Multi-energy cooperative intelligent charging energy management system

Abstract

The invention relates to the technical field of multi-energy collaborative intelligent charging, in particular to a multi-energy collaborative intelligent charging energy management system, which comprises a photovoltaic power generation unit, a power grid access unit, an energy storage battery unit, a charging unit, an energy management unit, a dynamic energy scheduling module, a peak-valley electricity price strategy module, a vehicle network interaction module and a virtual power plant access module, through cooperation of multiple hardware units and multiple modules, scheduling and management of electric energy in the system are realized. The system can integrate photovoltaic, energy storage battery and power grid electric energy, preferentially uses photovoltaic energy through dynamic energy management, has a dynamic energy scheduling capability, a peak-valley electricity price strategy and a vehicle-network interaction capability, supports access to a virtual power plant to participate in power grid frequency modulation, effectively reduces the overall operation cost, and improves the power grid frequency modulation efficiency. The method is suitable for distributed energy scenes such as industrial parks and light storage and charging integrated power stations.

Description

Technical Field

[0001] The present invention relates to the field of multi-energy collaborative intelligent charging technology, and in particular to a multi-energy collaborative intelligent charging energy management system. Background Art

[0002] As society develops, the demand for charging electrical devices is increasing. Traditional charging methods rely primarily on external power grids, which have certain limitations. First, the grid may face supply pressure during peak hours, and the simultaneous charging of a large number of electrical devices can impact grid stability. Second, relying solely on grid power cannot fully utilize renewable energy sources such as solar energy.

[0003] In recent years, distributed energy technologies such as photovoltaic power generation have made significant progress. By converting solar energy into electricity, these technologies have opened up new avenues for energy supply. However, photovoltaic power generation is intermittent and fluctuating, with output significantly affected by factors such as weather and sunlight, making it difficult to directly meet stable charging needs. Furthermore, energy storage battery technology is also developing continuously, storing excess energy and releasing it when needed, thus playing a role in "peak shaving and valley filling." However, currently, energy storage batteries mostly operate independently, lacking effective coordination with distributed energy resources and other energy supply systems, and thus failing to fully realize their role in energy management.

[0004] The stable operation of the power grid is crucial to the entire energy system. During peak demand periods, excessive grid load can lead to power shortages or even blackouts. During off-peak demand periods, idle power generation equipment wastes energy. Furthermore, while peak-off-peak electricity pricing policies have guided user behavior to a certain extent, the lack of a mechanism to adjust energy usage and storage strategies in charging devices makes it difficult for users to fully utilize the peak-off-peak price difference to reduce charging costs, nor can they effectively contribute to the grid's peak load regulation.

[0005] The emergence of vehicle-to-grid (V2G) technology enables energy exchange between power devices and the power grid. By dynamically adjusting the charging power of power devices, this technology not only meets the vehicle's own charging needs but also provides ancillary services based on grid conditions. Furthermore, virtual power plants, as a new type of energy aggregation and management system, can integrate distributed energy resources, energy storage devices, and other resources, participate in ancillary services such as grid frequency regulation, and improve grid efficiency and reliability. Currently, the application of V2G and virtual power plant technologies in power device charging energy management is still immature, lacking a comprehensive, intelligent energy management system that can organically integrate these technologies to achieve coordinated and optimized multi-energy operation. Summary of the Invention

[0006] The present invention provides a multi-energy collaborative intelligent charging energy management system, which aims to solve the problems of existing charging technologies such as dependence on the power grid leading to unstable power supply, inefficient utilization of renewable energy, insufficient coordination between distributed energy and energy storage, imbalance of peak and valley loads in the power grid, limitations of the peak and valley electricity price mechanism, and insufficient integration of vehicle-grid interaction and virtual power plants.

[0007] To solve the above technical problems, the present invention provides the following technical solutions: a multi-energy collaborative intelligent charging energy management system, comprising: Photovoltaic power generation units, which convert solar energy into electricity; A grid access unit, used for accessing an external grid; Energy storage battery cells for storing and releasing electrical energy; Charging unit, used to provide charging services for electrical equipment; The energy management unit is used to connect with multiple hardware units and realize the scheduling and management of power within the system through the synergy of multiple modules; Dynamic energy scheduling module, used to schedule electric energy according to energy supply; Peak-valley electricity price strategy module, used to dispatch electricity according to the peak-valley electricity price information of the power grid; The vehicle-grid interaction module is used to dispatch power according to the charging needs of power-consuming devices and the load of the power grid; The virtual power plant access module is used to support the system access to the virtual power plant and participate in grid frequency regulation.

[0008] Furthermore, the photovoltaic power generation unit includes a plurality of photovoltaic panels, and the photovoltaic panels are connected to the energy management unit via a photovoltaic inverter; The working principle of the photovoltaic power generation unit is as follows: When sunlight shines on a photovoltaic panel, the energy of the photons excites the electrons in the semiconductor material, forming a DC voltage at both ends of the panel, generating and outputting DC electricity; The photovoltaic inverter adjusts the operating point of the photovoltaic panel through the MPPT technology, converts the direct current output by the photovoltaic panel into alternating current and adjusts its voltage, frequency and phase, and transmits the alternating current to the charging unit.

