An integrated photovoltaic energy storage management system and control method thereof

Abstract

The present application provides an integrated photovoltaic energy storage management system and a control method thereof, which includes a photovoltaic power generation module, an energy storage module, an energy management module, a grid interaction module, a load management module, a communication and control system, and a user interface, and relates to the field of new energy technology. Specifically, through an intelligent energy management system, the status information of photovoltaic power generation, energy storage, and load is monitored and analyzed in real time, energy distribution and scheduling strategies are optimized, photovoltaic power generation is given priority, and excess electric energy is reasonably stored and utilized, thereby effectively improving energy utilization efficiency. Compared with traditional photovoltaic energy storage systems, it can make more full use of solar energy resources, reduce energy loss during conversion and transmission, reduce dependence on the power grid, and thus reduce electricity costs.

Description

Technical Field

[0001] The present invention relates to the field of new energy technology, and in particular to an integrated photovoltaic energy storage management system and a control method thereof, which is suitable for scenarios such as homes, industry and commerce, and microgrids, and can realize the intelligent integration of photovoltaic power generation, energy storage, and energy management. Background Art

[0002] As the global demand for clean energy continues to grow, the proportion of renewable energy in the energy structure continues to rise. Among them, photovoltaic power generation has become one of the important ways to obtain clean energy due to its advantages such as abundant resources and zero pollution. However, the characteristics of photovoltaic power generation itself determine that it is intermittent and unstable. For example, under poor lighting conditions such as cloudy days and nights, photovoltaic power generation will drop significantly or even stop generating electricity. On the other hand, when the sunlight is strong, the power generation may exceed the local load demand. This power generation characteristic makes it difficult to fully match the load demand of the power grid, posing a challenge to the stability and reliability of power supply.

[0003] To alleviate this problem, energy storage technology has been introduced into photovoltaic systems. However, the photovoltaic energy storage systems currently on the market have many drawbacks. First, the coordinated control efficiency between photovoltaic power generation, energy storage equipment and loads is low. During actual operation, there is a lack of effective information interaction and coordination mechanisms between the various parts, resulting in a large amount of energy loss during conversion and transmission, and low energy utilization. For example, when the photovoltaic power generation is sufficient, the excess electricity cannot be stored in the energy storage equipment in a timely and reasonable manner, or when the load demand changes, the discharge strategy of the energy storage equipment cannot be quickly adjusted to meet the demand.

[0004] Secondly, the system is not intelligent enough. Existing photovoltaic energy storage systems often find it difficult to dynamically manage energy and optimize scheduling based on multiple factors such as real-time light intensity, battery status, load changes, and grid conditions. Most systems can only operate according to simple preset rules and cannot flexibly respond to complex and changeable actual working conditions, making it difficult to further improve energy utilization efficiency.

[0005] In addition, many current photovoltaic energy storage systems lack the ability to respond to grid conditions in real time. When the grid experiences fluctuations, failures, or requires auxiliary services (such as peak shaving, frequency regulation, etc.), these systems are unable to participate in a timely and effective manner and cannot fully play their role in stabilizing grid operations.

[0006] In summary, existing photovoltaic energy storage systems have obvious deficiencies in terms of coordinated control, intelligence level, and grid response capabilities. There is an urgent need for an efficient and intelligent integrated photovoltaic energy storage management system to solve the above problems and improve the overall performance and reliability of photovoltaic energy storage systems. Summary of the Invention

[0007] To overcome existing problems, the embodiments of the present application provide an integrated photovoltaic energy storage management system and a control method thereof. Through an intelligent energy management system, the system monitors and analyzes the status information of photovoltaic power generation, energy storage, and load in real time, optimizes energy distribution and scheduling strategies, prioritizes photovoltaic power generation, and rationally stores and utilizes excess electrical energy, thereby effectively improving energy utilization efficiency. Compared with traditional photovoltaic energy storage systems, the system can more fully utilize solar energy resources, reduce energy losses during conversion and transmission, and reduce dependence on the power grid, thereby reducing electricity costs.

