Electricity utilization control method and device, computer device, readable storage medium and program product

Abstract

This application relates to an electricity control method, apparatus, computer equipment, computer-readable storage medium, and computer program product. It includes: receiving an activation plan package from a cloud-based energy management system; collecting multi-source electrical data and device status data from each controlled terminal within the home's electricity system; generating evaluation data based on the multi-source electrical data and device status data; performing a composite event trigger determination based on segmented constraint parameters and the evaluation data; generating a trigger signal; determining the power limits of charging piles with distribution authority based on the trigger signal; converting the power limits into a current limit sequence recognizable by the charging piles with distribution authority; performing differential processing on the current limit sequence to generate a charging strategy message; and sending the charging strategy message to the charging piles with distribution authority. This method enables layered collaborative control between the cloud and edge to enhance the autonomous decision-making capabilities of the home edge.

Description

Technical Field

[0001] This application relates to the field of power system technology, and in particular to an electricity control method, apparatus, computer equipment, computer-readable storage medium, and computer program product. Background Technology

[0002] With the integrated development of distributed energy technology, energy storage technology, and electric vehicle charging technology, the large-scale deployment of residential photovoltaic (PV) systems, home energy storage, and AC charging piles has become a trend. Home-side power systems are gradually forming a multi-source coupled operation pattern of PV, energy storage, and charging, possessing multiple functions of energy production, storage, and consumption, and becoming an important component of the smart grid's user side. The operation of home-side power systems is affected by multiple factors, including the intermittency of PV output, the randomness of base load, and the uncertainty of electric vehicle charging demand. Furthermore, there are rigid limitations on the capacity of the household's incoming power and the power supply capacity of the transformer substation. Without an effective power coordination and control mechanism, problems such as incoming power overload, grid tripping, and power quality degradation can easily occur. Therefore, the coordinated control of PV, energy storage, and charging piles has become a core requirement for home energy management.

[0003] In traditional technologies, the coordinated control of photovoltaic, energy storage, and charging on the home side is mostly dominated by a cloud-based energy management system. This system periodically sends high-frequency charging power curves or OCPP (Open Charge Point Protocol) charging strategy commands to the charging piles via public network links. The cloud then generates a refined charging control plan based on time-of-use pricing, load forecasting, and photovoltaic forecasting results, directly executing second-level / minute-level closed-loop power control on the charging piles. However, this management approach has shortcomings in engineering applications. The boundaries of the cloud-based energy management system's control responsibilities are unclear, and the home-side edge control terminal lacks autonomous decision-making and safety limit capabilities. When cloud communication is interrupted or policy updates are delayed, situations can easily arise where charging pile policy versions are inconsistent or no effective policies are available for execution. Furthermore, it cannot effectively mitigate the risk of incoming line overload and is difficult to adapt to the real-time operational needs of the home's power system. Summary of the Invention

[0004] Based on this, it is necessary to provide a power control method, device, computer equipment, computer-readable storage medium, and computer program product that can realize cloud-edge layered collaborative management and control to enhance the autonomous decision-making capabilities of the home edge.

[0005] In a first aspect, this application provides an electricity control method, comprising:

[0006] Receive activation plan packages from the cloud-based energy management system; the activation plan package includes segmented constraint parameters and plan version number;

[0007] Collect multi-source electrical data and equipment status data generated by each controlled terminal in the household power system during operation, and generate evaluation data based on the multi-source electrical data and equipment status data;

[0008] Based on segmented constraint parameters and evaluation data, a composite event trigger determination is performed to generate a trigger signal. Based on the trigger signal, the charging pile with the authority to issue the signal is determined.

[0009] Based on segmented constraint parameters and evaluation data, the power limit of the charging pile with the authority to issue the limit is determined. Based on the type of the charging pile with the authority to issue the limit, the power limit is converted into a current limit sequence that the charging pile with the authority to issue the limit can recognize.

[0010] The current limit sequence is differentially processed to generate a charging strategy message, which carries a charging strategy version number that maps to the plan version number.

[0011] Send charging strategy messages to charging piles with the authority to issue them.

[0012] In one embodiment, based on the segmented constraint parameters and evaluation data, a composite event triggering determination is performed to generate a trigger signal, including:

[0013] Based on the segmented incoming power upper limit, segmented electric vehicle total power budget, real-time incoming power, and real-time total charging power of the charging pile in the segmented constraint parameters, the real-time deviation of the incoming power and the real-time deviation of the electric vehicle charging budget are calculated. Pre-set filtering processing is performed on the real-time deviation of the incoming power and the real-time deviation of the electric vehicle charging budget to obtain a steady-state deviation value that eliminates instantaneous measurement spikes and random noise. If the steady-state deviation value and the evaluation data meet the target composite triggering criterion, a trigger signal is generated. The target composite triggering criterion is at least one of the following: deviation threshold triggering criterion, over-limit risk warning triggering criterion, equipment status event triggering criterion, planned synchronization triggering criterion, and link recovery triggering criterion.

[0014] In one embodiment, determining the charging pile with issuing authority based on a trigger signal includes:

[0015] Based on the evaluation data and preset basic access conditions, charging piles to be verified are selected from a preset number of charging piles to be issued; preset issuance permission constraint verification is performed on the charging piles to be verified, and the charging piles to be verified that pass the issuance permission constraint verification are designated as charging piles with issuance permissions; if the charging pile to be verified fails any issuance permission constraint verification, it is determined that the charging pile to be verified that fails any issuance permission constraint verification does not have issuance permissions.

[0016] In one embodiment, based on evaluation data and preset basic access conditions, charging piles to be verified are selected from a preset pool of issued charging piles, including:

[0017] Based on the evaluation data, candidate charging piles that meet the preset basic access conditions are selected from a plurality of preset charging piles. If the trigger event type corresponding to the trigger signal is a planned synchronization trigger or a link recovery trigger, a full coverage rule is adopted, and each candidate charging pile is used as a charging pile to be verified. If the trigger event type corresponding to the trigger signal is a deviation threshold trigger or an over-limit risk warning trigger, a deviation contribution screening rule is adopted to calculate the contribution ratio of each candidate charging pile to the total charging power deviation, and the candidate charging piles whose contribution ratio is not less than the preset minimum contribution threshold are used as charging piles to be verified. If the trigger event type is an equipment status event trigger, a single-pile directional coverage rule is adopted, and only candidate charging piles with equipment status changes are used as charging piles to be verified.

[0018] In one embodiment, based on segmented constraint parameters and evaluation data, the power limit of the charging pile with issuing authority is determined, including:

[0019] Based on the segmented incoming power upper limit and segmented total power budget of electric vehicles in the activation plan package, the hard constraint boundary for power limit calculation is determined. Based on the real-time household base load power, real-time photovoltaic output power, real-time energy storage charging and discharging power, and real-time incoming power measurement data, combined with the hard constraint boundary and preset incoming safety margin, an available power budget for electric vehicle charging is generated. If there is only one charging pile with the authority to issue power limits, the available power budget for electric vehicle charging is subject to upper and lower limits based on the rated maximum power of the charging pile with the authority to issue power limits and the hard constraint boundary, resulting in a power limit. If there are multiple charging piles with the authority to issue power limits, the available power budget for electric vehicle charging is subject to upper and lower limits based on the sum of the rated maximum power of all charging piles with the authority to issue power limits and the hard constraint boundary, resulting in a compliant power budget. Based on preset power allocation rules, the compliant power budget is allocated to each charging pile with the authority to issue power limits, resulting in a power limit for each charging pile with the authority to issue power limits.

[0020] In one embodiment, the current limit sequence is differentially processed to generate a charging strategy message, including:

[0021] A preset shaping process is performed on the current limit sequence to obtain a shaped current limit sequence. The preset shaping process includes at least one of amplitude limiting, quantization, and minimum duration merging. A set of change points is extracted from the shaped current limit sequence. The set of change points includes the starting point of the current limit sequence and the times when all current limits change and their corresponding limit values. The set of change points is then compressed based on a preset current tolerance threshold to generate a compressed set of change points. Based on the compressed set of change points and the charging strategy version number mapped to the plan version number of the activation plan package, a charging strategy message is generated.

