alternative approach, for a single tiered load, if the duration of a single time period is less than or equal to the backup power duration, the backup power demand corresponding to the single tiered load is predicted based on historical data. If the duration of a single time period is greater than the backup power duration, a preset value is used as the backup power demand corresponding to the single tiered load, where the preset value is zero. This can be expressed using the following formula: .

[0064] Among them, historical load data is Historical covariate data are .

[0065] The aforementioned historical data can include historical load time-series data and historical covariate time-series data. Historical load time-series data refers to the time-series dataset of actual active power consumed by each load level in past periods, stored separately according to load level, including important load power, general load power, and other load power for each time slice over multiple days, weeks, and months. Historical covariate time-series data refers to all external auxiliary time-series data that affect household load, used as model input features to correct load forecast biases. It can be divided into fixed time-series features and environmental external features; fixed time-series features include time, day of the week, holiday markers, and month sequence number; environmental external features include historical light intensity, ambient temperature, humidity, and season identifiers.

[0066] Predicting the backup power demand corresponding to a single tiered load based on historical data can involve inputting historical load data and historical covariate data of a single tiered load into a machine learning model or neural network model, and obtaining the backup power demand corresponding to the single tiered load based on the model's output. The model can be one of the following: ARIMA, LightGBM, LSTM, or large language models. Taking the LSTM model as an example: Align and organize the continuous time-series historical load data of a single tiered load with historical covariate data such as temperature, illumination, holidays, and time-series markers; standardize all features; set the input time-series step size; concatenate the historical load data features and historical covariate data features to construct time-series samples; divide the training and test sets according to time order; build a single-layer LSTM network with a fully connected output layer; use the Adam optimizer and mean absolute error loss function for training; set a fixed number of training epochs and use an early stopping strategy on the validation set to prevent overfitting; after training, use multi-step rolling; inference output the predicted power corresponding to each time period within the backup power duration coverage window; within the backup power duration range, use the predicted power as the backup power demand corresponding to the tiered load; outside the backup power duration, output zero. Taking a large language model as an example: construct cue words from historical load data and historical covariate data, input the cue words into the large language model, and obtain the result through the output of the large language model.

[0067] Understandably, for any level of load, the rated power of all equipment and the backup power demand are only calculated during the time period when power supply is guaranteed after a grid outage. Once the scheduling period exceeds the backup power duration corresponding to the load, the backup power demand is directly set to zero. This means the system will not reserve additional energy storage capacity for loads exceeding the guaranteed time limit, and there will be no unlimited stockpiling of energy storage capacity, eliminating redundant and wasteful backup power capacity at the source. For example, if the backup power duration for a typical load is set to 1 hour, and power supply to air conditioners and kitchen appliances is no longer guaranteed after a power outage exceeding 1 hour, energy storage capacity will not be calculated or reserved for such loads during scheduling periods exceeding 1 hour. The saved energy storage capacity can be used for self-consumption of photovoltaic power or for surplus electricity to be fed into the grid, improving overall electricity revenue. Furthermore, different backup power durations are configured for different load levels. Critical loads have the longest backup power duration, corresponding to more effective calculation periods, and their backup power demand is continuously calculated for a longer period, ensuring long-term power reserve by the system. General loads have shorter backup power durations, with backup power calculated only at the initial stage of a power outage. Other loads have zero backup power duration, with zero backup power demand at all times, and no energy storage is reserved throughout the outage. This judgment rule distinguishes the protection boundaries of each load level through a unified calculation logic, following a hierarchical control approach of prioritizing long-term protection for critical loads, short-term protection for secondary loads, and no protection for unnecessary loads, ensuring that backup power capacity allocation is perfectly matched to load importance. Additionally, the backup power demand for individual load levels is calculated by statistically analyzing rated power or through prediction, thereby increasing the backup power demand for individual load levels.

