Equipment scheduling method and device

Abstract

The invention discloses an equipment scheduling method and device, and the method comprises the steps: obtaining first operation data corresponding to a current moment of first equipment operating in a first operation period; under the condition that the first operation data is not matched with a first scheduling plan configured for the first equipment, an exception coping strategy corresponding to the first equipment is obtained, the first scheduling plan is used for indicating a scheduling action to be executed by the first equipment in a first operation period, and the first scheduling plan is used for indicating the first equipment to execute the exception coping strategy; the exception coping strategy is an exception coping strategy preset or selected in response to the first user account; and generating a second scheduling plan according to the exception coping strategy, and scheduling the first equipment according to the second scheduling plan in the remaining period of the first operation period. According to the invention, the technical problem of low equipment scheduling flexibility is solved.

Description

Technical Field

[0001] This application relates to the field of power energy dispatching technology, and more specifically, to a method and apparatus for equipment dispatching. Background Technology

[0002] With the rapid development of intelligent interconnection and automation technologies, equipment scheduling is not only the foundation for ensuring the stable operation of various systems, but also the key to improving user satisfaction and system performance. In related technologies, the common scheduling method for equipment is to pre-set a scheduling plan, and then strictly follow this plan during equipment operation, performing timed and quantitative scheduling of equipment. Even if the actual operating status of the equipment deviates from the preset plan, the equipment will still be scheduled according to the preset plan.

[0003] In other words, even with the equipment scheduling methods employed in related technologies, the technical problem of low equipment scheduling flexibility still exists due to the rigid adherence to scheduling rules.

[0004] There is currently no effective solution to the above problems. Summary of the Invention

[0005] This application provides a device scheduling method and apparatus to at least solve the technical problem of low device scheduling flexibility.

[0006] According to one aspect of the embodiments of this application, a device scheduling method is provided, comprising: acquiring first operating data corresponding to the current time of a first device running in a first operating cycle; if the first operating data and a first scheduling plan configured for the first device do not match, acquiring an anomaly response strategy corresponding to the first device, wherein the first scheduling plan is used to indicate the scheduling action to be performed by the first device in the first operating cycle, and the anomaly response strategy is a pre-set anomaly response strategy or an anomaly response strategy selected by a first user account; generating a second scheduling plan according to the anomaly response strategy, and scheduling the first device according to the second scheduling plan in the remaining period of the first operating cycle.

[0007] According to another aspect of the embodiments of this application, a device scheduling apparatus is also provided, comprising: an anomaly detection module, configured to acquire first operating data generated by a first device in a first operating cycle; an anomaly handling module, configured to acquire an anomaly response strategy corresponding to the first device when the first operating data and a first scheduling plan configured for the first device do not match, wherein the first scheduling plan is used to indicate the scheduling action to be performed by the first device in the first operating cycle, and the anomaly response strategy is determined from an anomaly response strategy pool according to an anomaly response mode matched with the first device; and a scheduling module, configured to generate a second scheduling plan according to the anomaly response strategy, and schedule the first device according to the second scheduling plan in the remaining period of the first operating cycle.

[0008] According to another aspect of the embodiments of this application, a device scheduling system is also provided, including: an anomaly detection module, an anomaly handling module, a scheduling module, a data acquisition module, and a control module, wherein: the data acquisition module is used to collect first operating data corresponding to the current time of a first device running in a first operating cycle; the anomaly detection module is used to compare the first operating data with a first scheduling plan configured for the first device, and if the first operating data and the first scheduling plan do not match, send an anomaly handling request to the anomaly handling module; the anomaly handling module is used to obtain an anomaly response strategy corresponding to the first device in response to the anomaly handling request, wherein the first scheduling plan is used to indicate the scheduling action to be performed by the first device in the first operating cycle, and the anomaly response strategy is a pre-set anomaly response strategy or an anomaly response strategy selected by a first user account; the scheduling module is used to generate a second scheduling plan according to the anomaly response strategy, and send scheduling instructions to the control module according to the second scheduling plan in the remaining period of the first operating cycle; the control module is used to control the first device according to the scheduling instructions.

[0009] According to another aspect of the embodiments of this application, a computer-readable storage medium is also provided, wherein a computer program is stored in the computer-readable storage medium, and the computer program is configured to execute the above-described device scheduling method at runtime.

[0010] According to another aspect of the embodiments of this application, a computer program product or computer program is provided, which includes computer instructions stored in a computer-readable storage medium. A processor of a computer device reads the computer instructions from the computer-readable storage medium and executes the computer instructions, causing the computer device to perform the device scheduling method described above.

[0011] According to another aspect of the embodiments of this application, an electronic device is also provided, including a memory and a processor, wherein the memory stores a computer program, and the processor is configured to execute the above-described device scheduling method through the computer program.

[0012] In this embodiment, first operating data corresponding to the current moment of a first device running within a first operating cycle is obtained; if the first operating data and the first scheduling plan configured for the first device do not match, an anomaly response strategy corresponding to the first device is obtained, wherein the first scheduling plan is used to indicate the scheduling action to be performed by the first device in the first operating cycle, and the anomaly response strategy is a pre-set anomaly response strategy or a response to an anomaly response strategy selected by a first user account; a second scheduling plan is generated according to the anomaly response strategy, and the first device is scheduled according to the second scheduling plan during the remaining period of the first operating cycle. By adopting this embodiment, the technical effect of improving the flexibility of device scheduling is achieved, solving the technical problem of low scheduling flexibility in the device scheduling methods provided in related technologies. Attached Figure Description

[0013] The accompanying drawings, which are included to provide a further understanding of this application and form part of this application, illustrate exemplary embodiments and are used to explain this application, but do not constitute an undue limitation of this application. In the drawings:

[0014] Figure 1 This is a flowchart of an optional device scheduling method according to an embodiment of this application;

[0015] Figure 2 A system architecture diagram of an optional device scheduling method according to an embodiment of this application;

[0016] Figure 3 This is a system architecture diagram of another optional device scheduling method according to an embodiment of this application;

[0017] Figure 4 This is a system architecture diagram of another optional device scheduling method according to an embodiment of this application;

[0018] Figure 5 This is a flowchart of another optional device scheduling method according to an embodiment of this application;

[0019] Figure 6 This is a schematic diagram of an optional equipment scheduling device according to an embodiment of this application. Detailed Implementation

[0020] To enable those skilled in the art to better understand the present application, the technical solutions in the embodiments of the present application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present application, and not all embodiments. Based on the embodiments in the present application, all other embodiments obtained by those of ordinary skill in the art without creative effort should fall within the scope of protection of the present application.

[0021] It should be noted that the terms "first," "second," etc., in the specification, claims, and accompanying drawings of this application are used to distinguish similar objects and are not necessarily used to describe a specific order or sequence. It should be understood that such data can be interchanged where appropriate so that the embodiments of this application described herein can be implemented in orders other than those illustrated or described herein. Furthermore, the terms "comprising" and "having," and any variations thereof, are intended to cover non-exclusive inclusion; for example, a process, method, system, product, or apparatus that comprises a series of steps or units is not necessarily limited to those steps or units explicitly listed, but may include other steps or units not explicitly listed or inherent to such processes, methods, products, or apparatus.

[0022] To better understand the technical solutions provided in the embodiments of this application, the key terms involved in the embodiments of this application will be introduced first:

[0023] A smart home system is an integrated platform that uses the internet and IoT technologies to connect various devices in the home (such as lighting, appliances, and security systems) to achieve remote control and automated management. Through a smart central controller, users can monitor and operate the devices in their homes, and the system can automatically adjust the operating status of the devices according to preset rules or user habits to achieve goals such as energy saving, safety, and comfort.

[0024] A microgrid is a small-scale power grid that can operate independently or in conjunction with the main grid. It is typically used for single or multiple buildings, communities, etc. A microgrid includes power generation equipment (such as solar or wind power generation), energy-consuming equipment (such as household appliances and industrial loads), energy storage equipment, as well as a control system and network. It can dynamically adjust its power supply strategy based on local energy demand and capacity, achieving energy self-sufficiency and optimized dispatch.