[0022] Secondly, this application also provides an electrical control device, comprising:

[0023] The receiving module is used to receive activation plan packages issued by the cloud-based energy management system; the activation plan package includes segmented constraint parameters and plan version number;

[0024] The data acquisition module is used to collect multi-source electrical data and equipment status data generated by each controlled terminal in the household power system during operation, and to generate evaluation data based on the multi-source electrical data and equipment status data;

[0025] The determination module is used to perform compound event trigger determination based on segmented constraint parameters and evaluation data, generate trigger signals, and determine the charging piles with the authority to issue the signal based on the trigger signals.

[0026] The conversion module is used to determine the power limit of the charging pile with the authority to issue the power limit based on the segmented constraint parameters and evaluation data, and to convert the power limit into a current limit sequence that the charging pile with the authority to issue the power limit can recognize based on the type of the charging pile with the authority to issue the power limit.

[0027] The processing module is used to perform differential processing on the current limit sequence and generate a charging strategy message. The charging strategy message carries a charging strategy version number that is mapped to the plan version number.

[0028] The sending module is used to send charging strategy messages to charging piles with the authority to send them.

[0029] Thirdly, this application also provides a computer device, including a memory and a processor, wherein the memory stores a computer program, and the processor executes the computer program to perform the following steps:

[0030] Receive activation plan packages from the cloud-based energy management system; the activation plan package includes segmented constraint parameters and plan version number;

[0031] Collect multi-source electrical data and equipment status data generated by each controlled terminal in the household power system during operation, and generate evaluation data based on the multi-source electrical data and equipment status data;

[0032] Based on segmented constraint parameters and evaluation data, a composite event trigger determination is performed to generate a trigger signal. Based on the trigger signal, the charging pile with the authority to issue the signal is determined.

[0033] Based on segmented constraint parameters and evaluation data, the power limit of the charging pile with the authority to issue the limit is determined. Based on the type of the charging pile with the authority to issue the limit, the power limit is converted into a current limit sequence that the charging pile with the authority to issue the limit can recognize.

[0034] The current limit sequence is differentially processed to generate a charging strategy message, which carries a charging strategy version number that maps to the plan version number.

[0035] Send charging strategy messages to charging piles with the authority to issue them.

[0036] Fourthly, this application also provides a computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, performs the following steps:

[0037] Receive activation plan packages from the cloud-based energy management system; the activation plan package includes segmented constraint parameters and plan version number;

[0038] Collect multi-source electrical data and equipment status data generated by each controlled terminal in the household power system during operation, and generate evaluation data based on the multi-source electrical data and equipment status data;

[0039] Based on segmented constraint parameters and evaluation data, a composite event trigger determination is performed to generate a trigger signal. Based on the trigger signal, the charging pile with the authority to issue the signal is determined.

[0040] Based on segmented constraint parameters and evaluation data, the power limit of the charging pile with the authority to issue the limit is determined. Based on the type of the charging pile with the authority to issue the limit, the power limit is converted into a current limit sequence that the charging pile with the authority to issue the limit can recognize.

[0041] The current limit sequence is differentially processed to generate a charging strategy message, which carries a charging strategy version number that maps to the plan version number.

[0042] Send charging strategy messages to charging piles with the authority to issue them.

[0043] Fifthly, this application also provides a computer program product, including a computer program that, when executed by a processor, performs the following steps:

[0044] Receive activation plan packages from the cloud-based energy management system; the activation plan package includes segmented constraint parameters and plan version number;

[0045] Collect multi-source electrical data and equipment status data generated by each controlled terminal in the household power system during operation, and generate evaluation data based on the multi-source electrical data and equipment status data;

[0046] Based on segmented constraint parameters and evaluation data, a composite event trigger determination is performed to generate a trigger signal. Based on the trigger signal, the charging pile with the authority to issue the signal is determined.

[0047] Based on segmented constraint parameters and evaluation data, the power limit of the charging pile with the authority to issue the limit is determined. Based on the type of the charging pile with the authority to issue the limit, the power limit is converted into a current limit sequence that the charging pile with the authority to issue the limit can recognize.

[0048] The current limit sequence is differentially processed to generate a charging strategy message, which carries a charging strategy version number that maps to the plan version number.

[0049] Send charging strategy messages to charging piles with the authority to issue them.

[0050] The aforementioned power control method, device, computer equipment, computer-readable storage medium, and computer program product receive an activation plan package from a cloud-based energy management system. The activation plan package includes segmented constraint parameters and a plan version number. It collects multi-source electrical data and equipment status data generated by each controlled terminal within the household power system during operation, and generates evaluation data based on this data. Based on the segmented constraint parameters and evaluation data, it performs a composite event trigger determination, generates a trigger signal, and identifies charging piles with distribution authority based on the trigger signal. Based on the segmented constraint parameters and evaluation data, it determines the power limit of the charging piles with distribution authority, and converts the power limit into a current limit sequence recognizable by the charging piles with distribution authority based on the type of the charging piles. It performs differential processing on the current limit sequence to generate a charging strategy message, which carries a charging strategy version number mapped to the plan version number. Finally, it distributes the charging strategy message to the charging piles with distribution authority. This application employs a three-layer collaborative architecture of cloud, edge, and charging pile, which integrates cloud-based activation plan packages, edge-end autonomous control through compound event-triggered judgment, and precise execution of differentiated charging strategies at the charging pile end. Combined with trigger-based charging pile permission filtering, standardized power-to-current limit conversion, current limit sequence differential compression processing, and a full-process technical approach of plan and strategy version number mapping, this architecture enables layered and decoupled control of home-side photovoltaic-storage-charging systems. It empowers the edge end with autonomous decision-making capabilities based on real-time operational data, enabling on-demand and precise distribution of charging strategies. This adapts to the multi-source coupling and variable operating states of home-side power systems. Furthermore, version number mapping ensures consistency in cloud-edge-charging strategy execution, resolving technical issues inherent in traditional cloud-based high-frequency dominant control models, such as uncertainty in strategy execution due to public network latency jitter, lack of autonomy at the edge due to blurred cloud-edge responsibilities, and chaotic strategy versions in scenarios of link failure / delay. This improves the real-time performance, robustness, and security of collaborative control of photovoltaic-storage-charging systems in home-side power systems. Attached Figure Description

[0051] To more clearly illustrate the technical solutions in the embodiments of this application or related technologies, the drawings used in the description of the embodiments of this application or related technologies will be briefly introduced below. Obviously, the drawings described below are only some embodiments of this application. For those skilled in the art, other related drawings can be obtained based on these drawings without creative effort.

[0052] Figure 1 This is an application environment diagram of the power control method in one embodiment;

[0053] Figure 2 This is a flowchart illustrating an electrical control method in one embodiment;

[0054] Figure 3 This is a structural block diagram of the power control device in one embodiment;

[0055] Figure 4 This is an internal structural diagram of a computer device in one embodiment. Detailed Implementation

[0056] To make the objectives, technical solutions, and advantages of this application clearer, the following detailed description is provided in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative and not intended to limit the scope of this application.

[0057] The power control method provided in this application embodiment can be applied to, for example, Figure 1In the application environment shown, the controlled terminal 106 communicates with the home-side edge control terminal 104 via a network, and the cloud-based energy management system 102 also communicates with the home-side edge control terminal 104 via a network. The data storage system can store the data that the home-side edge control terminal 104 needs to process. The data storage system can be integrated onto the home-side edge control terminal 104, or it can be located in the cloud or on other network servers. The home-side edge control terminal 104 receives an activation plan package from the cloud-based energy management system 102. The activation plan package includes segmented constraint parameters and a plan version number. It collects multi-source electrical data and device status data generated by each controlled terminal 106 within the home-side power system during operation, and generates evaluation data based on the multi-source electrical data and device status data. Based on the segmented constraint parameters and evaluation data, it performs a composite event trigger determination, generates a trigger signal, and determines the charging pile with the authority to issue the plan. Based on the segmented constraint parameters and evaluation data, it determines the power limit of the charging pile with the authority to issue the plan, and converts the power limit into a current limit sequence that the charging pile with the authority to issue the plan can recognize based on the type of the charging pile with the authority to issue the plan. It performs differential processing on the current limit sequence to generate a charging strategy message, which carries a charging strategy version number mapped to the plan version number. It then issues the charging strategy message to the charging pile with the authority to issue the plan.

[0058] In one exemplary embodiment, such as Figure 2 As shown, an electricity control method is provided, which is applied to... Figure 1 Taking the home-side edge control terminal 104 as an example, the explanation includes the following steps 202 to 212. Wherein:

[0059] Step 202: Receive the activation plan package from the cloud energy management system; the activation plan package includes segmented constraint parameters and plan version number.

