Photovoltaic energy storage fusion-based intelligent regulation and control system for electrical load rate of transformer substation

Abstract

The invention relates to the technical field of transformer substation intelligent regulation and control, and discloses a transformer substation electricity load rate intelligent regulation and control system based on photovoltaic energy storage fusion, which comprises a micro-grid layer for realizing frequency modulation and peak regulation based on interaction of electric energy allocation in a transformer substation and a main grid coordination control layer or finishing load transfer regulation and control through cooperation of a cross-transformer substation coordination layer, the main network coordination control layer formulates a dynamic power interaction strategy based on a main network operation state; the cross-substation coordination control layer is used for formulating a cross-substation coordination control strategy based on the overall load requirements of regional substations and the real-time operation states of the substations, and realizing balanced distribution of loads in the region through load transfer, so that the substations can dynamically adjust load distribution according to the state of a main network, and frequency modulation and peak regulation coordination with the main network is realized; the regulation and control capability of the transformer substations participating in the overall load optimization of the power grid is improved, information interaction and cooperative control between the transformer substations are established, and cross-site load dynamic balance in the large-scale power grid is realized.

Description

Technical Field

[0001] The present invention relates to the technical field of intelligent control of substations, and in particular to an intelligent control system for power load rate of substations based on photovoltaic energy storage fusion. Background Art

[0002] The existing intelligent control system for substation power load rates is designed to address the randomness, volatility, and intermittency of photovoltaic power generation. By collecting real-time operating data from distributed photovoltaic power plants, energy storage plants, and pilot substations, combined with meteorological information to predict photovoltaic output, it then adjusts energy storage output in real time, effectively smoothing out power fluctuations from distributed power sources.

[0003] In terms of overall data aggregation, by expanding the existing power grid model, integrated graphical and model management of 10kV distributed power stations is achieved, acquiring a model for real-time processing and calculation, accessing real-time operational information from the regional control automation system, and issuing control instructions. Specifically, the new energy management system provides ultra-short-term power forecast data for distributed photovoltaic regions, comprehensively considering energy storage output, energy storage SOC value, and predicted total photovoltaic output to calculate the energy storage output for the next time. When the photovoltaic change is positive and the energy storage SOC is within the feasible range, the energy storage absorbs electricity; otherwise, the energy storage device discharges. The system also features intelligent monitoring, power forecasting, and power quality monitoring, enabling real-time supervision of microgrid operations, achieving economically optimized scheduling, improving the ability to absorb new energy, and reducing grid operating costs.

[0004] In view of the above-mentioned and existing related technologies, the inventors believe that the following defects often exist: as a key node connecting the main grid and the regional power grid, the substation needs to achieve grid-level load balancing functions such as peak regulation and frequency regulation through dynamic power interaction. The existing solution lacks a two-way collaborative control strategy with the main grid, and cannot dynamically adjust its own load distribution according to the operating status of the main grid, resulting in insufficient control capabilities of the substation when participating in the overall load optimization of the power grid. Multiple substations in the regional power grid need to achieve overall load rate optimization through load distribution and collaborative control. The existing solution only designs multi-machine parallel coordination for distributed inverter clusters, and does not establish an information interaction and collaborative control mechanism between substations. It is difficult to achieve dynamic load balancing across sites in large-scale power grids, especially in fault scenarios, it is impossible to improve power supply reliability through multi-station mutual backup. Summary of the Invention

[0005] The technical problem to be solved by the present invention is that the existing technology has the disadvantages of insufficient control capabilities of substations when participating in the overall load optimization of the power grid and difficulty in achieving dynamic load balancing across sites in large-scale power grids. To this end, we propose an intelligent control system for substation power load rate based on photovoltaic energy storage integration.

[0006] To achieve the above objectives, this application adopts the following technical solution: an intelligent control system for substation power load rate based on photovoltaic energy storage integration, characterized by including a microgrid layer, a main grid coordination control layer, and an inter-substation coordination control layer: Microgrid layer: Energy is converted through photovoltaics, converted by smart inverters, and then supplied to or connected to the grid, and stored. Real-time monitoring and prediction of substation loads are carried out. Based on the interaction between substation power allocation and the main grid coordination control layer, frequency and peak regulation are achieved, or cross-substation coordination layer cooperates to complete load transfer control. Main grid coordination and control layer: used to establish a two-way communication channel between the microgrid layer and the main grid, obtain the main grid operation status information, upload the substation data of the microgrid layer to the main grid, and formulate dynamic power interaction strategies based on the main grid operation status; Cross-substation coordination control layer: used to collect real-time information on photovoltaic power generation, energy storage status, and power load in multiple substations. Based on the overall load demand of regional substations and the real-time operating status of each substation, a cross-substation coordinated control strategy is formulated to achieve balanced load distribution within the region through load transfer.