[0068] In another alternative approach, for a single tiered load, if the duration of a single time period is less than or equal to the backup power duration, the first backup power demand corresponding to the single tiered load is determined based on the rated power of all loads under the single tiered load, and the second backup power demand corresponding to the single tiered load is predicted based on historical data of the single tiered load. If the first backup power demand and the second backup power demand are the same, or the difference between the two is within the allowable error range, one of the first backup power demand and the second backup power demand can be used as the final backup power demand. If the first backup power demand and the second backup power demand are inconsistent, or the difference between the two is outside the allowable error range, one of them can be selected as the final backup power demand based on the actual situation. For example, the first backup power demand can be selected as the final backup power demand.

[0069] In this embodiment, under the grid-connected mode of the photovoltaic-storage system, the backup power duration corresponding to different tiered loads in each time period is obtained. For a single time period, the backup power demand corresponding to each tiered load in that time period is determined by comparing the backup power duration corresponding to each tiered load with the duration of the single time period. This allows for the accurate determination of the differentiated backup power demand corresponding to each tiered load in each time period. This provides a foundation for subsequently determining differentiated SOC lower limits for energy storage batteries based on different differentiated backup power demand.

[0070] In one feasible implementation, step S20, based on the backup power demand, determines the lower limit of the SOC of the energy storage battery for each time period, including: Step S21: For a single time period, determine the minimum remaining power of the energy storage battery corresponding to the backup power demand of each load level.

[0071] In one alternative approach, the backup power demand corresponding to each level of load can be input into the minimum surplus power calculation model of the energy storage battery. The minimum surplus power of the energy storage battery for a single time period can be obtained through the output of this calculation model. The principle of the minimum surplus power calculation model is as follows: using the backup power duration of the important load as the calculation window, the power difference between photovoltaic and graded loads under the power outage scenario is calculated for each time period. The energy shortage that needs to be replenished by energy storage and the charging energy that the photovoltaic surplus can be stored in the energy storage are calculated for each time period. The difference between the two is the net required reserve power for a single time period. Then, the power is summed over all time periods of the entire backup power window to obtain the minimum total power that the energy storage needs to retain. This is used to ensure that after the grid power outage, photovoltaic and energy storage can continuously support all graded loads to complete the backup power duration specified by the important load. This involves simulating the complete backup power window after a power outage, calculating hourly how much load photovoltaics can help us handle and how much surplus electricity they can store. After deducting the photovoltaics' own contribution, it calculates the minimum amount of electricity that needs to be stored during the entire backup power cycle. This ensures that the load can continue to be supplied with electricity for the specified duration after a power outage, while avoiding unnecessary excess power reserves that would waste photovoltaic revenue.

[0072] The calculation model for the minimum residual power of this energy storage battery can be expressed as: .

[0073] in, Let t be the minimum remaining charge of the energy storage battery that meets the backup power demand at time t. Let k∈(t, t+H1) represent the backup power demand of different load levels i during time period k. Backup power duration for critical loads; This represents the predicted DC power output of the photovoltaic system during time period k; The discharge conversion efficiency of the energy storage battery is used to convert the AC side load power into the amount of electricity that needs to be released on the DC side of the energy storage, since there are losses when the internal electrical energy of the energy storage is output to the outside. This indicates the maximum allowable charging power of the energy storage system; This indicates the charging conversion efficiency of the energy storage battery.

[0074] Step S22: Based on the minimum remaining charge of the energy storage battery for a single time period, the installed capacity of the energy storage battery, and the safe lower boundary value of the SOC of the energy storage battery, determine the lower limit value of the SOC of the energy storage battery for a single time period.

[0075] In one alternative approach, the minimum state of charge (SOC) of the energy storage battery for a single time period can be determined based on the ratio of the minimum remaining charge of the battery to its installed capacity. The lower limit of the SOC for a single time period is then obtained by summing the minimum SOC and the battery's safe lower boundary value. The lower limit of the SOC for a single time period can be calculated using the following formula: .

[0076] in, The minimum SOC value for energy storage batteries to take into account backup power requirements; It refers to the installed capacity of energy storage batteries; This represents the lower safety threshold value for the State of Charge (SOC) of the energy storage battery.

