Energy management control method and system based on 698.45 protocol

Abstract

The application discloses an energy management control method and system based on 698.45 protocol and relates to the technical field of smart grids.The method comprises the following steps: obtaining a device network access signal, a device native object list and a 698.45 registration service rule, identifying the network access device through the 698.45 protocol and completing identity verification, outputting a device logical address and a registered device list; based on a 698.45 standard object model, mapping into a standard object and outputting a unified device shadow model; based on a device real-time running state, a periodic collection strategy and a change reporting strategy, addressing the corresponding device through the device logical address, completing a hybrid mode collection, outputting a periodic collection data set and a change reporting data set; based on a macro-control strategy instruction issued by a master station and a local collaborative strategy, disassembling the macro-control instruction into executable instructions and outputting a device-level control target; writing the device-level control target into a control object of the corresponding device through the device logical address and outputting an instruction execution result and device state feedback data.

Description

Technical Field

[0001] This invention relates to the field of smart grid technology, and in particular to an energy management and control method and system based on the 698.45 protocol. Background Technology

[0002] Distributed energy devices such as distributed photovoltaics, electric vehicle charging piles, and distributed energy storage are characterized by geographically dispersed locations, diverse communication interfaces, and heterogeneous communication protocols. Different devices use various communication methods such as RS485, Ethernet, and wireless, as well as various protocols such as Modbus, DL / T 645, and CAN, making it difficult to achieve standardized interconnection and interoperability between devices.

[0003] Current traditional energy management systems mostly adopt a "one-to-one adaptation" or "many-to-many simple aggregation" control model, which has obvious shortcomings in multi-device collaborative scenarios: First, there are prominent protocol barriers, with each manufacturer's equipment using proprietary protocols or non-standard industry protocols, lacking a unified physical model specification, and insufficient data interoperability and interoperability capabilities; Second, the real-time control is insufficient, with centralized polling acquisition and control methods having low communication efficiency and large response delays, making it difficult to meet the grid's demand for second-level collaborative control of distributed resources that is "observable, measurable, adjustable, and controllable"; Third, multi-device collaborative capabilities are lacking, with existing solutions mostly designed for single-type equipment, failing to form an integrated control mechanism for photovoltaic, energy storage, and charging, and unable to achieve collaborative optimization in scenarios such as load smoothing and power constraints. Summary of the Invention

[0004] DL / T 698.45, as an object-oriented interoperability protocol in the field of electricity information collection, possesses technical advantages such as object-oriented, self-describing, and scalable characteristics, providing a unified data interaction and object modeling standard for multi-source heterogeneous devices. Therefore, this invention constructs an energy management and control method and system based on the DL / T 698.45 protocol, realizing unified access, standardized modeling, efficient data collection, and collaborative control of distributed photovoltaic, energy storage, and charging pile devices, solving the interoperability, real-time regulation, and collaborative optimization problems after multi-source heterogeneous devices are connected to the distribution network.

[0005] In a first aspect, the present invention provides an energy management and control method based on the 698.45 protocol, comprising the following steps: S1: Obtain the device network access signal, the device native object list and the 698.45 registration service rules, identify the network access device and complete the identity verification through the 698.45 protocol, and output the device logical address and the list of registered devices; S2: Based on the 698.45 standard object model, using the device logical address as an index, traverse the list of registered devices, map them to standard objects, and output a unified device shadow model; S3: Based on the real-time operating status of the device, the periodic acquisition strategy and the change reporting strategy, the corresponding device is addressed through the device logical address, and the hybrid mode acquisition is completed according to the unified device shadow model, outputting the periodic acquisition dataset and the change reporting dataset. S4: Based on the macro-control strategy instructions and local coordination strategies issued by the main station, and combined with the periodically collected data and the change reporting dataset, the macro-control instructions are decomposed into executable instructions, and the device-level control targets are output. S5: Write the device-level control target into the control object of the corresponding device through the device logical address, and output the instruction execution result and device status feedback data.

