High-low voltage electrical apparatus cooperative control method, system, device and medium

Abstract

The application discloses a kind of high-low voltage electrical equipment collaborative control method, system, equipment and medium.The method includes: for each electrical equipment, the control strategy set containing control parameter, capability description data and demand description data are established;Based on the matching relationship of capability description data and demand description data, collaborative control link is established between electrical equipment;When electrical equipment monitors that own operation index exceeds preset threshold range, based on collaborative control link, control request is initiated to associated collaborative equipment;Associated collaborative equipment is operated according to control request content and local preset control strategy set, and control response containing control parameter adjustment value is generated and returned;According to control response, coordinate control operation is executed, and the collaborative strength parameter of collaborative control link is updated based on operation effect;The control strategy set of electrical equipment is updated according to preset time period.The application realizes the distributed collaboration and adaptive optimization of electrical equipment.

Description

Technical Field

[0001] This invention belongs to the field of intelligent control technology for power systems, and relates to methods, systems, equipment and media for coordinated control of high and low voltage electrical equipment. Background Technology

[0002] In modern power systems, high-voltage electrical equipment (such as circuit breakers and transformers) and low-voltage electrical equipment (such as photovoltaic inverters and energy storage systems) together form a complex heterogeneous network. Achieving effective coordinated control of electrical equipment in this type of network is crucial to ensuring the stable and efficient operation of the power grid.

[0003] Currently, existing collaborative control technologies mainly suffer from the following shortcomings: First, existing methods typically rely on preset fixed rules or models for optimization, and the set of control parameters set for electrical equipment cannot be dynamically adjusted according to the actual operating conditions of the power grid. When the power grid conditions change, such static control strategies are difficult to adapt, leading to a decrease in control effectiveness or even failure.

[0004] Secondly, existing technologies fail to establish continuous and adaptive collaborative relationships between devices. Even if some solutions consider cooperation between devices, they lack dynamic maintenance and evaluation mechanisms for collaborative control links and collaborative strength parameters. This makes it impossible to quantitatively manage and optimize the collaborative relationships between devices based on historical collaborative benefit data, resulting in low collaborative efficiency.

[0005] Secondly, mainstream solutions generally adopt a centralized control architecture, with a central control unit collecting global information and making unified decisions. This approach not only has high requirements for communication bandwidth and heavy computational burden, but also poses a single point of failure risk. Once the central node or communication link fails, the collaborative control capability of the entire system will be severely affected.

[0006] Therefore, there is an urgent need in this field for a new distributed collaborative control method that can achieve autonomous decision-making by equipment, self-organization and dynamic optimization of collaborative relationships, and continuous evolution of control strategies. Summary of the Invention

[0007] To address the problems existing in the background technology, this invention proposes a method, system, equipment, and medium for coordinated control of high and low voltage electrical equipment.

[0008] To achieve the above objectives, the technical solution adopted by the present invention is as follows: a method for coordinated control of high and low voltage electrical equipment, comprising: Establish a set of control strategies, capability description data, and demand description data for each electrical device; Based on the matching relationship between capability description data and demand description data, a collaborative control link is established between electrical devices; When an electrical device detects that its own operating indicators exceed a preset threshold range, it initiates a control request to the associated collaborative device based on the collaborative control link. The associated and collaborative devices perform calculations based on the content of the control request and the set of locally preset control strategies, generate a control response including the adjustment values ​​of control parameters, and send the control response back to the electrical device that initiated the request; Perform coordinated control operations based on the control response, and update the coordination strength parameter of the coordinated control link based on the effect of the coordinated control operations; The set of control strategies for electrical equipment is optimized and updated according to a preset time cycle.

[0009] Specifically, the associated collaborative devices assess the resource consumption for executing supporting actions based on their current operating status, calculate the control benefit value in combination with the control cost, and generate a control response containing control parameter adjustment values ​​when the control benefit value exceeds the preset benefit threshold. The calculation of the control benefit value includes a quantitative assessment of direct and indirect benefits, wherein direct benefits come from the control costs in the control request, and indirect benefits come from the expected improvement of the synergy strength parameter. The control costs include at least one of the following: power consumption costs, equipment lifespan loss costs, communication resource consumption costs, and computing resource consumption costs.

[0010] Specifically, the optimization updates include: Statistical analysis of the operating indicators and synergistic benefits of electrical equipment within a preset time period; Performance evaluation of the control strategy set is conducted based on operational indicator data and synergistic benefit data. The set of control strategies is screened and parameters are optimized based on the performance evaluation results.

[0011] Specifically, the screening and parameter optimization include: Remove the control policy set that ranks last in the performance evaluation results; Perform parameter reorganization on the set of control strategies that rank high in the performance evaluation results; Random parameters are adjusted on the reorganized set of control strategies.

[0012] Specifically, the coordinated control method for high and low voltage electrical equipment also includes dynamic maintenance of the coordinated control link: Monitor the usage status and collaborative benefit data of each collaborative control link; When the unused time of the collaborative control link reaches the preset duration or the collaborative benefit data continues to be lower than the set value, the collaborative control link is terminated. Electrical equipment establishes new collaborative control links through periodic data exchange.

[0013] Specifically, establishing the collaborative control link includes: Calculate the matching degree between the capacity description data and the demand description data of different electrical devices; When the matching degree exceeds the preset matching threshold, a collaborative control link is established between the corresponding electrical devices; Initialize the cooperation strength parameter for each cooperative control link.