[0025] A hydrogen production system typically consists of an electrolyzer, production equipment (such as photovoltaic or wind turbines), and energy storage devices, used to convert electrical energy into hydrogen for storage. In a hydrogen production system, the scheduling mechanism is particularly important. It needs to determine when to start the electrolyzer for hydrogen production and whether supplemental power from the energy storage devices is needed, based on the power supply and demand situation and the operating status of the electrolyzer, to ensure the efficiency and economy of the hydrogen production process.

[0026] A scheduling plan is the basis for equipment to execute scheduling instructions. In smart home systems, scheduling plans may be formulated based on users' lifestyles and energy price fluctuations; in microgrids and hydrogen production systems, they may rely more on real-time energy supply and demand analysis and electricity price information.

[0027] As an alternative solution, such as Figure 1 As shown, the above-mentioned equipment scheduling method includes:

[0028] S102, Obtain the first operating data corresponding to the current moment of the first device running in the first operating cycle.

[0029] It should be noted that the above-mentioned equipment scheduling method can be applied to at least the following scenarios:

[0030] 1) In smart home scenarios, device scheduling methods can precisely manage various energy devices within the home, such as smart appliances, photovoltaic systems, energy storage units, and smart lighting. By analyzing user habits, electricity costs, and the availability of renewable energy, this method can dynamically adjust device operating times to ensure that the needs of family members are met under the most economical and environmentally friendly conditions. For example, a smart refrigerator is scheduled to cool during periods of lower electricity prices and higher photovoltaic output to reduce electricity bills; smart curtains can automatically adjust their opening and closing based on outdoor sunlight intensity, saving energy consumption for lighting and air conditioning.

[0031] 2) In microgrid scenarios, equipment scheduling methods can achieve unified scheduling and management of all energy assets, including photovoltaic (PV), wind power, energy storage systems, and loads. Microgrids are typically located far from the main grid or aim to achieve energy self-sufficiency; therefore, their scheduling must consider both instantaneous energy supply and demand balance and long-term planning. By predicting local energy production and consumption, this method can optimize energy storage charging and discharging strategies, coordinate the complementary operation of different energy sources, and ensure a stable and efficient power supply within the microgrid. For example, during sunny days, PV systems are prioritized for power supply, and excess power is used to charge energy storage units; while at night or during cloudy or rainy weather, energy storage units discharge to supplement power demand, reducing dependence on the external grid.

[0032] 3) In energy production scenarios, especially those involving renewable energy production such as wind and solar hydrogen production, equipment scheduling methods become particularly important. In wind and solar hydrogen production systems, precise matching of electrolyzer operation with renewable energy availability is crucial. Due to the intermittent and unstable nature of photovoltaic and wind power generation, scheduling methods can rationally arrange the start-up time of electrolyzers based on predicted energy output, ensuring hydrogen production occurs at the time of lowest energy cost and highest output, thereby improving energy conversion efficiency and economic benefits. Furthermore, by working in conjunction with energy storage systems, hydrogen production systems can maintain stable operation even when renewable energy output is insufficient, thus achieving continuous and efficient energy production.

[0033] It should be noted that the first piece of equipment mentioned above is a dispatchable piece of equipment. Dispatchable equipment can include, but is not limited to, various types of equipment such as production capacity, energy consumption, and energy storage.

[0034] Specifically, when the above-mentioned device scheduling method is applied to a smart home scenario, the first device may be, but is not limited to, any schedulable household appliance in the smart home system, such as a washing machine, a photovoltaic system, an energy storage system, etc.

[0035] Furthermore, when the above-mentioned equipment scheduling method is applied to a microgrid scenario, the first equipment may be, but is not limited to, distributed generation equipment (e.g., photovoltaic equipment), energy storage equipment, smart loads, energy conversion equipment, etc. When the above-mentioned equipment scheduling method is applied to a wind-solar hydrogen production scenario, the first equipment may be, but is not limited to, an electrolyzer, an energy storage system, a photovoltaic system, etc.

[0036] It should be noted that each device may, but is not limited to, be configured with a different scheduling cycle. For example, the operating cycle of a washing machine may be one day, while the scheduling cycle of a photovoltaic system may be 24 hours a day. The first operating cycle here may, but is not limited to, indicate a specific scheduling cycle associated with the first device.

[0037] Optionally, in this embodiment, the aforementioned first scheduling plan is a scheduling instruction formulated by the scheduling module for the first device, which should be followed during the first operating cycle. For example, the scheduling plan for the washing machine might be to operate between 10:00 AM and 11:00 AM.

[0038] It's important to note that the generation time for different types of scheduling plans is related to the device's operating cycle. That is, a scheduling plan for the device to be used during its operating cycle needs to be generated before the device's operating cycle begins. Taking a washing machine in a smart home scenario as an example, if the user sets it to be scheduled once a day, then its scheduling cycle is 24 hours, and the expected scheduling plan is obtained the day before. However, some other household appliances, unlike washing machines, may only be used once a week, in which case the expected scheduling plan is obtained a week in advance.

[0039] S104, if the first running data and the first scheduling plan configured for the first device do not match, obtain the abnormal response strategy corresponding to the first device. The first scheduling plan is used to indicate the scheduling action to be performed by the first device in the first running cycle, and the abnormal response strategy is a pre-set abnormal response strategy or a response to the abnormal response strategy selected by the first user account.

[0040] Optionally, in this embodiment, the mismatch between the first operating data and the first scheduling plan can be, but is not limited to, indicating a difference between the first operating data and the first scheduling plan in terms of time or value, i.e., the actual operating state of the equipment does not match the expected plan. For example, the equipment operating time may not match the operating time indicated by the first scheduling plan, the equipment may be damaged, the equipment may be shut down, the equipment power may not match the power indicated by the first scheduling plan, etc., and this embodiment does not limit this.

[0041] Furthermore, the above-mentioned anomaly response strategy can be a pre-configured strategy by the user, or a strategy temporarily selected by the user from the set of anomaly response strategies. This embodiment does not limit this.

[0042] S106, Generate a second scheduling plan according to the anomaly response strategy, and schedule the first device according to the second scheduling plan during the remaining period of the first operating cycle.

[0043] It should be noted that the above-mentioned generation of a second scheduling plan based on the anomaly response strategy may include, but is not limited to, regenerating a new second scheduling strategy, or selecting a scheduling plan from a pre-generated scheduling plan. In this embodiment, no limitation is imposed on this.

[0044] It should be noted that the above-mentioned generation of the second scheduling plan based on the anomaly response strategy may include, but is not limited to: generating the second scheduling plan based on the pre-configured first anomaly response strategy; or generating the second scheduling plan based on the second anomaly response strategy selected from the anomaly response strategy set by the first user account, wherein the anomaly response strategy set includes multiple anomaly response strategies.

[0045] Optionally, the aforementioned second scheduling plan is a new scheduling plan generated based on anomaly response strategies when anomalies occur between the first scheduling plan and actual operating data. It aims to correct or compensate for abnormal situations and optimize equipment operation. For example, if a washing machine fails to operate between 10:00 and 11:00 AM, the second scheduling plan might adjust the operating time to a later time in the afternoon based on a re-planned scheduling schedule. As another example, assuming the scheduling cycle for photovoltaic or energy storage equipment is 24 hours a day (0:00-24:00), and a scheduling anomaly occurs at 11:00 AM following the original scheduling plan, the scheduling equipment will re-derive the scheduling plan for the 11:00-24:00 period of that day.

[0046] It should be noted that scheduling the first device according to the second scheduling plan during the remaining period of the first operating cycle may include, but is not limited to, sending scheduling instructions to the control device used to control the first device according to the second scheduling plan during the remaining period of the first operating cycle.

[0047] Optionally, the aforementioned scheduling instructions may be, but are not limited to, start / stop instructions, power adjustment instructions, mode switching instructions, timetable adjustment instructions, priority setting instructions, etc., and are not limited to this in this embodiment.

[0048] It should be noted that in some scenarios, such as smart home scenarios, steps S102 to S106 above can be performed by the energy manager, but are not limited to.