[0006] The second invention provides an energy management and control system based on the 698.45 protocol, comprising: Physical device layer: Composed of various energy devices, which have built-in or external communication modules that support the DL / T 698.45 protocol, and provide standardized measurement point objects, control objects and parameter objects interfaces to the outside world; Edge aggregation layer: Composed of an energy management controller, which integrates a DL / T 698.45 protocol stack, an object model engine, a policy execution unit, and an edge computing module; The main station application layer consists of the power grid dispatching main station and communicates with the edge aggregation layer via 4G / 5G and fiber optics.

[0007] In summary, the present invention has at least the following beneficial effects: 1. Based on the DL / T 698.45 protocol, this invention is the first to construct a unified object model of "photovoltaic, energy storage and charging" applicable to distributed photovoltaic, energy storage and charging piles. It abstracts different manufacturers and different types of equipment into standardized measurement objects, control objects and parameter objects, so that the equipment can achieve unified identification, unified interaction and unified management at the edge controller level. It completely eliminates the data interoperability barriers caused by private protocols and heterogeneous interfaces, and has strong cross-vendor compatibility and plug-and-play capabilities.

[0008] 2. This invention adopts a push-pull mechanism that combines periodic data acquisition with proactive reporting of changes, abandoning the traditional centralized polling mode. When the equipment status is abnormal or the operating data changes, it can proactively report the data. Combined with local real-time processing by the edge controller, the system response latency is shortened from minutes to milliseconds / seconds. It can quickly respond to scenarios such as grid frequency fluctuations and load changes, meeting the real-time control requirements of distributed energy that are "observable, measurable, adjustable, and controllable".

[0009] 3. This invention pushes the strategy execution and decision-making logic down to the edge controller, constructing a local closed-loop control architecture for cloud-edge collaboration. The edge controller can independently complete control logic such as load over-limit handling, peak shaving and valley filling, and gate power constraint according to the preset collaborative strategy. It can achieve coordinated regulation of optical storage and charging without relying on real-time instructions from the master station. Even if cloud communication is interrupted, the system can still operate stably and autonomously, significantly improving the overall control reliability and anti-interference capability.

[0010] 4. This invention forms a system-level integrated control logic for the integration of light, energy storage and charging. According to the preset priority, it realizes the regulation of energy storage charging and discharging, the power limitation of charging piles and the regulation of photovoltaic active power output. It can effectively smooth load fluctuations, constrain the power at the threshold, optimize the operation status of the distribution network, and improve the distributed energy absorption capacity and the safe and stable operation level of the distribution network end. Attached Figure Description

[0011] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0012] Figure 1 This is the control flowchart of the present invention; Figure 2 This is a system architecture diagram of the present invention; Figure 3 This is a schematic diagram of the object model structure of the device of the present invention; Figure 4 This is a communication flowchart of the protocol converter of the present invention. Detailed Implementation

[0013] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0014] An energy management and control system based on the 698.45 protocol includes: Physical equipment layer: This layer includes distributed energy devices such as photovoltaic inverters, energy storage converters, and electric vehicle charging stations. These devices are connected to the system via protocol converters. For example... Figure 4 As shown, the protocol converter communicates through the following steps: First, the historical communication files stored in Flash memory are searched, and each valid file is checked one by one. If the downstream adapter responds normally, the process moves on to the next file. If a single file fails to respond after three consecutive checks, it is deemed invalid and deleted. After all files have been verified, if the number of successfully checked files has not reached the maximum number that Flash memory can store, the address adaptation process begins; if the maximum number has been reached, the process directly proceeds to the inverter address search stage.

[0015] During the address adaptation phase, the protocol converter sends address adaptation commands to search for adapter information not recorded in the archive. If a new adapter replies with an address, the address information is stored in the archive; if no reply is received after three consecutive adaptation commands, or if the archive limit has been reached, the adaptation process stops and the inverter address search process begins.

[0016] The protocol converter performs an inverter address search for each online adapter. First, it sends a switching command to the adapter, then checks if there is any historically successfully matched inverter information for that adapter. If historical matching information exists, it prioritizes matching with the original manufacturer and the historical address; if matching fails, it tries the manufacturer's default address; if still unsuccessful, it iterates through all addresses of that manufacturer. Successful matching at any step indicates that the inverter address search is complete.