[0060] Among them, the segmented constraint parameters are hard constraint boundaries provided by the edge end (home-side edge control end) for power calculation. They are used to determine whether the incoming power exceeds the limit and to allocate the total charging power limit for the charging pile. They are the core basis for compound event triggering judgment and power limit calculation. The plan version number is used to uniquely identify the current control plan issued by the cloud (cloud energy management system). Version mapping and binding are performed when generating charging policy messages to ensure that the policy version is consistent between the cloud and the edge, avoiding policy confusion due to plan updates and communication delays. It also serves as the version identification basis for plan validity verification and abnormal security policy switching.

[0061] Optionally, in addition to the segmented constraint parameters and the plan version number, the activation plan package also includes: the plan effective start time, the plan expiration end time, the upper limit of the rated power of the household incoming line, the segmented budget envelope of the total charging power of electric vehicles, the base load forecast value, the photovoltaic output forecast range, and the integrity check code.

[0062] The activation plan package is generated by the cloud-based energy management system 102 and sent to the home-side edge control terminal 104. The generation process is as follows: The cloud-based energy management system 102 first collects the basic configuration parameters of the home-side power system (including the physical rated power of the home's incoming line, the power supply capacity of the transformer substation, the rated power and number of connected charging piles, the photovoltaic installed capacity, and the rated capacity of energy storage, etc.). Simultaneously, it combines regional power grid dispatch requirements, time-of-use pricing policies, photovoltaic output forecast data for future preset time periods (e.g., 24 hours), home basic load forecast data, and electric vehicle charging demand statistics to determine the control and constraint standards for each time segment. Based on these control and constraint standards, it generates segmented constraint parameters and a plan version number, and packages them into an activation package. The plan package includes segmented constraint parameters, such as the upper limit of incoming power for each time segment and the total power budget of electric vehicles for each segment. The plan version number is used to uniquely identify the activated plan package, which facilitates the home-side edge control terminal 104 to associate and match the corresponding charging strategy version, ensuring the consistency of cloud and edge strategies. After the activated plan package is generated, the cloud energy management system 102 sends it to the home-side edge control terminal 104 through the public network link. It will also periodically update the activated plan package and resend it according to grid dispatch adjustments, home configuration changes, or forecast data updates, to ensure the timeliness and adaptability of the segmented constraint parameters.

[0063] Furthermore, when the activation plan package is sent from the cloud energy management system 102 to the home edge control terminal 104, reliable delivery and version consistency control are performed. The specific process includes: 1. Pre-delivery preparation: The cloud energy management system 102 first performs integrity verification on the activation plan package, confirming that core information such as segment constraint parameters, plan version number, effective / expiration time, and integrity check code are complete and unaltered. Then, the plan package is encrypted (using a symmetric encryption algorithm), and a unique delivery identifier is generated, associated with the plan version information, to ensure the integrity and security of the plan package. The version number and distribution time of the plan package are recorded simultaneously to form a delivery list for easy traceability later. 2. Transmission process control: The TCP protocol (Transmission Control Protocol) is used for data transmission to establish a stable transmission connection. The data transmission status is monitored in real time during transmission. If data packet loss, transmission timeout, or other anomalies occur, a retransmission mechanism is immediately triggered to ensure that every data packet is delivered accurately. At the same time, version verification information is embedded during transmission to compare the plan versions on the cloud and edge terminals in real time to avoid version inconsistencies. 3. Receiver Verification: After receiving the plan package, the home-side edge control terminal 104 first verifies the integrity of the data packet (checking if it matches the verification code sent from the cloud). Simultaneously, it verifies if the plan version number and activation / deactivation time match those in the cloud. If verification fails, it immediately reports back to the cloud, triggering a retransmission. If verification passes, it records the plan package version, activation time, and other information, completing the reception confirmation. 4. Version Consistency Maintenance: After receiving the plan package, the edge terminal compares the version information in the plan package with the locally stored plan version. If a version difference exists, it immediately reports back to the cloud, synchronously updating the local plan version to ensure consistency between the edge terminal and the cloud's plan versions. It also periodically reports the plan package reception status to the cloud, allowing the cloud to monitor transmission effectiveness in real time and adjust the delivery strategy accordingly. 5. Anomaly Handling Mechanism: If network interruption or data packet corruption occurs during transmission, the cloud-based energy management system 102 detects the anomaly, suspends the current delivery, and regenerates the activation plan package based on the latest plan version after network recovery, prioritizing the accuracy of core constraint parameters before re-initiating transmission to ensure reliable delivery of the plan package.

[0064] Step 204: Collect multi-source electrical data and equipment status data generated by each controlled terminal in the household power system during operation, and generate evaluation data based on the multi-source electrical data and equipment status data.

[0065] Optionally, each controlled terminal includes all monitorable and controllable electricity-related equipment on the home side, specifically covering electric vehicle charging piles, residential photovoltaic inverters, home energy storage systems, smart incoming meters, and core power load equipment, etc., which are the core data sources for the coordinated management and control of photovoltaic, energy storage, and charging on the home side; multi-source electrical data are electrical parameters reflecting the operating conditions of each controlled terminal, mainly including: real-time charging power, charging current, charging voltage, and remaining charging time of charging piles; real-time output power and power generation efficiency of photovoltaic inverters; real-time charging and discharging power, remaining power, and charging and discharging status of energy storage systems; real-time incoming power, incoming voltage, and current of smart incoming meters; and real-time power of the home's basic load; equipment status data are discrete data reflecting the operating status of each controlled terminal, mainly including: the operating / shutdown status of each controlled terminal, fault alarm information (such as charging pile faults, photovoltaic inverter anomalies), communication link status, plug-in / plug-out status of charging piles, charging session start / stop status, and charging and discharging mode switching status of energy storage systems, etc.

[0066] During the data acquisition process, the home-side edge control terminal 104 synchronously collects multi-source electrical data and equipment status data from each controlled terminal through preset acquisition interfaces (such as OCPP communication interface and Modbus protocol interface) according to a preset acquisition cycle. During the acquisition process, obviously abnormal data (such as invalid data exceeding the reasonable range and instantaneous peak interference data) are filtered in real time. Subsequently, the collected raw data is standardized and preprocessed, including data cleaning (removing outliers and filling missing values), unit unification (converting the electrical parameters of different terminals into preset standard units), filtering and noise reduction (eliminating measurement noise and instantaneous fluctuations), and data normalization processing. Finally, evaluation data with a unified format, accurate data, and can be directly used for subsequent composite event triggering judgment and power limit calculation are generated to ensure the accuracy and reliability of subsequent control links.

[0067] Step 206: Based on the segmented constraint parameters and evaluation data, perform composite event trigger determination, generate trigger signals, and determine the charging piles with the authority to issue commands based on the trigger signals.

[0068] Among them, the composite event triggering judgment is to comprehensively judge multiple events such as power over-limit, load fluctuation, equipment status change, plan update, and communication status switch to determine whether the charging strategy needs to be updated; the trigger signal corresponds to different triggering types, including deviation threshold triggering, over-limit risk warning triggering, equipment status event triggering, plan synchronization triggering, and link recovery triggering.

[0069] Step 208: Based on the segmented constraint parameters and evaluation data, determine the power limit of the charging pile with the authority to issue the limit, and based on the type of the charging pile with the authority to issue the limit, convert the power limit into a current limit sequence that the charging pile with the authority to issue the limit can recognize.

[0070] The conversion process of the current limit sequence is adapted to the communication protocols and execution logic of different types of charging piles: First, the type of charging pile with the authority to issue the limit is identified (such as AC charging piles, DC charging piles, or charging piles that support the OCPP 1.6J / 2.0.1 protocol). Based on the rated voltage parameters of the charging pile (the rated voltage of the power grid for AC charging piles and the current output voltage for DC charging piles), the power limit is converted into a basic current limit value according to a preset electrical formula. Then, the minimum current adjustment step size and maximum current adjustment range of the charging pile are combined for quantification. Finally, a continuous current limit sequence is generated according to a preset time granularity to ensure that the sequence meets the hardware execution capabilities of the charging pile and the data format requirements of the OCPP protocol, and can be directly recognized and executed by the charging pile.

[0071] Step 210: Differential processing is performed on the current limit sequence to generate a charging strategy message. The charging strategy message carries a charging strategy version number that maps to the plan version number.