[0077] In this embodiment, after determining the backup power demand corresponding to each load level, the minimum remaining power of the energy storage battery for a single time period is determined based on the backup power demand corresponding to each load level. Based on the minimum remaining power of the energy storage battery for a single time period, the installed capacity of the energy storage battery, and the safe lower boundary value of the energy storage battery's State of Charge (SOC), the lower limit value of the energy storage battery's SOC for a single time period is determined. By first accurately matching the backup power demand of each load level with the backup power duration required after a power outage, sufficient energy storage is ensured to support the load when the grid loses power. By superimposing the safe lower boundary value of the energy storage battery's SOC, over-discharge of the energy storage battery is avoided, preventing damage. The final output lower limit value of the energy storage battery's SOC serves as a hard constraint for the optimization model, controlling that the remaining energy storage capacity during grid-connected scheduling cannot fall below this value, thus achieving a balance between daily electricity economy and power outage backup safety.

[0078] Based on the first embodiment of this application, in the second embodiment of this application, the same or similar content as the above embodiment can be referred to the above description, and will not be repeated hereafter. Based on this, please refer to... Figure 2 The control method for the optical storage system may include steps S110 to S130 after step S40, or while performing steps S10 to S40: Step S110: In the off-grid mode of the photovoltaic-storage system, determine the remaining backup power duration for each level of load based on the backup power duration corresponding to each level of load, the status corresponding to each level of load, and the off-grid time of the photovoltaic-storage system.

[0079] Off-grid mode refers to the independent operation mode of a photovoltaic-storage system, where the system is electrically disconnected from the public power grid, does not interact with the grid in any way, and relies entirely on its own power generation and storage units to supply power to the load. Its function is to independently maintain power supply to the load during grid faults, power outages, or maintenance, ensuring the continuous operation of critical electrical equipment. For example, if the public power grid trips due to a fault, the grid-connected switch of the photovoltaic-storage system automatically trips, switching to off-grid mode. The energy storage batteries and photovoltaic power generation units then jointly supply power to the critical loads within the plant area, without relying on external power grid input.

[0080] The status corresponding to the graded load refers to the current energized and operating status of each load level, which is divided into two categories: power supply status and power outage status. Its function is to accurately count the actual load scale of current power consumption, avoid including loads that have been de-energized in the power consumption calculation, and ensure the accuracy of the calculation of remaining backup power time.

[0081] Off-grid time refers to the elapsed time from the moment the photovoltaic-storage system switches from grid-connected mode to off-grid mode until the current moment. It is used to measure the backup power resources consumed after off-grid operation. Combined with the backup power duration corresponding to each load level, the remaining backup power duration can be calculated. The remaining backup power duration refers to the duration from the current moment that the photovoltaic-storage system, relying on its existing remaining energy storage capacity and subsequent available photovoltaic power generation, can continuously and stably supply power to the corresponding load level. Its function is to serve as a target for control optimization in off-grid mode, directly reflecting the system's emergency power supply guarantee capability, and also an indicator for evaluating the rationality of power outage plans.

[0082] In one alternative approach, a mapping relationship can be pre-established for the backup power duration, preset status, preset off-grid time, and preset remaining backup power duration; based on this mapping relationship, the remaining backup power duration corresponding to each load level can be determined.

[0083] In another alternative approach, a remaining backup power duration calculation model can be set up. The backup power duration corresponding to each load tier, the state of each load tier, and the off-grid time of the photovoltaic-storage system are input into this model to obtain the remaining backup power duration for each load tier. The principle of this remaining backup power duration calculation model is as follows: For a single load tier, if the state of the load tier is powered on, the remaining backup power duration is obtained based on the time difference between the backup power duration of the load tier and the off-grid time of the photovoltaic-storage system. If the state of the load tier is powered off, a preset remaining backup power duration is used, where the preset remaining backup power duration is zero. This remaining backup power duration calculation model can be expressed as: .

