Cloud edge computing power collaborative scheduling method and device and cloud server

Abstract

The invention discloses a cloud edge computing power collaborative scheduling method and device and a cloud server. According to the invention, through collecting operation data of each node of a power grid, a system firstly evaluates whether the nodes meet requirements of power cooperative scheduling; and for the nodes meeting the conditions, the system calculates the total energy consumption to be dispatched of the nodes according to a preset energy consumption value, and collects related power dispatching emergency information. The information is then uploaded to an edge node for analysis to generate power dispatching emergency values, and the values are transmitted to a cloud server. And the cloud server calculates a scheduling sequence of each node of the power grid in combination with the emergency values and a cooperative scheduling model, and executes scheduling of the power system according to the scheduling sequence and the total energy consumption value to be scheduled of each node. According to the invention, the efficiency and quality of power dispatching are improved, and the problem that the data in the power Internet of Things cannot be efficiently dispatched in the prior art is solved.

Description

Technical Field

[0001] The present invention relates to the field of collaborative scheduling of cloud-edge computing power, and in particular to a method, device and cloud server for collaborative scheduling of cloud-edge computing power. Background Art

[0002] With the rapid development of Internet of Things technology, the global Internet of Things of the power grid, as an important direction of the digital transformation of the power industry, is gradually becoming a key means to achieve the intelligence, automation and efficiency of the power grid. The global Internet of Things of the power grid integrates various sensors, intelligent devices, communication networks and data processing platforms to achieve comprehensive perception and real-time monitoring of all aspects of the power grid, including power generation, transmission, transformation, distribution and power consumption.

[0003] However, with the continuous expansion of the scale of the power grid and the surge in data volume, the traditional centralized data processing method can no longer meet the requirements of real-time, efficiency and reliability. These impacts have resulted in the inability of existing technologies to efficiently schedule data in the power Internet of Things. Summary of the invention

[0004] The present invention provides a cloud-edge computing power collaborative scheduling method, device and cloud server to solve the problem in the prior art that data in the power Internet of Things cannot be efficiently scheduled.

[0005] In a first aspect, the present application provides a cloud-edge computing power collaborative scheduling method, including:

[0006] Obtain operation data of each node in the power grid;

[0007] According to the operation data of each node of the power grid, judging whether each node of the power grid meets the power coordinated dispatching requirements;

[0008] If the power coordinated dispatching requirements are met, the total power energy consumption value to be dispatched of each node in the power grid is calculated according to the preset energy consumption values ​​of the power grid, and the power dispatching emergency information of each node in the power grid is obtained;

[0009] Uploading each power dispatch emergency information to each edge node for parsing, so that each edge node sends each power dispatch emergency value of each node of the power grid;

[0010] The power dispatch emergency values ​​are uploaded to the cloud server so that the cloud server can calculate the dispatch order of each node in the power grid according to the power dispatch emergency values ​​and the collaborative dispatch model, and dispatch the power system according to the dispatch order of each node in the power grid and the total power energy consumption value to be dispatched.

[0011] This application can fully understand the operating status of the power grid by obtaining the operating data of each node in the power grid. On this basis, it is judged whether each node meets the needs of power coordinated dispatching, and the nodes suitable for participating in the dispatching can be screened out to ensure the rationality and feasibility of the dispatching. For nodes that meet the needs, the total value of the power energy consumption to be dispatched is calculated and the emergency information of power dispatching is obtained, which helps to accurately grasp the power resource situation and urgency of each node. The emergency information of power dispatching is uploaded to the edge node for parsing to obtain the emergency value, and then uploaded to the cloud, so as to realize efficient processing and transmission of data. The cloud calculates the node dispatching order according to these emergency values ​​and the coordinated dispatching model, and can comprehensively consider the emergency situation and importance of each node for reasonable sorting. Finally, the dispatching instructions are obtained according to the node dispatching order and the total value of the power energy consumption to be dispatched, so as to realize efficient and accurate dispatching of the power system, improve the efficiency and quality of power dispatching, and solve the problem that the data in the power Internet of Things cannot be efficiently dispatched in the prior art.

[0012] As a preferred embodiment of the first aspect, judging whether each node of the power grid meets the power coordinated dispatching demand according to the operation data of each node of the power grid is specifically:

[0013] Calculating the operation stability margin value of each node in the power grid according to the operation data of each node in the power grid;

[0014] If the operating stability margin value of each node in the power grid is greater than a preset threshold, it is determined that each node in the power grid meets the power coordinated dispatching requirements.