[0007] Preferably, the microgrid layer includes a photovoltaic control unit, a smart inverter, an energy storage device, a substation power load module, and a microgrid control module: The photovoltaic control unit is composed of the core of the photovoltaic module. The DC power output by the photovoltaic module is collected by the DC combiner box and then connected to the smart inverter; Smart inverters convert the DC power output from photovoltaic panels into AC power. They work closely with the microgrid control module and adjust power output based on the substation's operating status. Energy storage equipment is used to store electricity when there is excess power generation from photovoltaic panels or when the grid has low electricity prices. It is used to output electricity for deployment when there is insufficient power generation in the substation, when there is peak power demand, when there is peak frequency regulation of the main grid, or when there is a need for cross-substation dispatching. The substation power load module collects real-time substation operating data and uploads it to the microgrid control module. Based on historical load data, meteorological conditions, and business law parameters, it uses machine learning algorithms to predict short-term load fluctuation trends. This module assists the main grid coordination control layer in developing dynamic power interaction strategies and interacts with the cross-substation coordination layer to provide real-time load data for regional load balancing and support the execution of load transfer strategies. The microgrid control module is used to continuously monitor the power generation of photovoltaic modules, the charging and discharging status of energy storage equipment, and the power load of the substation. It gives priority to using photovoltaic power generation to meet the load within the station, and stores the surplus power in the energy storage equipment. When photovoltaic power is insufficient, discharge is scheduled according to the energy storage capacity and load demand. When energy storage is insufficient and photovoltaic power cannot meet the demand, electricity is purchased from the traditional power grid.

[0008] Preferably, the substation power load module can also classify and manage the loads within the substation, distinguishing between critical loads and non-critical loads. When the photovoltaic output is insufficient or the energy storage power is low, the microgrid control module issues load priority control instructions.

[0009] Preferably, the microgrid control module is also used to receive main grid frequency fluctuations, peak and valley load demands and dispatch instruction information in the interaction with the main grid coordination control layer, and adjust the energy distribution strategy within the station based on the received data.

[0010] Preferably, the microgrid control module is also used to cooperate with the cross-substation coordination layer to upload the substation photovoltaic power generation, energy storage status and power load data in real time, receive the overall load demand of the regional power grid, and participate in the load transfer between substations according to the coordinated control strategy when the regional power grid operates normally.

[0011] Preferably, the main network coordination control layer includes an information interaction module, a status analysis module, a power interaction formulation module, and an instruction execution module: The information interaction module is responsible for establishing a two-way communication channel between the substation and the main grid, receiving frequency fluctuation data, peak and valley load demand information, and grid dispatch instruction information from the main grid; and sending real-time data on photovoltaic power generation, energy storage device charge status, and power load at the microgrid layer to the main grid; The status analysis module tracks the changing trends of the main grid frequency fluctuations in real time, analyzes the patterns of peak and valley load demand, and evaluates the operating status of the main grid and substation by combining the photovoltaic power generation, energy storage device charge status, and real-time power load data within the substation. The power interaction module decides on specific plans to adjust photovoltaic output power, control the charging and discharging of energy storage equipment, or adjust non-critical loads within the station based on the frequency deviation value. It also plans the charging and discharging plan of energy storage equipment and the power purchase strategy of the power grid according to the dispatch instructions, thus realizing peak load regulation and frequency regulation. The instruction execution module receives the control instructions generated by the power interaction formulation module and accurately sends the instructions to the microgrid control module for execution.

[0012] Preferably, the cross-substation coordination control layer includes a data collaboration module, a data processing module, a control strategy formulation module, and an instruction execution and feedback module: The data collaboration module is responsible for building a high-speed communication network platform between the microgrid layers in the region, collecting and summarizing the photovoltaic power generation, energy storage status and power load information of each microgrid layer, and uploading the collected data to the data processing module; The data processing module monitors the overall load demand trend of the region, as well as the photovoltaic power generation, energy storage status, and power load information of each microgrid layer, and analyzes the load distribution balance of each microgrid layer. The algorithm formula for load distribution balance is: in, is the load balancing degree, is the number of substations, For the The load value of each substation, The average load value of the substations in the region is used to evaluate the coordinated operation status of each microgrid layer and determine whether load transfer is necessary. The control strategy formulation module formulates a cross-substation coordinated control strategy based on the results of the data processing module. Receive the control instructions generated by the control strategy formulation module and accurately transmit the instructions to the microgrid control modules of each substation to ensure that load transfer, energy storage charging and discharging adjustment, and power generation power regulation operations are carried out in accordance with the coordinated control strategy.