[0072] The core purpose of differential processing is to reduce the amount of message data and decrease the communication overhead of the OCPP protocol. The process of generating and binding the charging strategy version number is as follows: according to the preset encoding rules, the plan version number issued by the cloud is used as the core identifier, and the timestamp of this differential processing and the unique number of the charging pile are superimposed to generate a charging strategy version number that maps one-to-one with the plan version number. This version number will be embedded in the header field of the charging strategy message. On the one hand, it is used for version consistency verification between the edge terminal and the charging pile to ensure that the strategy executed by the charging pile matches the cloud plan. On the other hand, it facilitates subsequent strategy traceability and anomaly investigation.

[0073] Step 212: Send a charging strategy message to the charging pile with the authority to send the message.

[0074] The process of sending the policy message includes simultaneous message verification, timeout retransmission, and exception handling: if the charging pile returns a confirmation response within a preset time limit, the message sending is considered successful, and the policy version number and execution time are recorded; if communication timeout, message verification failure, or charging pile refusal to execute occurs, the retransmission mechanism is automatically activated, and the message is resent within a limited number of attempts; if multiple retransmissions still fail, the policy execution of the charging pile is marked as abnormal, a local alarm is triggered, and an exception log is retained for subsequent investigation. This reliable sending mechanism ensures that only charging piles with sending permissions can receive the corresponding charging policy message, achieving accurate, efficient, and safe charging control.

[0075] The aforementioned power control method receives an activation plan package from a cloud-based energy management system. The activation plan package includes segmented constraint parameters and a plan version number. It collects multi-source electrical data and equipment status data generated by each controlled terminal within the household power system during operation, and generates evaluation data based on this data. Based on the segmented constraint parameters and evaluation data, it performs a composite event trigger determination, generates a trigger signal, and identifies charging piles with distribution permissions based on the trigger signal. Based on the segmented constraint parameters and evaluation data, it determines the power limit of the charging piles with distribution permissions, and converts the power limit into a current limit sequence that the charging piles with distribution permissions can recognize, based on the type of the charging piles. It performs differential processing on the current limit sequence to generate a charging strategy message, which carries a charging strategy version number mapped to the plan version number. Finally, it distributes the charging strategy message to the charging piles with distribution permissions. This application employs a three-layer collaborative architecture of cloud, edge, and charging pile, which integrates cloud-based activation plan packages, edge-end autonomous control through compound event-triggered judgment, and precise execution of differentiated charging strategies at the charging pile end. Combined with trigger-based charging pile permission filtering, standardized power-to-current limit conversion, current limit sequence differential compression processing, and a full-process technical approach of plan and strategy version number mapping, this architecture enables layered and decoupled control of home-side photovoltaic-storage-charging systems. It empowers the edge end with autonomous decision-making capabilities based on real-time operational data, enabling on-demand and precise distribution of charging strategies. This adapts to the multi-source coupling and variable operating states of home-side power systems. Furthermore, version number mapping ensures consistency in cloud-edge-charging strategy execution, resolving technical issues inherent in traditional cloud-based high-frequency dominant control models, such as uncertainty in strategy execution due to public network latency jitter, lack of autonomy at the edge due to blurred cloud-edge responsibilities, and chaotic strategy versions in scenarios of link failure / delay. This improves the real-time performance, robustness, and security of collaborative control of photovoltaic-storage-charging systems in home-side power systems.

[0076] In an exemplary embodiment, based on segmented constraint parameters and evaluation data, a composite event trigger determination is performed to generate a trigger signal, including:

[0077] Based on the segmented incoming power upper limit, segmented electric vehicle total power budget, real-time incoming power, and real-time total charging power of the charging pile in the segmented constraint parameters, the real-time deviation of the incoming power and the real-time deviation of the electric vehicle charging budget are calculated. Pre-set filtering processing is performed on the real-time deviation of the incoming power and the real-time deviation of the electric vehicle charging budget to obtain a steady-state deviation value that eliminates instantaneous measurement spikes and random noise. If the steady-state deviation value and the evaluation data meet the target composite triggering criterion, a trigger signal is generated. The target composite triggering criterion is at least one of the following: deviation threshold triggering criterion, over-limit risk warning triggering criterion, equipment status event triggering criterion, planned synchronization triggering criterion, and link recovery triggering criterion.

[0078] For example, based on the current timestamp in the evaluation data, the segment index of the current plan segment is calculated by matching the segment step size within the activation plan package. Segment constraint parameters such as the segmented incoming power limit and the segmented total electric vehicle charging power budget corresponding to this plan segment are extracted. Simultaneously, out-of-bounds protection is applied to the index to ensure the validity of the constraint parameter reading. Then, based on the real-time active power of the household incoming line and the real-time total charging power of all charging piles in the evaluation data, the real-time deviation of the incoming power and the real-time deviation of the electric vehicle charging budget are calculated respectively. A real-time deviation of the incoming power greater than 0 indicates that the incoming power exceeds the limit and there is an overload risk. A real-time deviation of the electric vehicle charging budget greater than 0 indicates that the total charging power of the charging pile exceeds the budget. Finally, the real-time deviation of the incoming power and the electric vehicle charging budget are analyzed. The real-time budget deviation is processed by a preset exponential smoothing filter to obtain the corresponding steady-state deviation value. The filter eliminates deviation disturbances caused by instantaneous measurement spikes of the electricity meter and random noise in equipment communication. Then, the filtered steady-state deviation value is combined with the equipment status data, plan package version validity data, and communication link quality data in the evaluation data. The five composite triggering criteria of deviation threshold, over-limit risk warning, equipment status event, plan synchronization, and link recovery are matched and judged in sequence. If any one of the criteria is met, an event is triggered. If at least one of the five composite triggering criteria is met, a trigger signal for triggering the charging strategy update is immediately generated. If none of the criteria are met, no trigger signal is generated, and the current charging strategy of the charging pile remains unchanged.

[0079] The specific judgment rules for the five composite trigger criteria are as follows: Deviation threshold trigger criterion: The steady-state deviation value of the incoming power reaches a preset uplink protection threshold or is lower than a preset downlink release threshold, and the uplink protection threshold is less than the downlink release threshold. Over-limit risk warning trigger criterion: Based on the historical measurement values ​​of the incoming power in the evaluation data, the expected value and standard deviation of the incoming power in the next few evaluation periods are estimated through sliding window estimation, and the probability that the incoming power exceeds the upper limit of the corresponding planned segment in the future period reaches a preset probability threshold. Equipment status event trigger criterion: Detection of any charging pile undergoing a state switch of plugging in / unplugging, starting charging, or stopping charging, or an abnormal situation such as charging pile failure or continuous missing charging measurement data. Plan synchronization trigger criterion: The version number of the currently activated plan package is inconsistent with the version number bound to the issued charging strategy, or the remaining validity period of the plan package reaches a preset near-expiration threshold, or a switch occurs in the cross-plan package segment index at the current moment. Link recovery trigger criterion: Detection through communication link quality indicators that the communication link with the cloud energy management system or the OCPP communication link with the charging pile has recovered from a disconnected state to a normal connected state.

[0080] In this embodiment, by first matching the current plan segment and extracting effective constraint parameters, then calculating and filtering two types of core deviation values, and finally combining multi-dimensional system data to execute composite trigger criteria, precise event triggering for charging strategy updates is achieved. This not only avoids false triggering caused by instantaneous measurement disturbances through filtering, but also achieves comprehensive coverage of scenarios such as incoming power deviation, over-limit risk, equipment status changes, plan package updates, and link recovery based on five-dimensional composite criteria. Trigger signals are only generated when the system encounters an actual event that requires adjustment of the charging strategy, effectively reducing the frequency of meaningless updates to the charging strategy, lowering the OCPP protocol communication overhead and the frequency of charging pile upgrades. At the same time, the design of boundary protection and multi-criteria parallel judgment also improves the stability and reliability of trigger judgment.

[0081] In one exemplary embodiment, determining the charging pile with issuing authority based on a trigger signal includes:

[0082] Based on the evaluation data and preset basic access conditions, charging piles to be verified are selected from a preset number of charging piles to be issued; preset issuance permission constraint verification is performed on the charging piles to be verified, and the charging piles to be verified that pass the issuance permission constraint verification are designated as charging piles with issuance permissions; if the charging pile to be verified fails any issuance permission constraint verification, it is determined that the charging pile to be verified that fails any issuance permission constraint verification does not have issuance permissions.