[0009] Furthermore, the grid access unit includes a grid access switch and an electric energy metering device. The electric energy metering device includes an electric energy meter, a current transformer, and a voltage transformer for measuring the input and output of grid electric energy. The working principle of the grid access unit is as follows: When the system uses external grid power, the grid access switch is closed and the system is connected to the external grid; When the system only uses electricity from energy storage batteries and photovoltaic power generation, the grid access switch is disconnected and the system is disconnected from the external grid.

[0010] Furthermore, the energy storage battery unit includes a plurality of energy storage battery packs, and the energy storage battery packs are connected to the energy management unit via a bidirectional converter; The working principle of the energy storage battery unit is as follows: When the system charges the energy storage battery pack, the energy management unit converts the AC power from the photovoltaic power generation unit or the grid access unit into DC power through the bidirectional converter and transmits it to the energy storage battery pack; When the system uses the power of the energy storage battery pack, the energy management unit converts the direct current of the energy storage battery pack into alternating current through a bidirectional converter and transmits it to the charging unit.

[0011] Furthermore, the charging unit is connected to the power-consuming device through the charging port and is connected to the energy management unit through the charging controller. Its working principle is as follows: The user connects the charging port to the power-consuming device to charge the power-consuming device; The charging controller receives the scheduling instructions from the energy management unit and adjusts the charging power of each charging unit according to the instructions; During the charging process, the charging unit monitors the charging requirements of the power-consuming device and feeds back to the energy management unit. The charging requirements of the power-consuming device include the remaining power of the power-consuming device, the battery capacity, and the charging power.

[0012] Furthermore, the energy management unit works as follows: Data interaction and instruction transmission: The energy management unit receives data from each unit or module and sends it to the unit or module that uses the data; The unit or module generates a scheduling instruction based on the received data and sends it to the energy management unit, which distributes the scheduling instruction to the units or modules that received the instruction to achieve collaborative work; Define the priority of each module instruction: Determine the priority of the module based on its function, impact on system stability, and urgency, and assign a priority identifier: Virtual power plant access module: directly participates in grid frequency regulation, has the highest priority, and is assigned a priority identifier of 1; Dynamic energy scheduling module: used for energy allocation, with a middle priority and an allocation priority identifier of 2; Peak-valley electricity price strategy module: used for cost optimization, with a lower priority and assigned a priority identifier of 3; Vehicle-network interaction module: used for user benefit optimization, with the lowest priority and assigned a priority identifier of 4; The priority identifier is stored in the module's configuration file or directly embedded in the module code; When multiple modules issue instructions at the same time, the system executes the instructions issued by the modules in the order of priority identifiers.

[0013] Furthermore, the dynamic energy scheduling module generates scheduling instructions according to the energy supply status through a scheduling algorithm based on fuzzy logic. The principle is as follows: The dynamic energy scheduling module obtains input variables through the energy management unit and obtains the grid electricity price through the peak-valley electricity price strategy module. The input variables include the power generated by the photovoltaic panels and the charging requirements of the electrical equipment. A fuzzy set is established by combining the input variables with the grid electricity price and inputted into the fuzzy logic controller. The fuzzy logic controller analyzes the fuzzy set through a scheduling algorithm based on fuzzy logic to obtain fuzzy output variables; The fuzzy output variables are defuzzified by the center of gravity method to obtain a scheduling instruction, which includes a power regulation object, a power consumption object, and a charge and discharge power. The power regulation object includes a photovoltaic power generation unit, an energy storage battery unit, and an external power grid. The power consumption object includes an energy storage battery unit and power-consuming equipment.

[0014] Furthermore, the peak-valley electricity price strategy module obtains peak-valley electricity price information of the power grid from the power grid operator. The peak-valley electricity price information of the power grid includes peak electricity price period, valley electricity price period, and normal electricity price period. The scheduling instruction is generated according to the peak-valley electricity price information of the power grid. The scheduling instruction includes: During off-peak electricity price periods, the grid access unit connects to the external grid and uses grid power to provide power to the charging unit and energy storage battery unit. During peak electricity price periods, the grid access unit is disconnected from the external grid, and the energy storage battery unit is used to provide power to the charging unit. During the normal electricity price period, the peak-valley electricity price strategy module does not perform scheduling.