[0013] Preferably, the control strategy formulation module determines the substations that need to transfer load and the load transfer amount based on the load distribution balance calculation result, and formulates a load transfer plan through a load transfer optimization algorithm to achieve balanced load distribution in the region; Load transfer optimization algorithm: The formula is: ;in, and is the weight coefficient, which is used to balance the load balance and operating cost. is the regional power grid operating cost, Represents the objective function of the load transfer optimization algorithm.

[0014] Preferably, based on the load distribution balance algorithm, the time dimension and prediction deviation are introduced to calculate the dynamic load balance change rate per unit time. The specific formula is: ; in, for The dynamic load balancing rate of change at each moment, and They are Moment and Load balancing at all times, is the time interval, is the prediction correction coefficient, The future predicted by the LSTM model set by the data processing module Time balance.

[0015] Preferably, the load transfer optimization algorithm is adjusted based on the calculation of the dynamic load balance change rate within a unit time. The specific formula is: ; in, is the weight coefficient, used to balance the various objectives; for Moment The load value of each substation, for The average load value of the substation in the area at that time, for Regional power grid operating costs at all times, represent Objective function of the moment load transfer optimization algorithm.

[0016] Technical effects and advantages of the present invention: In the present invention, by acquiring the main grid frequency fluctuations, peak and valley load demands, and dispatching instructions in real time, the photovoltaic power generation, energy storage status, and power load data within the station are uploaded simultaneously. The state analysis module is used to deeply analyze the main grid operation status, and the power interaction formulation module is combined to generate a dynamic control strategy. For example, when the main grid frequency is abnormal, the photovoltaic power is adjusted, the energy storage charge and discharge is controlled, or non-critical loads are reduced. The energy storage charge and discharge plan is optimized during peak and valley periods to participate in peak regulation. The strategy is issued to the microgrid layer for execution through the instruction execution module, so that the substation can dynamically adjust the load distribution according to the main grid status, realize the coordination of frequency regulation and peak regulation with the main grid, improve the substation's control ability to participate in the overall load optimization of the power grid, and enhance the stability and economy of the power grid.

[0017] In the present invention, a cross-substation coordination control layer is built, and a regional power grid high-speed communication network is constructed through a data coordination module. The photovoltaic, energy storage and load data of each substation are summarized in a unified format to realize information sharing. The data processing module analyzes the regional load balance and dynamic change rate in real time. The control strategy formulation module formulates a load transfer plan and fault backup strategy based on the load balance calculation results and the multi-objective optimization algorithm. During normal operation, part of the load of the high-load rate substation is transferred to the low-load rate substation, and the load sharing mechanism of the surrounding substations is activated in the event of a fault. The instruction execution and feedback module ensures the implementation of the control instructions and feedbacks the execution effect, forming a coordinated control closed loop, establishing information interaction and coordinated control between substations, realizing dynamic load balance across sites in large-scale power grids, improving regional power supply reliability through multi-station backup in fault scenarios, and optimizing the overall load rate of the regional power grid. BRIEF DESCRIPTION OF THE DRAWINGS

[0018] The disclosure of the present invention is illustrated with reference to the accompanying drawings. It should be understood that the drawings are for illustrative purposes only and are not intended to limit the scope of protection of the present invention. In the drawings, the same reference numerals are used to refer to the same components: Figure 1 It is a schematic diagram of the overall module of the present invention; Figure 2 This is a schematic diagram of the main network coordination control layer module of the present invention; Figure 3 This is a schematic diagram of the cross-substation coordination control layer module of the present invention. DETAILED DESCRIPTION

[0019] It is easy to understand that according to the technical solution of the present invention, without changing the essential spirit of the present invention, a person skilled in the art can propose a variety of interchangeable structural modes and implementation modes. Therefore, the following specific embodiments and drawings are only exemplary descriptions of the technical solution of the present invention and should not be regarded as the entire invention or as a limitation or restriction of the technical solution of the present invention.

[0020] Reference Figure 1-3 As shown, the present invention provides a technical solution: an intelligent control system for substation power load rate based on photovoltaic energy storage integration, including a microgrid layer: Solar energy is converted into electrical energy through photovoltaics, which is then converted by smart inverters to supply power or connect to the grid, and stored to cooperate in realizing the storage and release of electrical energy. The load in the substation is monitored and predicted in real time. The photovoltaic, energy storage and power load inside or outside the substation are coordinated and used to interact with the main grid coordination control layer to realize frequency and peak regulation, and cooperate with the cross-substation coordination layer to complete load transfer regulation to ensure stable power supply and efficient energy utilization.