[0014] Specifically, this also includes updating and adjusting the collaborative control links based on collaborative strength parameters: Calculate the synergy benefit value based on the actual effect of the coordinated control operation; Adjust the magnitude of the synergy strength parameter based on the synergy benefit value; When the coordination strength parameter is lower than the set threshold, the corresponding coordination control link is released.

[0015] High and low voltage electrical equipment coordinated control system includes: Device control agents, deployed on each electrical device, manage sets of control strategies, capability description data, requirement description data, and collaborative control links, and execute local control decisions. An optimized processing engine is used to perform optimization and update operations on the set of control strategies according to a preset time period; The operation status monitoring module is used to collect operation status data of electrical equipment.

[0016] An electronic device includes: a processor, and a memory coupled to the processor for storing a computer program; and the processor for executing the computer program stored in the memory to cause the electronic device to perform the high- and low-voltage electrical equipment coordinated control method.

[0017] A computer-readable storage medium comprising a computer program or instructions that, when executed on a computer, cause the computer to perform the high- and low-voltage electrical equipment coordinated control method.

[0018] Compared with existing technologies, this invention has the following advantages: it achieves dynamic optimization and continuous self-adaptation of control strategies. By optimizing and updating the control strategy set of electrical equipment according to a preset time period, control parameters can be continuously screened and optimized based on actual operating index data and synergistic benefit data. This overcomes the shortcomings of traditional static control strategies, such as rigidity and inability to adapt to long-term changes in the power grid, and possesses the ability to continuously improve itself.

[0019] An efficient distributed collaborative decision-making mechanism was constructed. By establishing capability description data and demand description data for electrical equipment, and establishing collaborative control links based on their matching relationships, the equipment can autonomously initiate control requests and responses based on the collaborative control links when abnormal operating indicators are detected. This achieves true distributed decision-making, completely eliminates the dependence on the central control unit, and improves the robustness and response speed of the system.

[0020] A self-organizing collaborative network based on benefit evaluation was established. By introducing a collaborative strength parameter and its update mechanism, the collaborative value can be quantitatively evaluated based on the actual effect of coordinated control operations, and collaborative control links can be dynamically maintained accordingly. This strengthens efficient collaborative relationships, automatically dismantles inefficient or ineffective links, and the entire collaborative network possesses self-organizing and adaptive capabilities, significantly improving the overall collaborative efficiency and resource utilization of the system. Attached Figure Description

[0021] Figure 1 This is a flowchart of the high and low voltage electrical equipment coordinated control method of the present invention; Figure 2 This is a connection diagram of the high and low voltage electrical equipment collaborative control system module of the present invention. Detailed Implementation

[0022] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0023] like Figures 1-2 As shown, the technical solution adopted by the present invention is as follows: a method for coordinated control of high and low voltage electrical equipment, comprising: For each electrical device, establish a set of control strategies, capability description data, and demand description data, including control parameters.

[0024] Furthermore, the control strategy set serves as a data carrier storing the core control logic of electrical equipment, containing multiple sets of control parameters in a structured form. These control parameters correspond to specific control rules for the equipment under different operating conditions (such as voltage fluctuations, load surges, and fault recovery), including parameters like reactive power output curves (specifying reactive power output values ​​under different voltages), action delay thresholds (the longest delay time for the equipment to respond to commands), power regulation sensitivity (the rate at which power adjusts with load changes), and voltage support range (the voltage fluctuation range that the equipment can maintain). These parameters must also match the equipment's own hardware characteristics (such as rated power and regulation accuracy). The control strategy set provides a preset scheme basis for the equipment to execute local control decisions. When the equipment detects abnormal operating indicators and needs to initiate or coordinate control responses, it can directly call the control parameters within the set to calculate response schemes without relying on external commands, such as generating control parameter adjustment values. This ensures the standardization and specificity of the equipment's control behavior and avoids control chaos caused by the lack of preset strategies.

[0025] Capability description data is standardized data that quantifies the collaborative support that electrical equipment can provide. It must clearly indicate the type and intensity of support. For example, the capability description data for energy storage equipment may include short-term power support (maximum 2MW) and voltage regulation (±5% of rated voltage). The capability description data for photovoltaic inverters may include active power output range (0-1.2 times rated power) and reactive power compensation capacity (0-0.8 times rated capacity). The data must be based on the actual operating capabilities of the equipment, such as maximum output power and regulation accuracy, to ensure authenticity and feasibility. Capability description data provides a matching basis for resource supply when establishing collaborative control links. Other electrical equipment can read this data to determine whether it has the capability to meet its own collaborative needs. For example, when low-voltage equipment requires voltage support, the capability description data can be used to filter out high-voltage equipment with voltage regulation capabilities, avoiding invalid collaborative requests and improving the efficiency and accuracy of establishing collaborative links.

[0026] Demand description data is standardized data that quantifies the external collaborative support required for the operation of electrical equipment. It must clearly indicate the type and intensity of the demand. For example, demand description data for energy storage equipment may include charging opportunities and operational lifespan guarantees; demand description data for low-voltage load equipment may include voltage stability and continuous power supply. This data must be set based on equipment operational safety and efficiency requirements (such as battery life thresholds and load power supply reliability standards). Demand description data provides a basis for matching resource demands to establish collaborative control links. It establishes a correspondence between demands and capabilities with the capability description data of other electrical equipment. Electrical equipment can use this data to accurately locate collaborative partners that can meet its needs. For example, energy storage equipment can use demand description data to select photovoltaic equipment with continuous charging capabilities. Simultaneously, it allows other electrical equipment to clarify the demand boundaries of that equipment, ensuring that collaborative support effectively solves its operational problems and avoids wasting collaborative resources.