[0008] The technical solution adopted by the embodiment of the present application to solve the technical problem is:

[0009] An integrated photovoltaic energy storage management system and a control method thereof include a photovoltaic power generation module, an energy storage module, an energy management module, a grid interaction module, a load management module, a communication and control system, and a user interface; wherein,

[0010] The photovoltaic power generation module includes a photovoltaic component and an inverter, which is used to convert solar energy into electrical energy;

[0011] PV modules are the core components for achieving photoelectric conversion. Based on the photovoltaic effect, they convert solar photons into electrons, thereby generating direct current (DC). Different types of PV modules (such as monocrystalline silicon, polycrystalline silicon, and thin-film PV modules) have different photoelectric conversion efficiencies and characteristics, and can be selected based on actual application scenarios and needs. The inverter is responsible for converting the DC power generated by the PV modules into AC power that meets the requirements of the grid or load. Its conversion efficiency and output power quality directly affect the overall performance of the PV power generation module. For example, the use of advanced sinusoidal pulse width modulation (SPWM) technology or space vector pulse width modulation (SVPWM) technology can effectively improve the quality of the inverter's output AC power and reduce harmonic content.

[0012] The energy storage module includes a battery pack and a battery management system (BMS) for storing and releasing electrical energy;

[0013] Among them, the battery pack is the carrier of electrical energy storage. Different types of batteries (such as lead-acid batteries, lithium-ion batteries, sodium-sulfur batteries, etc.) have different energy density, charge and discharge efficiency, cycle life and cost characteristics. They need to be selected according to the specific application scenario and budget of the system. The BMS is the key control unit of the energy storage module. It monitors various parameters of the battery pack in real time, such as voltage, current, temperature, and state of charge (SOC). Through precise monitoring and analysis of these parameters, the BMS realizes charge and discharge control, balancing management and fault diagnosis of the battery pack, ensuring the safe and efficient operation of the battery pack and extending the battery life. For example, when the voltage of a single cell in the battery pack is too high or too low, the BMS can adjust it through the balancing circuit to keep the single cells in a consistent state of charge.

[0014] The energy management module includes an energy management system (EMS) for optimizing energy distribution and scheduling;

[0015] The EMS comprehensively analyzes data from photovoltaic power generation modules, energy storage modules, load management modules, and grid interaction modules, and uses advanced optimization algorithms (such as linear programming and dynamic programming) to optimize energy allocation and scheduling decisions. For example, based on factors such as real-time light intensity, battery SOC value, load power demand, and grid electricity prices, the EMS formulates optimal power generation, energy storage, and electricity consumption strategies to ensure efficient energy utilization and minimize costs. At the same time, the EMS also has the function of data exchange and command transmission with other system modules to achieve coordinated operation of the entire system.

[0016] The grid interaction module includes a grid-connected inverter and a protection device for realizing bidirectional power exchange with the grid;

[0017] The grid-connected inverter is responsible for achieving bidirectional power exchange with the power grid, transmitting excess power generated by the photovoltaic power generation modules to the grid and obtaining power from the grid when needed. To ensure the stability and power quality of the grid connection process, the grid-connected inverter must meet strict grid access standards, such as frequency, voltage deviation, and harmonic content. The protection device monitors the operating status of the grid and system in real time. When abnormal conditions such as overvoltage, undervoltage, overcurrent, and leakage occur, the circuit is quickly disconnected to protect the safety of system equipment and personnel. For example, when the grid voltage exceeds the normal range, the protection device immediately operates to prevent excessive voltage from damaging the electrical equipment in the system.

[0018] The load management module includes an intelligent load controller for adjusting the load according to the energy supply situation;

[0019] The controller intelligently adjusts connected loads based on energy supply conditions, such as photovoltaic power generation, energy storage battery capacity, and grid electricity prices. For some adjustable loads (such as smart home appliances and industrial equipment), the intelligent load controller can interact with the load through a communication interface (such as ZigBee, Wi-Fi, Bluetooth, etc.) and adjust the load's operating power or operating time according to the set strategy. For example, when photovoltaic power generation is sufficient and grid electricity prices are high, the intelligent load controller can prioritize starting high-power loads to fully utilize low-cost photovoltaic power generation. When photovoltaic power generation is insufficient or grid electricity prices are low, the intelligent load controller can appropriately reduce the power of non-critical loads or delay their operating time to achieve rational energy utilization and cost control.