[0015] Furthermore, the vehicle-grid interaction module is connected to an external billing system, and adopts a scheduling algorithm based on vehicle-grid interaction (V2G) to generate scheduling instructions based on grid load and grid peak and valley electricity price information. The scheduling instructions include: The peak and valley electricity price information of the power grid is obtained from the peak and valley electricity price strategy module. When the system is connected to the power grid, the vehicle-grid interaction module obtains the power grid load from the power grid and determines the power grid load level based on the load percentage. When the grid load is low or the electricity price is low, the vehicle-grid interaction module uses grid power to charge electrical equipment and energy storage battery units; When the grid load is high or during peak electricity price periods, the vehicle-grid interaction module calls on the electricity of the energy storage battery unit to charge the electrical equipment, and allows the electrical equipment to feed electricity back to the grid. The electricity feedback amount is obtained through the external billing system, and the user's profit is calculated based on the received electricity feedback amount and the grid electricity price information.

[0016] Furthermore, the virtual power plant access module establishes a connection with the control center of the virtual power plant through the standard communication protocol IEC 61850 to obtain grid information, wherein the grid information includes grid frequency deviation and frequency regulation requirements. The virtual power plant access module generates a dispatch instruction based on the grid information, wherein the dispatch instruction includes: When the grid frequency increases, the charging power of the energy storage battery is reduced or the discharging power is increased, and the charging power of the charging unit is reduced; When the grid frequency decreases, the charging power of the energy storage battery is increased or the discharging power is reduced, and the charging power of the charging unit is increased.

[0017] The beneficial effects brought about by the technical solution provided by the present invention include at least: The present invention realizes the coordinated utilization of multiple energy sources by integrating photovoltaic power generation units, energy storage battery units and grid access units, fully utilizes renewable energy, reduces dependence on traditional power grids, and effectively reduces operating costs. This multi-energy coordination and dynamic scheduling method not only improves energy utilization efficiency, but also saves users a lot of electricity expenses.

[0018] The vehicle-grid interaction module in the present invention is connected to an external billing system and adopts a V2G-based scheduling algorithm to dynamically adjust the charging power according to the grid load and peak and valley electricity price information. When the grid load is high or during peak electricity price periods, the power-consuming equipment is allowed to feed excess electric energy back to the grid. This two-way energy interaction optimizes the utilization efficiency of charging equipment, enhances the stability and flexibility of the grid, avoids the grid overload problem caused by centralized charging, and also brings economic benefits to users, achieving a win-win situation for users and the grid.

[0019] The virtual power plant access module in the present invention enables the system to establish a connection with the control center of the virtual power plant and obtain grid frequency deviation and frequency regulation demand information. In this way, the system participates in grid frequency regulation, provides auxiliary services for the grid, and improves grid operation efficiency and reliability. In addition, the virtual power plant access module also provides the system with a broader application scenario, enabling it to integrate resources such as distributed energy and energy storage equipment, further optimize energy management, and provide strong support for the realization of smart grids and low-carbon economy.

[0020] The present invention realizes the collaborative work of multiple hardware units and multiple modules through the energy management unit. Each module generates and executes scheduling instructions according to different functions and priorities. The addition of the vehicle-grid interaction module and the virtual power plant access module further enhances the flexibility and intelligence level of the system. This multi-dimensional collaborative optimization not only improves the overall performance of the system, but also provides strong technical support for the intelligent development of future energy systems and promotes technological progress in the field of energy management. BRIEF DESCRIPTION OF THE DRAWINGS

[0021] In order to more clearly illustrate the technical solutions in the embodiments of the present invention, the following briefly introduces the drawings required for use in the description of the embodiments. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without creative work.

[0022] Figure 1 It is a schematic diagram of the system structure of the present invention. DETAILED DESCRIPTION

[0023] To make the objectives, technical solutions and advantages of the present invention more clear, the embodiments of the present invention will be described in further detail below with reference to the accompanying drawings.

[0024] Reference Figure 1 , multi-energy collaborative intelligent charging energy management system, including: 1. Photovoltaic power generation unit, used to convert solar energy into electrical energy: The photovoltaic power generation unit includes a plurality of photovoltaic panels, which are connected to the energy management unit through a photovoltaic inverter; The working principle of photovoltaic power generation unit is as follows: When sunlight shines on a photovoltaic panel, the energy of the photons excites the electrons in the semiconductor material, forming a DC voltage at both ends of the panel, generating and outputting DC electricity; The photovoltaic inverter adjusts the operating point of the photovoltaic panel through MPPT technology, converts the DC power output by the photovoltaic panel into AC power and adjusts its voltage, frequency and phase, and transmits the AC power to the charging unit; It should be noted that the output power of photovoltaic panels is affected by factors such as light intensity and temperature. Its output characteristics can be described by the volt-ampere characteristic curve (IV curve) and the power-voltage curve (PV curve). There is a point on the PV curve where the output power reaches its maximum value. This point is called the maximum power point (MPP). The core of MPPT technology is to maximize output power by dynamically adjusting the operating point of the photovoltaic panel so that it is always near the maximum power point. The specific steps are as follows: Real-time monitoring: The output voltage and current of photovoltaic panels are monitored in real time through sensors; Calculate power: Calculate the current output power based on the monitored voltage and current; Dynamic adjustment: The operating point of the photovoltaic panel is dynamically adjusted through an algorithm to keep it close to the maximum power point. For example, the algorithm: Perturbation and observation method: By periodically changing the operating voltage of the photovoltaic panel and comparing the power changes before and after, the voltage is adjusted; Incremental conductance method: Dynamically adjust the operating point of the photovoltaic panel by calculating the incremental conductance to ensure that it is always in the maximum power output state.