[0027] Based on the matching relationship between capability description data and demand description data, a collaborative control link is established between electrical devices.

[0028] Matching relationships are the logical foundation for establishing links. The capability description data and demand description data of each electrical device constitute the potential for collaboration. This technical solution compares these two sets of data for different electrical devices to find device pairs where supply and demand correspond.

[0029] Specifically, establishing a collaborative control link includes: calculating the matching degree between capability description data and demand description data between different electrical devices.

[0030] Calculating the matching degree is a quantitative screening process. Specifically, it involves calculating the similarity between the capability description data of electrical appliance A and the requirement description data of electrical appliance B. For example, it involves calculating the cosine similarity or the reciprocal of the Euclidean distance between the two vectors. The result is a numerical value used to objectively measure the likelihood that appliance A meets the requirements of appliance B. The matching degree is a comprehensive quantitative result of functional fit and electrical relevance.

[0031] First, for the corresponding dimensions of the capability description data and the demand description data (such as voltage regulation capability and voltage stability demand, power support capability and power supplementation demand, etc.), calculate the functional fit of each dimension.

[0032] For example, if the voltage regulation range of a high-voltage device is ±5% of the rated voltage, while the voltage stability requirement of a low-voltage device is a deviation of no more than 3%, then it is necessary to determine whether the capability dimension fully covers the requirement dimension. In this example, since the regulation range fully meets the stability requirement, the functional fit can be determined to be 100%.

[0033] Subsequently, a weighted composite score is calculated by combining the electrical compatibility between devices (e.g., calculated using the node impedance matrix, where lower impedance indicates higher compatibility). For example, functional fit accounts for 70% of the total weight, and electrical compatibility accounts for 30%, ultimately yielding a comprehensive matching degree. This method ensures that the matching result is based on functional complementarity while also considering electrical response efficiency.

[0034] Matching and quantifying the filtering function to find compatible and electrically reachable collaborative devices. This avoids issues such as functionally compatible devices being too far apart electrically, resulting in delayed collaborative responses, or devices being close in electrical distance but lacking complementary functions, thus failing to meet requirements.

[0035] When the matching degree exceeds the preset matching threshold, a collaborative control link is established between the corresponding electrical devices.

[0036] Specifically, the preset matching threshold is a configurable system parameter. Only when the calculated matching degree value is higher than this threshold is device A considered a qualified and valid candidate for associated collaboration with device B, thus allowing the establishment of a link.

[0037] Furthermore, the preset matching threshold is a minimum standard for effective links based on the reliability requirements of power grid coordination. If the matching degree is below the threshold, either the functional fit is insufficient (e.g., only 60% fit), meaning the equipment capabilities cannot fully cover the requirements; or the electrical correlation is low, and the transmission delay of the coordination signal may exceed the equipment's tolerance range, making it highly unlikely that effective coordination operations can be completed after the link is established. Only when the matching degree exceeds the threshold does it mean that the equipment can both meet the actual needs through functional complementarity and respond quickly at the electrical level, thus meeting the conditions for establishing an effective link. The preset matching threshold filters out inefficient and invalid matching combinations, ensuring the actual value of each coordinated control link.

[0038] Initialize the cooperation strength parameter for each cooperative control link.

[0039] Specifically, the initialization coordination strength parameter assigns an initial weight or trust value to each newly established coordination control link. The initialization coordination strength parameter is a dynamic variable used to record and reflect the historical coordination effectiveness of this link; its initial value can be set based on the initial matching degree.

[0040] Furthermore, the collaboration strength parameter serves as a benchmark value for quantifying the initial tightness of the collaborative control link. Its value is directly linked to the initial matching degree between the capability description data and the demand description data. The higher the matching degree, the larger the initial parameter value; for example, the parameter value is set to 0.9 when the matching degree is 90%, and 0.8 when the matching degree is 80%. When subsequently associated collaborative devices determine whether to respond to a control request, they will consider this parameter, the control cost provided by the initiating electrical device, and the action cost they themselves need to incur to respond. The higher the parameter, the easier it is to meet the condition that the benefits outweigh the costs under the same cost and effort, thus making them more willing to respond to the request.

[0041] The collaboration strength parameter provides initial relationship weights for subsequent collaboration decisions. On one hand, the parameter distinguishes the initial tightness of different links, with links of higher matching degree having higher parameter values ​​and participating in collaboration first. On the other hand, it provides a benchmark for subsequent parameter updates, supporting the dynamic maintenance of collaboration control links.

[0042] When an electrical device detects that its operating indicators exceed a preset threshold range, it initiates a control request to the associated collaborative device based on the collaborative control link.

[0043] Operating indicators are electrical quantities (such as voltage and frequency) monitored locally by electrical equipment. Preset threshold ranges define the boundaries for the safe and stable operation of electrical equipment. When operating indicators exceed these limits, it signifies that the electrical equipment faces operational risks, triggering the need for external collaboration.

[0044] Specifically, the associated collaborative devices assess the resource consumption for executing support actions based on their current operating status, calculate the control benefit value in combination with the control cost, and generate a control response that includes control parameter adjustment values ​​when the control benefit value exceeds the preset benefit threshold.

[0045] The decision-making criterion for collaborative devices is that the benefits outweigh the costs. By quantitatively assessing the resource consumption and expected benefits of response actions, it determines whether to provide collaborative support. The core basis is the calculation logic of control benefit value to ensure that the response behavior is rational and in line with the overall optimization goal of the system.