[0084] in, Used to represent the initial state corresponding to the i-th level load. This indicates that the state corresponding to the graded load is the power-off state. This indicates that the state corresponding to the graded load is the power supply state. This represents the backup power duration for the i-th level load; Indicates the off-grid time of the photovoltaic-storage system; This represents the remaining backup power duration corresponding to the i-th level load.

[0085] Step S120: With maximizing the remaining backup power duration as the optimization objective, the output of each energy device in the photovoltaic-storage system and the power outage plan of each graded load are optimized to obtain the second optimization result.

[0086] The second optimization result refers to the optimal solution output by this off-grid mode optimization calculation, which includes the optimal output of each energy device in each time period, the optimal power outage time of each load level, and the corresponding maximum remaining backup power duration.

[0087] In one alternative approach, optimization is first categorized by load level, with higher-level loads having higher priority, prioritizing the power supply duration of high-level loads. The first optimization level targets the highest-level load, constraining it to maintain power supply throughout the entire off-grid process and preventing premature disconnection. Energy storage discharge power and photovoltaic self-consumption ratio are used as decision variables, with the objective of maximizing the remaining backup power duration of the highest-level load. Optimization calculations are performed under these constraints to obtain the longest power supply duration for the highest-level load and the corresponding energy equipment output curve. After completing the first optimization level, a second optimization level is performed, using the remaining available energy as the boundary. This level targets the next lower load level, maximizing its remaining backup power duration without affecting the power supply duration of the highest-level load, thus obtaining the power outage time and corresponding output adjustment scheme for the next lower load level. After completing optimization at all levels from highest to lowest, the output schemes and power outage times of each level are integrated to form a complete optimal solution, which is the second optimization result.

[0088] In another optional approach, the total off-grid duration is divided into multiple equal-length calculation periods. The self-consumption power of photovoltaic power generation and the discharge power of energy storage are set as continuous decision variables for each period, while the power outage period of each load level is set as a discrete decision variable, with constraints added. When constructing the objective function, a corresponding weight coefficient is assigned to the remaining backup power duration of each level; the higher the level, the greater the weight. The objective function is the sum of the products of the remaining backup power duration of each load level and its corresponding weight. Subsequently, a genetic algorithm is used for global optimization. Multiple initial schemes containing power output and power outage times are randomly generated. The objective function value of each scheme is calculated, and schemes with low fitness are eliminated. A new generation of schemes is generated through crossover and mutation. After multiple iterations, the scheme with the largest objective function value converges, which is the second optimization result.

[0089] The purpose of optimization is to maximize the remaining backup power duration while ensuring system power balance. This involves optimizing the scheduling of power output from energy devices such as photovoltaic power generation, energy storage charging and discharging, and electric vehicle charging loads, as well as the power outage plans for tiered loads. The objective function used in optimization can be expressed as: .

[0090] in, This represents the state of the i-th level load, where 1 indicates power supply and 0 indicates power failure. The optimization timeframe is the period from the current time period to the backup power duration of the critical load (i=1). .

[0091] During the optimization process, pre-set constraints can be applied to the optimization process. These constraints can be expressed as follows:

[0092] in, Let i represent the state of the i-th load, where 1 indicates a power supply state and 0 indicates a power outage state. Constraint (1) represents the household energy balance constraint under off-grid conditions, where the i-th load is in a power supply state. The value is 0, meaning no power supply is needed to the i-level load; For the initial power supply state of the i-th level load, constraints (2) and (3) ensure that once the load is de-energized, power supply will not be restored. Constraint (4) specifies the order of power outages, i.e., other loads (i=3) are de-energized first, followed by general loads (i=2), and finally important loads (i=1). Constraints (5) to (7) indicate that when neither photovoltaic output nor energy storage can meet the power supply demand, the batteries of electric vehicles are allowed to supply power to important loads.