[0049] In this embodiment, first operating data corresponding to the current moment of a first device running within a first operating cycle is obtained. If the first operating data does not match the first scheduling plan configured for the first device, an anomaly response strategy corresponding to the first device is obtained. The first scheduling plan indicates the scheduling actions to be performed by the first device in the first operating cycle, and the anomaly response strategy is a pre-set strategy or a strategy selected by a first user account. A second scheduling plan is generated based on the anomaly response strategy, and the first device is scheduled according to the second scheduling plan during the remaining period of the first operating cycle. In other words, by continuously collecting the actual operating data of the device within the operating cycle, the real-time status of the device can be grasped, providing basic data for subsequent anomaly detection and response strategy selection. Then, when the actual operating data of the device does not match the preset scheduling plan, the abnormal state can be quickly identified, avoiding scheduling failures caused by the failure to adjust the scheduling plan in time due to changes in device status. Next, after detecting an abnormal device operation, a new second scheduling plan is generated based on the anomaly response strategy. This means that even if the device deviates from the initial preset path, a rapid response can be made to adjust the scheduling plan to adapt to the new operating conditions, ensuring the effectiveness of device scheduling and the overall operating efficiency of the system. Next, during the remaining time of the first operating cycle, the scheduling equipment will adjust the scheduling of the first device in real time according to the second scheduling plan, ensuring that the device operates according to the latest scheduling plan, thereby improving the timeliness and accuracy of scheduling instructions. In summary, the embodiments of this application significantly improve the real-time performance, flexibility, and intelligence of device scheduling, solving the technical problem of low device scheduling flexibility in the prior art, enabling device scheduling to better adapt to the dynamic changes in device operation, and improving the overall operating efficiency of the system and user satisfaction.

[0050] As an optional approach, generating a second scheduling plan based on the anomaly response strategy includes:

[0051] A second scheduling plan is generated based on the pre-configured first anomaly response strategy; or

[0052] A second scheduling plan is generated based on the second exception handling strategy selected from the exception handling strategy set by the first user account. The exception handling strategy set includes multiple exception handling strategies.

[0053] It should be noted that the above-mentioned first exception handling strategy is the default exception response method in the first exception handling mode. That is, the user does not need to select an exception handling strategy every time an exception occurs. The exception handling device will automatically use the default exception handling strategy preset by the user or the system to handle it. The default handling strategy can be selected from the strategy pool or can be marked by the user in advance in the strategy pool. In this embodiment, there is no limitation on this.

[0054] It should be noted that the above set of anomaly response strategies is a collection of a series of anomaly response strategies, covering different responses that different devices may take when encountering scheduling anomalies. The above anomaly response modes are the methods for selecting strategies.

[0055] Optionally, the aforementioned second exception handling strategy is an exception response method specified by the user in real time under the second exception handling mode. When an exception occurs, the system will send a notification to the user's primary user account, requiring the user to select or input a specific exception handling strategy. This allows the user to make an immediate decision based on the current situation. That is, when a scheduling exception occurs, the exception handling settings module will send a real-time notification to the user, allowing the user to temporarily select from the strategy pool.

[0056] It should be noted that the aforementioned first user account may be, but is not limited to, an account used to log in to the management software. Users can configure the above-mentioned anomaly response modes, anomaly response strategies, and scheduling plans through the management software. Specifically, the aforementioned management software may be, but is not limited to, instructing home energy management software, microgrid management software, or hydrogen production system management software; this embodiment does not impose any limitations on this.

[0057] In this embodiment, a second scheduling plan is generated based on a pre-configured first anomaly response strategy; or a second scheduling plan is generated based on a second anomaly response strategy selected from a set of anomaly response strategies by a first user account, wherein the set of anomaly response strategies includes multiple anomaly response strategies. In other words, this embodiment generates an alternative plan by using a preset anomaly response strategy or a user-selected strategy. This enhances the system's flexibility and user control over the scheduling strategy. Users can choose anomaly response strategies based on their individual needs and preferences, rather than relying solely on the system's default strategy. This allows the system to better meet the specific needs of users, improving the personalization and efficiency of energy scheduling.

[0058] As an optional approach, the second scheduling plan is generated based on the second exception handling strategy selected from the exception handling strategy set by the first user account, including:

[0059] If the second anomaly response strategy belongs to the first type of strategy, the second scheduling plan is generated according to the first preset algorithm.

[0060] It should be noted that the first preset algorithm mentioned above is the scheduling plan generation algorithm used by default by the scheduling module. Specifically, the type of the first preset algorithm may be related to, but is not limited to, specific system requirements, and is not limited in this embodiment.

[0061] For example, but not limited to, the above steps can be illustrated using the following examples. For photovoltaic (PV) and energy storage devices: the scheduling module uses its current algorithm to calculate the scheduling plan for the remaining period. For instance, assuming the PV / energy storage scheduling period is 24 hours a day (0:00-24:00), and the PV / energy storage system experiences a scheduling anomaly at 11:00 AM, the scheduling module will recalculate the PV / energy storage scheduling plan for 11:00 AM to 24:00 AM and push it to the corresponding devices. For schedulable loads (such as household appliances): the scheduling module uses its corresponding algorithm to calculate the operating time of the load in the remaining period. It should be noted that the scheduling period for each load is independent and can differ. For example, a washing machine is originally scheduled to operate from 10:00 AM to 11:00 AM. However, due to some reason, it is detected that the washing machine is not operating normally from 10:00 AM to 11:00 AM. The scheduling module will then recalculate the washing machine's operating time for the remaining period from 11:00 AM to 24:00 AM and send it to the washing machine control device.

[0062] If the second anomaly response strategy belongs to the second type of strategy, a second scheduling plan is generated according to the second preset algorithm configured by the first user account, or the candidate scheduling plan configured by the first user account is determined as the second scheduling plan.

[0063] Optionally, the second scheduling plan is generated according to the second preset algorithm configured by the first user account, or the candidate scheduling plan configured by the first user account is determined as the second scheduling plan. This can be, but is not limited to, instructions, allowing users to set individual scheduling plans for each device after a scheduling anomaly occurs. For example, for photovoltaic and energy storage devices: users can pre-set the inference algorithm after a scheduling anomaly occurs. Common algorithms include: artificial intelligence algorithms, expert experience algorithms, etc. For schedulable loads (such as home appliances): users can pre-set the fixed working time after a scheduling anomaly occurs. Taking a washing machine as an example, if the user sets the fixed backup working time after an anomaly occurs to 7 PM to 8 PM, and the washing machine experiences a scheduling anomaly between 10 PM and 11 PM, the scheduling module does not need to recalculate the scheduling time and will directly control the device to send the scheduling plan for 7 PM to 8 PM. If the washing machine experiences a scheduling anomaly between 8 PM and 9 PM, the scheduling module will not send a scheduling plan in the current cycle.

[0064] If the second anomaly response strategy belongs to the third type of strategy, a second scheduling plan is generated to indicate that scheduling of the first device should be abandoned for the remaining period.

[0065] In this application embodiment, when the second anomaly response strategy belongs to the first type of strategy, a second scheduling plan is generated according to the first preset algorithm; when the second anomaly response strategy belongs to the second type of strategy, a second scheduling plan is generated according to the second preset algorithm configured by the first user account, or the candidate scheduling plan configured by the first user account is determined as the second scheduling plan; when the second anomaly response strategy belongs to the third type of strategy, a second scheduling plan is generated to indicate that scheduling of the first device should be abandoned in the remaining period. In other words, this application embodiment provides multiple specific ways to generate a second scheduling plan based on the anomaly response strategy selected by the first user account, including using a preset algorithm, a configured algorithm, or abandoning scheduling. In other words, this application embodiment provides diverse adjustment strategies that can optimize the scheduling plan according to the specific type of device anomaly and user instructions. For example, for photovoltaic systems, AI algorithms can be used to dynamically adjust the scheduling plan; for energy storage systems, users may choose to replace the original planned scheduling with a self-consumption mode; for some non-critical devices, scheduling can be stopped directly in the current period to save energy or avoid cost increases. The selection of these strategies helps to improve energy utilization efficiency and user satisfaction while ensuring system stability.

[0066] As an optional approach, after acquiring the first operational data generated by the first device operating within the first operational cycle at the current moment, one of the following is also included:

[0067] If the current time is within the first time interval and the first operating state of the first device is inconsistent with the second operating state, it is determined that the first operating data and the first scheduling plan do not match. The first scheduling plan is used to instruct the first device to operate according to the second operating state within the first time interval.