[0017] If no historical compatibility information is available or the specified manufacturer's address traversal fails, the protocol converter switches to a full-manufacturer fallback search mode, first polling each manufacturer's default address. If the default address polling fails, a segmented polling method is used to traverse all addresses, first searching segments 0-9, then segments 10-19, and so on up to 254. Manufacturers and addresses already searched during the traversal are not retried. If there is still no response after all addresses have been traversed, the process ends, completing the entire communication initialization logic.

[0018] Through the above communication process, the converter can uniformly convert the private protocols of various devices into standard external interfaces, providing standardized interfaces for measurement point objects, control objects, and parameter objects, and providing a hardware foundation for device registration, object modeling, and instruction execution.

[0019] Edge Aggregation Layer: The core is the edge gateway, which integrates the DL / T 698.45 protocol stack, object model engine, policy execution unit, and edge computing module. The object model engine is used to complete standardized object modeling and unified device shadow generation of distributed energy devices based on the DL / T 698.45 protocol; the policy execution unit is used to load and execute local collaborative policies to complete the combined control of energy storage, charging piles, and photovoltaic inverters according to preset priorities; the edge computing module is used to collect data in real time, calculate transformer load rate and gate power, and perform anomaly detection and local closed-loop decision-making.

[0020] This layer is responsible for automatic device discovery and logical address allocation, unified object modeling and shadow generation, periodic data collection and change reporting, macro-level policy parsing and device-level instruction decomposition, local anomaly detection and collaborative control execution. It is the core unit for realizing device registration, object mapping, data collection, policy parsing, instruction issuance, anomaly judgment and collaborative control.

[0021] The main station application layer includes the power grid dispatching main station, virtual power plant platform, load aggregation platform, or park energy management platform, which can be built using MyEMS. It communicates with the edge aggregation layer via 4G / 5G, fiber optics, etc. The main station is responsible for issuing macro-control targets and control execution blocks, receiving operational data and execution results uploaded from the edge aggregation layer, and archiving them in cloud storage.

[0022] like Figure 1 As shown, an energy management and control method based on the 698.45 protocol includes the following steps: Step 1: Device registration and discovery.

[0023] When photovoltaic inverters, energy storage converters, and electric vehicle charging piles are connected to the system via RS485, Ethernet, or wireless means, the edge gateway immediately initiates the DL / T 698.45 protocol standard registration service to automatically identify and detect the newly connected devices online.

[0024] The edge gateway reads the device's native list of measurement point objects, control objects, and parameter objects to complete the device's identity and legitimacy verification. Measurement point objects are used to collect operational data such as voltage, current, power, energy storage SOC, and charging capacity; control objects are used to execute control actions such as start / stop, charge / discharge switching, power adjustment, and current limiting; parameter objects are used to configure device parameters such as rated values, protection thresholds, maximum charging current, and operating limits.

[0025] Subsequently, a globally unique logical address is assigned to each device, and a list of registered devices containing device type, communication address, object capabilities, and protocol version is generated to complete the plug-and-play access of multi-source heterogeneous devices, providing basic identity information for subsequent unified modeling and management.

[0026] Step 2: Object modeling and mapping of the device.

[0027] The edge gateway uses the device's logical address as an index and performs standardized mapping on registered devices based on the preset DL / T 698.45 standard object model. Following the interface class specifications defined in the DL / T 698.45 protocol, photovoltaic inverters, energy storage converters, and electric vehicle charging piles are abstracted and mapped as measurement point objects, control objects, and parameter objects, respectively.

[0028] By mapping to form a unified device shadow model, devices from different manufacturers, with different interfaces and different proprietary protocols can present a completely consistent management interface within the edge gateway, achieving unified interoperability across vendor devices.

[0029] Step 3: Multi-mode data acquisition of the device.

[0030] The edge gateway uses a unified device shadow model and a hybrid acquisition mode that combines periodic data collection with proactive change reporting to obtain the real-time status of devices. The slowly varying analog quantities such as the SOC of the energy storage converter, the active power output of the photovoltaic inverter, the load rate of the distribution transformer, and the voltage and current of the electric vehicle charging pile are collected periodically at set time intervals. For sudden changes in switching quantities such as the start / stop status of electric vehicle charging piles, the switching of operating modes of energy storage converters and photovoltaic inverters, fault signals of the three types of equipment, and protection actions, the DL / T 698.45 protocol change reporting strategy is enabled, and the equipment actively reports the status changes.