[0020] The communication and control system includes a communication module and a control system for realizing data transmission and instruction execution between modules;

[0021] Among them, the communication module is responsible for realizing data transmission between various system modules to ensure accurate and real-time interaction of information. A variety of communication methods can be used. For example, wired communication (such as RS485, Ethernet, etc.) is suitable for modules with short distances, large data transmission volume and high stability requirements; wireless communication (such as ZigBee, LoRa, 4G / 5G, etc.) is suitable for scenarios with long distances, difficult wiring or mobility requirements. The control system receives data information from each module and coordinates and controls each module according to the preset control strategy and the instructions of the EMS to ensure the stable operation of the system. For example, when the EMS issues an instruction to adjust the output power of the photovoltaic power generation module, the control system conveys the instruction to the inverter of the photovoltaic power generation module through the communication module to achieve precise adjustment of the generated power.

[0022] The user interface includes a mobile application and a web interface for real-time monitoring of system status and energy consumption data;

[0023] Among them, the mobile application allows users to monitor system status and energy consumption data anytime and anywhere through mobile devices such as mobile phones and tablets. It is easy to operate and has strong real-time performance. The Web interface provides more comprehensive and detailed system information display and management functions. Users can access it through a computer browser. It is suitable for scenarios that require in-depth data analysis and system configuration. The user interface not only displays the system's various operating parameters in real time, such as photovoltaic power generation, energy storage battery power, load power, grid interaction power, etc., but also provides energy consumption data statistical analysis functions to help users understand energy usage and formulate energy-saving strategies. At the same time, users can remotely control some equipment (such as smart loads, charging equipment, etc.) through the user interface to achieve a more intelligent energy management experience.

[0024] Preferably, the energy management module implements energy optimization scheduling through an energy management system (EMS), and its optimization objective function is:

[0025] min(C grid *P grid +C battery *P battery )

[0026] Among them, C grid is the grid electricity price, P grid is the power obtained from the grid, C battery is the battery charging and discharging cost, P battery It is the battery charging and discharging power.

[0027] Preferably, the energy management system (EMS) needs to meet the following constraints during the scheduling process:

[0028] P pv +P battery +Pgrid =P load

[0029] Among them, P pv is the photovoltaic power generation power, P load The power demanded by the load.

[0030] Preferably, the battery state of charge (SOC) of the energy storage module is calculated by the following formula:

[0031]

[0032] Among them, SOC(t) is the battery state at the current moment, SOC(t-1) is the battery state at the previous moment, Δt is the time interval, E max The maximum capacity of the battery.

[0033] Preferably, the grid-connected inverter output power P of the grid interaction module inv The following relations are satisfied:

[0034] P inv =η*P DC

[0035] Where, η is the inverter efficiency, P DC is the DC input power.

[0036] Preferably, the load priority control strategy of the load management module is implemented by the following formula:

[0037] P critical ≤P pv +P battery +P grid

[0038] Among them, P critical The power requirements of the critical loads.

[0039] Preferably, the user interface displays the energy balance state of the system in real time, and the energy balance formula is:

[0040] E pv +E battery +E grid =E load

[0041] Among them, E pv is the photovoltaic power generation energy, E battery is the battery charging and discharging energy, E grid is the grid interaction energy, E load Consumes energy for the load.

[0042] The following steps are involved:

[0043] Step 1: Real-time collection of photovoltaic power generation data, energy storage status, load demand and grid information;

[0044] Step 2: Based on the collected data, the energy management system (EMS) performs energy optimization scheduling, giving priority to photovoltaic power generation and storing excess electricity in the battery pack;

[0045] Step 3: Charge when the grid electricity price is low and discharge when the electricity price is high, thus achieving peak shaving and valley filling;

[0046] Step 4: When the power grid fails, switch to off-grid mode to provide backup power for the load;

[0047] Step 5: Display system status and energy consumption data in real time through the user interface and provide remote control function.

[0048] Preferably, the objective function of the energy optimization scheduling is:

[0049] min(C grid *P grid +C battery *P battery )

[0050] And satisfy the following constraints:

[0051] P pv +P battery +P grid =P load

[0052] And the constraints of battery charge and discharge state (SOC): SOC (t)

[0053] SOC min ≤SOC(t)≤SOC max

[0054] Among them, SOC min and SOC max are the minimum and maximum allowable states of the battery, respectively.