[0046] The calculation of the control benefit value includes a quantitative assessment of direct and indirect benefits, where direct benefits come from the control costs in the control request, and indirect benefits come from the expected improvement of the synergy strength parameter.

[0047] The associated and collaborative devices first assess the support actions to be taken based on their current operating status, such as remaining power capacity, voltage deviation, and equipment aging. This includes assessing the various resources required to provide reactive power support, thus providing accurate basic data for subsequent control cost calculations and avoiding decision-making errors due to inaccurate resource assessments.

[0048] In the evaluation system of control benefit value, there is a clear logical relationship between direct benefits, indirect benefits, costs, single benefits, and total benefits, which together form the basis of collaborative decision-making: Direct benefits refer to the immediate compensation that the requesting electrical equipment is willing to pay in order to obtain collaborative support, such as compensation for power loss.

[0049] Indirect benefits are not reflected in the immediate returns of a single collaboration, but rather in the long-term positive impact on the collaborative relationship after successful collaboration, specifically manifested in the collaboration strength parameter. This improvement could lead to higher priority and greater returns in future collaborative decision-making, making it a long-term relationship investment.

[0050] Cost is the sum of all resource costs incurred by the associated collaborative devices to carry out this support action, including power consumption, equipment lifespan loss, and consumption of communication and computing resources.

[0051] Single-event benefit refers specifically to the net benefit generated by a particular collaborative action, that is, the result of direct benefits minus costs, which reflects the immediate benefits of that collaboration.

[0052] Total revenue is the sum of net benefits accumulated from multiple collaborative actions over a period of time. It includes the sum of direct benefits and cost differences from each instance, as well as long-term indirect benefits resulting from increased collaboration intensity.

[0053] It should be clarified that the calculation of control benefit value is oriented towards a single coordinated control request and is used to determine whether the current control response has immediate benefits. Its calculation does not cover long-term or multi-round cumulative effects.

[0054] The specific formula for calculating the control benefit value is as follows:

[0055] in: This represents the control benefit value generated by a single control action, i.e., the net benefit of this collaboration; The pre-defined symbiosis strength weighting coefficient; This represents the cooperation strength parameter of the current cooperative control link; The cost of control declared in the control request reflects the direct benefits; The preset action cost weighting coefficient; The total cost is the sum of the control costs incurred by the associated and coordinating devices to execute this support action.

[0056] In this formula Partially representing the direct benefits adjusted for synergy intensity, while Represents the costs borne by the responder. Value of a single control operation. This is the difference between the direct benefits and costs of this collaboration, reflecting the net benefit of a single collaborative action. The system determines the net benefit based on each collaboration... Determine whether to respond to the request and update the cooperation strength parameter based on its value. This will affect future profit expectations and decision-making behavior in collaborative decision-making.

[0057] When the calculated control benefit value of a single control action Greater than the cost, that is (Here, 0 represents a preset benefit threshold.) Only when the response is considered profitable will a control response be generated.

[0058] The preset benefit threshold is a critical value for judging the feasibility of a response (e.g., When the control benefit value exceeds the threshold, it indicates that the benefit of the response action outweighs the cost. The associated collaborative devices perform calculations based on the local control strategy set to generate a control response containing specific control parameter adjustment values. The function is to ensure that the response action is accurate and executable, while avoiding ineffective resource waste.

[0059] The control costs include at least one of the following: power consumption costs, equipment lifespan loss costs, communication resource consumption costs, and computing resource consumption costs.

[0060] Furthermore, there is the cost of energy loss: the additional active power loss caused by performing the control actions themselves.

[0061] Cost of equipment lifespan loss: such as the reduction in mechanical lifespan due to increased switching frequency.

[0062] Communication resource consumption cost and computing resource consumption cost: the bandwidth and computing power consumed in processing requests and generating responses.

[0063] To achieve a quantitative assessment of control costs, the system can employ a pre-defined cost calculation model to map various resource consumptions to a unified cost. For example, the optional quantification criteria for each cost are as follows: The cost of energy loss can be calculated by multiplying the active power consumed to support the operation by the preset unit energy cost.

[0064] The cost of equipment life loss can be estimated based on the cumulative damage caused to critical components of the equipment (such as circuit breaker contacts and battery cycle counts) by support actions, combined with the unit life cost of that component.

[0065] The cost of communication resource consumption can be determined based on the amount of data transmitted and the preset unit communication resource cost.

[0066] The cost of computing resources can be calculated based on the computing time or processor cycles consumed in processing control requests, as well as the preset unit computing cost.

[0067] When making decisions, the associated and collaborative devices will comprehensively consider one or more of the aforementioned costs to form a total control cost, which will be used to calculate the final control benefit value. Those skilled in the art should understand that the above quantification method is merely an example, and other applicable models or industry standard methods can be used to achieve the objectives of this invention.

[0068] The associated and collaborative devices perform calculations based on the content of the control request and the set of locally preset control strategies, generate a control response including the adjustment values ​​of control parameters, and send the control response back to the electrical device that initiated the request.

[0069] After deciding to initiate a control response, the associated and coordinated device searches for and calculates a specific, executable solution from its control strategy set—that is, its local library of all available control solutions. This solution is ultimately quantified into control parameter adjustment values, such as increasing the reactive power output setpoint by +5kVar, and is encapsulated in the control response and sent back.