[0093] In addition, the constraints also include battery SOC constraints and equipment output boundary constraints for electric vehicles, such as:

[0094] Step S130: Based on the second optimization result, obtain the second output plan of each energy device and the power outage plan of each graded load, so as to control each energy device accordingly based on the second output plan and control each load accordingly based on the power outage plan.

[0095] A power outage plan refers to a pre-planned schedule for sequentially cutting off loads at different levels according to their priority. It specifies the outage time and scope for different load levels. Its purpose is to reduce energy consumption by orderly cutting off low-priority loads when the system's total power supply capacity is insufficient, thereby concentrating limited energy on high-priority loads and extending the power supply duration for critical loads. This power outage plan can be implemented by first cutting off other loads, then general loads, and finally critical loads. A secondary output plan refers to the output schemes of each energy device, formed based on the results of the second optimization and divided by time period. Its purpose is to serve as the basis for the operation and control of energy devices in off-grid mode, guiding each energy device to output power according to the optimal strategy. Energy devices include photovoltaics, energy storage batteries, and electric vehicle batteries. The secondary output plan includes: using photovoltaics to supply power to the load; if photovoltaic output is insufficient, using energy storage batteries to supplement power; or, if photovoltaics meet the load's power needs and there is surplus power, the surplus power is used to charge the energy storage battery; if the energy storage battery is fully charged, the surplus power is used to charge the electric vehicle battery; or, if neither photovoltaics nor energy storage batteries can meet the load's power demand, the electric vehicle battery is used to supply power to critical loads. Based on real-time photovoltaic and load handling conditions, a reasonable load-level power outage plan should be arranged to ensure continuous power supply to important loads while avoiding premature power outages to general loads.

[0096] In one optional approach, the data from the second optimization result is structured and organized chronologically. The photovoltaic output target value and energy storage discharge target value for each time period are summarized to form a second output plan, clearly defining the required output power of each energy device at each time node. Simultaneously, the power outage times corresponding to each load level are compiled into a power outage plan list, marking the cut-off time and range for each load level. The system controller has a built-in timing module that advances segment by segment according to a unified time period step. At the start of each time period, it reads the output target for the corresponding time period from the second output plan and issues power adjustment commands to the photovoltaic inverter and discharge power commands to the energy storage converter. Through closed-loop control, the actual output of the equipment tracks the planned value. At each load power outage time, the controller issues a trip command to the main power switch of the corresponding load level, disconnecting the power supply circuit for all loads at that level, completing the load cut-off.

[0097] In this embodiment, for the off-grid operation scenario of the photovoltaic-storage system, the remaining power supply capacity is first accurately calculated by combining the off-grid duration, load status, and pre-installed power requirements to provide accurate status for optimized control. Secondly, the output adjustment of energy equipment and the hierarchical load power outage planning are simultaneously incorporated into the optimization dimension to maximize the remaining backup power duration. This approach can fully tap the power supply potential of photovoltaics and energy storage, improve the utilization efficiency of limited electricity, and strictly follow load priorities, prioritizing the power supply duration of important loads and avoiding production losses and safety risks caused by disorderly power outages. Furthermore, an optimization model is constructed in the off-grid scheduling with the goal of maximizing the remaining backup power duration.

[0098] Reference Figure 3 , Figure 3 This is a schematic diagram of the overall flow of the control method for the photovoltaic-storage system of this application. First, the operating mode of the residential photovoltaic-storage system is detected; if it is in grid-connected mode, a home energy dispatching method with dynamic backup power is considered, and the specific content of the first embodiment described above is executed. If it is in off-grid mode, an off-grid mode control method based on load grading protection is executed, and the specific content of the second embodiment described above is executed.

[0099] It should be noted that the above examples are only for understanding this application and do not constitute a limitation on the control method of the optical storage system of this application. Any simple modifications based on this technical concept are within the protection scope of this application.

[0100] Based on the same inventive concept, this application provides a control device for an optical storage system, comprising: at least one processor; and a memory communicatively connected to the at least one processor; wherein the memory stores instructions executable by the at least one processor, the instructions being executed by the at least one processor to enable the at least one processor to perform the control method of the optical storage system described above.

