Power grid system and operation control method based on light storage building group and charging station

Abstract

The present application relates to the technical field of direct current micro-grid, and particularly relates to a power grid system based on a light storage building group and a charging station and an operation control method, the system comprises a power grid system based on a light storage building group and a charging station, the system comprises a cluster direct current bus, at least one sub-light storage system, a centralized energy storage device, a V2G charging station, a data acquisition device, a data processing device, a cluster control manager and a plurality of energy managers; the present application realizes deep interconnection of multiple types of energy storage and charging and discharging resources through a unified direct current bus architecture, solves the problems of insufficient coordination and large loss of the existing system; constructs a multi-mode adaptive operation control architecture, realizes dynamic switching of normal economic optimization, priority of consumption, charging guarantee, power grid interaction and emergency island, solves the defect of single existing operation mode; improves the engineering applicability and comprehensive operation benefit of the system, realizes the unification of maximum consumption of renewable energy, reliable guarantee of charging demand and friendly interaction of the power grid.

Description

Technical Field

[0001] This invention belongs to the field of DC microgrid technology, specifically relating to a power grid system and operation control method based on photovoltaic-storage building complexes and charging stations. Background Technology

[0002] With the rapid development of renewable energy and electric vehicles, the integration of photovoltaic and energy storage building complexes with electric vehicle charging stations has become a trend. However, traditional microgrid systems have shortcomings in coordinating building energy storage, centralized energy storage, and electric vehicle charging and discharging resources, affecting the overall economic efficiency and power supply reliability.

[0003] While existing technologies have addressed the issue of photovoltaic-storage-charging microgrid systems, significant limitations remain. Firstly, most solutions are limited to optimizing a single microgrid or charging facility, lacking a holistic architecture that enables deep interconnection between photovoltaic-storage building clusters and large-scale V2G charging stations via a unified DC bus. This makes it difficult to support cross-system energy sharing and backup support. Secondly, traditional AC bus-based designs involve numerous conversion steps and significant losses, failing to fully leverage the advantages of DC systems in improving transmission efficiency and flexibly allocating power.

[0004] Furthermore, existing methods typically treat various energy storage resources independently, lacking multi-level coordination strategies for centralized energy storage, distributed building energy storage, and V2G vehicle-mounted energy storage, making it difficult to comprehensively optimize system economy and equipment lifespan. Simultaneously, operation control strategies are often designed for specific scenarios, lacking a comprehensive framework capable of intelligent judgment and smooth mode switching based on multiple conditions such as grid status and source-load balance, thus limiting their adaptability to complex operating conditions. These limitations collectively constrain the system's overall performance in improving absorption rate, ensuring charging reliability, and enhancing resilience, urgently requiring a new system and operation control method to address these issues. Summary of the Invention

[0005] To address the problems existing in the prior art, this invention provides a power grid system based on photovoltaic-storage building complexes and charging stations. It achieves deep interconnection between photovoltaic-storage subsystems, centralized energy storage, and V2G charging stations through a unified DC bus, and constructs a multi-mode adaptive operation control architecture to achieve dynamic and smooth switching between economic optimization, consumption priority, charging guarantee, grid interaction, and emergency islanding modes, thereby improving system energy utilization, power supply reliability, and overall operational efficiency.

[0006] The technical solution of the present invention is as follows: The power grid system based on photovoltaic-storage building complexes and charging stations includes a cluster DC bus, at least one sub-photovoltaic-storage system, centralized energy storage equipment, V2G charging stations, data acquisition equipment, data processing equipment, a cluster control manager, and multiple energy managers.

[0007] Each sub-photovoltaic and energy storage system is equipped with distributed photovoltaic units and distributed energy storage units, which are connected to the cluster DC bus through a first DC / DC converter and a first circuit breaker; the centralized energy storage equipment is connected to the cluster DC bus through a second DC / DC converter and a second circuit breaker; each charging pile of the V2G charging station is connected to the cluster DC bus through an independent bidirectional power conversion unit and a third circuit breaker, and the V2G charging station is equipped with a charging and discharging control module and a vehicle status detection module.