[0070] Perform coordinated control operations based on the control response, and update the coordination strength parameter of the coordinated control link based on the effect of the coordinated control operations.

[0071] Specifically, this also includes updating and adjusting the collaborative control links based on the collaborative strength parameter: calculating the collaborative benefit value based on the actual effect of the coordinated control operation.

[0072] Adjust the magnitude of the synergy strength parameter based on the synergy benefit value.

[0073] When the coordination strength parameter is lower than the set threshold, the corresponding coordination control link is released.

[0074] After the coordinated control operation is executed, this technical solution will evaluate its actual effect, such as how much the requester's voltage deviation has been restored. Based on this objective effect, a synergistic benefit value is calculated, which is used to accurately measure the true value of this coordinated action.

[0075] Based on the calculated synergy benefit value, the synergy strength parameter of the synergy control link is adjusted according to certain rules. A high benefit value results in a significant increase in the parameter; a low or negative benefit value results in a decrease in the parameter. This ensures that the weight of the synergy control link accurately reflects its historical performance.

[0076] If the coordination strength parameter of a coordination control link continues to decrease due to repeated poor coordination results and falls below another set threshold, it proves that this coordination control link has failed or is inefficient, and the system will release it to free up resources.

[0077] Furthermore, first collect actual operating data after coordinated control operations (such as the voltage deviation of the initiating equipment decreasing from 6% to 2%, survival pressure). (From 0.0036 to 0.0004), the formula for survival pressure is: , This is the rated voltage.

[0078] Based on the formula for calculating control benefit value, the actual benefit of this collaboration is calculated. value.

[0079] like If the synergistic effect is positive and the operation is effective, then proceed according to the preset ratio (e.g., For every increase of 0.1, The coordination strength parameter of this coordination control link is increased by 10%.

[0080] like If the synergistic effect is negative or non-existent, or the operation is ineffective, then the adjustment should be lowered. ;when If the value falls below a preset threshold (e.g., 0.3), the subsequent termination of the collaborative control link will be triggered.

[0081] High-value collaborative control links (with consistently positive benefits) have their strength parameters increased and are prioritized when initiating subsequent collaborative requests; low-value collaborative control links (with negative benefits) have their strength parameters decreased and are eventually eliminated, ensuring that collaborative control links always maintain an efficient matching state, avoiding invalid links from consuming communication and computing resources, and improving the overall collaborative efficiency of the system.

[0082] Specifically, the collaborative control method for high and low voltage electrical equipment also includes dynamic maintenance of collaborative control links: monitoring the usage status and collaborative benefit data of each collaborative control link.

[0083] When the unused time of the collaborative control link reaches the preset duration or the collaborative benefit data continues to be lower than the set value, the collaborative control link is terminated.

[0084] Electrical equipment establishes new collaborative control links through periodic data exchange.

[0085] Dynamic maintenance is a continuously running background process that ensures the collaborative network remains efficient and robust at all times.

[0086] Monitoring usage status and synergistic benefits data: The system continuously tracks two key indicators: Usage status: such as whether the link has been idle for a long time (unused time).

[0087] In the dynamic maintenance of collaborative control links, collaborative benefit data specifically refers to the statistical indicators calculated based on the control benefit values ​​of all collaborative events recently triggered by the link, i.e., the comprehensive benefit value.

[0088] The system continuously tracks these metrics to determine the long-term value of collaborative control links: The collection of recent single benefit values: records every single control benefit value generated by this link within the most recent statistical window (e.g., the last 5 collaborations or the past 24 hours). This is the most direct, raw data.

[0089] Key statistical indicators: Based on the above set of single values, the system will focus on two derived indicators: Average benefit value: All recent single transactions of this link The arithmetic mean of the values. If this value remains below a set threshold (e.g., the average is consistently less than 0), it indicates that the collaborative behavior of this link is generally unprofitable.

[0090] Benefit achievement rate: In recent collaborative events, the single-event benefit achievement rate. The percentage of times a link is used. If this percentage remains consistently low (e.g., below 20%), it indicates that the link is becoming inefficient or unreliable.

[0091] Therefore, when the data describing synergistic benefits is consistently below the set value, the system detects that the average synergistic benefit value of a certain synergistic control link is consistently below zero (or another set negative threshold), or its benefit achievement rate is consistently below a certain minimum acceptable level. This means that the link not only cannot currently generate effective benefits, but its historical performance also proves its poor quality. Therefore, the system will automatically disconnect the link to optimize the overall resource allocation of the synergistic network.

[0092] If a system is not used for an extended period (exceeding a preset duration) or if synergy benefit data indicates that its recent performance has been consistently poor (below another set value), it will be automatically deactivated even if its synergy strength parameter has not dropped to the deactivation threshold.

[0093] Furthermore, the unused time reaches the preset duration: the preset duration is set according to the daily coordination frequency of the power grid (e.g., 3 days). If the link is not activated for 3 consecutive days, it means that the corresponding capacity and demand matching relationship is no longer suitable for the current power grid operating conditions, and it is judged as an inefficient link.

[0094] Synergy benefit data consistently falls below the set value: The set value is determined based on the principle that benefits ≥ costs (e.g., average). If the average of three consecutive statistical periods of the collaborative control link If all values ​​are below this value, it indicates that the benefits of collaborative behavior are less than the costs, and the link is judged as a negative benefit link.

[0095] Release operation logic: First, set the coordination strength parameter of the coordination control link. Reduce the priority to 0 (eliminate its association priority), then disconnect the virtual association between electrical devices to complete the link release and avoid system disturbances caused by direct disconnection.