[0068] It should be noted that the aforementioned first time interval refers to the time window reserved in the equipment scheduling plan for a specific operating state. It can be any time period within the equipment's operating cycle, such as 10:00 AM to 11:00 AM.

[0069] Furthermore, the aforementioned first operating state refers to the actual working condition of the equipment at a certain moment, such as the washing machine being in standby mode or the air conditioner being turned off.

[0070] Optionally, the aforementioned second operating state is used to indicate the operating mode that the first device is expected to be in during the first time interval in the scheduling plan, such as on, off, low energy consumption, etc.

[0071] In other words, in some embodiments, when the operating state of the first device within a first time interval is detected to be inconsistent with the second operating state specified in the first scheduling plan, a scheduling anomaly will be identified. For example, suppose the scheduling plan for the washing machine specifies that it should run from 10:00 to 11:00 AM (second operating state), but the data acquisition module finds that the washing machine actually starts running at 10:30 AM (first operating state), which constitutes a mismatch between the first operating data and the first scheduling plan.

[0072] If the first power consumed by the first device in the first operating cycle is not within the first power range, it is determined that the first operating data and the first scheduling plan do not match, wherein the first scheduling plan is used to indicate that the power consumed by the first device in the first operating cycle is within the first power range.

[0073] Optionally, the first operating cycle mentioned above is used to represent a complete time period of the equipment scheduling plan, such as 24 hours.

[0074] It should be noted that the aforementioned first power includes the total power consumption of the equipment at all times during the first operating cycle.

[0075] Furthermore, the aforementioned first power range is the range of maximum and minimum power consumption allowed for the equipment during the first operating cycle as specified in the scheduling plan.

[0076] Optionally, the aforementioned determination of a mismatch between the first operating data and the first scheduling plan is used to indicate that when the power consumption of the first device exceeds a preset upper limit or falls below a preset lower limit, a scheduling anomaly is considered to exist. For example, if the first scheduling plan stipulates that the refrigerator's power consumption should be between 50 watts and 100 watts per day, but the data acquisition module shows that the refrigerator's actual power consumption reached 120 watts on a certain day, this constitutes a mismatch between the first operating data and the first scheduling plan.

[0077] If the amount of energy generated by the first device during the first operating cycle is not within the first energy quantity range, it is determined that the first operating data and the first scheduling plan do not match. The first scheduling plan is used to instruct the first device to generate a predetermined amount of energy during the first operating cycle, and the predetermined amount is within the first energy quantity range.

[0078] It should be noted that the aforementioned first energy quantity refers to the cumulative amount of energy generated by the first equipment during the first operating cycle, such as the total electricity generated by photovoltaic power generation or the total hydrogen production of the hydrogen production system.

[0079] Furthermore, the aforementioned first energy quantity range is the upper and lower limit range of energy generation set for the first equipment in the scheduling plan.

[0080] Optionally, the above-mentioned determination of a mismatch between the first operating data and the first scheduling plan is used to indicate that the system determines whether there is a scheduling anomaly by comparing the actual energy generated by the first device with the range allowed in the plan. For example, if the photovoltaic system plans to generate 300 kWh of electricity per hour (first operating cycle) (first energy quantity range), but actually only generates 200 kWh, then the system considers the first operating data to be mismatched with the first scheduling plan.

[0081] If the equipment detection result corresponding to the first device indicates that the first device is faulty, it is determined that the first operating data and the first scheduling plan are mismatched.

[0082] Optionally, the above-mentioned equipment detection results are used to represent the data collected by the system through sensors or detection modules, and are used to assess the operating status and health level of the equipment.

[0083] It should be noted that the aforementioned first equipment malfunction includes, but is not limited to, situations where the equipment reports error codes, the equipment performance is significantly lower than expected, or the equipment fails to respond to scheduling instructions.

[0084] Furthermore, the aforementioned determination of a mismatch between the first operating data and the first scheduling plan indicates that the system, through equipment fault status identification, determines that the actual operating condition of the first device (first operating data) cannot conform to the original scheduling plan (first scheduling plan). For example, suppose the original scheduling plan for the energy storage system (first device) is to charge it to full capacity during a low electricity price period (second operating state), but the equipment detection results show that the energy storage system has battery damage and cannot receive power normally (first operating state). This constitutes a mismatch between the first operating data and the first scheduling plan.

[0085] It should be noted that, but not limited to, the anomaly detection module can be used to compare the first operating data and the first scheduling plan, and the scheduling module can be used to send an acquisition request to the anomaly response device to request an anomaly response strategy. In some embodiments, both the anomaly detection module and the scheduling module are configured in the energy manager, such as a home energy manager. In other embodiments, the anomaly detection module is configured in the hydrogen production energy manager, and the scheduling module is configured in the hydrogen production digital computing controller.

[0086] In this embodiment, if the current time is within a first time interval and the first operating state of the first device is inconsistent with its second operating state, it is determined that the first operating data and the first scheduling plan do not match. The first scheduling plan instructs the first device to operate according to the second operating state within the first time interval. Alternatively, if the first power consumed by the first device within the first operating cycle is not within the first power range, it is determined that the first operating data and the first scheduling plan do not match. The first scheduling plan instructs the first device to consume power within the first operating cycle within the first power range. Or, if the amount of energy generated by the first device within the first operating cycle is not within the first energy quantity range, it is determined that the first operating data and the first scheduling plan do not match. The first scheduling plan instructs the first device to generate a predetermined amount of energy within the first operating cycle, and the predetermined amount is within the first energy quantity range. Or, if the device detection result corresponding to the first device indicates a fault in the first device, it is determined that the first operating data and the first scheduling plan do not match. In other words, using this embodiment, multiple scenarios are used to determine whether the device operating data matches the scheduling plan within the first operating cycle, including abnormalities in operating state, power consumption, and energy generation, as well as device faults. By employing the embodiments of this application, and through comprehensive detection of the operating parameters of the equipment, abnormal situations in equipment scheduling can be identified more accurately, and corresponding response strategies can be adopted for adjustment. This ensures that the system responds promptly to changes in equipment status, avoids unnecessary energy consumption, and improves the overall scheduling accuracy.

[0087] As an optional approach, after obtaining the first operating data corresponding to the current moment of the first device running within the first operating cycle, the method further includes:

[0088] S1, if the first running data and the first scheduling plan do not match, find the second device that is associated with the first device.

[0089] Optionally, the second device may be, but is not limited to, another device that has an interactive or dependent relationship with the first device in terms of energy use, storage, or production. For example, a washing machine may be associated with an energy storage system, as the energy storage system can provide the electricity required for the washing machine to operate.

[0090] Furthermore, the aforementioned correlation refers to the ability of the operating status or scheduling plan of one device to affect the operating efficiency or scheduling of another device. For example, if a washing machine requires electricity, and the electricity comes from a photovoltaic system and an energy storage system, then there is a correlation between the washing machine and the energy storage system.

[0091] Optionally, in the case where the first operating data and the first scheduling plan do not match, the above-mentioned method of finding a second device that is associated with the first device may be used, but is not limited to, to indicate that when the operating data of the first device does not match the scheduling plan, other devices that may need to be coordinated to adjust their operation will be identified and located in order to cope with the decline in overall scheduling efficiency.

[0092] S2, if a second device is found, obtain the third anomaly response strategy corresponding to the second device.

[0093] Optionally, the aforementioned third anomaly response strategy is a strategy pre-set for the second device or selected by the user to deal with anomalies related to the first device, ensuring the overall operating efficiency and resource optimization of the system.

[0094] It should be noted that the above-mentioned search for second devices that are related to the first device can be achieved, but is not limited to, by the following methods: analyzing the energy demand pattern of the first device and determining which devices (such as energy storage systems and photovoltaic systems) may need to adjust their scheduling to compensate for the anomalies of the first device.

[0095] Furthermore, when the second device is located, obtaining the third anomaly handling strategy corresponding to the second device can be used, but is not limited to, to indicate that when the second device that needs adjustment is determined, an anomaly handling strategy for the second device will be searched or selected by the user to ensure that the anomaly of the first device will not affect the operating efficiency of the entire system.