[0031] Ultimately, a complete periodic data collection dataset and change reporting dataset are formed, providing real-time and highly reliable data support for strategy decision-making and anomaly detection.

[0032] Step 4: The system parses and generates the strategy.

[0033] The edge gateway receives control execution blocks issued by the power grid dispatch master station, virtual power plant platform, or load aggregation platform via the DL / T 698.45 protocol to obtain macro-control objectives such as peak shaving and valley filling, threshold power constraints, load limiting, and demand response. Combined with real-time collected data such as active power output, SOC, charging pile load, and transformer load rate, as well as preset local coordination strategies, the macro-instructions are broken down into device-level control objectives that can be directly issued to the equipment. These include energy storage charging and discharging power settings, charging pile output power limits, and photovoltaic inverter active / reactive power adjustment values, providing a basis for precise instruction execution.

[0034] Step 5: System instruction execution and feedback.

[0035] The edge gateway locates the target device through its logical address, strictly follows the DL / T 698.45 protocol format, and writes the device-level control target into the control object attribute of the corresponding device to complete the actual adjustment of the device. Perform charging / discharging mode switching and power increase / decrease on the energy storage converter; Implement start / stop and output current / power limits for charging piles; The photovoltaic inverter is subject to active power reduction and output constraint.

[0036] After the command is executed, the device returns the execution status in real time, and the edge gateway generates command execution results and device status feedback data to complete the single device control closed loop.

[0037] Step six: Detection and judgment of equipment malfunctions.

[0038] After confirming that the previous instruction has been executed stably, the edge gateway calculates the gate power and transformer load rate in real time based on the periodically collected dataset. It then compares the calculated values ​​with a preset transformer load rate threshold to determine if the current load exceeds the limit and if the gate power meets the constraints. If the transformer load rate does not exceed the threshold and the gate power is normal, it is considered normal; if the transformer load rate exceeds the threshold, it is considered an overload anomaly, requiring the activation of a local collaborative strategy.

[0039] Step 7: Execution of the local collaboration strategy.

[0040] When an abnormal load exceeding limits is detected, the edge gateway immediately activates its local coordination strategy, issuing combined control actions via the DL / T 698.45 protocol according to a fixed priority: first adjusting energy storage, then limiting charging piles, and finally adjusting photovoltaic inverters. Prioritize energy storage adjustment: reduce the charging power of energy storage converters, or directly switch energy storage from charging mode to discharging mode to smooth grid-side load; Simultaneous restriction of charging piles: Reduce the output power of individual / group charging piles for electric vehicles to reduce the overall load on the park; If the first two levels of adjustment still fail to bring the transformer load rate back to within the threshold, then reduce the active power output of the photovoltaic inverter to further constrain the cut-off power.

[0041] By combining photovoltaic, energy storage, and charging technologies, the transformer load can be quickly pulled back to a safe range, ensuring that the power limit at the control point is not exceeded and achieving stable load control at the end of the distribution network.

[0042] Step 8: System process closure and archiving.

[0043] Once a single device command executes normally, or collaborative control is completed, the edge gateway uploads the entire process data—including device registration, object modeling, data acquisition, policy parsing, command issuance, anomaly detection, and collaborative control—as well as the device's operating status, control process, and execution results, to the application layer of the power grid dispatch master station via 4G / 5G or fiber optic cable, and simultaneously archives it to cloud storage. Upon archiving, a process loop completion signal is output, marking the official end of the entire process from device access to control execution, achieving a complete control loop and data traceability under cloud-edge collaboration.

[0044] Implementation examples of system architecture: like Figure 2As shown, at the physical equipment layer, an industrial park deploys a 200kW distributed photovoltaic system, five 120kW DC fast charging piles, and a 500kWh / 250kW energy storage system. The photovoltaic inverters, charging piles, and energy storage PCS are all connected to an external DL / T 698.45 protocol conversion module based on an MCU via an RS485 interface. This enables these devices, which originally supported the Modbus protocol, to provide an external DL / T 698.45 protocol interface, providing the ability to interact with standard measurement point objects, control objects, and parameter objects.