[0096] At the same time, all electrical devices will periodically (e.g., at set times) rebroadcast their capability description data and demand description data, continuously explore new potential partners, and establish new collaborative control links with those that meet the matching criteria, thereby realizing the metabolism and self-organization of the network.

[0097] The set of control strategies for electrical equipment is optimized and updated according to a preset time cycle.

[0098] Furthermore, the optimization updates are not performed in real time, but rather on a schedule (such as once a day) or triggered by specific events, which is called a preset time period.

[0099] Specifically, the optimization update includes: statistically analyzing the operating indicators and synergistic benefits of electrical equipment within a preset time period.

[0100] Furthermore, the operational index data consists of real-time electrical quantity data of the collected electrical equipment within the cycle, including but not limited to voltage, frequency, active power, reactive power, and survival pressure calculated based on these data.

[0101] The collaborative benefit data is based on the control benefit value calculation formula, which is the comprehensive benefit value of all collaborative behaviors of the equipment within the statistical period. The comprehensive benefit value includes the single benefit value, the average benefit value, and the total benefit value.

[0102] Collaborative benefit data is evaluated based on all collaborative behaviors involving equipment within a preset statistical period. Its core is the control benefit value generated by each collaboration (i.e., single-event value). Multi-dimensional statistical and fusion analysis is performed. The specific logic is as follows: The single-event benefit value refers to the control benefit value calculated in each collaborative event. It serves as the basic unit for benefit evaluation, used to determine the effectiveness of a single collaboration in real time, and as the basis for updating the collaboration strength parameter.

[0103] The total benefit value is the sum of all effective single control benefit values ​​within the statistical period. It is used to measure the total benefit that the equipment brings to the system through collaboration within the period from the perspective of overall contribution, reflecting the overall scale of its collaborative behavior.

[0104] The average benefit value is the arithmetic mean of the single control benefit values ​​within the statistical period. It is used to evaluate the benefit level of each equipment collaboration from the perspective of average efficiency, reflecting the stability and efficiency of collaboration quality.

[0105] Single-event benefit values, average benefit values, and total benefit values ​​are integrated and work together in the performance evaluation process: the total value reflects the quantity of collaboration, the average value reveals the quality of collaboration, and the set of all single-event values ​​provides raw data support for calculation and analysis. By comprehensively considering the above indicators, the system comprehensively evaluates the effectiveness of equipment collaboration strategies. For example, high total values ​​and high average values ​​are considered efficient strategies, while high total values ​​and low average values ​​are considered high-frequency and inefficient modes, thereby achieving precise optimization of control strategies.

[0106] The performance of the control strategy set is evaluated based on operational indicator data and synergistic benefit data.

[0107] The set of control strategies is screened and parameters are optimized based on the performance evaluation results.

[0108] At the end of each preset time period, this technical solution will summarize the performance of each control strategy set in two dimensions: Operational metrics data: These reflect the optimization effect of the strategy on the equipment's own operating status, such as whether the average voltage deviation is small.

[0109] The operational metrics are centered on survival pressure, and the calculation period is based on the equipment's performance. The average value (the lower the value, the more stable the equipment operation is due to the set of control strategies) is combined with auxiliary indicators such as voltage deviation rate and power fluctuation amplitude to judge the control effect of the control strategy on the equipment's own operating status.

[0110] Collaboration benefit data: This reflects the contribution and benefits of a strategy in collaborative interactions, such as the number of successful request responses and total benefits. Strategies are then comprehensively scored and ranked based on this data.

[0111] Synergistic benefits are measured by the overall benefit value within the period and the single benefit value. Compliance rate ( The core of the assessment is the percentage of times the control strategy set is used to determine the profitability of the control strategy set in the process of collaboration between the equipment and other equipment. The higher the comprehensive benefit value and the higher the compliance rate, the better the collaboration effect.

[0112] Specifically, the screening and parameter optimization include: removing the control strategy set that ranks last in the performance evaluation results.

[0113] Perform parameter reorganization on the set of control strategies that rank highly in the performance evaluation results.

[0114] Random parameters are adjusted on the reorganized set of control strategies.

[0115] Filtering (removal) is a control strategy that simulates natural selection and directly eliminates the lowest-ranking and poorly performing components.

[0116] The screening process ranks the control strategy sets of the same type of electrical equipment (such as high-voltage circuit breakers and photovoltaic inverters) according to the comprehensive performance score, eliminates the inefficient strategies at the bottom of the ranking, eliminates the inefficient strategies in the bottom 20% of the ranking, and retains the efficient strategies in the top 80% of the ranking, so as to ensure that the retained strategies have good operational stability and synergistic benefit capabilities.

[0117] Parameter recombination (cross-combination) involves mixing the top-ranked, high-performance control strategies and cross-combining their control parameters to generate a new set of strategies.

[0118] In the retained set of efficient strategies, two sets are randomly selected and their core control parameters, such as reactive power output curves, action delay thresholds, and power regulation sensitivity, are cross-exchanged. For example, the reactive power output curve of strategy A and the action delay threshold of strategy B are recombined to generate a new set of strategies that take into account the advantages of both.

[0119] Random parameter adjustment (mutation) involves introducing low-probability random adjustments to the recombined new strategy set and the retained efficient strategy set. This involves fine-tuning the values ​​of one or two control parameters, such as adjusting the power regulation sensitivity from 0.8 to 0.85. This prevents the strategy from getting trapped in local optima and improves its adaptability to grid changes. By randomly changing some parameter values ​​with a low probability, diversity is introduced, new possible solutions are explored, and the algorithm avoids getting trapped in local optima.