[0015] The operation stability margin value of each node of the power grid is calculated based on the operation data of each node of the power grid, specifically:

[0016] According to the operation data of each node in the power grid, the apparent power value of the load of the power grid node, the active output value of the power grid node, the reactive output value of the power grid node, the line impedance value and the line reactance value are obtained;

[0017] According to the obtained apparent power value of the grid node load, the active output value of the grid node, the reactive output value of the grid node, the line impedance value and the line reactance value, and the stability margin calculation formula, the operation stability margin value of each node of the grid is calculated;

[0018] The stability margin calculation formula is:

[0019]

[0020] Where R is the total resistance of the line connected to the grid node, U is the node voltage of the grid node, VSM is the operation stability margin value corresponding to the grid node, S is the apparent power value of the grid node load, P is the active output value of the grid node, Q is the reactive output value of the grid node, Z is the line impedance value, and X is the line reactance value.

[0021] In this preferred embodiment, the present application determines whether the node meets the power collaborative dispatching requirements by calculating the operation stability margin value based on the operation data of each node in the power grid, and comparing it with the preset threshold value. First of all, the present application calculates the stability margin value based on the operation data, and can quantitatively evaluate the operation stability of each node. This quantitative evaluation provides an objective basis for subsequent decision-making. When the operation stability margin value of the node is greater than the preset threshold, it is determined that the collaborative dispatching requirements are met, which means that the node is only allowed to participate in the dispatching when it has sufficient stability, thereby ensuring that the nodes participating in the dispatching have a good operation basis and avoiding the interference of unstable nodes with the entire power collaborative dispatching process. This helps to improve the reliability and stability of power collaborative dispatching, thereby ensuring the safety and efficiency of power grid operation, ensuring that electricity can be stably transmitted and distributed, and meeting the electricity needs of users.

[0022] As a preferred embodiment of the first aspect, the power dispatch emergency information is uploaded to the edge node for parsing to obtain the power dispatch emergency value of each node of the power grid, specifically:

[0023] According to various power dispatch emergency information, the loads of various nodes in the power grid are calculated at the edge node to exceed various values ​​of the preset load capacity;

[0024] According to various power dispatch emergency information, the failure rates of various node devices in the power grid and various external environment values ​​of various nodes in the power grid are obtained at the edge node;

[0025] According to the external environment values, each external environment emergency value corresponding to each external environment value is calculated;

[0026] According to the values ​​of each load exceeding the preset load capacity, each failure rate, and each external environment emergency value, each power dispatch emergency value of each node in the power grid is calculated.

[0027] The power dispatch emergency values ​​of each node of the power grid are calculated based on the values ​​of each load exceeding the preset load capacity, each failure rate, and each external environment emergency value, specifically:

[0028] According to the values ​​of each load exceeding the preset load capacity, each failure rate, each external environment emergency value and the power dispatch emergency value calculation formula, each power dispatch emergency value of each node of the power grid is calculated;

[0029] The calculation formula of the power dispatch emergency value is:

[0030]

[0031] Where JJZ is the power dispatch emergency value of the power grid node, FHZ is the preset load capacity, H is the external environment emergency value, FH is the value of the load exceeding the preset load capacity, e is the preset value, and θ is the failure rate.

[0032] In this preferred embodiment, the present application can timely understand the load pressure situation of each node by calculating the value of the load exceeding the preset load at the edge node, which is crucial for judging whether the node is facing the risk of overload. Obtaining the failure rate of the node equipment can know the possible problems of the equipment in advance, which is helpful to take preventive measures. The external environment emergency value corresponding to the external environment value is calculated, taking into account the impact of the external environment on the power grid, such as factors that may cause power grid failures, such as bad weather. Finally, the power dispatch emergency value is calculated by combining the values ​​of these load excesses, the failure rate and the external environment emergency value, which can comprehensively and accurately reflect the urgency of each node. Based on this, the power dispatch system can reasonably arrange the dispatch order according to these emergency values, give priority to nodes with serious emergencies, thereby improving the ability of the power system to respond to emergencies, ensuring the stable operation of the power grid, reducing power outages caused by untimely power dispatching, and improving the reliability and stability of power supply.