[0096] S3 generates a third scheduling plan based on the third anomaly response strategy, and schedules the second device according to the third scheduling plan within the remaining period of the current operating cycle of the second device.

[0097] It should be noted that the aforementioned third scheduling plan is a new scheduling plan generated based on the third anomaly response strategy. It is used to adjust the operation of the second device to cope with the abnormal scheduling of the first device, thereby minimizing the impact on the overall system operation.

[0098] Optionally, the above-mentioned generation of a third scheduling plan based on the third anomaly response strategy, and scheduling of the second device according to the third scheduling plan within the remaining period of the current operating cycle of the second device, indicates that: a new scheduling plan will be generated for the second device according to the selected third anomaly response strategy, and the operation of the second device will be adjusted according to this plan within the remaining time of the current operating cycle to optimize resource utilization and system performance.

[0099] In this embodiment, when the first operating data and the first scheduling plan do not match, a second device associated with the first device is located. If the second device is found, a third anomaly response strategy corresponding to the second device is obtained. A third scheduling plan is generated based on the third anomaly response strategy, and the second device is scheduled according to the third scheduling plan within the remaining cycle of its current operating cycle. In other words, by using this embodiment, when an anomaly in the scheduling of the first device is detected, a second device associated with it can be located, and a third scheduling plan can be generated based on the anomaly response strategy of the second device, thereby scheduling the second device within its operating cycle. Its technical effect is that, through coordinated scheduling between devices, the impact of the first device's anomaly can be effectively compensated, maintaining the overall system operating efficiency. For example, if the washing machine fails to operate as planned, the system may adjust the charging and discharging plan of the energy storage system to ensure sufficient power supply when the user uses the washing machine at other times. This coordinated scheduling mechanism improves the overall adaptability and resource optimization capability of the system.

[0100] As an optional approach, scheduling the first device according to the second scheduling plan during the remaining period of the first operating cycle includes:

[0101] If the first device is a smart home device, during the remaining period of the first operating cycle, a scheduling instruction is sent to the control device used to control the first device according to the second scheduling plan, so that the first device adjusts its operating state according to the scheduling instruction.

[0102] Optionally, adjusting the operating status of the first device according to the scheduling instructions may include, but is not limited to, changing the operating time, operating mode, or energy consumption level of the first device according to the received scheduling instructions, so as to meet the requirements of the second scheduling plan.

[0103] For example, suppose a user sets a default response strategy on the anomaly response device to run according to a user-defined schedule. That is, if the washing machine doesn't start between 10:00 and 11:00 AM, it will run during a user-defined standby time that evening (e.g., 7:00 PM to 8:00 PM). Based on the user's anomaly response strategy, the anomaly response device will generate a new scheduling plan, allowing the washing machine to run between 7:00 and 8:00 PM. During the remaining operating cycle of the day (from 10:00 AM to midnight in this case), the scheduling device sends scheduling instructions to the washing machine according to the generated second scheduling plan. Upon receiving the scheduling instructions, the washing machine automatically adjusts its operating status to ensure it starts between 7:00 and 8:00 PM, instead of the originally planned 10:00 to 11:00 AM, thus adapting to changes in the user's lifestyle and avoiding unnecessary energy waste.

[0104] In this embodiment, when the first device is a smart home device, during the remaining period of the first operating cycle, a scheduling instruction is sent to the control device used to control the first device according to the second scheduling plan, so that the first device adjusts its operating state according to the scheduling instruction. In other words, using this embodiment, when the first device is a smart home device, the operating state of the device is adjusted according to the second scheduling plan. By precisely controlling the operation of smart home devices, the system can respond more intelligently to device scheduling anomalies, such as rescheduling the washing machine during periods of low electricity prices, which not only saves energy costs but also improves user satisfaction and convenience with the smart home system.

[0105] As an optional approach, scheduling the first device according to the second scheduling plan during the remaining period of the first operating cycle also includes:

[0106] When the first device is a microgrid node device, during the remaining period of the first operating cycle, a scheduling instruction is sent to the control device used to control the first device in accordance with the second scheduling plan, so that the first device performs at least one of the following tasks in accordance with the scheduling instruction: power resource production task, power resource release task, and power resource storage task.

[0107] Optionally, the aforementioned microgrid node devices are any node devices in the microgrid architecture that can produce, consume, or store electricity, including but not limited to photovoltaic systems, energy storage batteries, electric vehicle charging piles, home appliances, etc., and are not limited in this embodiment.

[0108] Furthermore, the aforementioned power resource production task refers to the task of generating power resources by production equipment (such as photovoltaic panels and wind turbines) in the microgrid according to the dispatch plan, which is an important component of microgrid energy management. The power resource release task refers to the task of energy storage devices in the microgrid releasing stored energy according to the dispatch plan to supply power to the grid or other equipment, which helps balance grid demand and the output of production equipment. The power resource storage task refers to the task of storing excess power resources in the microgrid into energy storage devices for later use, which is a key measure to achieve optimized energy dispatch and reduce waste.

[0109] For example, in a home microgrid, photovoltaic systems, energy storage batteries, electric vehicle charging stations, and household appliances (such as washing machines and air conditioners) are all microgrid node devices. Suppose that the washing machine is scheduled to work between 10:00 and 11:00 AM, but the user does not put clothes in the washing machine before 10:00 AM, causing the washing machine to not start as scheduled, resulting in a scheduling anomaly.

[0110] At this point, the home energy manager (acting as an anomaly response device) detects a mismatch between the washing machine's actual operating data and the scheduling plan. Based on the user-defined anomaly response strategy (such as "execute according to user-defined plan"), the home energy manager adjusts the washing machine's running time to 7 PM to 8 PM and sends a new scheduling command to the washing machine.

[0111] Meanwhile, considering the energy balance of the home microgrid, the home energy manager may also adjust the charging and discharging schedule of the energy storage battery to ensure that the power resources in the microgrid can be rationally allocated after the washing machine's operating time is adjusted. For example, if the washing machine is scheduled to run at night, the energy storage battery may charge during the day when photovoltaic output is high and release power at night to support the washing machine's operation, avoiding excessive pressure on the grid.

[0112] In this embodiment, when the first device is a microgrid node device, during the remaining period of the first operating cycle, a scheduling instruction is sent to the control device used to control the first device according to the second scheduling plan, so that the first device performs at least one of the following tasks according to the scheduling instruction: power resource production task, power resource release task, and power resource storage task. In other words, by using this embodiment, a new scheduling plan (i.e., the second scheduling plan) can be generated and applied in real time by detecting the mismatch between the actual operating data of the microgrid node device and the expected scheduling plan. This means that when the microgrid system faces power supply and demand imbalances, power generation efficiency fluctuations, etc., the power resource production, release, or storage strategies can be quickly adjusted to ensure dynamic optimization and balance of resources.

[0113] As an optional approach, scheduling the first device according to the second scheduling plan during the remaining period of the first operating cycle also includes:

[0114] When the first device is a node in the hydrogen production system, during the remaining period of the first operating cycle, a scheduling instruction is sent to the control device used to control the first device in accordance with the second scheduling plan, so that the first device performs at least one of the following according to the scheduling instruction: adjusting the operating status of the first device, adjusting the resource production power of the first device.

[0115] Optionally, in a hydrogen production system, each device involved in energy conversion or energy use is considered a node (i.e., a hydrogen production system node). These nodes include, but are not limited to: an electrolyzer for producing hydrogen by electrolyzing water, a storage tank for storing hydrogen, an energy storage system for adjusting energy input / output, and a control center for detecting and controlling the operation of the entire system, etc., which are not limited in this embodiment.

[0116] Furthermore, adjusting the operating state of the first device can be, but is not limited to, indicating a change in the current operating mode of a hydrogen production system node, such as switching from an operating state to a standby state, or from a low-power operating mode to a high-power operating mode. For example, if it is detected that there is sufficient and cheap electricity from the grid at night, a command can be sent to the electrolyzer to switch its operating state from "standby" to "full-power operation".