[0021] The microgrid layer includes photovoltaic control units: The PV control unit consists of high-efficiency PV modules installed on the substation roof or wall in a well-lit, load-bearing area. The module's specifications and quantity are optimally configured based on the substation's power demand and installation area. High-efficiency monocrystalline or polycrystalline solar cells, coupled with an automatically adjustable PV mounting system, maximize solar energy utilization. The DC power output from the PV modules is combined in a DC combiner box and then fed into a smart inverter.

[0022] The microgrid layer includes smart inverters: Smart inverters are used to convert the direct current (DC) power output by photovoltaic modules into standard alternating current (AC) power. Working closely with the microgrid control module, they power equipment within the substation or connect it to the main grid. They adjust power output based on the substation's operating status. For example, when there's excess photovoltaic power, the excess energy is charged into energy storage devices. When power is insufficient, the energy storage device is controlled to discharge and its own output is adjusted to ensure stable power consumption within the station and facilitate clean energy dispatch.

[0023] The microgrid layer includes energy storage equipment: Energy storage equipment is used to store the direct current converted by the smart inverter in the form of chemical energy or electric field energy during periods of excess power generation from photovoltaic modules or low electricity prices in the grid. At the same time, it is activated when power generation in the substation is insufficient, when there is a peak in electricity demand, when the main grid is required to regulate peak frequency or when there is a need for cross-substation scheduling, to convert the stored chemical energy into direct current output. After being converted into alternating current by the smart inverter, it can meet the electricity demand within the substation or the allocation outside the substation, thus realizing flexible energy allocation.

[0024] The microgrid layer includes the substation power load module: The substation power load module collects real-time operational data, including power, voltage, and current, from various electrical equipment within the substation. After preliminary processing by the edge computing unit, data is uploaded to the microgrid control module, providing a basis for clean energy scheduling and energy storage charging and discharging strategies. Based on historical load data and parameters such as meteorological and business patterns, machine learning algorithms are used to predict short-term load fluctuation trends, assisting the main grid coordination and control layer in developing dynamic power interaction strategies. This module also interacts with the cross-substation coordination layer, providing real-time load data for regional load balancing and scheduling, supporting the execution of load transfer strategies, and ultimately optimizing substation power efficiency and improving power supply stability.

[0025] The substation power load module can also classify and manage the loads within the substation, distinguishing between critical loads, such as relay protection devices, and non-critical loads, such as lighting systems. When the photovoltaic output is insufficient or the energy storage power is low, the microgrid control module will issue load priority control instructions to ensure the power supply reliability of key equipment.

[0026] The microgrid layer includes the microgrid control module: The microgrid control module continuously monitors the power generation of photovoltaic panels, the charge and discharge status of energy storage devices, and the substation's power load. It prioritizes photovoltaic power generation to meet the station's load, with excess power stored in the energy storage devices. When photovoltaic power is insufficient, discharge is scheduled based on the energy storage capacity and load demand. When energy storage is insufficient and photovoltaic power cannot meet the demand, power is purchased from the traditional grid, maximizing clean energy utilization and maintaining the original efficient scheduling logic.

[0027] In its interaction with the main grid's coordination control layer, the microgrid control module receives information about main grid frequency fluctuations, peak and valley load demands, and dispatch instructions. Based on this information, it adjusts the station's energy distribution strategy. For example, when the main grid's frequency is abnormal, it rapidly adjusts PV output power, controls energy storage charging and discharging, or reduces non-critical loads to assist in main grid frequency regulation. During peak and valley periods, it follows dispatch instructions to optimize energy storage charging and discharging plans, reducing electricity costs and contributing to the main grid's peak load regulation.

[0028] Working in conjunction with the cross-substation coordination layer, the microgrid control module uploads real-time data on substation photovoltaic power generation, energy storage status, and power load, while also receiving overall load demand from the regional power grid. When the regional power grid is operating normally, the module participates in load transfer based on coordinated control strategies, rationally transferring excess load from the local station to substations with lower load rates. This ensures regional power supply reliability and achieves dynamic load balancing and collaborative support across substations.

[0029] It also includes the main network coordination control layer: The main grid coordination control layer is used to establish a two-way communication channel between the microgrid layer and the main grid, and obtain real-time main grid operation status information, including frequency fluctuations, peak and valley load demands, and grid dispatch instructions; at the same time, it uploads the photovoltaic power generation, energy storage device charge status, and power load data of the microgrid layer to the main grid, and formulates dynamic power interaction strategies based on the main grid operation status.

[0030] When the main grid experiences frequency fluctuations, the substation participates in the main grid frequency regulation by adjusting the photovoltaic output power, controlling the charging and discharging of energy storage equipment, or adjusting non-critical loads within the station according to the frequency deviation value. During the peak and valley periods of the main grid, according to dispatch instructions, energy storage discharge is increased and power purchases from the grid are reduced during peak periods, while low-priced electricity is used to charge energy storage during valley periods to achieve peak regulation, thereby assisting the main grid in achieving load balance and improving the overall stability and economy of the grid.