[0055] The advantages of the embodiments of the present application are:

[0056] 1. Through the intelligent energy management system, the status information of photovoltaic power generation, energy storage and load is monitored and analyzed in real time, the energy distribution and scheduling strategy is optimized, photovoltaic power generation is given priority, and excess electricity is reasonably stored and utilized, effectively improving energy utilization efficiency. Compared with traditional photovoltaic energy storage systems, it can make fuller use of solar energy resources, reduce energy loss during conversion and transmission, reduce dependence on the power grid, and thus reduce electricity costs.

[0057] 2. The system implements the peak-to-valley load-filling function. Based on the peak-to-valley changes in grid electricity prices, the system rationally arranges the charging and discharging time and power of the energy storage modules. Charging occurs when electricity prices are low, reducing the grid's valley load; discharging occurs when electricity prices are high, alleviating the grid's peak power supply pressure. This effectively balances the grid load and reduces the peak-to-valley difference. This helps improve the grid's stability and reliability, and reduces the risk of grid failures caused by excessive load fluctuations. It also provides certain auxiliary services for the grid, such as peak shaving and frequency regulation.

[0058] 3. In the event of a power grid failure, the system can quickly switch to off-grid mode, with the energy storage module providing backup power for the load, ensuring the continued operation of important loads. This enhances the reliability and anti-interference capability of the power system and provides users with a more stable power supply. For some places with high requirements for power supply continuity (such as hospitals, data centers, communication base stations, etc.), the backup power supply function of this system can effectively avoid significant losses caused by power outages.

[0059] 4. The user interface is friendly and provides real-time monitoring and remote control functions. Users can view the system's operating status and energy consumption data anytime and anywhere through mobile applications or web interfaces, making it convenient for users to understand energy usage and formulate personalized energy-saving strategies. At the same time, the remote control function enables users to control the equipment in the system at different locations, realizing more intelligent energy management. BRIEF DESCRIPTION OF THE DRAWINGS

[0060] Figure 1 The figure is a flow chart of an integrated photovoltaic energy storage management system and its control method according to the present invention. DETAILED DESCRIPTION

[0061] The technical solutions in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without making creative work are within the scope of protection of the present invention. In addition, for the convenience of description below, the "upper", "lower", "left" and "right" quoted are the same as the upper, lower, left and right directions of the drawings themselves. The "first", "second" and so on in the following text are distinguished for the description and have no other special meanings.

[0062] The embodiment of the present application solves the problems in the prior art by providing an integrated photovoltaic energy storage management system and a control method thereof. Through the intelligent energy management system, it monitors and analyzes the status information of photovoltaic power generation, energy storage and load in real time, optimizes energy distribution and scheduling strategies, gives priority to photovoltaic power generation, reasonably stores and utilizes excess electric energy, and effectively improves energy utilization efficiency. Compared with traditional photovoltaic energy storage systems, it can make more full use of solar energy resources, reduce energy loss in the conversion and transmission process, reduce dependence on the power grid, and thus reduce electricity costs; the system realizes the peak shaving and valley filling function, and reasonably arranges the charging and discharging time and power of the energy storage module according to the peak and valley changes of the power grid electricity price, charges when the electricity price is low, and reduces the valley load of the power grid; discharges when the electricity price is peak, and reduces the peak power supply pressure of the power grid, effectively balances the power grid load, and reduces the peak-valley difference of the power grid, which helps to improve the stability and reliability of the power grid and reduce the power grid caused by load It reduces the risk of failures caused by excessive load fluctuations, and also provides certain auxiliary services to the power grid, such as peak load regulation and frequency regulation. In the event of a grid failure, the system can quickly switch to off-grid mode, with the energy storage module providing backup power for the load to ensure the continuous operation of important loads. This enhances the reliability and anti-interference capability of the power system and provides users with a more stable power supply. For some places with high requirements for power supply continuity (such as hospitals, data centers, communication base stations, etc.), the backup power supply function of this system can effectively avoid significant losses caused by power outages. The user interface is user-friendly and provides real-time monitoring and remote control functions. Users can view the system's operating status and energy consumption data anytime and anywhere through mobile applications or web interfaces, making it easier for users to understand energy usage and formulate personalized energy-saving strategies. At the same time, the remote control function enables users to control the equipment in the system from different locations, achieving more intelligent energy management.