[0120] Based on the above-described method for coordinated control of high and low voltage electrical equipment, this technical solution also provides a coordinated control system for high and low voltage electrical equipment, including: Device control agents are deployed on each electrical device to manage sets of control policies, capability description data, requirement description data, and collaborative control links, and to execute local control decisions.

[0121] The device control agent is the core software module that grants autonomy to each electrical device. It is responsible for maintaining all local data (policies, capabilities, requirements, links) and independently completing all local control decisions, including status assessment, request initiation, response calculation, and decision-making.

[0122] Furthermore, this technical solution performs a closed-loop operation of statistics, evaluation, and optimization based on historical data uploaded by the equipment control agent. First, it statistically analyzes the operation and coordination data of electrical equipment; then, it quantitatively evaluates the performance of the strategies; finally, it filters out inefficient strategies and generates better ones. The core relies on the calculation of control benefit values ​​combined with formulas to quantify the collaborative benefits, ensuring that the optimization results possess both operational stability and collaborative benefits.

[0123] An optimization processing engine is used to perform optimization and update operations on the set of control strategies according to a preset time period.

[0124] The optimization processing engine is a module responsible for macro-level optimization. It is not in the real-time control loop, but is triggered periodically, and is specifically responsible for performing optimization and update operations on the entire set of device control strategies, namely performance evaluation, filtering, reorganization, and mutation.

[0125] The optimized set of superior control strategies is distributed to the corresponding types of electrical equipment (e.g., the optimized photovoltaic inverter strategy is distributed to all photovoltaic equipment) to guide the equipment control agent to update the local strategy.

[0126] The operation status monitoring module is used to collect operation status data of electrical equipment.

[0127] The operation status monitoring module is responsible for collecting various operation status data from the power grid, such as voltage, current, and power, to provide data support for performance evaluation of the optimization processing engine. It can also be used for system-level monitoring and analysis.

[0128] The operation status monitoring module transmits the collected data to the optimization processing engine in real time, providing basic data for the performance evaluation of the control strategy set. Simultaneously, it monitors the usage status and effectiveness data of the collaborative control links. When it detects that a link has been inactive for an extended period or its effectiveness remains below a set value, it sends a prompt to the device control agent to assist in triggering a link termination operation.

[0129] In a specific embodiment, within a distribution network area, control strategy sets, capacity description data, and demand description data are established for a photovoltaic inverter and a high-voltage circuit breaker, respectively. System calculations reveal that the "reactive power regulation capability" in the photovoltaic inverter's capacity description data and the "voltage stability demand" in the high-voltage circuit breaker's demand description data have a high degree of matching, exceeding a preset matching threshold. Therefore, a cooperative control link is established between the two, and a cooperative strength parameter is initialized for it.

[0130] When the high-voltage circuit breaker detects that its node voltage, an operating indicator, exceeds the normal range, it initiates a control request to the photovoltaic inverter through this coordinated control link. Based on the request, the photovoltaic inverter assesses the resources required to execute the supporting action and, considering the control cost attached to the request, calculates that the control benefit value is positive and exceeds a preset benefit threshold. Therefore, the photovoltaic inverter performs calculations based on its local control strategy set, generates a control response containing specific reactive power output adjustments, and sends it back to the high-voltage circuit breaker.

[0131] After the high-voltage circuit breaker executed this control response, the node voltage returned to normal. The system calculated the collaborative benefit value based on the actual effect of this coordinated control operation and adjusted the collaborative strength parameter of the collaborative control link accordingly. After a preset time period, the system collected operational index data and collaborative benefit data for all electrical equipment in the area. Based on this, it evaluated the performance of their control strategy sets, removed the lowest-ranked control strategy set, and reorganized and randomly adjusted the parameters of the top-ranked sets, completing the optimization update. Simultaneously, the system continuously performed dynamic maintenance on the collaborative control links, disconnecting another long-unused link and establishing a new collaborative control link for a newly connected energy storage device through periodic data exchange.

[0132] This technical solution also provides an electronic device, the electronic device comprising: a processor, and a memory coupled to the processor, the memory being used to store a computer program; and the processor being used to execute the computer program stored in the memory, so that the electronic device performs the high and low voltage electrical equipment coordinated control method.

[0133] This technical solution also provides a computer-readable storage medium, which includes a computer program or instructions that, when executed on a computer, cause the computer to perform the high- and low-voltage electrical equipment coordinated control method.

[0134] Although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art can still modify the technical solutions described in the foregoing embodiments or make equivalent substitutions for some of the technical features. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of the present invention should be included within the protection scope of the present invention.