[0031] The main network coordination and control layer includes the information interaction module: The information exchange module is responsible for establishing a two-way communication channel between the substation and the main grid, enabling real-time data transmission. On the one hand, it receives frequency fluctuation data, peak and valley load demand information, and grid dispatch instructions from the main grid; on the other hand, it sends real-time data on photovoltaic power generation, energy storage device charge status, and power load at the microgrid level to the main grid.

[0032] The main network coordination and control layer includes the status analysis module: The Status Analysis Module monitors and analyzes the main grid's operating status information and substation operating data, acquired from the Information Interaction Module, in real time. It tracks the changing trends of main grid frequency fluctuations and analyzes peak and valley load patterns. Combined with real-time data on substation photovoltaic power generation, energy storage device charge status, and power load, it assesses the operating status of the main grid and substation, providing a basis for developing dynamic power interaction strategies.

[0033] The main network coordination and control layer includes the power interaction formulation module: The power interaction planning module develops dynamic power interaction strategies based on the results of the state analysis module. When the main grid frequency fluctuates, the module determines specific plans for adjusting PV output power, controlling the charging and discharging of energy storage devices, or adjusting non-critical loads within the substation based on the frequency deviation. During peak and off-peak periods, the module follows dispatch instructions to plan energy storage device charging and discharging plans and power purchase strategies, implementing peak and frequency regulation functions and ensuring coordinated operation of the substation and the main grid.

[0034] Response to Main Grid Frequency Fluctuations: When the main grid frequency deviates from the rated value, the system first calculates the frequency deviation. If the deviation exceeds a preset threshold, the frequency regulation strategy is activated: The system prioritizes the maximum power point tracking output of the photovoltaic modules to adjust the power generation. If photovoltaic regulation is insufficient, the system controls the charging and discharging of energy storage devices. Finally, non-critical loads are reduced based on load priority. This three-step regulation ensures main grid frequency stability.

[0035] Peak-valley period strategy planning: Based on the main grid dispatch instructions, peak and valley periods are identified. Combined with the station's load forecast, a cost optimization algorithm is used to develop energy storage equipment charging and discharging plans and grid power purchase strategies. During off-peak periods, when electricity prices are low, grid power is used to charge energy storage equipment, reducing the proportion of photovoltaic power generation used for self-use. During peak periods, when electricity prices are high, energy storage is prioritized for discharge to meet station load demand, reducing high-priced electricity purchases and lowering overall electricity costs.

[0036] The main network coordination and control layer includes the instruction execution module: The Command Execution Module receives control commands generated by the Power Interaction Module and accurately transmits them to the Microgrid Control Module for execution. It also monitors the execution of these commands to ensure that photovoltaic output power adjustment, energy storage device charging and discharging operations, and load switching are accurately executed according to the commands. The results are then fed back to the Status Monitoring and Analysis Module, forming a closed control loop.

[0037] It also includes cross-substation coordination control layer: It is used to collect real-time information on photovoltaic power generation, energy storage status and power load within the microgrid layer. Based on the overall load demand of the regional substation and the real-time operating status of each substation, it formulates a cross-substation coordinated control strategy, achieves balanced load distribution within the region through load transfer, and transfers part of the load from high-load substations to low-load substations to improve the overall load rate.

[0038] The cross-substation coordination control layer includes the data coordination module: The data collaboration module is responsible for building a high-speed communication network platform between each microgrid layer within the region, providing a stable and reliable data transmission channel between them. It collects and aggregates information on photovoltaic power generation, energy storage status, and power load at each microgrid layer. This data is encoded according to a unified data format and communication protocol and uploaded to the data processing module, enabling rapid information sharing and interaction between substations within the region.

[0039] The cross-substation coordination control layer includes the data processing modules: The data transmitted by the data collaboration module is monitored in real time and analyzed in depth. On the one hand, the overall load demand trends of the monitoring area, as well as the photovoltaic power generation, energy storage status, and power load information of each microgrid layer, are monitored; on the other hand, the load distribution balance of each microgrid layer is analyzed. Through comprehensive analysis of the collected data, the coordinated operation status of each microgrid layer is evaluated, and the need for load transfer is determined, providing a scientific basis for the formulation of coordinated control strategies.