[0008] Each sub-photovoltaic-storage system, centralized energy storage device, and V2G charging station corresponds to an energy manager for flexible control of the devices under its jurisdiction; data acquisition equipment collects data in real time on the power generation, load power, energy storage status, grid status, and vehicle charging demand status within the system; data processing equipment processes and predicts the collected data; the cluster control manager generates system-level coordinated control commands based on the processed data and preset strategies, and executes them through each energy manager.

[0009] Operation control method based on the above system The method is executed by the cluster control manager and includes three core steps: data acquisition and analysis, operating mode determination, and control command generation and execution. (1) Data acquisition and analysis: Real-time acquisition and analysis of the power generation, load demand, state of charge of each energy storage unit, grid connection status, grid dispatch instructions, and real-time charging demand and vehicle battery status of the DC microgrid system through data acquisition and data processing equipment. (2) Operation mode determination: Based on the preset multi-mode judgment logic, the grid connection status, grid dispatching instructions, power generation and load power relationship, and charging demand are detected in sequence to determine whether the system enters emergency island mode, grid interaction mode, consumption priority mode, charging guarantee mode or normal mode. (3) Control command generation and execution: Based on the determined operating mode, the corresponding core control strategy is invoked to generate coordinated control commands and send them to each energy manager to dynamically regulate the charging and discharging power of distributed energy storage, centralized energy storage and V2G vehicles, so as to achieve optimized system operation.

[0010] The multi-mode judgment logic is as follows: If the main power grid fails, it will enter emergency islanding mode; If the power grid connection is normal and a power grid dispatch instruction is received, the system will enter the power grid interaction mode. If the grid connection is normal, there are no grid commands, and the power generation capacity is greater than the load demand capacity, then the power consumption priority mode is entered. If the power grid connection is normal, there are no power grid commands, the power generation capacity is less than or equal to the load demand power, and the charging demand exceeds the system's capacity, then the system will enter the charging guarantee mode. In other cases, normal mode is entered.

[0011] The core control strategies for each operating mode are as follows: Normal mode: With the goal of optimal economic efficiency, it integrates time-of-use pricing, power generation and load forecasting information, and uses optimization algorithms to allocate charging and discharging plans to minimize operating costs and power fluctuations; Prioritized consumption mode: Implement a tiered consumption strategy, consuming surplus power sequentially through V2G vehicle charging, distributed energy storage charging, and centralized energy storage charging, ensuring 100% local consumption of renewable energy. Charging guarantee mode: Implement a tiered guarantee strategy, classifying charging needs according to urgency, reservation information, and battery status, prioritizing high-level charging needs, and calling on various energy storage discharge support. Grid interaction mode: Responding to grid peak shaving, frequency regulation and other commands, coordinating various energy storage and V2G resources to adjust tie-line power and provide ancillary services; Emergency islanding mode: disconnect from the faulty main grid, cut off non-critical loads, and use internal energy storage and photovoltaics to maintain power supply to critical loads, achieving black start and autonomous operation.