[0063] The technical solution in the embodiments of the present application is to solve the above problems, and the overall idea is as follows:

[0064] Example

[0065] This embodiment provides an integrated photovoltaic energy storage management system and a control method thereof. Figure 1 As shown, it includes photovoltaic power generation module, energy storage module, energy management module, grid interaction module, load management module, communication and control system and user interface; among which,

[0066] Photovoltaic power generation modules include photovoltaic panels and inverters, which are used to convert solar energy into electrical energy;

[0067] PV modules are the core components for achieving photoelectric conversion. Based on the photovoltaic effect, they convert solar photons into electrons, thereby generating direct current (DC). Different types of PV modules (such as monocrystalline silicon, polycrystalline silicon, and thin-film PV modules) have different photoelectric conversion efficiencies and characteristics, and can be selected based on actual application scenarios and needs. The inverter is responsible for converting the DC power generated by the PV modules into AC power that meets the requirements of the grid or load. Its conversion efficiency and output power quality directly affect the overall performance of the PV power generation module. For example, the use of advanced sinusoidal pulse width modulation (SPWM) technology or space vector pulse width modulation (SVPWM) technology can effectively improve the quality of the inverter's output AC power and reduce harmonic content.

[0068] The energy storage module includes a battery pack and a battery management system (BMS) for storing and releasing electrical energy;

[0069] Among them, the battery pack is the carrier of electrical energy storage. Different types of batteries (such as lead-acid batteries, lithium-ion batteries, sodium-sulfur batteries, etc.) have different energy density, charge and discharge efficiency, cycle life and cost characteristics. They need to be selected according to the specific application scenario and budget of the system. The BMS is the key control unit of the energy storage module. It monitors various parameters of the battery pack in real time, such as voltage, current, temperature, and state of charge (SOC). Through precise monitoring and analysis of these parameters, the BMS realizes charge and discharge control, balancing management and fault diagnosis of the battery pack, ensuring the safe and efficient operation of the battery pack and extending the battery life. For example, when the voltage of a single cell in the battery pack is too high or too low, the BMS can adjust it through the balancing circuit to keep the single cells in a consistent state of charge.

[0070] The energy management module includes the energy management system (EMS) to optimize energy distribution and scheduling;

[0071] The EMS comprehensively analyzes data from photovoltaic power generation modules, energy storage modules, load management modules, and grid interaction modules, and uses advanced optimization algorithms (such as linear programming and dynamic programming) to optimize energy allocation and scheduling decisions. For example, based on factors such as real-time light intensity, battery SOC value, load power demand, and grid electricity prices, the EMS formulates optimal power generation, energy storage, and electricity consumption strategies to ensure efficient energy utilization and minimize costs. At the same time, the EMS also has the function of data exchange and command transmission with other system modules to achieve coordinated operation of the entire system.

[0072] The grid interaction module includes a grid-connected inverter and protection devices to achieve bidirectional power exchange with the grid;

[0073] The grid-connected inverter is responsible for achieving bidirectional power exchange with the power grid, transmitting excess power generated by the photovoltaic power generation modules to the grid and obtaining power from the grid when needed. To ensure the stability and power quality of the grid connection process, the grid-connected inverter must meet strict grid access standards, such as frequency, voltage deviation, and harmonic content. The protection device monitors the operating status of the grid and system in real time. When abnormal conditions such as overvoltage, undervoltage, overcurrent, and leakage occur, the circuit is quickly disconnected to protect the safety of system equipment and personnel. For example, when the grid voltage exceeds the normal range, the protection device immediately operates to prevent excessive voltage from damaging the electrical equipment in the system.