[0040] Load distribution balance calculation algorithm: used to measure the balance of load distribution among substations in a region. The formula is: ; in, The load balance degree ranges from 0 to 1. The closer to 1, the more balanced. is the number of substations, For the The load value of each substation, The average load value of the substations in the region is converted into a numerical value between 0 and 1 through a mathematical formula to intuitively present the load distribution status. The closer it is to 1, the better the balance is, providing a clear quantitative basis for scheduling decisions. Based on the balance results, it can accurately identify load distribution imbalances and guide the formulation of cross-substation coordinated control strategies, such as promoting load transfer from high-load substations to low-load substations, optimizing the overall load layout of the regional power grid, and improving power supply stability and resource utilization.

[0041] Based on the original load distribution balance formula, the time dimension and prediction deviation are introduced to calculate the dynamic load balance change rate per unit time. The formula is: ; for The dynamic load balancing rate of change at each moment, and They are Moment and Load balancing at all times, is the time interval, is the prediction correction coefficient, is the future predicted by the LSTM model Time balance: By monitoring the rate of change, the trend of load distribution imbalance can be discovered in time and the control strategy can be triggered in advance.

[0042] By monitoring the rate of change, the trend of load distribution imbalance can be discovered in time and the control strategy can be triggered in advance.

[0043] Based on the time dimension, the ratio of the balance difference at different moments to the time interval is calculated. This can accurately capture the real-time change trend of load balance and quickly detect the initial signs of load distribution imbalance. For example, the balance fluctuation caused by the sudden change of load in a certain area due to the start-up of a factory can be combined with prediction correction to introduce the LSTM model to predict the future balance. By integrating forecast deviations and incorporating future trends into current rate of change calculations, we can predict imbalance trends in advance. Instead of passively responding to imbalances that have already occurred, we can proactively identify potential risks.

[0044] In terms of coordinated control, rate of change monitoring provides a quantitative basis for triggering control strategies. When the rate of change exceeds the normal range, strategies such as cross-substation load transfer and energy storage charge and discharge adjustment can be initiated in advance. Intervention can be carried out before the load imbalance worsens, optimize the regional power grid load layout, improve power supply stability and control foresight, and enhance the resilience of the power grid to dynamic loads. The cross-substation coordination control layer includes the control strategy formulation module: Based on the results of the data processing module, a cross-substation coordinated control strategy is formulated. Under normal operating conditions, based on the load balance calculation results, the substations requiring load transfer and the load transfer amount are determined. A load transfer optimization algorithm is used to formulate a load transfer plan to achieve balanced load distribution within the region.

[0045] Load transfer optimization algorithm: The objective function is to improve the overall load rate of the regional power grid and minimize the operating cost. The formula is: ; in, and is the weight coefficient, which is used to balance the load balance and operating cost. The operating cost of the regional power grid, including electricity purchase cost and equipment loss cost, represents the objective function of the load transfer optimization algorithm, It is a multi-objective optimization function about load balance and operating cost. The optimal load transfer scheme is determined by taking the minimum value of the load factor of the regional power grid as the guide and minimizing the operating cost as the guide. By constructing an objective function including load balancing and cost, the two are incorporated into a unified optimization framework. and Balancing the relationship between the two, taking into account both the efficiency and economy of grid operation, can not only promote a more balanced distribution of loads, but also control operating costs such as electricity purchases and equipment losses.

[0046] The algorithm provides a quantitative decision-making basis for cross-substation load transfer, accurately calculates the objective function values ​​under different transfer schemes, screens out the optimal scheme, and guides the reasonable transfer of loads from high-load substations to low-load sites, thereby optimizing the regional power grid load layout, enhancing power supply stability, and helping to achieve dynamic load balancing across stations in large-scale power grids, thereby improving the grid resource utilization efficiency and overall regulation level.

[0047] In each optimization cycle, based on the dynamic load balancing rate change rate, the multi-objective function is to improve the overall load rate of the regional power grid, minimize the operating cost, and optimize the dynamic load balancing degree: ; in, is the weight coefficient, used to balance the various objectives; for Moment The load value of each substation, for The average load value of the substation in the area at that time, for Regional power grid operating costs at all times, represent The objective function of the load transfer optimization algorithm is used to quantify the comprehensive optimization effect of the three goals of improving the overall load rate, reducing operating costs and optimizing dynamic load balance. The minimum value of determines the optimal cross-substation load transfer strategy at that moment, allowing the power grid to achieve efficient, economical and balanced operation in dynamic changes. This is the core quantitative indicator guiding the real-time regulation of the regional power grid.