[0025] 2. Grid access unit, used to access the external grid: The grid access unit includes a grid access switch and an electric energy metering device. The electric energy metering device includes an electric energy meter, a current transformer, and a voltage transformer, which are used to measure the input and output of grid electric energy: The working principle of the grid access unit is as follows: When the system uses external grid power, the grid access switch is closed and the system is connected to the external grid; When the system uses only energy from the energy storage battery and photovoltaic power generation, the grid access switch is disconnected and the system is disconnected from the external grid; It should be noted that the grid access switch is one of the core components of the grid access unit, used to control the connection and disconnection of external grid power. It is usually a high-voltage or low-voltage switchgear that can withstand the voltage and current of the grid; Common grid access switches include circuit breakers, disconnectors, and contactors. In intelligent charging energy management systems, automatic control is usually adopted, with the energy management unit sending instructions to control the closing and opening of the switches. The electric energy metering device is used to measure the input and output of power in the power grid. It can accurately measure the exchange of electric energy between the power grid and the system, and provide data support for the operation management and cost accounting of the system.

[0026] 3. Energy storage battery unit, used to store and release electrical energy: The energy storage battery unit includes multiple energy storage battery packs, which are connected to the energy management unit through a bidirectional converter; The working principle of the energy storage battery unit is as follows: When the system charges the energy storage battery pack, the energy management unit converts the AC power from the photovoltaic power generation unit or the grid access unit into DC power through the bidirectional converter and transmits it to the energy storage battery pack; When the system uses the power of the energy storage battery pack, the energy management unit converts the DC power of the energy storage battery pack into AC power through the bidirectional converter and transmits it to the charging unit; It should be noted that the energy storage battery pack is the core part of the energy storage battery unit, which is usually composed of multiple battery cells (such as lithium-ion batteries, lead-acid batteries, flow batteries, etc.) connected in series or parallel to meet the voltage and capacity requirements of the system; The bidirectional converter is a key interface device between the energy storage battery pack and the energy management unit. It can realize bidirectional conversion between DC and AC, that is, it can convert the DC power of the energy storage battery pack into AC power (discharge mode) and also convert AC power into DC power (charging mode).

[0027] 4. Charging unit, used to provide charging services for electrical equipment: The charging unit is connected to the power-consuming device through the charging port and is connected to the energy management unit through the charging controller. Its working principle is as follows: The user connects the charging port to the power-consuming device to charge the power-consuming device; The charging controller receives the scheduling instructions from the energy management unit and adjusts the charging power of each charging unit according to the instructions; During the charging process, the charging unit monitors the charging requirements of the power-consuming device and feeds back to the energy management unit. The charging requirements of the power-consuming device include the remaining power of the power-consuming device, the battery capacity, and the charging power. It should be noted that the charging terminal is the core part of the charging unit, used to provide charging services for electrical devices (such as electrical appliances and power tools). The charging terminal can be a DC charging terminal or an AC charging terminal, and the specific type depends on the needs of the charging object. DC charging terminals are generally used for fast charging, while AC charging terminals are suitable for slow charging. The charging unit can include multiple charging terminals to meet the charging needs of multiple electrical devices or other electrical devices. These charging terminals can be distributed in different locations, such as in a parking lot in an industrial park or in an integrated photovoltaic storage and charging power station.

[0028] 5. The energy management unit is used to connect with multiple hardware units and realize the scheduling and management of power within the system through the synergy of multiple modules. Its working principle is as follows: Data interaction and instruction transmission: The energy management unit receives data from each unit or module and sends it to the unit or module that uses the data; The unit or module generates a scheduling instruction based on the received data and sends it to the energy management unit, which distributes the scheduling instruction to the units or modules that received the instruction to achieve collaborative work; Define the priority of each module instruction: Determine the priority of the module based on its function, impact on system stability, and urgency, and assign a priority identifier: Virtual power plant access module: directly participates in grid frequency regulation, has the highest priority, and is assigned a priority identifier of 1; Dynamic energy scheduling module: used for energy allocation, with a middle priority and an allocation priority identifier of 2; Peak-valley electricity price strategy module: used for cost optimization, with a lower priority and assigned a priority identifier of 3; Vehicle-network interaction module: used for user benefit optimization, with the lowest priority and assigned a priority identifier of 4; Priority identifiers are stored in the module's configuration file or embedded directly in the module's code; When multiple modules issue instructions at the same time, the system executes the instructions issued by the modules in the order of priority identifiers.