[0074] The load management module includes an intelligent load controller for adjusting the load according to the energy supply situation;

[0075] The controller intelligently adjusts connected loads based on energy supply conditions, such as photovoltaic power generation, energy storage battery capacity, and grid electricity prices. For some adjustable loads (such as smart home appliances and industrial equipment), the intelligent load controller can interact with the load through a communication interface (such as ZigBee, Wi-Fi, Bluetooth, etc.) and adjust the load's operating power or operating time according to the set strategy. For example, when photovoltaic power generation is sufficient and grid electricity prices are high, the intelligent load controller can prioritize starting high-power loads to fully utilize low-cost photovoltaic power generation. When photovoltaic power generation is insufficient or grid electricity prices are low, the intelligent load controller can appropriately reduce the power of non-critical loads or delay their operating time to achieve rational energy utilization and cost control.

[0076] The communication and control system includes a communication module and a control system, which are used to realize data transmission and instruction execution between modules;

[0077] Among them, the communication module is responsible for realizing data transmission between various system modules to ensure accurate and real-time interaction of information. A variety of communication methods can be used. For example, wired communication (such as RS485, Ethernet, etc.) is suitable for modules with short distances, large data transmission volume and high stability requirements; wireless communication (such as ZigBee, LoRa, 4G / 5G, etc.) is suitable for scenarios with long distances, difficult wiring or mobility requirements. The control system receives data information from each module and coordinates and controls each module according to the preset control strategy and the instructions of the EMS to ensure the stable operation of the system. For example, when the EMS issues an instruction to adjust the output power of the photovoltaic power generation module, the control system conveys the instruction to the inverter of the photovoltaic power generation module through the communication module to achieve precise adjustment of the generated power.

[0078] The user interface includes a mobile app and a web interface for real-time monitoring of system status and energy consumption data;

[0079] Among them, the mobile application allows users to monitor system status and energy consumption data anytime and anywhere through mobile devices such as mobile phones and tablets. It is easy to operate and has strong real-time performance. The Web interface provides more comprehensive and detailed system information display and management functions. Users can access it through a computer browser. It is suitable for scenarios that require in-depth data analysis and system configuration. The user interface not only displays the system's various operating parameters in real time, such as photovoltaic power generation, energy storage battery power, load power, grid interaction power, etc., but also provides energy consumption data statistical analysis functions to help users understand energy usage and formulate energy-saving strategies. At the same time, users can remotely control some equipment (such as smart loads, charging equipment, etc.) through the user interface to achieve a more intelligent energy management experience.

[0080] The energy management module realizes energy optimization scheduling through the energy management system (EMS), and its optimization objective function is:

[0081] min(C grid *P grid +C battery *P battery )

[0082] Among them, C grid is the grid electricity price, P grid is the power obtained from the grid, C battery is the battery charging and discharging cost, P battery It is the battery charging and discharging power.

[0083] The energy management system (EMS) must meet the following constraints during the scheduling process:

[0084] P pv +P battery +P grid =P load

[0085] Among them, P pv is the photovoltaic power generation power, P load The power demanded by the load.

[0086] The battery state of charge (SOC) of the energy storage module is calculated using the following formula:

[0087]

[0088] Among them, SOC(t) is the battery state at the current moment, SOC(t-1) is the battery state at the previous moment, Δt is the time interval, E max The maximum capacity of the battery.

[0089] The grid-connected inverter output power P of the grid interaction module inv The following relations are satisfied:

[0090] P inv =η*P DC

[0091] Where, η is the inverter efficiency, P DC is the DC input power.

[0092] The load priority control strategy of the load management module is implemented by the following formula:

[0093] P critical ≤P pv +P battery +P grid

[0094] Among them, P critical The power requirements of the critical loads.

[0095] The user interface displays the energy balance status of the system in real time. The energy balance formula is:

[0096] E pv +E battery +E grid =E load

[0097] Among them, E pv is the photovoltaic power generation energy, E battery is the battery charging and discharging energy, E grid is the grid interaction energy, E load Consumes energy for the load.