[0117] Optionally, adjusting the resource production power of the first device may include, but is not limited to, changing the energy consumption level of the hydrogen production system nodes during hydrogen production. For example, if the photovoltaic system's capacity increases, a scheduling command can be sent to the electrolyzer to increase its hydrogen production power, thereby making full use of the additional green energy.

[0118] In this embodiment, when the first device is a node in a hydrogen production system, during the remaining period of the first operating cycle, a scheduling instruction is sent to the control device used to control the first device according to the second scheduling plan, so that the first device performs at least one of the following according to the scheduling instruction: adjusting the operating status of the first device, adjusting the resource production power of the first device. In other words, using this embodiment, when the operating data of a hydrogen production system node (such as a photovoltaic system, electrolyzer, etc.) is inconsistent with the original scheduling plan, a new scheduling plan (second scheduling plan) can be generated according to the anomaly response strategy. This means that in this embodiment, the working status and production power of the hydrogen production system node can be dynamically adjusted to adapt to actual conditions, such as fluctuations in photovoltaic output caused by weather changes, or changes in energy demand caused by changes in user behavior.

[0119] According to another aspect of the embodiments of this application, a device scheduling system for implementing the above-described device scheduling method is also provided, such as... Figure 2 As shown, the above-mentioned equipment scheduling system includes: an anomaly detection module 202, an anomaly handling module 204, a scheduling module 206, a data acquisition module 208, and a control module 210, wherein:

[0120] The data acquisition module is used to collect the first operating data corresponding to the current moment of the first device running in the first operating cycle;

[0121] An anomaly detection module is used to compare the first running data with the first scheduling plan configured for the first device, and send an anomaly handling request to the anomaly handling module if the first running data and the first scheduling plan do not match.

[0122] An exception handling module is used to respond to an exception handling request and obtain the exception handling strategy corresponding to the first device. The first scheduling plan is used to indicate the scheduling action to be performed by the first device in the first running cycle. The exception handling strategy is a pre-set exception handling strategy or an exception handling strategy selected by the first user account.

[0123] The scheduling module is used to generate a second scheduling plan based on the anomaly response strategy, and send scheduling instructions to the control module according to the second scheduling plan during the remaining period of the first running cycle.

[0124] The control module is used to control the first device according to the scheduling instructions.

[0125] It should be noted that the scheduling module can be, but is not limited to, a home energy manager or a hydrogen production digital computing controller (Programmable Logic Controller, or PLC), depending on the specific application scenario.

[0126] It should be further explained that the aforementioned first device is as follows: Figure 2 The device cluster 212 shown includes multiple schedulable devices, such as home appliances (washing machines, dishwashers, dryers, etc.), energy storage, photovoltaic systems, and charging piles. The data acquisition module collects real-time operating data of the scheduled load, such as time and power, and sends data to the anomaly detection module. The scheduling module receives response strategies from the anomaly handling settings module and data from the data acquisition module, and sends scheduling instructions to the scheduled load. The anomaly detection module receives operating data from the data acquisition module and the expected scheduling plan from the scheduling module; detects whether the real-time operating data matches the expected scheduling plan; and sends anomaly handling requests to the anomaly handling module.

[0127] As an optional example, taking the application of the above-described equipment scheduling method to a home energy management scenario equipped with photovoltaic and energy storage systems as an example, the above-described equipment scheduling system can, but is not limited to, the following: Figure 3 As shown, it includes a washing machine 302, a dishwasher 304, a smart switch 1, a smart switch 2, a photovoltaic system 306, an energy storage system 308, a home energy manager 310, and home energy management software 312.

[0128] Specifically, the photovoltaic system, energy storage system, smart switch 1, and smart switch 2 form a group of dispatchable devices, each containing a corresponding data acquisition module. The home energy manager includes a scheduling module and a scheduling anomaly detection module. The home energy management software, as an anomaly handling module, allows users to select and set anomaly response strategies. The scheduling module can be, but is not limited to, an Energy Management System (EMS) controller. The scheduling anomaly detection and anomaly handling modules are separate modules. The EMS controller can be, but is not limited to, used to set corresponding control strategies. The energy storage system is controlled by the connected inverter EMS. The home energy manager can be used to formulate strategies.

[0129] As an optional example, the above-mentioned device scheduling method is applied to a home energy management scenario equipped with photovoltaic and energy storage systems, combined with... Figure 3 The system architecture described above illustrates the scheduling method with an example as follows:

[0130] Taking a certain day as the scheduling cycle for the scheduling devices as an example, the home energy manager generates scheduling plans for each device in advance, such as: washing machine: start at 10:00-11:00; dishwasher: start at 13:00-14:00; energy storage system: charge when there is excess power from the photovoltaic system, and discharge when the photovoltaic system output is insufficient; photovoltaic system: unlimited power generation.

[0131] Then, when the scheduling cycle is reached, each device will operate according to the predetermined scheduling plan. However, for some reason, the user did not put the clothes in the washing machine before 10:00 AM, causing the washing machine's internal system to fail to detect the clothes and therefore not start. At this time, the home energy manager detects the washing machine scheduling anomaly and automatically sends an anomaly handling request to the user's home energy management software. Subsequently, the home energy management software will respond according to the user's default response strategy.

[0132] Specifically, home energy management software offers the following coping strategies:

[0133] 1) The scheduling plan is re-planned; specifically, the home energy manager will recalculate the washing machine's scheduling time.

[0134] 2) Execute according to the user-defined plan. Specifically, if the energy storage system prepares the corresponding green electricity or low-priced electricity in advance, the home energy manager will send the user-defined start time to the smart switch of the washing machine and re-plan the charging and discharging plan of the energy storage.

[0135] 3) The device will no longer be scheduled for the current cycle; specifically, the home energy manager will ignore the washing machine for the remainder of the day.

[0136] 4) Send a strategy selection request to the user. Specifically, the home energy management software will prompt the user that the washing machine scheduling is abnormal and ask the user to select the current response strategy.

[0137] As another alternative example, taking the above scheduling method applied to the energy management scenario of wind and solar hydrogen production, the above scheduling system can be, but is not limited to, as follows: Figure 4 As shown, it includes: a photovoltaic system 402, an energy storage system 404, an electrolyzer 1, an electrolyzer 2, a hydrogen production PLC 406, a hydrogen production energy manager 408, and hydrogen production management software 410.

[0138] The system comprises a group of dispatchable devices, including the photovoltaic system, energy storage system, electrolyzer 1, and electrolyzer 2, each containing a corresponding data acquisition module. The hydrogen production PLC serves as the scheduling module for the electrolyzers, controlling their start-up, shutdown, and power operation. The hydrogen production energy manager includes a scheduling anomaly detection module and an anomaly response setting module. The hydrogen production management software displays the hydrogen production system page, which is a user interface allowing users to select anomaly response modes and set custom scheduling plans.

[0139] As another alternative example, taking the above scheduling method applied to the energy management scenario of wind and solar hydrogen production as an example, combined with... Figure 4 The system architecture described above illustrates the scheduling method with an example as follows:

[0140] Taking the day-ahead scheduling of electrolyzers as an example, the hydrogen production energy manager generates scheduling plans for photovoltaics, energy storage, and each electrolyzer for the next day. For example: Electrolyzer 1: Based on the AI ​​algorithm instructions built into the hydrogen production energy manager, electrolyzer 1 will operate from 10:00 to 16:00; the hydrogen production power will be 300kW from 10:00 to 11:00, 500kW from 11:00 to 14:00, and 200kW from 14:00 to 16:00; Electrolyzer 2: Based on the AI ​​algorithm instructions built into the hydrogen production energy manager, electrolyzer 2 will operate from 10:00 to 16:00; the hydrogen production power will be 200kW from 10:00 to 11:00, 400kW from 11:00 to 14:00, and 100kW from 14:00 to 16:00; Energy storage system: Operates based on instructions issued by the AI ​​algorithm built into the hydrogen production energy manager; Photovoltaic system: Unlimited power generation; Photovoltaic output power is basically consistent with the predicted curve power.

[0141] Before the equipment is scheduled to run, users can select the default response mode through the hydrogen production system page and set the default response strategy for photovoltaic anomalies: "When the deviation between the photovoltaic predicted power and the actual power is higher than a certain value, the algorithm strategy of the electrolyzer and energy storage system will be changed to a self-consumption strategy."