[0012] Compared with the prior art, the present invention has the following beneficial effects: Achieving multi-resource collaborative and optimized operation: Through the cluster DC bus architecture and multi-mode control mechanism, the problem of balancing local consumption of renewable energy and charging service guarantee has been solved, realizing the synergistic mutual support of photovoltaic and energy storage building clusters, centralized energy storage and V2G charging stations, significantly improving the overall energy efficiency and operational economy of the system; Ensuring the dual goals of energy consumption and charging demand: Through a gradient strategy of consumption priority mode and a tiered strategy of charging guarantee mode, we ensure full consumption of renewable energy when there is a power generation surplus, and prioritize high-priority demand during peak charging times, while taking into account both energy utilization efficiency and user satisfaction. Enhancing grid interaction capabilities: The grid interaction mode enables the system to respond to grid peak shaving, frequency regulation and other commands in an aggregated manner, which enhances the microgrid's active support capability for the main grid, while improving the system's operating benefits by providing value-added services; Enhanced system resilience: Five operating modes and their seamless switching mechanism provide a complete contingency plan for the system to cope with grid failures, power fluctuations and sudden changes in demand. In particular, the emergency islanding mode ensures continuous power supply to critical loads, improving power supply reliability and system resilience. It has good versatility and scalability: the modular architecture can be flexibly adapted to different scales of photovoltaic and energy storage building complexes and V2G charging station combination scenarios, and the strategy framework can be easily adjusted and optimized according to policies, electricity prices and technological developments, with broad engineering applicability and promotion prospects. Attached Figure Description

[0013] Figure 1 This is an architecture diagram of a DC microgrid system based on a photovoltaic-storage-DC-flexible building complex and V2G charging / battery swapping stations; Figure 2 This is a flowchart illustrating the connection control and multi-mode collaborative operation of various units within the cluster system. Detailed Implementation

[0014] The present invention will now be described in detail with reference to the accompanying drawings and specific embodiments.

[0015] Taking a science and technology park located in a hot-summer, cold-winter region as an example, this paper constructs a real-world example of a "photovoltaic-storage building complex and charging station" power grid system. The system serves five R&D office buildings (sub-photovoltaic-storage systems), one centralized energy storage station, and one public charging station equipped with V2G functionality. Key system parameters are designed as follows: The cluster DC bus is a 750V DC bus. Each sub-photovoltaic-storage system is configured with a 250kWp distributed photovoltaic unit and a 500kWh / 250kW distributed energy storage unit (lithium iron phosphate battery), connected to the cluster DC bus via a 250kW bidirectional DC / DC converter. The centralized energy storage device is configured with a 1MWh / 500kW flow battery, connected to the cluster DC bus via a 500kW bidirectional DC / DC converter. The V2G charging station is equipped with 10 DC charging piles, each with a rated power of 120kW, connected to the cluster DC bus via an independent bidirectional AC / DC power conversion unit. The total power capacity of the charging station is 1.2MW. Data acquisition, processing, and control equipment is built upon industrial servers and IoT gateways.

[0016] See Figure 1 The power grid system based on photovoltaic and energy storage building clusters and charging stations includes a cluster DC bus, at least one sub-photovoltaic and energy storage system, centralized energy storage equipment, V2G charging station, data acquisition equipment, data processing equipment, cluster control manager and multiple energy managers. The data acquisition equipment is used to collect real-time operational data from each sub-system of photovoltaic-storage-direct-drive-flexible energy storage, the status data of centralized energy storage devices, and the operational data of V2G charging / battery swapping stations. The collected data includes, but is not limited to, building load data for each subsystem, distributed photovoltaic power generation data, the charging / discharging status and remaining capacity data of distributed energy storage, the charging / discharging status and remaining capacity data of centralized energy storage devices, and the total power demand, charging gun status, vehicle battery status, and charging / discharging request data of V2G charging / battery swapping stations. This data is collected by the data acquisition equipment and uploaded to the data processing equipment, providing a basis for the system's overall energy management and operational mode decisions.

[0017] In this system, each sub-PV-storage-DC-flexible system is interconnected with a common cluster DC bus via a DC / DC converter and is equipped with its own circuit breaker. The centralized energy storage device is connected to the cluster DC bus via a DC / DC converter and is also equipped with a circuit breaker. Each charging gun in the V2G charging / battery swapping station is connected to the cluster DC bus via an independent bidirectional power conversion unit and is also equipped with a circuit breaker. The cluster control manager connects and exchanges information with the energy managers of each sub-PV-storage-DC-flexible system, the management system of the centralized energy storage device, and the charging and discharging control module of the V2G charging / battery swapping station through a communication network.