[0045] At the edge aggregation layer, an edge IoT gateway is deployed. This gateway runs a Linux system and integrates a complete DL / T 698.45 protocol stack, object model engine, policy execution unit, and edge computing module. Internally, the edge gateway constructs an object model conforming to the DL / T 698.45 standard. For example, it models an energy storage system as a DC measurement point and a schedulable storage unit, enabling it to complete the entire process, including device registration and discovery, object modeling and mapping, multi-mode data acquisition, policy parsing, command execution, anomaly detection, collaborative control, and process closure.

[0046] At the main station application layer, a virtual power plant platform, load aggregation platform, or park energy management platform of the power grid company has been established. It can be deployed based on an open source energy management system and cloud server. It communicates with the edge aggregation layer through 4G / 5G or fiber optics to realize the issuance of macro-control instructions, data reception, cloud storage archiving, and cloud-edge collaborative management.

[0047] Examples of object modeling and mapping for devices: like Figure 3 As shown, for charging pile equipment, this invention pre-defines a charging pile interface class in the energy management controller. This class includes: Logical device: Charging pile_01; Connection attributes: Communication rate, Port; Instance of measurement objects: Phase A voltage, protocol identifier F201, Charging current, protocol identifier F202, Cumulative power, protocol identifier F203; Control object instances: Start charging, protocol identifier is E101, data type is Boolean; Set charging power, protocol identifier is E102, data type is integer.

[0048] Based on this, the edge IoT gateway uses the device logical address as an index and performs a unified standardized mapping on the registered photovoltaic inverters, energy storage converters, and charging piles based on the preset DL / T 698.45 standard object model. These are abstracted into three types of standard objects: measurement point objects, control objects, and parameter objects, forming a unified device shadow model.

[0049] When the main station needs to control the charging pile to reduce its power, it only needs to write the target power value to the E102 object through the DL / T 698.45 protocol, and the edge IoT gateway will automatically complete the issuance and execution confirmation of the command.

[0050] Examples of load shaving and coordinated control in industrial parks: When the power grid issues a demand response command requiring the industrial park to reduce its load by 500kW, the following steps shall be performed: The main station sends a "control execution block" to the edge IoT gateway via the DL / T 698.45 protocol, along with the peak shaving target value and time window. The edge IoT gateway parses the command and reads that the current photovoltaic power generation is 300kW, the energy storage SOC is 80%, and the real-time power of the charging piles is 400kW. The edge IoT gateway executes a local coordination strategy: first, it sets the energy storage PCS to switch from standby to discharge mode via the DL / T 698.45 protocol, setting the discharge power to 200kW; at the same time, it limits the total power of the charging piles to no more than 200kW. At this time, the power at the point where the park draws power from the grid is reduced by 400kW, which, in conjunction with the photovoltaic output, meets the peak shaving requirements.

[0051] The above are merely preferred embodiments of the invention and are not intended to limit the invention. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of the invention should be included within the protection scope of the invention.

Claims

1. An energy management and control method based on the 698.45 protocol, characterized in that, Includes the following steps: S1: Obtain the device network access signal, the device native object list and the 698.45 registration service rules, identify the network access device and complete the identity verification through the 698.45 protocol, and output the device logical address and the list of registered devices; S2: Based on the 698.45 standard object model, using the device logical address as an index, traverse the list of registered devices, map them to standard objects, and output a unified device shadow model; S3: Based on the real-time operating status of the device, the periodic acquisition strategy and the change reporting strategy, the corresponding device is addressed through the device logical address, and the hybrid mode acquisition is completed according to the unified device shadow model, outputting the periodic acquisition dataset and the change reporting dataset. S4: Based on the macro-control strategy instructions and local coordination strategies issued by the power grid dispatch master station, and combined with the periodically collected data and the change reporting dataset, the macro-control instructions are decomposed into executable instructions, and the device-level control targets are output. S5: Write the device-level control target into the control object of the corresponding device through the device logical address, and output the instruction execution result and device status feedback data.