[0098] The following steps are involved:

[0099] Step 1: Real-time collection of photovoltaic power generation data, energy storage status, load demand and grid information. Various sensors are used to collect photovoltaic power generation data (such as photovoltaic module output voltage, current, power, light intensity, etc.), energy storage status (such as battery pack voltage, current, temperature, SOC, etc.), load demand (such as load power, type, operating status, etc.) and grid information (such as grid voltage, frequency, electricity price, etc.) in real time. These sensors are distributed in various key locations of the system to ensure the accuracy and real-time nature of the collected data. For example, voltage and current sensors are installed at the output end of the photovoltaic module to monitor the power generation of the photovoltaic module in real time; temperature sensors and power sensors are installed in the battery pack to accurately obtain battery status information. The collected data is transmitted to the EMS of the energy management module through the communication module for processing;

[0100] Step 2: Based on the collected data, the energy management system (EMS) performs energy optimization scheduling, giving priority to photovoltaic power generation and storing excess electricity in the battery pack. The EMS uses the optimization algorithm to optimize energy scheduling based on the collected data. First, photovoltaic power generation is given priority to meet local load demand. When the photovoltaic power generation exceeds the load demand, the excess electricity is stored in the battery pack to improve the energy self-sufficiency rate. For example, through real-time monitoring and analysis of the output power of the photovoltaic module, the load power and the battery SOC value, the EMS calculates the amount of storable electricity and sends charging instructions to the BMS of the energy storage module to control the charging process of the battery pack and ensure the safety and efficiency of the charging process.

[0101] Step 3: Charge when the grid electricity price is low and discharge when the electricity price is high, thus achieving peak shaving and valley filling. Taking into account the peak-valley changes in the grid electricity price, the EMS formulates a corresponding charging and discharging strategy. During the period of low grid electricity price, the energy storage module is controlled to charge from the grid and store the low-priced electricity; during the period of peak electricity price, the energy storage module is controlled to discharge to the load, reducing the purchase of electricity from the grid, thereby achieving peak shaving and valley filling and reducing electricity costs. For example, by communicating with the grid to obtain real-time electricity price information, combined with the battery SOC value and load demand forecast, the EMS plans the charging and discharging time and power of the energy storage module in advance to achieve the best economic benefits. At the same time, this peak shaving and valley filling operation helps to balance the grid load, reduce the peak-valley difference of the grid, and improve the stability and reliability of the grid.

[0102] Step 4: When the power grid fails, switch to off-grid mode to provide backup power for the load, wherein the power grid status is monitored in real time. When a power grid failure (such as power outage, voltage anomaly, frequency anomaly, etc.) is detected, the control system quickly switches to off-grid mode. In off-grid mode, the energy storage module provides power support to the load as a backup power source to ensure the continuous operation of important loads. For example, by installing a voltage and frequency monitoring device at the grid access end, the grid parameters are monitored in real time. Once a grid fault signal is detected, the control system immediately cuts off the connection with the grid and starts the circuit for the energy storage module to supply power to the load. At the same time, the output voltage and frequency of the energy storage module are adjusted to match the requirements of the load. In off-grid mode, the EMS continues to monitor and manage the power of the energy storage module, reasonably allocates power according to the load demand, and ensures that the backup power supply can continuously and stably supply power to the load until the grid returns to normal or the energy storage module is exhausted.

[0103] Step 5. Display the system status and energy consumption data in real time through the user interface, and provide remote control function. The system status (such as the operating parameters and working mode of each module) and energy consumption data (such as daily, weekly and monthly power generation, power consumption, energy storage power changes, etc.) are displayed in real time through the user interface. Users can intuitively understand the operation of the system and discover potential problems in time. At the same time, the user interface provides remote control function. Users can remotely send instructions through mobile applications or web interfaces to control some devices in the system (such as smart loads, charging equipment, etc.). For example, when users are out, they can check the operating status of the photovoltaic energy storage system at home through mobile applications on their mobile phones. If they find that the photovoltaic power generation is sufficient and the energy storage battery is full, they can remotely start the smart appliances at home to make full use of the excess electricity.

[0104] The objective function of energy optimization scheduling is:

[0105] min(C grid *P grid +C battery *P battery )

[0106] And satisfy the following constraints:

[0107] P pv +P battery +P grid =P load

[0108] And the constraints of battery charge and discharge state (SOC): SOC (t)

[0109] SOC min ≤SOC(t)≤SOC max

[0110] Among them, SOC min and SOC max are the minimum and maximum allowable states of the battery, respectively.