[0048] From the perspective of target coverage, the integration of the three dimensions of regional power grid overall load rate improvement, operation cost minimization, and dynamic load balancing optimization is achieved through the weight coefficient. Balancing various objectives and fully adapting to grid operation needs, it focuses on optimizing the current load layout while also considering cost control and dynamic trends. Based on the dynamic load balance change rate, it can respond to load fluctuations in real time, capture load imbalance trends, and dynamically adjust strategies over time to avoid a "one-size-fits-all" approach. During the optimization cycle, it accurately calculates parameters such as the load and cost of each substation at different times, providing quantitative guidance for cross-station load transfer and energy storage scheduling. It promotes the rational transfer of load from high-load stations to low-load stations, improves the overall load rate, reduces operating costs, enhances the grid's resilience to dynamic changes and the accuracy of regulation, and helps regional power grids operate efficiently and stably.

[0049] The cross-substation coordination control layer includes the command execution and feedback modules: The control strategy module receives control commands generated by the control strategy formulation module and accurately transmits them to the microgrid control modules at each substation, ensuring that load transfer, energy storage charging and discharging adjustments, and power generation adjustments are executed in accordance with the coordinated control strategy. The module monitors the execution of commands in real time, collects execution status data, and feeds this data back to the data processing module for timely evaluation of the coordinated control effect and, if necessary, adjusts the strategy, forming a closed-loop management system for coordinated control.

[0050] Also includes the communication network layer: A high-speed communication network is constructed using various communication methods, including industrial Ethernet and fiber optic communications, to ensure real-time and reliable data transmission across all parts of the system. Communication security is strengthened in the coordinated control of the main network and in cross-substation collaborative interactions. Multiple security measures, including encrypted transmission, identity authentication, and access control, are implemented to prevent data leakage and unauthorized intrusion, ensuring the secure and stable operation of the communication network.

[0051] The technical scope of the present invention is not limited to the contents of the above description. Those skilled in the art can make various deformations and modifications to the above embodiments without departing from the technical idea of ​​the present invention, and these deformations and modifications should all fall within the protection scope of the present invention.

Claims

1. An intelligent control system for power load rate of substation based on photovoltaic energy storage integration, characterized in that: Including microgrid layer, main grid coordination control layer and cross-substation coordination control layer: Microgrid layer: Energy is converted through photovoltaics, converted by smart inverters, and then supplied to or connected to the grid, and stored. Real-time monitoring and prediction of substation loads are carried out. Based on the interaction between substation power allocation and the main grid coordination control layer, frequency and peak regulation are achieved, or cross-substation coordination layer cooperates to complete load transfer control. Main grid coordination and control layer: used to establish a two-way communication channel between the microgrid layer and the main grid, obtain the main grid operation status information, upload the substation data of the microgrid layer to the main grid, and formulate dynamic power interaction strategies based on the main grid operation status; Cross-substation coordination control layer: used to collect real-time information on photovoltaic power generation, energy storage status, and power load in multiple substations. Based on the overall load demand of regional substations and the real-time operating status of each substation, a cross-substation coordinated control strategy is formulated to achieve balanced load distribution within the region through load transfer.

2. The intelligent control system for power load rate of substation based on photovoltaic energy storage integration according to claim 1 is characterized in that: The microgrid layer includes a photovoltaic control unit, a smart inverter, an energy storage device, a substation power load module, and a microgrid control module: The photovoltaic control unit is composed of the core of the photovoltaic module. The DC power output by the photovoltaic module is collected by the DC combiner box and then connected to the smart inverter; Smart inverters convert the DC power output from photovoltaic panels into AC power. They work closely with the microgrid control module and adjust power output based on the substation's operating status. Energy storage equipment is used to store electricity when there is excess power generation from photovoltaic panels or when the grid has low electricity prices. It is used to output electricity for deployment when there is insufficient power generation in the substation, when there is peak power demand, when there is peak frequency regulation of the main grid, or when there is a need for cross-substation dispatching. The substation power load module collects real-time substation operating data and uploads it to the microgrid control module. Based on historical load data, meteorological conditions, and business law parameters, it uses machine learning algorithms to predict short-term load fluctuation trends. This module assists the main grid coordination control layer in developing dynamic power interaction strategies and interacts with the cross-substation coordination layer to provide real-time load data for regional load balancing and support the execution of load transfer strategies. The microgrid control module is used to continuously monitor the power generation of photovoltaic modules, the charging and discharging status of energy storage equipment, and the power load of the substation. It gives priority to using photovoltaic power generation to meet the load within the station, and stores the surplus power in the energy storage equipment. When photovoltaic power is insufficient, discharge is scheduled according to the energy storage capacity and load demand. When energy storage is insufficient and photovoltaic power cannot meet the demand, electricity is purchased from the traditional power grid.

3. The intelligent control system for power load rate of substation based on photovoltaic energy storage integration according to claim 2 is characterized in that: The substation power load module can also classify and manage the loads within the substation, distinguishing between critical loads and non-critical loads. When the photovoltaic output is insufficient or the energy storage power is low, the microgrid control module issues load priority control instructions.