[0142] In actual operation, each device will operate according to the predetermined scheduling plan. However, due to the low photovoltaic forecast, the predicted power was very low at 9 o'clock, while the actual power was already relatively high, causing an anomaly in the operation of the photovoltaic system. After detecting this anomaly, the hydrogen production energy manager selects an anomaly response strategy. According to the user's settings, if the photovoltaic equipment scheduling is abnormal, the electrolyzer and energy storage algorithm strategies inside the hydrogen production energy manager will be switched to the self-consumption algorithm to make the most of photovoltaic resources and maximize photovoltaic consumption.

[0143] As another alternative example, it can be, but is not limited to, by means of... Figure 5 The following steps are illustrated to provide a general explanation of the above-mentioned equipment scheduling method:

[0144] Step S502, Strategy and mode configuration: Configure the exception handling strategy pool and exception handling mode;

[0145] Step S504: Formulate the expected plan and assign a first scheduling plan to the first device;

[0146] Step S506, data acquisition, acquiring the first operating data generated by the first device in the first operating cycle, such as power output, energy consumption, operating status, etc.

[0147] Step S508: Plan comparison. Compare the first running data with the first scheduling plan configured for the first device to check for any mismatches.

[0148] Step S510, anomaly detection: if the first running data does not match the first scheduling plan, determine that the equipment scheduling is abnormal.

[0149] Step S512, strategy acquisition: select an exception handling strategy from the exception handling strategy pool according to the exception handling mode.

[0150] Step S514: Plan generation, generating a second scheduling plan that matches the first running data.

[0151] Step S516, Instruction Sending: During the remaining time of the first operating cycle, a scheduling instruction is sent to the first device according to the second scheduling plan to adjust its operating status or resource production power.

[0152] It should be noted that, for the sake of simplicity, the foregoing method embodiments are all described as a series of actions. However, those skilled in the art should understand that this application is not limited to the described order of actions, as some steps may be performed in other orders or simultaneously according to this application. Furthermore, those skilled in the art should also understand that the embodiments described in the specification are preferred embodiments, and the actions and modules involved are not necessarily essential to this application.

[0153] According to another aspect of the embodiments of this application, an apparatus for implementing the above-described equipment scheduling method is also provided. For example... Figure 6 As shown, the device is applied to a scheduling equipment and includes:

[0154] The anomaly detection module 602 is used to obtain the first operating data corresponding to the current moment of the first device running in the first operating cycle.

[0155] An exception handling module 604 is used to obtain an exception handling strategy corresponding to the first device when the first running data and the first scheduling plan configured for the first device do not match. The first scheduling plan is used to indicate the scheduling action to be performed by the first device in the first running cycle, and the exception handling strategy is determined from the exception handling strategy pool according to the exception handling mode matched with the first device.

[0156] The scheduling module 606 is used to generate a second scheduling plan based on the anomaly response strategy, and to schedule the first device according to the second scheduling plan during the remaining period of the first operating cycle.

[0157] Optionally, in this embodiment, the scheduling module includes: a first generation unit, configured to generate a second scheduling plan according to a pre-configured first anomaly response strategy; and a second generation unit, configured to generate a second scheduling plan according to a second anomaly response strategy selected from the anomaly response strategy set by the first user account, wherein the anomaly response strategy set includes multiple anomaly response strategies.

[0158] Optionally, in this embodiment, the second generation unit is further configured to: generate a second scheduling plan according to a first preset algorithm when the second anomaly response strategy belongs to the first type of strategy; generate a second scheduling plan according to a second preset algorithm configured by the first user account when the second anomaly response strategy belongs to the second type of strategy, or determine the candidate scheduling plan configured by the first user account as the second scheduling plan; and generate a second scheduling plan to indicate abandoning the scheduling of the first device in the remaining period when the second anomaly response strategy belongs to the third type of strategy.

[0159] Optionally, the above-mentioned device further includes an anomaly detection module, configured to: determine that the first operating data and the first scheduling plan do not match when the current time is within a first time interval and the first operating state of the first device is inconsistent with the second operating state, wherein the first scheduling plan is used to instruct the first device to operate according to the second operating state within the first time interval; or determine that the first operating data and the first scheduling plan do not match when the first power consumed by the first device within the first operating cycle is not within the first power range, wherein the first scheduling plan is used to instruct the power consumed by the first device within the first operating cycle to be within the first power range; or determine that the first operating data and the first scheduling plan do not match when the amount of energy generated by the first device within the first operating cycle is not within the first energy quantity range, wherein the first scheduling plan is used to instruct the first device to generate a predetermined amount of energy within the first operating cycle, the predetermined amount being within the first energy quantity range; or determine that the first operating data and the first scheduling plan do not match when the device detection result corresponding to the first device indicates that the first device has a fault.

[0160] Optionally, in this embodiment, the above-mentioned device is further configured to: find a second device that is associated with the first device when the first running data and the first scheduling plan do not match; if the second device is found, obtain a third anomaly response strategy corresponding to the second device; generate a third scheduling plan according to the third anomaly response strategy, and schedule the second device according to the third scheduling plan within the remaining period of the current running cycle of the second device.

[0161] Optionally, in this embodiment, the scheduling module includes: a first scheduling unit, configured to send scheduling instructions to a control device for controlling the first device according to a second scheduling plan during the remaining period of the first operating cycle when the first device is a smart home device, so that the first device adjusts its operating state according to the scheduling instructions.

[0162] Optionally, in this embodiment, the scheduling module further includes: a second scheduling unit, configured to, in the remaining period of the first operating cycle when the first device is a microgrid node device, send a scheduling instruction to the control device for controlling the first device according to the second scheduling plan, so that the first device performs at least one of the following according to the scheduling instruction: power resource production task, power resource release task, and power resource storage task.

[0163] Optionally, in this embodiment, the scheduling module further includes: a third scheduling unit, configured to send a scheduling instruction to the control device for controlling the first device in accordance with a second scheduling plan during the remaining period of the first operating cycle when the first device is a node of the hydrogen production system, so that the first device performs at least one of the following according to the scheduling instruction: adjusting the operating status of the first device, adjusting the resource production power of the first device.

[0164] For specific implementation examples, please refer to the examples shown in the above device scheduling method. This embodiment will not be repeated here.

[0165] According to another aspect of the embodiments of this application, an electronic device for implementing the above-described device scheduling method is also provided, including a memory and a processor, wherein the memory stores a computer program and the processor is configured to run the computer program to perform the steps in any of the above-described method embodiments.

[0166] In one exemplary embodiment, the electronic device may further include a transmission device and an input / output device, wherein the transmission device is connected to the processor and the input / output device is connected to the processor.

[0167] According to one aspect of this application, a computer program product is provided, comprising a computer program / instructions containing program code for performing the methods described above. In such embodiments, the computer program can be downloaded and installed from a network via a communication component, and / or installed from a removable medium. When the computer program is executed by a central processing unit, it performs various functions provided in the embodiments of this application.

[0168] According to one aspect of this application, another computer program product is also provided, including a non-volatile computer-readable storage medium storing a computer program that, when executed by a processor, implements the steps of the methods in various embodiments of this application.

[0169] According to one aspect of this application, a computer-readable storage medium is provided, wherein a processor of a computer device reads computer instructions from the computer-readable storage medium and executes the computer instructions, causing the computer device to perform the above-described method.

[0170] Optionally, in this embodiment, the computer-readable storage medium may be configured to store a computer program for performing the following steps:

[0171] S1, Obtain the first operating data corresponding to the current moment of the first device running in the first operating cycle;

[0172] S2, if the first running data and the first scheduling plan configured for the first device do not match, obtain the abnormal response strategy corresponding to the first device. The first scheduling plan is used to indicate the scheduling action to be performed by the first device in the first running cycle, and the abnormal response strategy is a pre-set abnormal response strategy or a response to the abnormal response strategy selected by the first user account.

[0173] S3, generate a second scheduling plan based on the anomaly response strategy, and schedule the first device according to the second scheduling plan during the remaining period of the first operating cycle.