[0083] The basic access conditions are that the charging pile is in a normal working state with online connectivity and no hardware or communication failures, and the charging pile is currently in a charging-related state that can receive charging policy issuance, such as plug-in ready or charging, and the charging pile is not included in the local safety current limiting mode.

[0084] For example, based on the online status, charging session status, and fault status of each charging pile in the evaluation data, combined with preset basic access conditions, charging piles to be verified that are online and in normal condition, without fault, and in the charging ready or charging process are selected from all preset charging piles issued on the home side, while offline, faulty, and charging piles that have not entered the charging process are excluded. Then, for the selected charging piles to be verified, preset issuance permission constraint checks are performed sequentially. The issuance permission constraint checks include minimum issuance interval checks, charging pile limit change checks, and trigger criterion hysteresis status checks. Among them, the minimum issuance interval check verifies whether the time since the last successful issuance of the charging policy to be verified for the charging pile to be verified has reached a preset interval threshold. The current limit change verification checks whether the difference between the proposed current limit and the current effective limit of the charging pile to be verified reaches the preset minimum change step size. The trigger criterion hysteresis state verification checks whether the trigger criterion hysteresis state corresponding to the charging pile to be verified is in the trigger active state. If a charging pile to be verified passes all the above-mentioned issuance permission constraint verifications in sequence, it is determined that the charging pile to be verified has the issuance permission and the updated charging strategy can be issued to it. If a charging pile to be verified fails any of the above-mentioned issuance permission constraint verifications, even if the trigger signal has been generated, it is determined that the charging pile to be verified does not have the issuance permission, and the charging strategy issuance operation will not be performed on it for the time being, and its current effective charging strategy will remain unchanged.

[0085] In this embodiment, the initial screening of charging piles is completed based on basic access conditions, eliminating charging piles that are offline, faulty, not charging, or in safe current limiting mode. Then, a refined judgment is achieved through multi-dimensional permission constraint verification, ensuring that the charging policy is only executed on charging piles that meet the basic operating conditions and satisfy constraints such as the timing of the issuance and the change of the limit. This avoids meaningless issuance operations to invalid charging piles from the bottom layer, reduces OCPP protocol communication redundancy, and effectively suppresses the problem of frequent changes in charging piles through verification rules such as minimum issuance interval, limit change amount, and hysteresis status, avoiding the instability of charging pile equipment operation caused by small and high frequency updates of the policy.

[0086] In an exemplary embodiment, based on evaluation data and preset basic access conditions, charging piles to be verified are selected from a preset pool of issued charging piles, including:

[0087] Based on the evaluation data, candidate charging piles that meet the preset basic access conditions are selected from a plurality of preset charging piles. If the trigger event type corresponding to the trigger signal is a planned synchronization trigger or a link recovery trigger, a full coverage rule is adopted, and each candidate charging pile is used as a charging pile to be verified. If the trigger event type corresponding to the trigger signal is a deviation threshold trigger or an over-limit risk warning trigger, a deviation contribution screening rule is adopted to calculate the contribution ratio of each candidate charging pile to the total charging power deviation, and the candidate charging piles whose contribution ratio is not less than the preset minimum contribution threshold are used as charging piles to be verified. If the trigger event type is an equipment status event trigger, a single-pile directional coverage rule is adopted, and only candidate charging piles with equipment status changes are used as charging piles to be verified.

[0088] For example, based on the online status, fault status, charging session status, and whether it is in safe current limiting mode of each charging pile in the evaluation data, candidate charging piles that meet the basic access conditions are selected from all the charging piles preset on the home side, and charging piles that are offline, faulty, have no charging-related status, or are in safe current limiting mode are eliminated; then, the specific type of triggering event corresponding to the triggering signal is identified, and the corresponding screening rules are matched according to different event types to determine the charging piles to be verified. Specifically: if the triggering signal is generated by a planned synchronization triggering event or a link recovery triggering event, a full coverage rule is adopted to include all the selected candidate charging piles in the scope of the charging piles to be verified, to ensure the consistency and synchronization of the full pile strategy; if the triggering signal is triggered by a deviation threshold... When an event or over-limit risk warning is triggered, a deviation contribution screening rule is adopted. Based on the evaluation data, the proportion of the real-time charging power of each candidate charging pile to the total charging power of all candidate charging piles is calculated, i.e., the contribution ratio of each pile to the total charging power deviation. Candidate charging piles with a contribution ratio not less than the preset minimum contribution threshold are selected as charging piles to be verified. Subsequent permission verification is only performed on key piles that have a significant impact on the power deviation. If the trigger signal is generated by a device status event, a single-pile directional coverage rule is adopted to accurately locate the charging piles that have undergone changes in status such as plugging in, unplugging, starting charging, stopping charging, or fault status from the candidate charging piles. Only the charging piles with status changes are selected as charging piles to be verified, realizing targeted strategy update verification.

[0089] In this embodiment, by first completing the preliminary screening of candidate charging piles based on basic admission criteria, and then determining the charging piles to be verified by matching differentiated screening rules according to the event type corresponding to the trigger signal, the scope of charging strategy distribution is accurately and scenario-basedly managed.

[0090] In an exemplary embodiment, the power limit for charging piles with issuing authority is determined based on segmented constraint parameters and evaluation data, including:

[0091] Based on the segmented incoming power upper limit and segmented total power budget of electric vehicles in the activation plan package, the hard constraint boundary for power limit calculation is determined. Based on the real-time household base load power, real-time photovoltaic output power, real-time energy storage charging and discharging power, and real-time incoming power measurement data, combined with the hard constraint boundary and preset incoming safety margin, an available power budget for electric vehicle charging is generated. If there is only one charging pile with the authority to issue power limits, the available power budget for electric vehicle charging is subject to upper and lower limits based on the rated maximum power of the charging pile with the authority to issue power limits and the hard constraint boundary, resulting in a power limit. If there are multiple charging piles with the authority to issue power limits, the available power budget for electric vehicle charging is subject to upper and lower limits based on the sum of the rated maximum power of all charging piles with the authority to issue power limits and the hard constraint boundary, resulting in a compliant power budget. Based on preset power allocation rules, the compliant power budget is allocated to each charging pile with the authority to issue power limits, resulting in a power limit for each charging pile with the authority to issue power limits.

[0092] For example, from the segmented constraint parameters of the activation plan package, the segmented incoming power limit and the segmented total electric vehicle power budget corresponding to the current plan segment are extracted and used as the core hard constraint boundary for calculating the charging pile power limit, clarifying the overall upper limit requirement for power allocation; then, based on the real-time household base load power, real-time photovoltaic output power, real-time energy storage charging and discharging power, and real-time incoming power measurement in the evaluation data, combined with the preset incoming safety margin, the available power budget for electric vehicle charging in the current period is comprehensively calculated and generated, while ensuring that the budget does not exceed the aforementioned hard constraint boundary; if it is determined that there is only one charging pile with the authority to issue the limit, then the power allocation is based on that charging pile. The rated maximum power of the charging pile, combined with the established hard constraint boundary, is used to apply upper and lower limits to the available power budget for electric vehicle charging. The resulting value is the power limit for that charging pile. If there are multiple charging piles with the authority to issue power limits, the sum of the rated maximum power of all such charging piles is first used, along with the hard constraint boundary, to apply upper and lower limits to the available power budget for electric vehicle charging, resulting in a compliant and allocable total power budget for electric vehicle charging. Finally, according to the preset power allocation rules, this compliant power budget is fairly and reasonably allocated to each charging pile with the authority to issue power limits, ultimately obtaining the power limit corresponding to each charging pile.

[0093] In this embodiment, by designing differentiated limit calculation logic for different scenarios of single-pile and multi-pile charging, the power limit of the charging pile is adapted to the power balance requirements of photovoltaic energy storage and charging on the home side. This avoids exceeding the limit of incoming power and maximizes the utilization of photovoltaic green electricity and energy storage resources. At the same time, the differentiated calculation logic is adapted to home scenarios with different numbers of charging piles.

[0094] In one exemplary embodiment, the current limit sequence is differentially processed to generate a charging strategy message, including:

[0095] A preset shaping process is performed on the current limit sequence to obtain a shaped current limit sequence. The preset shaping process includes at least one of amplitude limiting, quantization, and minimum duration merging. A set of change points is extracted from the shaped current limit sequence. The set of change points includes the starting point of the current limit sequence and the times when all current limits change and their corresponding limit values. The set of change points is then compressed based on a preset current tolerance threshold to generate a compressed set of change points. Based on the compressed set of change points and the charging strategy version number mapped to the plan version number of the activation plan package, a charging strategy message is generated.