[0029] It should be noted that defining scheduling priorities can ensure that the system can reasonably allocate limited resources and optimize overall performance in complex energy supply and demand scenarios. By prioritizing the use of clean energy, dynamically adjusting energy distribution, reducing operating costs, meeting user needs, supporting distributed energy scenarios and realizing intelligent scheduling, scheduling priorities help the system operate efficiently and stably in different application scenarios, providing important support for achieving a low-carbon economy and sustainable development.

[0030] 6. Dynamic energy scheduling module, used to schedule electric energy according to energy supply: The dynamic energy scheduling module generates scheduling instructions based on the energy supply status through a scheduling algorithm based on fuzzy logic. The principle is as follows: The dynamic energy scheduling module obtains input variables through the energy management unit and obtains the grid electricity price through the peak-valley electricity price strategy module. The input variables include the power generated by the photovoltaic panels and the charging requirements of the electrical equipment. A fuzzy set is established by combining the input variables with the grid electricity price and inputted into the fuzzy logic controller. The fuzzy logic controller analyzes the fuzzy set through a scheduling algorithm based on fuzzy logic to obtain fuzzy output variables; Defuzzifying the fuzzy output variables by the centroid method to obtain a dispatch instruction, wherein the dispatch instruction includes a power dispatch object, a power consumption object, and a charge and discharge power. The power dispatch object includes a photovoltaic power generation unit, an energy storage battery unit, and an external power grid. The power consumption object includes an energy storage battery unit and power consumption equipment. It should be noted that fuzzy logic is a mathematical method for dealing with uncertainty and ambiguity. It allows the value of variables to vary within a certain range, rather than strict binary (0 or 1) logic. Fuzzy logic describes and handles ambiguity through fuzzy sets and fuzzy rules, and can better simulate the human decision-making process. Define fuzzy sets for input variables, for example: Photovoltaic panel power generation: low (L, power generation is less than 30% of the rated power), medium (M, power generation is between 30% and 70% of the rated power), high (H, power generation is greater than 70% of the rated power); Energy storage battery SOC: low (charge less than 30% of battery capacity), medium (charge between 30% and 70% of battery capacity), high (charge greater than 70% of battery capacity); Grid electricity price: low (L, electricity price during off-peak electricity price period), medium (M, electricity price during normal electricity price period), high (H, electricity price during peak electricity price period); Charging demand of the power device: Low (L, remaining power is greater than 70% of the power device's battery capacity), Medium (M, remaining power is between 30% and 70% of the power device's battery capacity), High (H, remaining power is less than 30% of the power device's battery capacity); Define fuzzy sets for output variables, for example: Energy storage battery charging and discharging power: negative (N, indicating discharge), zero (Z, indicating neither charging nor discharging), positive (P, indicating charging); Charging power of electrical equipment: low (L), medium (M), high (H), defined according to the maximum charging power of the battery of the electrical equipment; Define fuzzy rules, for example: Rule 1: If the PV panel power generation is high (H) and the energy storage battery SOC is low (L), the energy storage battery charging power is positive (P); Rule 2: If the PV panel power generation is low (L) and the energy storage battery SOC is high (H), the energy storage battery charging power is negative (N); Rule 3: If the grid electricity price is high (H) and the energy storage battery SOC is high (H), the energy storage battery charging power is negative (N); Rule 4: If the grid electricity price is low (L) and the energy storage battery SOC is low (L), the energy storage battery charging power is high (H); Rule 5: If the charging demand of the electric device is medium (M) or high (H) and the energy storage battery SOC is high (H), the charging power of the electric device is high (H); Rule 6: If the charging demand of the electric device is low (L) and the SOC of the energy storage battery is low (L), the charging power of the electric device is low (L); Rule 7: If the grid electricity price is high (H) and the charging demand of the electric device is medium (M) or low (L), the charging power of the electric device is low (L); Rule 8: If the grid electricity price is low (L) and the charging demand of the electric device is high (H), the charging power of the electric device is high (H).

[0031] Fuzzy reasoning: According to the input variables and the defined fuzzy rules, the output variables are obtained; Defuzzification: The output variables are converted into specific numerical values ​​through defuzzification methods to generate scheduling instructions, for example: If the photovoltaic panel power generation power is high (H) and the energy storage battery charging power is positive (P), the photovoltaic power generation unit's power is used to charge the electrical equipment and the energy storage battery; If the photovoltaic panel power generation power is low (L) and the energy storage battery charging power is negative (N), the energy storage battery unit will be used to charge the electrical equipment; If the grid electricity price is low (L) and the energy storage battery charging power is positive (P), grid electricity is used to charge the electrical equipment and energy storage battery; If the grid electricity price is high (H) and the energy storage battery charging power is negative (N), the energy storage battery unit's power is used to charge the electrical equipment; The centroid method is a commonly used defuzzification method that converts fuzzy output into specific numerical values ​​by calculating the centroid (i.e., weighted average) of the fuzzy output.