2. The energy management and control method based on the 698.45 protocol according to claim 1, characterized in that, The specific steps for obtaining the device's network access signal, the list of native devices, and the 698.45 registration service rules, identifying the network access device and completing identity verification through the 698.45 protocol, and outputting the device's logical address and the list of registered devices are as follows: The system acquires the device network access signal, the device native object list, and the 698.45 registration service rules. It identifies the measurement point object, control object, and parameter object list of the network access device through the 698.45 protocol and completes the identity verification. It assigns a unique device logical address to each device, forming the registered device list that includes device type, communication address, and object capabilities.

3. The energy management and control method based on the 698.45 protocol according to claim 1, characterized in that, The 698.45 standard object model includes measurement point objects, control objects, and parameter objects; The measurement point objects correspond to E101 / E102 identifiers, which are used to define the acquisition attributes and reading and reporting methods of the running data; The control object corresponds to the F201 / F202 identifier, which is used to define the execution attributes and writing and execution methods of the control instructions; The parameter object corresponds to the P301 / P302 identifier and is used to define the parameter attributes and configuration and verification methods of the configuration item.

4. The energy management and control method based on the 698.45 protocol according to claim 1, characterized in that, The local coordination strategy is to prioritize reducing the energy storage charging power or controlling the energy storage to switch to discharge mode to smooth the load when the energy management controller performs peak shaving, power constraint or load over-limit processing, while limiting the output power of the charging pile. If the transformer load rate still exceeds the limit after the first two levels of regulation, then adjust the active power output of the photovoltaic inverter to ensure that the threshold power does not exceed the limit and the load meets the grid demand.

5. The energy management and control method based on the 698.45 protocol according to any one of claims 1-4, characterized in that, It also includes step S6: confirming the completion of instruction execution based on the instruction execution result, and calculating the transformer load rate in real time based on the periodic acquisition dataset; The transformer load rate is compared with the transformer load rate threshold, and the transformer load anomaly determination result is output. If the transformer load anomaly determination result shows an anomaly, then the local coordination strategy is executed, and the coordination control result is output.

6. The energy management and control method based on the 698.45 protocol according to claim 5, characterized in that, It also includes step S7: when the transformer load anomaly determination result is normal, or the collaborative control result is completed, the entire process data of this equipment access, data acquisition, strategy parsing, instruction execution, anomaly detection and collaborative control is uploaded to the power grid dispatch master station and archived to cloud storage, and the process closed loop completion signal is output.

7. An energy management and control system based on the 698.45 protocol, characterized in that, include: Physical device layer: Composed of various energy devices, which are connected to communication modules and provide standardized measurement point objects, control objects and parameter objects interfaces to the outside world; Edge aggregation layer: Composed of an energy management controller, which integrates a DL / T 698.45 protocol stack, an object model engine, a policy execution unit, and an edge computing module; The main station application layer consists of the power grid dispatching main station and communicates with the edge aggregation layer via 4G / 5G and fiber optics.

8. The energy management and control method based on the 698.45 protocol according to claim 7, characterized in that, The communication module includes a protocol converter, and the communication steps of the protocol converter are as follows: Search for files stored in flash memory, and call out each valid file one by one. If the connected adapter responds, call out the next file. If there is no response after calling out a file 3 times, delete the file information. After all files have been named, if the number of successfully named files is less than the maximum number of files that can be saved, an address adaptation command is sent to find adapter information that is not in the record table. If a new device responds, the address information is recorded. If the number of files reaches the upper limit or there is no response to the adaptation command for 3 consecutive times, the inverter address search process is initiated. For each downstream adapter, the inverter address is searched one by one. First, a switching command is sent to check if there is any historically successfully adapted inverter information. If so, the historically adapted manufacturer and address are used to attempt adaptation first. If adaptation fails, the default address of the manufacturer is used to continue trying. If it still fails, all addresses of the manufacturer are traversed. If there is no historical adaptation information or the traversal of the specified manufacturer's address fails, the default address of each manufacturer is used in round-robin. If it still fails, all manufacturer addresses are traversed. When traversing all manufacturer addresses, a segmented round-robin method is used. First, the address range 0-9 is traversed. If it fails, the address range 10-19 is traversed. This process is repeated until 254 is reached. Manufacturers and addresses that have already been searched during the traversal are not searched again.

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