[0096] For example, a preset shaping process is performed on the calculated current limit sequence. If there are values ​​in the sequence that exceed the rated current range of the charging pile, a limiting process is first performed. Then, the limited current value is quantized according to the minimum current adjustment step size that the charging pile can recognize. At the same time, continuous current limit change segments in the sequence that are shorter than the preset minimum effective duration are merged to obtain a smooth current limit sequence that meets the requirements of the charging pile. Then, a set of change points is extracted from the shaped current limit sequence. This set includes the current limit value at the beginning of the sequence and all current limit occurrence values. The system identifies the changing time and corresponding limit value, removing redundant time points with unchanged values ​​from the sequence. Then, based on a preset current tolerance threshold, it determines the difference in current limits between adjacent changing points in the set of changing points. If the difference is less than the tolerance threshold, these adjacent changing points are merged into one changing point, retaining only the merged start time and final limit value to generate a compressed set of changing points, significantly reducing the number of changing points. Finally, using the compressed set of changing points as the core content, it binds a charging strategy version number mapped to the current activation plan package version number and encapsulates it into a structured charging strategy message according to the OCPP protocol specification.

[0097] In this embodiment, the shaping process, through amplitude limiting, quantization, and minimum duration merging, ensures that the current limit sequence perfectly matches the hardware execution capabilities of the charging pile, avoiding invalid instructions and equipment malfunctions. Change point extraction removes redundant data with no change in the sequence, focusing on core limit change information. Tolerance merging and compression further merges small, meaningless limit changes, significantly reducing the number of valid data points in the message, thereby reducing the communication load of the OCPP protocol and the frequency of charging pile upgrades from the root. Simultaneously, mapping the charging strategy version number to the activation plan package's plan version number allows each charging strategy message to be traced back to the corresponding cloud plan package, ensuring version consistency between the cloud and edge strategies and providing a clear version identification basis for subsequent strategy verification and rollback in the event of a connection failure.

[0098] In one exemplary embodiment, the method further includes:

[0099] The system checks for any abnormalities in the communication link status between itself and the cloud energy management system, as well as the validity period of the activation plan package. If there are any abnormalities in the communication link status or the validity period of the activation plan package, the system calculates the safe charging limit for the charging pile based on the upper limit of the physical rated power of the household incoming line, the conservative estimate of the household base load, and the conservative value of the photovoltaic output, and sends a safe charging strategy message corresponding to the safe charging limit to the charging pile. If there are no abnormalities in the communication link status or the validity period of the activation plan package, the system maintains the current charging strategy message used by the charging pile.

[0100] For example, during the daily execution of charging strategy distribution and control processes, the edge controller continuously monitors the system's operating status from multiple dimensions. This includes real-time monitoring of the reachability, packet loss rate, and latency of the communication link between itself and the cloud energy management system to determine if the link is normal, verifying whether the remaining validity period of the current activation plan package is within the safe execution range, and simultaneously monitoring the connectivity of the OCPP communication link between itself and each charging pile, as well as whether the data feedback from the charging pile is normal. If an anomaly is detected in the communication link with the cloud, such as disconnection, high packet loss, or timeout, or if the current activation plan package has exceeded its validity period, the remaining validity period is lower than the preset near-expiration threshold, or if an abnormal disconnection occurs in the OCPP communication link with the charging pile, it is determined that the system is experiencing an operational anomaly. At this time, the local safety limit emergency calculation process is immediately initiated, using the upper limit of the physical rated power of the household incoming line as the core hard benchmark. Combining the high percentile conservative estimate of household base load and the lower limit conservative estimate of photovoltaic output, while reserving a preset safety margin for incoming lines, the global safe charging limit for charging piles is comprehensively calculated. Based on this safe charging limit, a safe charging strategy message adapted to the OCPP protocol is generated and sent to all charging piles that are online and communicable. For charging piles with abnormal communication links, the safe limit is triggered by their local preset link failure self-governance mechanism to ensure that all charging piles operate according to the safe limit. If the communication link with the cloud energy management system is detected to be normal, the current activation plan package is still in the effective execution period, and the OCPP communication links with each charging pile are maintained and data interaction is normal, without any abnormalities, no additional limit calculation and strategy distribution operations are performed, and the charging strategy message currently being used by the charging pile remains unchanged.

[0101] In this embodiment, by constructing a multi-dimensional anomaly detection system that integrates cloud and charging pile dual links and the validity period of the plan package, the edge controller can fully perceive the operating status of the communication link and the plan command. Compared with single link detection, it is more in line with the actual operating scenario of home-side photovoltaic energy storage and charging collaboration, and can promptly identify various risk scenarios such as cloud-edge disconnection, edge-pile communication anomalies, and plan package expiration.

[0102] In an exemplary embodiment, an electricity control method includes: receiving an activation plan package from a cloud-based energy management system; the activation plan package includes segmented constraint parameters and a plan version number; collecting multi-source electrical data and equipment status data generated by each controlled terminal in the household electricity system during operation, and generating evaluation data based on the multi-source electrical data and equipment status data; calculating the real-time deviation of the incoming power and the real-time deviation of the electric vehicle charging budget based on the segmented incoming power upper limit, the segmented electric vehicle total power budget in the segmented constraint parameters, the real-time incoming power in the evaluation data, and the real-time total charging power of the charging pile; performing preset filtering processing on the real-time deviation of the incoming power and the real-time deviation of the electric vehicle charging budget to obtain a steady-state deviation value that eliminates instantaneous measurement spikes and random noise; generating a trigger signal if the steady-state deviation value and the evaluation data meet a target composite triggering criterion; the target composite triggering criterion is at least one of a deviation threshold triggering criterion, an over-limit risk warning triggering criterion, an equipment status event triggering criterion, a plan synchronization triggering criterion, and a link recovery triggering criterion. Based on the evaluation data, candidate charging piles that meet the preset basic access conditions are selected from a plurality of preset charging piles. If the trigger event type corresponding to the trigger signal is a planned synchronization trigger or a link recovery trigger, a full coverage rule is adopted, and each candidate charging pile is treated as a charging pile to be verified. If the trigger event type corresponding to the trigger signal is a deviation threshold trigger or an over-limit risk warning trigger, a deviation contribution screening rule is adopted to calculate the contribution ratio of each candidate charging pile to the total charging power deviation, and candidate charging piles whose contribution ratio is not less than the preset minimum contribution threshold are treated as charging piles to be verified. If the trigger event type is a device status event trigger, a single-pile directional coverage rule is adopted, and only candidate charging piles with device status changes are treated as charging piles to be verified. A preset distribution permission constraint verification is performed on the charging piles to be verified, and the charging piles to be verified that pass the distribution permission constraint verification are treated as charging piles with distribution permission. If the charging pile to be verified fails any distribution permission constraint verification, it is determined that the charging pile to be verified that fails any distribution permission constraint verification does not have distribution permission.Based on the segmented incoming power upper limit and segmented total power budget of electric vehicles in the activation plan package, the hard constraint boundary for power limit calculation is determined. Based on the real-time household base load power, real-time photovoltaic output power, real-time energy storage charging and discharging power, and real-time incoming power measurement data, combined with the hard constraint boundary and preset incoming safety margin, an available power budget for electric vehicle charging is generated. If there is only one charging pile with the authority to issue power limits, the available power budget for electric vehicle charging is subject to upper and lower limits based on the rated maximum power of the charging pile with the authority to issue power limits and the hard constraint boundary, resulting in a power limit. If there are multiple charging piles with the authority to issue power limits, the available power budget for electric vehicle charging is subject to upper and lower limits based on the sum of the rated maximum power of all charging piles with the authority to issue power limits and the hard constraint boundary, resulting in a compliant power budget. Based on preset power allocation rules, the compliant power budget is allocated to each charging pile with the authority to issue power limits, resulting in a power limit for each charging pile with the authority to issue power limits. Based on the type of charging pile with distribution authority, the power limit is converted into a current limit sequence that can be recognized by the charging pile with distribution authority. A preset shaping process is performed on the current limit sequence to obtain a shaped current limit sequence. The preset shaping process includes at least one of amplitude limiting, quantization, and minimum duration merging. A set of change points is extracted from the shaped current limit sequence, containing the starting point of the current limit sequence and the times when all current limits change, along with their corresponding limit values. Based on a preset current tolerance threshold, the set of change points is merging and compressed to generate a compressed set of change points. Based on the compressed set of change points and the charging strategy version number mapped to the plan version number of the activation plan package, a charging strategy message is generated. The charging strategy message is then distributed to the charging pile with distribution authority. The system checks for any abnormalities in the communication link status between itself and the cloud energy management system, as well as the validity period of the activation plan package. If there are any abnormalities in the communication link status or the validity period of the activation plan package, the system calculates the safe charging limit for the charging pile based on the upper limit of the physical rated power of the household incoming line, the conservative estimate of the household base load, and the conservative value of the photovoltaic output, and sends a safe charging strategy message corresponding to the safe charging limit to the charging pile. If there are no abnormalities in the communication link status or the validity period of the activation plan package, the system maintains the current charging strategy message used by the charging pile.