[0032] 7. Peak-valley electricity price strategy module, used to dispatch electricity according to the peak-valley electricity price information of the power grid: The peak-valley electricity price strategy module obtains the peak-valley electricity price information of the power grid through the power grid operator or the system's built-in electricity price table. The peak-valley electricity price information of the power grid includes peak electricity price period, valley electricity price period, and normal electricity price period. The dispatch instructions are generated based on the peak-valley electricity price information of the power grid. The dispatch instructions include: During off-peak electricity price periods, the grid access unit connects to the external grid and uses grid power to provide power to the charging unit and energy storage battery unit. During peak electricity price periods, the grid access unit is disconnected from the external grid, and the energy storage battery unit is used to provide power to the charging unit. During the normal electricity price period, the peak and valley electricity price strategy module does not perform scheduling; It should be noted that peak-valley electricity pricing is a time-of-use electricity pricing mechanism that encourages users to use electricity during periods with lower electricity prices and reduce electricity consumption during periods with higher electricity prices by setting different electricity prices in different time periods. It is specifically divided into the following time periods: Peak electricity price period: Usually during the day when electricity demand is high, the electricity price is higher; Off-peak electricity price period: Usually during the night when electricity demand is low, electricity prices are lower; Normal electricity price period: between peak and off-peak periods, with moderate electricity prices; The scheduling method based on the peak-valley electricity price strategy dynamically adjusts energy distribution, optimizes the system's operating costs, and improves the system's flexibility and grid stability. In distributed energy scenarios such as industrial parks and integrated photovoltaic storage and charging power stations, this method can significantly reduce operating costs, improve energy utilization efficiency, support the collaborative operation of multiple energy sources, and provide important support for achieving a low-carbon economy and sustainable development.

[0033] 8. Vehicle-grid interaction module, used to dispatch power according to the charging needs of power-consuming equipment and grid load: The vehicle-grid interaction module is connected to the external billing system and uses a dispatching algorithm based on vehicle-grid interaction (V2G). It generates dispatching instructions based on grid load and peak and valley electricity price information. The dispatching instructions include: The peak and valley electricity price information of the power grid is obtained from the peak and valley electricity price strategy module. When the system is connected to the power grid, the vehicle-grid interaction module obtains the power grid load from the power grid and determines the power grid load level based on the load percentage. When the grid load is low or the electricity price is low, the vehicle-grid interaction module uses grid power to charge electrical equipment and energy storage battery units; During periods of high grid load or peak electricity prices, the vehicle-grid interaction module uses the energy from the energy storage battery unit to charge the power-consuming devices and allows the power-consuming devices to feed back the energy to the grid. The external billing system obtains the energy feedback amount and calculates the user's profit based on the received energy feedback and grid electricity price information. It should be noted that Vehicle-to-Grid (V2G) is a technology that allows electrical devices to not only obtain electricity from the grid for charging, but also feed electricity back to the grid. This two-way energy flow can optimize grid operation, improve grid flexibility and stability, and provide economic incentives for users of electrical devices.

[0034] 9. Virtual power plant access module, used to support system access to virtual power plants and participate in grid frequency regulation: The virtual power plant access module establishes a connection with the virtual power plant control center through the standard communication protocol IEC 61850 to obtain grid information, including grid frequency deviation and frequency regulation requirements. The virtual power plant access module generates dispatch instructions based on the grid information. The dispatch instructions include: When the grid frequency increases, the charging power of the energy storage battery is reduced or the discharging power is increased, and the charging power of the charging unit is reduced; When the grid frequency decreases, the charging power of the energy storage battery is increased or the discharging power is reduced, and the charging power of the charging unit is increased; It should be noted that the virtual power plant access module is an important component of the energy management unit. Its main function is to enable the multi-energy collaborative intelligent charging energy management system to access the virtual power plant (VPP) and participate in grid frequency regulation according to the dispatch instructions of the virtual power plant. Specific functions include: Establish a connection with the control center of the virtual power plant through the communication interface to receive dispatch instructions; Adjust the charge and discharge power of the energy storage battery unit or control the charging power of the charging unit according to the grid frequency deviation; By participating in grid frequency regulation, the flexibility and stability of the system can be improved.

[0035] Furthermore, it should be noted that the present invention may be provided as a method, apparatus, or computer program product. Thus, embodiments of the present invention may take the form of entirely hardware embodiments, entirely software embodiments, or embodiments combining software and hardware aspects. Furthermore, embodiments of the present invention may take the form of a computer program product embodied on one or more computer-usable storage media containing computer-usable program code.