[0111] By adopting the above technical solutions:

[0112] Collect photovoltaic power generation data, energy storage status, load demand and grid information in real time; based on the collected data, optimize energy scheduling through the energy management system (EMS), give priority to photovoltaic power generation, and store excess electricity in the battery pack; charge when the grid electricity price is low, and discharge when the electricity price is high, so as to achieve peak shaving and valley filling; in the event of a grid failure, switch to off-grid mode to provide backup power for the load; display system status and energy consumption data in real time through the user interface, and provide remote control function; through the intelligent energy management system, monitor and analyze the status information of photovoltaic power generation, energy storage and load in real time, optimize energy distribution and scheduling strategies, give priority to photovoltaic power generation, reasonably store and utilize excess electricity, effectively improve energy utilization efficiency, and compared with traditional photovoltaic energy storage systems, can make more full use of solar energy resources, reduce energy loss during conversion and transmission, reduce dependence on the grid, and thus reduce electricity costs.

[0113] Finally, it should be noted that the above embodiments are merely examples for the purpose of illustrating the present invention and are not intended to limit the embodiments. Those skilled in the art will readily appreciate that other variations or modifications based on the above description are possible. It is not necessary and impossible to provide an exhaustive list of all embodiments. However, obvious variations or modifications arising therefrom remain within the scope of protection of the present invention.

Claims

1. An integrated photovoltaic energy storage management system, characterized in that: It includes photovoltaic power generation module, energy storage module, energy management module, grid interaction module, load management module, communication and control system and user interface; The photovoltaic power generation module includes a photovoltaic component and an inverter, which is used to convert solar energy into electrical energy; The energy storage module includes a battery pack and a battery management system (BMS) for storing and releasing electrical energy; The battery state of charge (SOC) of the energy storage module is calculated using the following formula: = + ， in, is the current battery status, The battery status at the last moment. is the time interval, is the maximum capacity of the battery; The energy management module includes an energy management system (EMS) for optimizing energy distribution and scheduling; The energy management module implements energy optimization scheduling through the energy management system (EMS), and its optimization objective function is: min( * + * ) in, is the grid electricity price, is the power obtained from the grid, is the battery charging and discharging cost, The charging and discharging power of the battery; The energy management system (EMS) must meet the following constraints during the scheduling process: + + = ， in, is the photovoltaic power generation power, is the load demand power; The objective function of the energy optimization scheduling is: min( * + * ) And satisfy the following constraints: + + = ， And the constraints of battery state of charge and discharge (SOC): , ， in, and are the minimum and maximum allowable states of the battery respectively; The grid interaction module includes a grid-connected inverter and a protection device for realizing bidirectional power exchange with the grid; The load management module includes an intelligent load controller for adjusting the load according to the energy supply situation; The communication and control system includes a communication module and a control system for realizing data transmission and instruction execution between modules; The user interface includes a mobile application and a web interface for real-time monitoring of system status and energy consumption data.

2. The integrated photovoltaic energy storage management system according to claim 1, characterized in that: The grid-connected inverter output power of the grid interaction module The following relations are satisfied: =h* , Where η is the inverter efficiency, is the DC input power.

3. The integrated photovoltaic energy storage management system according to claim 1, characterized in that: The load priority control strategy of the load management module is implemented by the following formula: + + ， in, The power requirements of the critical loads.

4. The integrated photovoltaic energy storage management system according to claim 1, characterized in that: The user interface displays the energy balance status of the system in real time, and the energy balance formula is: + + = ， in, For photovoltaic power generation energy, Charge and discharge energy for the battery, is the grid interaction energy, Consumes energy for the load.

5. A control method for an integrated photovoltaic energy storage management system, applied to an integrated photovoltaic energy storage management system according to any one of claims 1 to 4, characterized in that: The following steps are involved: Step 1: Real-time collection of photovoltaic power generation data, energy storage status, load demand and grid information; Step 2: Based on the collected data, the energy management system (EMS) performs energy optimization scheduling, giving priority to photovoltaic power generation and storing excess electricity in the battery pack; Step 3: Charge when the grid electricity price is low and discharge when the electricity price is high, thus achieving peak shaving and valley filling; Step 4: When the power grid fails, switch to off-grid mode to provide backup power for the load; Step 5: Display system status and energy consumption data in real time through the user interface and provide remote control function.

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