[0018] The control unit within the data acquisition equipment includes a processing unit, such as a microprocessor or programmable logic controller, that connects to various sensors, metering instruments, and status monitoring modules. This processing unit is responsible for receiving and initially processing data from each acquisition point and transmitting it to the data processing equipment and the cluster control manager.

[0019] The cluster control manager receives optimization instructions from the data processing equipment and real-time data from the data acquisition equipment. Based on the preset multi-mode operation control strategy, it generates and sends coordinated control instructions to the energy managers of each subsystem, centralized energy storage equipment, and charging and discharging control modules of V2G charging stations / battery swapping stations to achieve flexible power regulation and optimized allocation, and ensure energy consumption and charging needs.

[0020] 2. Data processing equipment and its control device The data processing equipment receives and integrates real-time operational data from all sub-photovoltaic-storage-DC-flexible systems, centralized energy storage devices, and V2G charging / battery swapping stations from the data acquisition equipment. This data forms the basis for system-level energy management, developing multi-mode operation strategies, and achieving coordinated control between units. The data processing equipment includes, but is not limited to, servers, network devices, and databases.

[0021] Through its internal computing resources and algorithms, the data processing equipment performs comprehensive analysis, pattern judgment, and optimization calculations on the collected data. Based on judgments of grid status, grid commands, comparison results of generation and load power, and charging demand status, the data processing equipment determines the specific operating mode the system should enter and generates corresponding optimized control commands. These commands are output to the cluster control manager, including the expected power exchange values ​​for each sub-photovoltaic-storage-DC-flexible system, the charging and discharging plan for centralized energy storage devices, the charging and discharging power commands for V2G charging stations / battery swapping stations, and system operating mode identifiers. This provides the cluster control manager with a decision-making basis for executing multi-mode collaborative operation control.

[0022] 3. Connection control of units within the cluster system and multi-mode collaborative operation control methods The cluster DC bus serves as the system's common power exchange hub. Each unit includes a photovoltaic-storage-DC-flexible system, centralized energy storage devices, and V2G charging / battery swapping stations. Each unit is connected to the cluster DC bus via circuit breakers with fast shutdown capabilities and finely adjustable power converters. This connection control mechanism is the foundation for the system's flexible operation and topology reconfiguration. When the cluster control manager receives instructions from the data processing equipment, or detects an internal fault, performance limit exceedance, or planned isolation requirement in a unit through data acquisition equipment, it generates and executes specific connection control instructions for that unit. For planned operations, such as maintenance, the control instructions will systematically adjust the output of the unit's power converter to zero before disconnecting its circuit breaker, achieving shock-free grid disconnection. For emergencies such as faults, the control instructions will directly trip the circuit breaker to achieve millisecond-level isolation and quickly compensate for the power imbalance caused by the unit's disconnection by adjusting the power output of other units, ensuring stable voltage on the cluster DC bus. The voltage stability condition can be expressed as: ; in, This represents a shortfall in total power. This is the power compensation for the i-th unit. This process ensures the continued normal operation of the remaining units.

[0023] The core of this invention lies in a multi-mode collaborative operation control method based on state judgment, whereby data processing equipment and cluster control manager work together. This method continuously analyzes real-time and predicted data uploaded by data acquisition equipment to dynamically determine the core state of the system and switches to the corresponding optimal operating mode according to preset priority logic. The state judgment and mode decision logic is as follows.