[0036] The embodiments of the present invention are described with reference to the flowcharts and / or block diagrams of the methods, terminal devices (systems), and computer program products according to the embodiments of the present invention. It should be understood that each process and / or block in the flowchart and / or block diagram, as well as the combination of the processes and / or blocks in the flowchart and / or block diagram, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, an embedded processor, or other programmable data processing terminal device to generate a machine, so that the instructions executed by the processor of the computer or other programmable data processing terminal device generate instructions for implementing the process in the flowchart and / or block diagram. Figure 1 a process or multiple processes and / or boxes Figure 1 A device that provides the functions specified in a block or multiple blocks.

[0037] These computer program instructions may also be stored in a computer readable memory that can direct a computer or other programmable data processing terminal device to operate in a specific manner, so that the instructions stored in the computer readable memory produce a manufactured product including an instruction device, which implements the process Figure 1 a process or multiple processes and / or boxes Figure 1 These computer program instructions can also be loaded onto a computer or other programmable data processing terminal device, so that a series of operation steps are executed on the computer or other programmable terminal device to produce a computer-implemented process, thereby providing instructions for implementing the process in the process. Figure 1 a process or multiple processes and / or boxes Figure 1 A step that specifies a function in one or more boxes.

[0038] It should also be noted that, in this document, relational terms such as first and second, etc., are used only to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply any actual relationship or order between these entities or operations. The terms "comprises," "includes," or any other variants thereof are intended to cover non-exclusive inclusion, so that a process, method, article, or terminal device that includes a series of elements includes not only those elements, but also other elements not explicitly listed, or elements inherent to such process, method, article, or terminal device. In the absence of further restrictions, an element defined by the phrase "comprises a ..." does not exclude the presence of additional identical elements in the process, method, article, or terminal device that includes the element.

[0039] Finally, it should be noted that the above is a preferred embodiment of the present invention. It should be noted that although the preferred embodiment of the present invention has been described, it is clear that those skilled in the art, once they understand the basic inventive concept of the present invention, can make various improvements and modifications without departing from the principles of the present invention. Such improvements and modifications should also be considered as within the scope of protection of the present invention. Therefore, the appended claims are intended to be interpreted as including the preferred embodiment and all changes and modifications that fall within the scope of the embodiments of the present invention.

Claims

1. Multi-energy collaborative intelligent charging energy management system, characterized by: include: Photovoltaic power generation units, which convert solar energy into electricity; A grid access unit, used for accessing an external grid; Energy storage battery cells for storing and releasing electrical energy; Charging unit, used to provide charging services for electrical equipment; The energy management unit is used to connect with multiple hardware units and realize the scheduling and management of power within the system through the synergy of multiple modules; Dynamic energy scheduling module, used to schedule electric energy according to energy supply; Peak-valley electricity price strategy module, used to dispatch electricity according to the peak-valley electricity price information of the power grid; The vehicle-grid interaction module is used to dispatch power according to the charging needs of power-consuming devices and the load of the power grid; The virtual power plant access module is used to support the system access to the virtual power plant and participate in grid frequency regulation.

2. The multi-energy collaborative intelligent charging energy management system according to claim 1 is characterized in that: The photovoltaic power generation unit includes a plurality of photovoltaic panels, and the photovoltaic panels are connected to the energy management unit through a photovoltaic inverter; The working principle of the photovoltaic power generation unit is as follows: When sunlight shines on a photovoltaic panel, the energy of the photons excites the electrons in the semiconductor material, forming a DC voltage at both ends of the panel, generating and outputting DC electricity; The photovoltaic inverter adjusts the operating point of the photovoltaic panel through the MPPT technology, converts the direct current output by the photovoltaic panel into alternating current and adjusts its voltage, frequency and phase, and transmits the alternating current to the charging unit.

3. The multi-energy collaborative intelligent charging energy management system according to claim 1 is characterized in that: The grid access unit includes a grid access switch and an electric energy metering device. The electric energy metering device includes an electric energy meter, a current transformer, and a voltage transformer, which are used to measure the input and output of grid electric energy. The working principle of the grid access unit is as follows: When the system uses external grid power, the grid access switch is closed and the system is connected to the external grid; When the system only uses electricity from energy storage batteries and photovoltaic power generation, the grid access switch is disconnected and the system is disconnected from the external grid.

4. The multi-energy collaborative intelligent charging energy management system according to claim 1 is characterized in that: The energy storage battery unit includes a plurality of energy storage battery packs, and the energy storage battery packs are connected to the energy management unit through a bidirectional converter; The working principle of the energy storage battery unit is as follows: When the system charges the energy storage battery pack, the energy management unit converts the AC power from the photovoltaic power generation unit or the grid access unit into DC power through the bidirectional converter and transmits it to the energy storage battery pack; When the system uses the power of the energy storage battery pack, the energy management unit converts the direct current of the energy storage battery pack into alternating current through a bidirectional converter and transmits it to the charging unit.