[0101] like Figure 4 As shown, the control unit of the optical storage system may include a processing unit 1001 (e.g., a central processing unit, a graphics processing unit, etc.), which can perform various appropriate actions and processes according to a program stored in read-only memory (ROM) 1002 or a program loaded from storage device 1003 into random access memory (RAM) 1004. The random access memory 1004 also stores various programs and data required for the operation of the control unit of the optical storage system. The processing unit 1001, ROM 1002, and RAM 1004 are interconnected via a bus 1005. An input / output (I / O) interface 1006 is also connected to the bus. Typically, the following systems can be connected to I / O interface 1006: input devices 1007 including, for example, touchscreens, touchpads, keyboards, mice, image sensors, microphones, accelerometers, gyroscopes, etc.; output devices 1008 including, for example, liquid crystal displays (LCDs), speakers, vibrators, etc.; storage devices 1003 including, for example, magnetic tapes, hard disks, etc.; and communication devices 1009. Communication device 1009 allows the control device of the optical storage system to communicate wirelessly or wiredly with other devices to exchange data. Although the figure shows a control device for an optical storage system with various systems, it should be understood that it is not required to implement or possess all the systems shown. More or fewer systems can be implemented alternatively.

[0102] Specifically, according to the embodiments disclosed in this application, the processes described above with reference to the flowcharts can be implemented as computer software programs. For example, embodiments disclosed in this application include a computer program product comprising a computer program carried on a computer-readable medium, the computer program containing program code for performing the methods shown in the flowcharts. In such embodiments, the computer program can be downloaded and installed from a network via a communication device, or installed from storage device 1003, or installed from read-only memory 1002. When the computer program is executed by processing device 1001, it performs the functions defined in the methods of the embodiments disclosed in this application.

[0103] The control device for the photovoltaic-storage system provided in this application, employing the control method for the photovoltaic-storage system described in the above embodiments, can solve the technical problem of simultaneously considering backup power demand and electricity economy during the grid-connected operation of the photovoltaic-storage system. Compared with the prior art, the beneficial effects of the control device for the photovoltaic-storage system provided in this application are the same as those of the control method for the photovoltaic-storage system provided in the above embodiments, and other technical features in the control device for the photovoltaic-storage system are the same as those disclosed in the previous embodiment method, and will not be repeated here.

[0104] It should be understood that the various parts disclosed in this application can be implemented using hardware, software, firmware, or a combination thereof. In the description of the above embodiments, specific features, structures, materials, or characteristics can be combined in any suitable manner in one or more embodiments or examples.

[0105] The above are merely specific embodiments of this application, but the scope of protection of this application is not limited thereto. Any variations or substitutions that can be easily conceived by those skilled in the art within the scope of the technology disclosed in this application should be included within the scope of protection of this application. Therefore, the scope of protection of this application should be determined by the scope of the claims.

[0106] Based on the same inventive concept, this application provides a computer-readable storage medium having computer-readable program instructions (i.e., a computer program) stored thereon, which are used to execute the control method of the optical storage system in the above embodiments.

[0107] The computer-readable storage medium provided in this application may be, for example, a USB flash drive, but is not limited to, electrical, magnetic, optical, electromagnetic, infrared, or semiconductor systems, devices, or any combination thereof. More specific examples of computer-readable storage media may include, but are not limited to: electrical connections having one or more wires, portable computer disks, hard disks, random access memory, read-only memory, erasable programmable read-only memory (EPROM), optical fibers, portable compact disk read-only memory (CD-ROM), optical storage devices, magnetic storage devices, or any suitable combination thereof. In this embodiment, the computer-readable storage medium may be any tangible medium containing or storing a program that can be used by or in conjunction with an instruction execution system, system, or device. The program code contained on the computer-readable storage medium may be transmitted using any suitable medium, including but not limited to: wires, optical cables, radio frequency (RF), etc., or any suitable combination thereof.