[0024] First, the electrical status of the grid connection point is continuously monitored. If a main grid voltage loss or frequency anomaly is detected, the system immediately enters emergency islanding mode, which has the highest priority. If the grid connection is normal, it checks whether a clear regulation instruction has been received from the superior grid dispatching agency, such as peak shaving or frequency regulation signals. If so, it enters grid interaction mode. If no grid instruction is received, the system further compares the real-time total renewable energy generation power within the system. With total load demand Total load demand includes building load and charging load. If power generation consistently exceeds load demand and the difference exceeds a set threshold... In this embodiment, the following is set The power is 50kW, which satisfies the following: ; Then, it enters the consumption priority mode. If the power generation is less than or close to the load demand, the urgency of the real-time charging demand of V2G charging stations / battery swapping stations is assessed. If there are high-priority charging requests or the overall charging demand satisfaction rate is lower than the preset target, it will enter the consumption priority mode. In this embodiment, the following is set It is 85%, that is: ; Then it enters the charging protection mode, where Actual charging power This is to meet charging requirements. If none of the above specific conditions are met, the system will run in the default normal mode.

[0025] The specific collaborative control strategies for each operating mode are as follows.

[0026] (1) Normal Mode: The core objective is to optimize the daily economic efficiency of the system. The data processing equipment performs rolling optimization calculations based on electricity price curves, photovoltaic power generation forecasts, and load forecasts, with the objective function of minimizing total electricity costs or maximizing grid revenue. The objective function can be expressed as: ; in, For electricity purchase price, For the power purchase capacity, For grid connection electricity price, For internet access power, The time interval is defined as follows. Optimization calculations generate the power exchange plan between each sub-PV-Storage-DC-Flexible system and the grid, the charging and discharging plan for centralized energy storage, and the baseline charging and discharging power reference for V2G stations over a future period. The cluster control manager executes this plan and introduces a power smoothing algorithm to mitigate renewable energy fluctuations using energy storage and flexible loads. The smoothing objective can be expressed as: ; in This refers to the exchange power between the cluster and the grid. Based on the parameters of the above embodiments, a typical normal mode execution case is as follows: Assume rolling optimization is performed on a certain afternoon. Based on the prediction, the data processing equipment generates instructions: During off-peak hours (00:00-08:00), the centralized energy storage device is instructed to charge at its maximum power of 500kW for 4 hours, replenishing approximately 2000kWh of electricity; During the midday peak photovoltaic power generation period (11:00-14:00), each sub-photovoltaic-storage system is instructed to prioritize local consumption, with surplus photovoltaic power supplied to the centralized energy storage and V2G charging station through the cluster bus, and the excess power fed into the grid at a set power; During the evening peak electricity price period (18:00-21:00), the centralized energy storage is instructed to discharge at a power of 400kW, while the power limit of the V2G charging station is adjusted to 60% of the total capacity (i.e., 720kW) to reduce the power purchased at high prices and to ensure the total exchange power of the cluster. Its volatility is less than 100 kW / minute.

[0027] (2) Priority Consumption Mode: The core objective is to ensure 100% local consumption of renewable energy. A tiered consumption strategy is implemented. The first tier involves adjusting the flexible building load within each sub-system (PV-Storage-DC-Flexible) to an acceptable high-energy-consumption state. For example, lowering the building's air conditioning setpoint by 1°C within a comfortable range is expected to increase the total load by approximately 200kW. The second tier instructs the distributed energy storage units and centralized energy storage devices of each subsystem to charge, prioritizing the use of distributed energy storage, with the charging power allocation satisfying: ; in For real-time surplus power, This represents the maximum total charging power of the energy storage system. Continuing the previous example, if the total photovoltaic output at midday... The total building load is 1.8MW. The charging demand is 0.7MW. If it is 0.25MW, then the surplus power is... =1.8 - 0.7 - 0.25 = 0.85MW. Total maximum charging power of energy storage within the system. Each sub-energy storage unit is 250kW * 5 + centralized energy storage is 500kW = 1.75MW. Therefore, the total energy storage charging power is... =min(850kW, 1750kW) = 850kW. The cluster control manager can instruct: the five subsystems of distributed energy storage to allocate charging power according to the SOC ratio. Assuming the total demand is 850kW, each unit will handle approximately 170kW on average. The centralized energy storage will remain inactive to reserve adjustment capacity. The third tier involves adjusting the V2G charging / battery swapping stations to charge connected electric vehicles at maximum or optimal power after the energy storage capacity is exhausted, storing the surplus energy in the vehicle's battery. For example, if the energy storage is full or has reached its charging limit, but there is still a 200kW surplus, the V2G charging stations can be instructed to increase the charging power of all idle or acceptable charging vehicles, for a total increase of 200kW. The fourth tier, if there is still a surplus, can instruct some non-critical building loads to temporarily increase consumption. Through this tiered strategy, local absorption capacity is maximized.