[0103] It should be understood that although the steps in the flowcharts of the above embodiments are shown sequentially according to the arrows, these steps are not necessarily executed in the order indicated by the arrows. Unless explicitly stated herein, there is no strict order restriction on the execution of these steps, and they can be executed in other orders. Moreover, at least some steps in the flowcharts of the above embodiments may include multiple steps or multiple stages. These steps or stages are not necessarily completed at the same time, but can be executed at different times. The execution order of these steps or stages is not necessarily sequential, but can be performed alternately or in turn with other steps or at least some of the steps or stages in other steps. It is understood that the steps in different embodiments can be freely combined as needed, and all non-contradictory solutions formed by such combinations are within the scope of protection of this application.

[0104] In one exemplary embodiment, such as Figure 3 As shown, an electricity control device is provided, including: a receiving module 301, a data acquisition module 302, a judgment module 303, a conversion module 304, a processing module 305, and a transmitting module 306, wherein:

[0105] The receiving module is used to receive activation plan packages issued by the cloud-based energy management system; the activation plan package includes segmented constraint parameters and plan version number;

[0106] The data acquisition module is used to collect multi-source electrical data and equipment status data generated by each controlled terminal in the household power system during operation, and to generate evaluation data based on the multi-source electrical data and equipment status data;

[0107] The determination module is used to perform compound event trigger determination based on segmented constraint parameters and evaluation data, generate trigger signals, and determine the charging piles with the authority to issue the signal based on the trigger signals.

[0108] The conversion module is used to determine the power limit of the charging pile with the authority to issue the power limit based on the segmented constraint parameters and evaluation data, and to convert the power limit into a current limit sequence that the charging pile with the authority to issue the power limit can recognize based on the type of the charging pile with the authority to issue the power limit.

[0109] The processing module is used to perform differential processing on the current limit sequence and generate a charging strategy message. The charging strategy message carries a charging strategy version number that is mapped to the plan version number.

[0110] The sending module is used to send charging strategy messages to charging piles with the authority to send them.

[0111] In one exemplary embodiment, the determination module is further configured to:

[0112] Based on the segmented incoming power upper limit, segmented electric vehicle total power budget, real-time incoming power, and real-time total charging power of the charging pile in the segmented constraint parameters, the real-time deviation of the incoming power and the real-time deviation of the electric vehicle charging budget are calculated. Pre-set filtering processing is performed on the real-time deviation of the incoming power and the real-time deviation of the electric vehicle charging budget to obtain a steady-state deviation value that eliminates instantaneous measurement spikes and random noise. If the steady-state deviation value and the evaluation data meet the target composite triggering criterion, a trigger signal is generated. The target composite triggering criterion is at least one of the following: deviation threshold triggering criterion, over-limit risk warning triggering criterion, equipment status event triggering criterion, planned synchronization triggering criterion, and link recovery triggering criterion.

[0113] In one exemplary embodiment, the determination module is further configured to:

[0114] Based on the evaluation data and preset basic access conditions, charging piles to be verified are selected from a preset number of charging piles to be issued; preset issuance permission constraint verification is performed on the charging piles to be verified, and the charging piles to be verified that pass the issuance permission constraint verification are designated as charging piles with issuance permissions; if the charging pile to be verified fails any issuance permission constraint verification, it is determined that the charging pile to be verified that fails any issuance permission constraint verification does not have issuance permissions.

[0115] In one exemplary embodiment, the determination module is further configured to:

[0116] Based on the evaluation data, candidate charging piles that meet the preset basic access conditions are selected from a plurality of preset charging piles. If the trigger event type corresponding to the trigger signal is a planned synchronization trigger or a link recovery trigger, a full coverage rule is adopted, and each candidate charging pile is used as a charging pile to be verified. If the trigger event type corresponding to the trigger signal is a deviation threshold trigger or an over-limit risk warning trigger, a deviation contribution screening rule is adopted to calculate the contribution ratio of each candidate charging pile to the total charging power deviation, and the candidate charging piles whose contribution ratio is not less than the preset minimum contribution threshold are used as charging piles to be verified. If the trigger event type is an equipment status event trigger, a single-pile directional coverage rule is adopted, and only candidate charging piles with equipment status changes are used as charging piles to be verified.

[0117] In one exemplary embodiment, the conversion module is further configured to:

[0118] Based on the segmented incoming power upper limit and segmented total power budget of electric vehicles in the activation plan package, the hard constraint boundary for power limit calculation is determined. Based on the real-time household base load power, real-time photovoltaic output power, real-time energy storage charging and discharging power, and real-time incoming power measurement data, combined with the hard constraint boundary and preset incoming safety margin, an available power budget for electric vehicle charging is generated. If there is only one charging pile with the authority to issue power limits, the available power budget for electric vehicle charging is subject to upper and lower limits based on the rated maximum power of the charging pile with the authority to issue power limits and the hard constraint boundary, resulting in a power limit. If there are multiple charging piles with the authority to issue power limits, the available power budget for electric vehicle charging is subject to upper and lower limits based on the sum of the rated maximum power of all charging piles with the authority to issue power limits and the hard constraint boundary, resulting in a compliant power budget. Based on preset power allocation rules, the compliant power budget is allocated to each charging pile with the authority to issue power limits, resulting in a power limit for each charging pile with the authority to issue power limits.

[0119] In one exemplary embodiment, the processing module is further configured to:

[0120] A preset shaping process is performed on the current limit sequence to obtain a shaped current limit sequence. The preset shaping process includes at least one of amplitude limiting, quantization, and minimum duration merging. A set of change points is extracted from the shaped current limit sequence. The set of change points includes the starting point of the current limit sequence and the times when all current limits change and their corresponding limit values. The set of change points is then compressed based on a preset current tolerance threshold to generate a compressed set of change points. Based on the compressed set of change points and the charging strategy version number mapped to the plan version number of the activation plan package, a charging strategy message is generated.

[0121] Each module in the aforementioned power control device can be implemented entirely or partially through software, hardware, or a combination thereof. These modules can be embedded in or independent of the processor in a computer device, or stored in the memory of a computer device as software, so that the processor can call and execute the operations corresponding to each module.

[0122] In one exemplary embodiment, a computer device is provided, which may be a server, and its internal structure diagram may be as follows: Figure 4As shown, this computer device includes a processor, memory, input / output interfaces (I / O), and a communication interface. The processor, memory, and I / O interfaces are connected via a system bus, and the communication interface is also connected to the system bus via the I / O interfaces. The processor provides computational and control capabilities. The memory includes non-volatile storage media and internal memory. The non-volatile storage media stores the operating system, computer programs, and a database. The internal memory provides the environment for the operation of the operating system and computer programs stored in the non-volatile storage media. The database stores multi-source electrical data and device status data. The I / O interfaces are used for exchanging information between the processor and external devices. The communication interface is used for communicating with external terminals via a network connection. When the computer program is executed by the processor, it implements an electrical control method.

[0123] Those skilled in the art will understand that Figure 4 The structure shown is merely a block diagram of a portion of the structure related to the present application and does not constitute a limitation on the computer device to which the present application is applied. Specific computer devices may include more or fewer components than those shown in the figure, or combine certain components, or have different component arrangements.

[0124] In one exemplary embodiment, a computer device is provided, including a memory and a processor, wherein the memory stores a computer program, and the processor executes the computer program to implement the steps in the above-described method embodiments.

[0125] In one embodiment, a computer-readable storage medium is provided having a computer program stored thereon, which, when executed by a processor, implements the steps in the above method embodiments.

[0126] In one embodiment, a computer program product is provided, including a computer program that, when executed by a processor, implements the steps in the above method embodiments.