[0108] The aforementioned computer-readable storage medium may be included in the control device of the optical storage system; or it may exist independently and not be assembled into the control device of the optical storage system.

[0109] The aforementioned computer-readable storage medium carries one or more programs, which, when executed by the control device of the optical storage system, cause the control device of the optical storage system to perform the steps corresponding to the aforementioned method.

[0110] Computer program code for performing the operations of this application can be written in one or more programming languages ​​or a combination thereof, including object-oriented programming languages ​​such as Java, Smalltalk, and C++, and conventional procedural programming languages ​​such as the "C" language or similar programming languages. The program code can be executed entirely on the user's computer, partially on the user's computer, as a standalone software package, partially on the user's computer and partially on a remote computer, or entirely on a remote computer or server. In cases involving remote computers, the remote computer can be connected to the user's computer via any type of network—including a Local Area Network (LAN) or a Wide Area Network (WAN)—or can be connected to an external computer (e.g., via the Internet using an Internet service provider).

[0111] The flowcharts and block diagrams in the accompanying drawings illustrate the architecture, functionality, and operation of possible implementations of systems, methods, and computer program products according to various embodiments of this application. In this regard, each block in a flowchart or block diagram may represent a module, segment, or portion of code containing one or more executable instructions for implementing a specified logical function. It should also be noted that in some alternative implementations, the functions indicated in the blocks may occur in a different order than those indicated in the drawings. For example, two consecutively indicated blocks may actually be executed substantially in parallel, and they may sometimes be executed in reverse order, depending on the functions involved. It should also be noted that each block in the block diagrams and / or flowcharts, and combinations of blocks in the block diagrams and / or flowcharts, can be implemented using a dedicated hardware-based system that performs the specified function or operation, or using a combination of dedicated hardware and computer instructions.

[0112] The modules described in the embodiments of this application can be implemented in software or hardware. The names of the modules do not necessarily limit the functionality of the unit itself.

[0113] The readable storage medium provided in this application is a computer-readable storage medium that stores computer-readable program instructions (i.e., a computer program) for executing the control method of the aforementioned photovoltaic-storage system. This solves the technical problem of simultaneously considering backup power demand and electricity economy during the grid-connected operation of the photovoltaic-storage system. Compared with the prior art, the beneficial effects of the computer-readable storage medium provided in this application are the same as those of the control method of the photovoltaic-storage system provided in the above embodiments, and will not be elaborated upon here.

[0114] The above are only some embodiments of this application and do not limit the patent scope of this application. All equivalent structural transformations made under the technical concept of this application and using the contents of the specification and drawings of this application, or direct / indirect applications in other related technical fields, are included in the patent protection scope of this application.

Claims

1. A control method for a photovoltaic energy storage system, characterized in that, The method includes: In the grid-connected mode of the photovoltaic-storage system, the backup power demand corresponding to different load levels in each time period is determined according to the backup power duration corresponding to different load levels in each time period. Based on the backup power demand, the lower limit of the SOC of the energy storage battery for each time period is determined, and the SOC constraint conditions of the energy storage battery are constructed based on the lower limit of the SOC of the energy storage battery. Based on the SOC constraint of the energy storage battery and with the goal of maximizing economic benefits, the output plan of each energy device in the photovoltaic-storage system is optimized. Based on the first optimization result, a first output plan is obtained, which includes the output of each energy device in each time period, so as to control each energy device accordingly in each time period based on the first output plan.

2. The control method for the photovoltaic energy storage system as described in claim 1, characterized in that, The determination of backup power demand corresponding to different load levels in each time period based on the backup power duration for different load levels in each time period includes: Obtain the backup power duration corresponding to different load levels in different time periods, wherein the importance of different load levels is different, and the backup power duration is positively correlated with the importance of the load level. For a single time period, the backup power demand corresponding to each level of load is determined based on the comparison between the backup power duration corresponding to each level of load in the single time period and the duration of the single time period.