5. The multi-energy collaborative intelligent charging energy management system according to claim 1 is characterized in that: The charging unit is connected to the power-consuming device through the charging port and is connected to the energy management unit through the charging controller. Its working principle is as follows: The user connects the charging port to the power-consuming device to charge the power-consuming device; The charging controller receives the scheduling instructions from the energy management unit and adjusts the charging power of each charging unit according to the instructions; During the charging process, the charging unit monitors the charging requirements of the power-consuming device and feeds back to the energy management unit. The charging requirements of the power-consuming device include the remaining power of the power-consuming device, the battery capacity, and the charging power.

6. The multi-energy collaborative intelligent charging energy management system according to claim 1 is characterized in that: The working principle of the energy management unit is as follows: Data interaction and instruction transmission: The energy management unit receives data from each unit or module and sends it to the unit or module that uses the data; The unit or module generates a scheduling instruction based on the received data and sends it to the energy management unit, which distributes the scheduling instruction to the units or modules that received the instruction to achieve collaborative work; Define the priority of each module instruction: Determine the priority of the module based on its function, impact on system stability, and urgency, and assign a priority identifier: Virtual power plant access module: directly participates in grid frequency regulation, has the highest priority, and is assigned a priority identifier of 1; Dynamic energy scheduling module: used for energy allocation, with a middle priority and an allocation priority identifier of 2; Peak-valley electricity price strategy module: used for cost optimization, with a lower priority and assigned a priority identifier of 3; Vehicle-network interaction module: used for user benefit optimization, with the lowest priority and assigned a priority identifier of 4; The priority identifier is stored in the module's configuration file or directly embedded in the module code; When multiple modules issue instructions at the same time, the system executes the instructions issued by the modules in the order of priority identifiers.

7. The multi-energy collaborative intelligent charging energy management system according to claim 1 is characterized in that: The dynamic energy scheduling module generates scheduling instructions based on the energy supply status through a scheduling algorithm based on fuzzy logic. The principle is as follows: The dynamic energy scheduling module obtains input variables through the energy management unit and obtains the grid electricity price through the peak-valley electricity price strategy module. The input variables include the power generated by the photovoltaic panels and the charging requirements of the electrical equipment. A fuzzy set is established by combining the input variables with the grid electricity price and inputted into the fuzzy logic controller. The fuzzy logic controller analyzes the fuzzy set through a scheduling algorithm based on fuzzy logic to obtain fuzzy output variables; The fuzzy output variables are defuzzified by the center of gravity method to obtain a scheduling instruction, which includes a power regulation object, a power consumption object, and a charge and discharge power. The power regulation object includes a photovoltaic power generation unit, an energy storage battery unit, and an external power grid. The power consumption object includes an energy storage battery unit and power-consuming equipment.

8. The multi-energy collaborative intelligent charging energy management system according to claim 1 is characterized in that: The peak-valley electricity price strategy module obtains the peak-valley electricity price information of the power grid from the power grid operator. The peak-valley electricity price information of the power grid includes the peak electricity price period, the valley electricity price period, and the normal electricity price period. The scheduling instruction is generated according to the peak-valley electricity price information of the power grid. The scheduling instruction includes: During off-peak electricity price periods, the grid access unit connects to the external grid and uses grid power to provide power to the charging unit and energy storage battery unit. During peak electricity price periods, the grid access unit is disconnected from the external grid, and the energy storage battery unit is used to provide power to the charging unit. During the normal electricity price period, the peak-valley electricity price strategy module does not perform scheduling.

9. The multi-energy collaborative intelligent charging energy management system according to claim 1 is characterized in that: The vehicle-grid interaction module is connected to the external billing system and adopts a scheduling algorithm based on vehicle-grid interaction (V2G) to generate scheduling instructions based on grid load and grid peak and valley electricity price information. The scheduling instructions include: The peak and valley electricity price information of the power grid is obtained from the peak and valley electricity price strategy module. When the system is connected to the power grid, the vehicle-grid interaction module obtains the power grid load from the power grid and determines the power grid load level based on the load percentage. When the grid load is low or the electricity price is low, the vehicle-grid interaction module uses grid power to charge electrical equipment and energy storage battery units; When the grid load is high or during peak electricity price periods, the vehicle-grid interaction module calls on the electricity of the energy storage battery unit to charge the electrical equipment, and allows the electrical equipment to feed electricity back to the grid. The electricity feedback amount is obtained through the external billing system, and the user's profit is calculated based on the received electricity feedback amount and the grid electricity price information.

10. The multi-energy collaborative intelligent charging energy management system according to claim 1, characterized in that: The virtual power plant access module establishes a connection with the control center of the virtual power plant through the standard communication protocol IEC 61850 to obtain grid information, including grid frequency deviation and frequency regulation requirements. The virtual power plant access module generates a dispatch instruction based on the grid information, and the dispatch instruction includes: When the grid frequency increases, the charging power of the energy storage battery is reduced or the discharging power is increased, and the charging power of the charging unit is reduced; When the grid frequency decreases, the charging power of the energy storage battery is increased or the discharging power is reduced, and the charging power of the charging unit is increased.

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