4. The intelligent control system for power load rate of substation based on photovoltaic energy storage integration according to claim 2 is characterized in that: The microgrid control module is also used to receive main grid frequency fluctuations, peak and valley load demands, and dispatch instruction information during interaction with the main grid coordination control layer, and adjust the energy distribution strategy within the station based on the received data.

5. The intelligent control system for power load rate of substation based on photovoltaic energy storage integration according to claim 2 is characterized in that: The microgrid control module is also used to cooperate with the cross-substation coordination layer to upload the substation photovoltaic power generation, energy storage status and power load data in real time, receive the overall load demand of the regional power grid, and participate in the load transfer between substations according to the coordinated control strategy when the regional power grid is operating normally.

6. The intelligent control system for power load rate of substation based on photovoltaic energy storage integration according to claim 2 or 4 is characterized in that: The main network coordination control layer includes an information interaction module, a status analysis module, a power interaction formulation module, and an instruction execution module: The information interaction module is responsible for establishing a two-way communication channel between the substation and the main grid, receiving frequency fluctuation data, peak and valley load demand information, and grid dispatch instruction information from the main grid; And send real-time data of photovoltaic power generation, energy storage device charge status and power load of the microgrid layer to the main grid; The status analysis module tracks the changing trends of the main grid frequency fluctuations in real time, analyzes the patterns of peak and valley load demand, and evaluates the operating status of the main grid and substation by combining the photovoltaic power generation, energy storage device charge status, and real-time power load data within the substation. The power interaction module decides on specific plans to adjust photovoltaic output power, control the charging and discharging of energy storage equipment, or adjust non-critical loads within the station based on the frequency deviation value. It also plans the charging and discharging plan of energy storage equipment and the power purchase strategy of the power grid according to the dispatch instructions, thus realizing peak load regulation and frequency regulation. The instruction execution module receives the control instructions generated by the power interaction formulation module and accurately sends the instructions to the microgrid control module for execution.

7. The intelligent control system for power load rate of substation based on photovoltaic energy storage integration according to claim 2 or 5 is characterized in that: The cross-substation coordination control layer includes a data collaboration module, a data processing module, a control strategy formulation module, and an instruction execution and feedback module: The data collaboration module is responsible for building a high-speed communication network platform between the microgrid layers in the region, collecting and summarizing the photovoltaic power generation, energy storage status and power load information of each microgrid layer, and uploading the collected data to the data processing module; The data processing module monitors the overall load demand trend of the region, as well as the photovoltaic power generation, energy storage status, and power load information of each microgrid layer, and analyzes the load distribution balance of each microgrid layer. The algorithm formula for load distribution balance is: ,in, is the load balancing degree, is the number of substations, For the The load value of each substation, The average load value of the substation in the region is used to evaluate the coordinated operation status between the microgrid layers and determine whether load transfer is needed; The control strategy formulation module formulates cross-substation coordinated control strategies based on the results of the data processing module; Receive the control instructions generated by the control strategy formulation module and accurately transmit the instructions to the microgrid control modules of each substation to ensure that load transfer, energy storage charging and discharging adjustment, and power generation power regulation operations are carried out in accordance with the coordinated control strategy.

8. The intelligent control system for power load rate of substation based on photovoltaic energy storage integration according to claim 7 is characterized in that: The control strategy formulation module specifically determines the substations that need to transfer load and the load transfer amount based on the load distribution balance calculation results, and formulates a load transfer plan through the load transfer optimization algorithm to achieve balanced distribution of load in the region; Load transfer optimization algorithm: The formula is: ； in, and is the weight coefficient, which is used to balance the load balance and operating cost. is the regional power grid operating cost, Represents the objective function of the load transfer optimization algorithm.

9. The intelligent control system for power load rate of substation based on photovoltaic energy storage integration according to claim 8 is characterized in that: Based on the load distribution balance algorithm, the time dimension and prediction deviation are introduced to calculate the dynamic load balance change rate per unit time. The specific formula is: ； in, for The dynamic load balancing rate of change at each moment, and They are Moment and Load balancing at all times, is the time interval, is the prediction correction factor, The future predicted by the LSTM model set by the data processing module Time balance.

10. The intelligent control system for power load rate of substation based on photovoltaic energy storage integration according to claim 9 is characterized in that: The load transfer optimization algorithm is adjusted based on the dynamic load balance degree change rate within the calculation unit time. The specific formula is: ； in, is the weight coefficient, which is used to balance the various objectives; for Moment The load value of each substation, for The average load value of the substation in the area at that time, for Regional power grid operating costs at all times, represent Objective function of the moment load transfer optimization algorithm.

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