Claims

1. A method for coordinated control of high and low voltage electrical equipment, characterized in that, include: For each electrical device, establish a set of control strategies, capability description data, and demand description data, including control parameters. The capability description data includes the type and intensity of collaborative support that the electrical device can provide, and the demand description data includes the type and intensity of external collaborative support that the electrical device needs. For two electrical appliances, calculate the functional fit between the capability description data of one electrical appliance and the demand description data of the other electrical appliance in the corresponding dimensions, and calculate the electrical correlation between the two electrical appliances through the nodal impedance matrix; The matching degree between the two electrical devices is obtained by weighting and summing the functional compatibility and electrical correlation. When the matching degree exceeds a preset matching threshold, a collaborative control link is established between the two corresponding electrical devices, and the collaborative strength parameter of the collaborative control link is initialized according to the matching degree. When the electrical device initiating the request detects that its own operating indicators exceed the preset threshold range, it initiates a control request to the associated collaborative device based on the collaborative control link; The associated collaborative device assesses the resource consumption for executing the supporting action based on its current operating status, and calculates the control benefit value based on the control cost in the control request and the collaboration strength parameter; When the control benefit value exceeds the preset benefit threshold, the associated collaborative device generates a control response containing control parameter adjustment values ​​based on the locally preset control strategy set, and sends the control response back to the electrical device that initiated the request; The electrical device that initiates the request performs a coordinated control operation based on the control response, calculates a collaborative benefit value based on the degree of recovery of the operating indicators after the coordinated control operation, and adjusts the collaborative strength parameter of the coordinated control link based on the collaborative benefit value. The set of control strategies for electrical equipment is optimized and updated according to a preset time cycle.

2. The method for coordinated control of high and low voltage electrical equipment according to claim 1, characterized in that, The calculation of the control benefit value includes a quantitative assessment of direct and indirect benefits, wherein the direct benefits come from the control costs in the control request, and the indirect benefits come from the expected improvement of the synergy strength parameter; The control costs corresponding to the resource consumption include at least one of the following: power consumption cost, equipment lifespan loss cost, communication resource consumption cost, and computing resource consumption cost.

3. The method for coordinated control of high and low voltage electrical equipment according to claim 1, characterized in that, The optimization and updating of the control strategy set for electrical equipment according to a preset time period includes: Statistical analysis of the operating indicators and synergistic benefits of electrical equipment within a preset time period; The performance of the control strategy set is evaluated based on the operational indicator data and the synergistic benefit data. The set of control strategies is screened and parameters are optimized based on the performance evaluation results.

4. The method for coordinated control of high and low voltage electrical equipment according to claim 3, characterized in that, The process of filtering and optimizing the control strategy set based on performance evaluation results includes: Remove the control policy set that ranks last in the performance evaluation results; Perform parameter reorganization on the set of control strategies that rank high in the performance evaluation results; Random parameters are adjusted on the reorganized set of control strategies.

5. The method for coordinated control of high and low voltage electrical equipment according to claim 1, characterized in that, It also includes dynamic maintenance of the collaborative control links: Monitor the usage status and collaborative benefit data of each collaborative control link; When the unused time of the collaborative control link reaches the preset duration or the collaborative benefit data continues to be lower than the set value, the collaborative control link is terminated. Electrical equipment establishes new collaborative control links through periodic data exchange.

6. The method for coordinated control of high and low voltage electrical equipment according to claim 5, characterized in that, The functional fit is determined based on the coverage relationship between the capability description data and the demand description data in corresponding dimensions. The corresponding dimensions include at least one of the dimensions corresponding to voltage regulation capability and voltage stability demand, and the dimensions corresponding to power support capability and power supplementation demand.

7. The method for coordinated control of high and low voltage electrical equipment according to claim 6, characterized in that, The electrical correlation degree is calculated using the node impedance matrix. The smaller the impedance between two electrical devices, the higher the electrical correlation degree.

8. A coordinated control system for high and low voltage electrical equipment, characterized in that, include: The device control agent is deployed on each electrical device to manage a set of control strategies, capability description data, requirement description data, and collaborative control links containing control parameters. The capability description data includes the type and strength of collaborative support that the electrical device can provide, and the requirement description data includes the type and strength of external collaborative support that the electrical device needs. The link establishment module is used to calculate the functional fit between the capability description data of one electrical appliance and the demand description data of the other electrical appliance in the corresponding dimension for two electrical appliances, and to calculate the electrical correlation between the two electrical appliances through the node impedance matrix. The functional fit and the electrical correlation are weighted and combined to obtain the matching degree between the two electrical appliances. When the matching degree exceeds the preset matching threshold, a collaborative control link is established between the two electrical appliances, and the collaborative strength parameter of the collaborative control link is initialized according to the matching degree. The operation status monitoring module is used to collect the operation status data of electrical equipment, and when the electrical equipment that initiated the request detects that its own operation indicators exceed the preset threshold range, it triggers the electrical equipment that initiated the request to send a control request to the associated collaborative equipment based on the collaborative control link. The request-response module is used to enable the associated collaborative device to assess the resource consumption of performing the supporting action based on its current operating status, and to calculate the control benefit value based on the control cost in the control request and the collaboration strength parameter. When the control benefit value exceeds the preset benefit threshold, a control response containing the control parameter adjustment value is generated based on the locally preset control strategy set, and the control response is sent back to the electrical device that initiated the request. The benefit update module is used to enable the electrical equipment that initiated the request to perform coordinated control operations according to the control response, calculate the coordinated benefit value based on the degree of recovery of the operating indicators after the coordinated control operation, and adjust the coordinated strength parameter of the coordinated control link based on the coordinated benefit value. An optimization processing engine is used to optimize and update the set of control strategies for electrical equipment according to a preset time cycle.

9. An electronic device, characterized in that, include: A processor, and a memory coupled to the processor, the memory being used to store computer programs; The processor is configured to execute the computer program stored in the memory, such that the electronic device performs the high- and low-voltage electrical equipment coordinated control method as described in any one of claims 1-7.

10. A computer-readable storage medium, characterized in that, The computer-readable storage medium includes a computer program or instructions that, when executed on a computer, cause the computer to perform the high- and low-voltage electrical equipment coordinated control method as described in any one of claims 1-7.

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