[0028] (3) Charging Guarantee Mode: The core objective is to ensure the reliability and satisfaction of user charging services. A tiered guarantee strategy is implemented. First, the data processing equipment dynamically calculates the guarantee level and required guarantee power for each charging gun based on the vehicle's remaining battery power, reservation time, and user-set priority information. Guarantee Level It can be quantified as: ; in, This refers to the vehicle's battery state of charge. This is the reservation deadline. Set priority coefficients for users. These are the weighting coefficients. In this embodiment, let α=0.5, β=0.3, and γ=0.2. A vehicle with SOC=30%, scheduled to leave in 30 minutes, and set as high priority by the user, its... The calculated value will be significantly higher than that of a vehicle with a SOC of 70%, scheduled to leave in 2 hours, and of standard priority. Subsequently, the cluster control manager prioritizes scheduling available power resources to meet the highest level of charging demand. The scheduling order is as follows: First, real-time renewable energy generation power is used. Second, centralized energy storage discharge is invoked. Third, each sub-PV-storage-DC-flexible system is instructed to reduce its power draw from the cluster bus, and its distributed energy storage is invoked for discharge if necessary. Finally, while ensuring charging, the power of non-critical building loads can be appropriately reduced. Simultaneously, V2G vehicles can be requested to discharge in reverse to support high-priority charging demands, while ensuring their core off-site power. In a specific implementation example: The current PV output is 300kW, and all of it is prioritized for charging. If this still cannot meet high-priority demand, the centralized energy storage is instructed to discharge at a maximum power of 500kW to supplement it. If this is still insufficient, each building's energy manager can be instructed to activate its local energy storage discharge, with each building providing 50kW, totaling 250kW, to support the charging bus. As a last resort, a vehicle with a SOC of 80% and no urgent need to leave can be requested to discharge 50kW to the cluster bus to provide charging power for another emergency vehicle with a SOC of only 20%.

[0029] (4) Grid Interaction Mode: The core objective is to respond to grid demands safely and accurately. Data processing equipment parses grid commands and transforms them into overall power regulation targets for the cluster. The cluster control manager breaks down this overall goal into individual controllable units. First, it adjusts the charging and discharging power of the centralized energy storage devices. Secondly, coordinate the adjustment of the switching power between each sub-photovoltaic-storage-direct current-flexible system and the cluster bus, changing the internal energy storage charging and discharging state or flexible load power, with a total adjustment amount of [missing information]. Finally, V2G resources are invoked and aggregated into a controllable distributed energy storage cluster to participate in grid peak shaving or frequency response and contribute power. Decomposition must satisfy: ; For example, receiving a "peak shaving" instruction from the power grid, requiring a reduction of 300kW (i.e., ...) in power consumption during the evening peak period. =+300kW, the positive sign indicates a reduction in power draw from the grid). The cluster control manager can decompose the following command: Centralized energy storage discharges at a power of 200kW ( =+200kW), coordinating with each of the 5 buildings to reduce power draw from the cluster bus by 15kW (mainly achieved by adjusting indoor temperature settings). =+75kW), and adjust the V2G charging station to reduce the total charging power by 25kW ( =+25kW). A total of 300kW of peak shaving effect is achieved. In this mode, the various units within the system work together to present a controllable and reliable aggregated entity to the outside world.