3. The control method for the photovoltaic energy storage system as described in claim 2, characterized in that, The step of determining the backup power demand for each load level in a single time period based on the comparison between the backup power duration corresponding to each load level in a single time period and the duration of the single time period includes: For a single graded load, if the duration of the single time period is less than or equal to the backup power duration, the backup power demand corresponding to the single graded load is determined based on the rated power of all loads under the single graded load. If the duration of a single time period is greater than the backup power duration, a preset value will be used as the backup power demand corresponding to the single tiered load, wherein the preset value is zero.

4. The control method for the photovoltaic energy storage system as described in claim 2, characterized in that, The step of determining the backup power demand for each load level in a single time period based on the comparison between the backup power duration corresponding to each load level in a single time period and the duration of the single time period includes: For a single tiered load, if the duration of the single time period is less than or equal to the backup power duration, the backup power demand corresponding to the single tiered load is predicted based on the historical data of the single tiered load. If the duration of a single time period is greater than the backup power duration, a preset value will be used as the backup power demand corresponding to the single tiered load, wherein the preset value is zero.

5. The control method for the photovoltaic-storage system as described in claim 1, characterized in that, The determination of the lower limit of the SOC of the energy storage battery for each time period based on the backup power demand includes: For a single time period, the minimum remaining power of the energy storage battery is determined based on the backup power demand corresponding to each level of load. Based on the minimum remaining charge of the energy storage battery, the installed capacity of the energy storage battery, and the safe lower boundary value of the SOC of the energy storage battery for the single time period, the lower limit value of the SOC of the energy storage battery for the single time period is determined.

6. The control method for the photovoltaic energy storage system as described in claim 1, characterized in that, The method further includes: In the off-grid mode of the photovoltaic-storage system, the remaining backup power duration for each level of load is determined based on the backup power duration corresponding to each level of load, the status corresponding to each level of load, and the off-grid time of the photovoltaic-storage system. With the goal of maximizing the remaining backup power duration, the output of each energy device in the photovoltaic-storage system and the power outage plan of each graded load are optimized to obtain a second optimization result. Based on the second optimization result, the second output plan of each energy device and the power outage plan of each graded load are obtained, so as to control each energy device accordingly based on the second output plan and control each load accordingly based on the power outage plan.

7. The control method for the photovoltaic energy storage system as described in claim 6, characterized in that, The determination of the remaining backup power duration for each load level, based on the backup power duration corresponding to each load level, the status of each load level, and the off-grid time of the photovoltaic-storage system, includes: For a single tiered load, if the state corresponding to the single tiered load is the power supply state, the remaining backup power duration corresponding to the single tiered load is obtained based on the time difference between the backup power duration corresponding to the single tiered load and the off-grid time of the photovoltaic energy storage system.

8. The control method for the photovoltaic energy storage system as described in claim 6, characterized in that, The energy equipment includes photovoltaics, energy storage batteries, and batteries for electric vehicles; the second power output plan includes: Photovoltaics are used to supply power to the load. If the output of the photovoltaics is insufficient, energy storage batteries are used to supplement the power supply. Alternatively, if the photovoltaic system has surplus power after meeting the load's power consumption, the surplus power is used to charge the energy storage battery; if the energy storage battery is fully charged, the surplus power is used to charge the battery of the electric vehicle. Alternatively, if neither the photovoltaic nor the energy storage battery can meet the power supply requirements of the load, the battery of the electric vehicle can be used to supply power to the critical load.

9. A control device for a photovoltaic energy storage system, characterized in that, The apparatus includes: a memory, a processor, and a computer program stored in the memory and executable on the processor, the computer program being configured to implement the steps of the control method for the optical storage system as described in any one of claims 1 to 8.

10. A storage medium, characterized in that, The storage medium is a computer-readable storage medium, and a computer program is stored on the storage medium. When the computer program is executed by a processor, it implements the steps of the control method of the optical storage system as described in any one of claims 1 to 8.

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