[0174] Optionally, in the embodiments of this application, the terms "module" or "unit" refer to a computer program or part of a computer program with a predetermined function, which works together with other related parts to achieve a predetermined goal, and can be implemented wholly or partially using software, hardware (such as processing circuitry or memory), or a combination thereof. Similarly, a processor (or multiple processors or memory) can be used to implement one or more modules or units. Furthermore, each module or unit can be part of an overall module or unit that includes the functionality of that module or unit.

[0175] Optionally, in this embodiment, those skilled in the art will understand that all or part of the steps in the various methods of the above embodiments can be implemented by a program instructing the hardware related to the terminal device. The program can be stored in a computer-readable storage medium, which may include: flash drive, read-only memory (ROM), random access memory (RAM), disk or optical disk, etc.

[0176] If the integrated units in the above embodiments are implemented as software functional units and sold or used as independent products, they can be stored in the aforementioned computer-readable storage medium. Based on this understanding, the technical solution of this application, in essence, or the part that contributes to the prior art, or all or part of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions to cause one or more computer devices (which may be personal computers, servers, or network devices, etc.) to execute all or part of the steps of the methods described in the various embodiments of this application.

[0177] In the above embodiments of this application, the descriptions of each embodiment have different focuses. For parts not described in detail in a certain embodiment, please refer to the relevant descriptions of other embodiments.

[0178] In the several embodiments provided in this application, it should be understood that the disclosed client can be implemented in other ways. The device embodiments described above are merely illustrative; for example, the division of units is only a logical functional division, and in actual implementation, there may be other division methods. For example, multiple units or components may be combined or integrated into another system, or some features may be ignored or not executed. Furthermore, the coupling or direct coupling or communication connection shown or discussed may be through some interfaces, indirect coupling or communication connection between units or modules, and may be electrical or other forms.

[0179] The units described as separate components may or may not be physically separate. The components shown as units may or may not be physical units; that is, they may be located in one place or distributed across multiple network units. Some or all of the units can be selected to achieve the purpose of this embodiment according to actual needs.

[0180] Furthermore, the functional units in the various embodiments of this application can be integrated into one processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit. The integrated unit can be implemented in hardware or as a software functional unit.

[0181] The above description is only a preferred embodiment of this application. It should be noted that for those skilled in the art, several improvements and modifications can be made without departing from the principle of this application, and these improvements and modifications should also be considered within the scope of protection of this application.

Claims

1. A method for scheduling equipment, characterized in that, include: Obtain the first operating data corresponding to the current moment of the first device running within the first operating cycle; If the first running data and the first scheduling plan configured for the first device do not match, an anomaly response strategy corresponding to the first device is obtained. The first scheduling plan is used to indicate the scheduling action to be performed by the first device in the first running cycle. The anomaly response strategy is a pre-set anomaly response strategy or a response to an anomaly response strategy selected by the first user account. A second scheduling plan is generated based on the anomaly response strategy, and the first device is scheduled according to the second scheduling plan during the remaining period of the first operating cycle.

2. The method according to claim 1, characterized in that, The step of generating the second scheduling plan based on the anomaly response strategy includes: The second scheduling plan is generated based on the pre-configured first anomaly response strategy; or The second scheduling plan is generated based on the second anomaly response strategy selected from the anomaly response strategy set by the first user account, wherein the anomaly response strategy set includes multiple anomaly response strategies.

3. The method according to claim 2, characterized in that, The step of generating the second scheduling plan based on the second anomaly response strategy selected from the anomaly response strategy set by the first user account includes: If the second anomaly response strategy belongs to the first type of strategy, the second scheduling plan is generated according to the first preset algorithm; If the second anomaly response strategy belongs to the second type of strategy, the second scheduling plan is generated according to the second preset algorithm configured by the first user account, or the candidate scheduling plan configured by the first user account is determined as the second scheduling plan; If the second anomaly response strategy belongs to the third type of strategy, a second scheduling plan is generated to indicate that scheduling of the first device should be abandoned during the remaining period.

4. The method according to claim 1, characterized in that, After acquiring the first operating data generated by the first device operating within the first operating cycle at the current moment, the method further includes: If the current time falls within a first time interval and the first operating state of the first device is inconsistent with its second operating state, it is determined that the first operating data and the first scheduling plan do not match. The first scheduling plan is used to instruct the first device to operate according to the second operating state within the first time interval; or If the first power consumed by the first device during the first operating cycle is not within the first power range, it is determined that the first operating data and the first scheduling plan do not match, wherein the first scheduling plan is used to indicate that the power consumed by the first device during the first operating cycle is within the first power range; or If the amount of energy generated by the first device during the first operating cycle is not within a first energy quantity range, it is determined that the first operating data and the first scheduling plan are mismatched. The first scheduling plan is used to instruct the first device to generate a predetermined amount of energy during the first operating cycle, where the predetermined amount falls within a first energy quantity range; or If the device detection result corresponding to the first device indicates that the first device is faulty, it is determined that the first operating data and the first scheduling plan do not match.

5. The method according to claim 1, characterized in that, After obtaining the first operating data corresponding to the current moment of the first device running within the first operating cycle, the process also includes: If the first operating data and the first scheduling plan do not match, find a second device that is associated with the first device; If the second device is located, obtain the third anomaly response strategy corresponding to the second device; A third scheduling plan is generated based on the third anomaly response strategy, and the second device is scheduled according to the third scheduling plan within the remaining period of the current operating cycle of the second device.

6. The method according to any one of claims 1 to 5, characterized in that, The step of scheduling the first device according to the second scheduling plan during the remaining period of the first operating cycle includes: If the first device is a smart home device, during the remaining period of the first operating cycle, a scheduling instruction is sent to the control device used to control the first device according to the second scheduling plan, so that the first device adjusts its operating state according to the scheduling instruction.

7. The method according to any one of claims 1 to 5, characterized in that, The step of scheduling the first device according to the second scheduling plan during the remaining period of the first operating cycle further includes: When the first device is a microgrid node device, during the remaining period of the first operating cycle, a scheduling instruction is sent to the control device used to control the first device according to the second scheduling plan, so that the first device performs at least one of the following according to the scheduling instruction: power resource production task, power resource release task, and power resource storage task.

8. The method according to any one of claims 1 to 5, characterized in that, The step of scheduling the first device according to the second scheduling plan during the remaining period of the first operating cycle further includes: When the first device is a node in a hydrogen production system, during the remaining period of the first operating cycle, a scheduling instruction is sent to the control device used to control the first device according to the second scheduling plan, so that the first device performs at least one of the following according to the scheduling instruction: adjusting the operating status of the first device, adjusting the resource production power of the first device.

9. An equipment scheduling device, characterized in that, include: The anomaly detection module is used to acquire the first operating data generated by the first device within the first operating cycle; An exception handling module is used to obtain an exception handling strategy corresponding to the first device when the first running data and the first scheduling plan configured for the first device do not match. The first scheduling plan is used to indicate the scheduling action to be performed by the first device in the first running cycle. The exception handling strategy is determined from the exception handling strategy pool according to the exception handling mode matched with the first device. The scheduling module is used to generate a second scheduling plan according to the anomaly response strategy, and to schedule the first device according to the second scheduling plan during the remaining period of the first operating cycle.

10. An equipment scheduling system, characterized in that, include: The system includes an anomaly detection module, an anomaly handling module, a scheduling module, a data acquisition module, and a control module, among which: The data acquisition module is used to acquire the first operating data corresponding to the current moment of the first device running in the first operating cycle. The anomaly detection module is used to compare the first running data with the first scheduling plan configured for the first device, and send an anomaly handling request to the anomaly handling module if the first running data and the first scheduling plan do not match. The exception handling module is used to respond to the exception handling request and obtain the exception handling strategy corresponding to the first device. The first scheduling plan is used to indicate the scheduling action to be performed by the first device in the first running cycle. The exception handling strategy is a pre-set exception handling strategy or an exception handling strategy selected by the first user account. The scheduling module is used to generate a second scheduling plan according to the anomaly response strategy, and send scheduling instructions to the control module according to the second scheduling plan during the remaining period of the first running cycle. The control module is used to control the first device according to the scheduling instructions.

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