[0030] (5) Emergency Islanding Mode: The core objective is to maintain continuous power supply to critical loads within the system. In the event of a main grid failure, the cluster control manager immediately trips the circuit breaker at the grid connection point and quickly adjusts the control strategy according to the preset islanding operation plan. First, non-critical building loads and general charging loads are cut off. In this embodiment, all V2G charging pile power supply and non-critical air conditioning and lighting loads within the buildings are immediately cut off, with approximately 500kW of critical loads expected to be retained. Second, the cluster DC bus voltage is stabilized. To directly control the target, the centralized energy storage device switches to voltage source mode, serving as a main grid support unit. Its control law can be expressed as: ; in, The voltage is 750V. The controller of the centralized energy storage (500kW) will adjust the output in real time according to the bus voltage deviation to maintain the voltage within the range of (750±10)V. The energy managers of each sub-PV-storage-DC-flexible system switch to autonomous operation mode, prioritizing the use of local PV and energy storage to maintain the power supply of their critical loads, and realizing emergency power mutual assistance between them through the cluster DC bus. V2G charging stations / battery swapping stations stop charging and can connect qualified vehicle batteries as emergency power sources according to instructions to provide additional support for system recovery or critical loads, achieving black start capability. For example, dispatching a vehicle with SOC>90% can supply power to the cluster bus at 30kW through its bidirectional charging pile to provide startup power for the system's critical control equipment.

[0031] Based on the mode commands and corresponding optimization target commands issued in real time by the data processing equipment, and combined with the instantaneous status of each unit, such as energy storage SOC, converter margin, and vehicle connection status, the cluster control manager dynamically calculates and allocates specific power command values ​​for each unit, enabling smooth and rapid switching between five operating modes. This allows for continuous dynamic optimization of the system's operating status in complex and ever-changing internal and external environments, collaboratively ensuring the maximum absorption of renewable energy and the high reliability of meeting users' charging needs.

[0032] The above description is merely an embodiment of the present invention and does not limit the patent scope of the present invention. Any equivalent structural or procedural transformations made based on the content of the present invention's specification and drawings, or direct or indirect applications in other related technical fields, are similarly included within the patent protection scope of the present invention.

Claims

1. A power grid system based on photovoltaic-storage building complexes and charging stations, characterized in that, The system includes a cluster DC bus, at least one sub-photovoltaic-storage system, a centralized energy storage device, a V2G charging station, data acquisition equipment, data processing equipment, a cluster control manager, and multiple energy managers. Each of the sub-photovoltaic-storage systems is equipped with a distributed photovoltaic unit and a distributed energy storage unit, and is connected to the cluster DC bus via a first DC / DC converter, with a first circuit breaker configured on the connection line; The centralized energy storage device is connected to the cluster DC bus via a second DC / DC converter, and a second circuit breaker is configured on the connection line; The V2G charging station is equipped with multiple charging piles. The charging gun of each charging pile is connected to the DC bus of the cluster through a bidirectional power conversion unit, and a third circuit breaker is configured on each connection line. Each of the aforementioned sub-photovoltaic energy storage system, the centralized energy storage device, and the V2G charging station is connected to an energy manager, which is used to flexibly control the devices under its jurisdiction. The V2G charging station is also equipped with a charging and discharging control module and a vehicle status detection module. The data acquisition equipment is used to collect data on power generation, load power, energy storage status, grid status, and vehicle charging demand status within the system in real time. The data processing equipment is used to process and predict the collected data; The cluster control manager is used to generate system-level coordination control instructions based on the processed data and preset strategies, and executes them through each of the energy managers.

2. A method for operation control of a power grid system based on photovoltaic-storage building complexes and charging stations as described in claim 1, characterized in that, The method is executed by the cluster control manager and includes: The data acquisition and processing equipment are used to acquire and analyze in real time the power generation, load demand, state of charge of each energy storage unit, grid connection status, grid dispatch instructions, and real-time charging demand and vehicle battery status of the DC microgrid system. Based on preset multi-mode judgment logic, determine the current operating mode that the system should be in; Based on the determined operating mode, the system invokes the preset core control strategy corresponding to that mode, generates and sends coordination control commands to the energy managers of each subsystem, and dynamically adjusts the distributed energy storage, centralized energy storage, and vehicle charging and discharging power in the sub-photovoltaic energy storage system and V2G charging stations to achieve optimized system operation.