[0127] Those skilled in the art will understand that all or part of the processes in the methods of the above embodiments can be implemented by a computer program instructing related hardware. The computer program can be stored in a non-volatile computer-readable storage medium, and when executed, it can include the processes of the embodiments of the above methods. Any references to memory, databases, or other media used in the embodiments provided in this application can include at least one of non-volatile memory and volatile memory. Non-volatile memory can include read-only memory (ROM), magnetic tape, floppy disk, flash memory, optical memory, high-density embedded non-volatile memory, resistive random access memory (ReRAM), magnetic random access memory (MRAM), ferroelectric random access memory (FRAM), phase change memory (PCM), graphene memory, etc. Volatile memory can include random access memory (RAM) or external cache memory, etc. By way of illustration and not limitation, RAM can take many forms, such as Static Random Access Memory (SRAM) or Dynamic Random Access Memory (DRAM). The databases involved in the embodiments provided in this application may include at least one type of relational database and non-relational database. Non-relational databases may include, but are not limited to, blockchain-based distributed databases. The processors involved in the embodiments provided in this application may be general-purpose processors, central processing units, graphics processing units, digital signal processors, programmable logic devices, quantum computing-based data processing logic devices, artificial intelligence (AI) processors, etc., and are not limited to these.

[0128] The technical features of the above embodiments can be combined in any way. For the sake of brevity, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this application.

[0129] The embodiments described above are merely illustrative of several implementation methods of this application, and while the descriptions are specific and detailed, they should not be construed as limiting the scope of this patent application. It should be noted that those skilled in the art can make various modifications and improvements without departing from the concept of this application, and these all fall within the protection scope of this application. Therefore, the protection scope of this application should be determined by the appended claims.

Claims

1. An electrical control method, characterized in that, The method includes: Receive an activation plan package from the cloud-based energy management system; the activation plan package includes segmentation constraint parameters and a plan version number; Collect multi-source electrical data and equipment status data generated by each controlled terminal in the household power system during operation, and generate evaluation data based on the multi-source electrical data and the equipment status data; Based on the segmented constraint parameters and the evaluation data, a composite event trigger determination is performed to generate a trigger signal. Based on the trigger signal, the charging pile with the authority to issue the trigger signal is determined. Based on the segmented constraint parameters and the evaluation data, the power limit of the charging pile with the authority to issue the power limit is determined. Based on the type of the charging pile with the authority to issue the power limit, the power limit is converted into a current limit sequence that the charging pile with the authority to issue the power limit can recognize. The current limit sequence is differentially processed to generate a charging strategy message, which carries a charging strategy version number that maps to the plan version number. The charging strategy message is sent to the charging pile with the authority to issue the message.

2. The method according to claim 1, characterized in that, The step of performing a composite event trigger determination and generating a trigger signal based on the segmented constraint parameters and the evaluation data includes: Based on the segmented incoming power upper limit, segmented electric vehicle total power budget in the segmented constraint parameters, the real-time incoming power in the evaluation data, and the real-time total charging power of the charging pile, calculate the real-time deviation of the incoming power and the real-time deviation of the electric vehicle charging budget. A preset filtering process is performed on the real-time deviation of the incoming power and the real-time deviation of the electric vehicle charging budget to obtain a steady-state deviation value that eliminates instantaneous measurement spikes and random noise. If the steady-state deviation value and the evaluation data satisfy the target composite triggering criterion, a trigger signal is generated; the target composite triggering criterion is at least one of the following: deviation threshold triggering criterion, over-limit risk warning triggering criterion, equipment status event triggering criterion, planned synchronization triggering criterion, and link recovery triggering criterion.

3. The method according to claim 1, characterized in that, The step of determining the charging pile with issuing authority based on the trigger signal includes: Based on the evaluation data and preset basic access conditions, charging piles to be verified are selected from a preset number of distributed charging piles. Perform a preset distribution permission constraint verification on the charging pile to be verified, and regard the charging pile to be verified that passes the distribution permission constraint verification as a charging pile with distribution permission; If the charging pile to be verified fails any of the permission issuance constraints, it is determined that the charging pile to be verified does not have the permission to issue permissions.

4. The method according to claim 3, characterized in that, The step of selecting charging piles to be verified from a preset pool of charging piles based on the evaluation data and preset basic access conditions includes: Based on the evaluation data, candidate charging piles that meet the preset basic access conditions are selected from a plurality of preset charging piles. If the trigger event type corresponding to the trigger signal is planned synchronization trigger or link recovery trigger, then the full coverage rule is adopted, and each candidate charging pile is treated as a charging pile to be verified. If the trigger event type corresponding to the trigger signal is deviation threshold trigger or over-limit risk warning trigger, then the deviation contribution screening rule is adopted to calculate the contribution ratio of each candidate charging pile to the total charging power deviation, and the candidate charging piles whose contribution ratio is not less than the preset minimum contribution threshold are selected as the charging piles to be verified. If the triggering event type is device status event triggering, then the single-pile directional coverage rule is adopted, and only the candidate charging piles that have undergone device status changes are selected as charging piles to be verified.

5. The method according to claim 1, characterized in that, The process of determining the power limit for charging piles with issuing authority based on the segmented constraint parameters and the evaluation data includes: Based on the segmented incoming power limit and the segmented electric vehicle total power budget in the activation plan package, determine the hard constraint boundary for power limit calculation; Based on the real-time household base load power, real-time photovoltaic output power, real-time energy storage charging and discharging power and real-time incoming line measured power in the assessment data, combined with the hard constraint boundary and the preset incoming line safety margin, a budget of available power for electric vehicle charging is generated. If the number of charging piles with the authority to issue commands is a single one, then based on the rated maximum power of the charging pile with the authority to issue commands and the hard constraint boundary, the upper and lower limits are applied to the available power budget for electric vehicle charging to obtain the power limit. If there are multiple charging piles with the authority to issue power, the available power budget for electric vehicle charging is subject to upper and lower limits based on the sum of the rated maximum power of all charging piles with the authority to issue power and the hard constraint boundary, so as to obtain a compliant power budget. Based on the preset power allocation rules, the compliant power budget is allocated to each charging pile with the authority to issue power, so as to obtain the power limit of each charging pile with the authority to issue power.

6. The method according to claim 1, characterized in that, The differential processing of the current limit sequence to generate a charging strategy message includes: The current limit sequence is subjected to a preset shaping process to obtain a shaped current limit sequence; the preset shaping process includes at least one of amplitude limiting, quantization, and minimum duration merging. Extract a set of change points from the shaped current limit sequence. The set of change points includes the starting point of the current limit sequence and the times when all current limits change and their corresponding limit values. Based on a preset current tolerance threshold, the set of change points is merging and compressed to generate a compressed set of change points. Based on the compressed set of change points, and combined with the charging strategy version number that maps to the plan version number of the activation plan package, a charging strategy message is generated.

7. An electrical control device, characterized in that, The device includes: The receiving module is used to receive an activation plan package issued by the cloud-based energy management system; the activation plan package includes segmentation constraint parameters and a plan version number; The data acquisition module is used to collect multi-source electrical data and equipment status data generated by each controlled terminal in the household power system during operation, and to generate evaluation data based on the multi-source electrical data and the equipment status data. The determination module is used to perform composite event trigger determination based on the segmented constraint parameters and the evaluation data, generate a trigger signal, and determine the charging pile with the authority to issue the signal based on the trigger signal. The conversion module is used to determine the power limit of the charging pile with the authority to issue the power limit based on the segmented constraint parameters and the evaluation data, and to convert the power limit into a current limit sequence that the charging pile with the authority to issue the power limit can recognize based on the type of the charging pile with the authority to issue the power limit. The processing module is used to perform differential processing on the current limit sequence to generate a charging strategy message, wherein the charging strategy message carries a charging strategy version number that maps to the plan version number. The sending module is used to send the charging strategy message to the charging pile with the authority to send the message.

8. A computer device comprising a memory and a processor, wherein the memory stores a computer program, characterized in that, When the processor executes the computer program, it implements the steps of the method according to any one of claims 1 to 6.

9. A computer-readable storage medium having a computer program stored thereon, characterized in that, When the computer program is executed by a processor, it implements the steps of the method according to any one of claims 1 to 6.

10. A computer program product, comprising a computer program, characterized in that, When the computer program is executed by a processor, it implements the steps of the method according to any one of claims 1 to 6.

Images