3. The operation control method according to claim 2, characterized in that, The multi-mode judgment logic includes the following steps: The system detects the grid connection status; if a fault occurs in the main grid, it determines that it is entering emergency islanding mode. If the power grid connection is normal, determine whether a clear power grid dispatch instruction has been received. If so, determine whether to enter the power grid interaction mode. If there is no grid instruction, the total renewable energy generation capacity in the system is compared with the total load demand capacity. If the generation capacity is greater than the load demand capacity, the system is determined to enter the consumption priority mode. If the power generation is not greater than the load demand, then it is further determined whether the real-time charging demand of the V2G charging station exceeds the current capacity that the system can guarantee. If it does, it is determined to enter the charging guarantee mode. If the time limit is not exceeded, the system is determined to enter normal mode.

4. The operation control method according to claim 2, characterized in that, When the system is determined to be in normal mode, the core control strategy is to optimize the economic efficiency of system operation. It comprehensively considers time-of-use pricing, power generation and load forecasting information, and the need to smooth system power fluctuations. Through optimization algorithms, it dynamically allocates the charging and discharging plans of centralized energy storage, distributed energy storage, and V2G vehicles to minimize system operating costs and power fluctuations within the grid.

5. The operation control method according to claim 3, characterized in that, When the system determines that the elimination priority mode is adopted, the core control strategy executed is the gradient elimination strategy, which specifically includes: Prioritize supplying surplus renewable energy power to vehicle batteries that are charging at V2G charging stations; If there is still a surplus, it will be supplied to the distributed energy storage units in each sub-photovoltaic energy storage system for charging. If there is still a surplus after the distributed energy storage is fully charged, it will be supplied to the centralized energy storage equipment for charging. This strategy ensures that 100% of the renewable energy generated within the system is consumed locally first.

6. The operation control method according to claim 3, characterized in that, When the system determines that it is in charging protection mode, the core control strategy executed is a tiered protection strategy, which specifically includes: Charging needs are categorized based on the urgency of vehicle charging, user reservation information, and battery status. Prioritize power supply for high-level charging needs, utilize centralized energy storage and distributed energy storage discharge from various sub-photovoltaic and energy storage systems, and guide V2G vehicles to discharge in an orderly manner while ensuring charging, so as to ensure the reliability of charging services and user satisfaction.

7. The operation control method according to claim 3, characterized in that, When the system is determined to be in emergency islanding mode, the core control strategy is to maintain continuous power supply to critical loads within the system and achieve black start. The cluster control manager immediately disconnects from the faulty main grid and reallocates available power generation and energy storage resources based on the remaining capacity of each energy storage unit and the priority of critical loads, maintaining the voltage and frequency stability of the islanded system, and guiding the system to smoothly switch back to grid-connected mode when conditions permit.

8. The operation control method according to claim 2, characterized in that, When generating coordinated control commands, the cluster control manager also comprehensively considers the current state of charge, health status, charging and discharging efficiency, and power limits of each energy storage unit, including centralized energy storage devices and distributed energy storage units. It also performs secondary power optimization allocation within the same type of energy storage unit to balance the cyclic losses between energy storage units and extend the overall energy storage life of the system.

9. The operation control method according to claim 3, characterized in that, The execution of the operation control method is a continuous dynamic closed-loop process; The cluster control manager continuously receives data, determines the operating mode, generates and issues control commands at fixed intervals, and realizes smooth switching between different operating modes and coordinated optimization of multiple controllable resources within the system, while simultaneously meeting the dual objectives of ensuring renewable energy consumption and ensuring electric vehicle charging needs.

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