[0033] As a preferred embodiment of the first aspect, the total amount of power energy consumption to be dispatched of each node in the power grid is calculated according to each preset energy consumption value of the power grid, specifically:

[0034] According to the total power demand energy consumption of all lines connected to each node of the power grid, the non-renewable resource energy consumption, the renewable resource energy consumption and the first formula, the total value of each power energy consumption to be dispatched of each node of the power grid is calculated;

[0035] The first formula is

[0036] Where L is the total power consumption to be dispatched, N is the number of lines connected to the grid node, α is the average transmission loss of each line, L1 is the total power consumption of all lines connected to each grid node, L2 is the energy consumption of non-renewable resources, and L3 is the energy consumption of renewable resources.

[0037] In this preferred embodiment, the present application considers the total power demand energy consumption, non-renewable resource energy consumption and renewable resource energy consumption of all lines connected to each node of the power grid, and this method can comprehensively evaluate the energy consumption demand of each node of the power grid. Secondly, by introducing the average loss of line transmission, this method can more accurately predict the energy loss of the power grid during the transmission process, so as to more accurately calculate the total value of the power consumption to be dispatched. This precise energy consumption calculation helps to optimize the allocation of power resources, reduce unnecessary energy waste, and improve the operating efficiency of the power grid. In addition, this method can also provide more accurate data support for power grid operators, helping them to formulate more effective energy management strategies, thereby reducing operating costs and improving economic benefits while meeting power demand.

[0038] As a preferred embodiment of the first aspect, the cloud server calculates the dispatching order of each node of the power grid according to each power dispatching emergency value and the collaborative dispatching model, specifically:

[0039] The cloud server calculates the weight values ​​of the dispatching order of each node in the power grid according to the power dispatching emergency values, the coordinated dispatching model and the second formula, and sorts the weight values ​​to obtain the dispatching order of each node in the power grid;

[0040] The second formula is

[0041] Where ZYZ is the weight value of the grid node dispatch order, β is the basic weight value of the dispatch order, and n is the number of grid nodes.

[0042] In this preferred embodiment, the present application calculates the dispatching order of each node of the power grid according to each power dispatching emergency value and the collaborative dispatching model through the cloud server, which can realize the refined management of the power grid and optimize the allocation of power resources. First, by using the power dispatching emergency value, it is possible to quickly respond to emergencies or abnormal situations in the power grid and ensure the stability and security of the power grid. Secondly, the collaborative dispatching model can comprehensively consider the global state of the power grid and the specific conditions of each node to achieve the optimal configuration of resources. The weight value calculated by the second formula not only reflects the urgency of each node, but also takes into account the overall operating status of the power grid, making the dispatching order more scientific and reasonable. The sorting process further ensures that nodes with high weight values ​​are dispatched first, thereby reducing energy loss and operating costs while meeting power demand. Finally, the generated dispatching instructions clarify the specific dispatching tasks of each power grid node, improve the executability and efficiency of the dispatching, and provide strong support for the safe and economical operation of the power grid.

[0043] As a preferred embodiment of the first aspect, the power system is dispatched according to the dispatching order of each node of the power grid and the total value of each power energy consumption to be dispatched, specifically:

[0044] So that the cloud server generates a dispatch instruction according to the dispatch order of each node of the power grid and the total value of the power energy consumption to be dispatched;

[0045] So that the cloud server can dispatch the power system according to the dispatch instruction; wherein the dispatch instruction includes the dispatch time, dispatch amount and dispatch method of each power grid node.

[0046] In this preferred embodiment, the present application generates dispatch instructions according to the dispatch order of each node in the power grid and the total value of the power energy consumption to be dispatched by the cloud server, which can ensure the accuracy and real-time performance of power dispatch. First, the dispatch order takes into account the urgency and efficiency of the power grid operation, ensuring that high-priority nodes can be dispatched first, thereby optimizing the allocation of power resources. Secondly, the total value of the power energy consumption to be dispatched provides the energy consumption requirements of each node, so that the dispatch instructions can accurately match the actual requirements and avoid waste of resources. The dispatch instructions generated by the cloud server based on these data, including the dispatch time, dispatch amount and dispatch method, provide a clear execution guide for the operation of the power grid. This refined dispatch management not only improves the operating efficiency of the power grid and reduces energy loss, but also enhances the adaptability of the power grid to renewable energy and its ability to respond to emergencies.

[0047] In a second aspect, the present application provides a cloud-edge computing power collaborative scheduling device. The cloud-edge computing power collaborative scheduling device includes an acquisition module, a judgment module, a calculation module, a parsing module, and a scheduling module;

[0048] The acquisition module is used to obtain the operation data of each node in the power grid;

[0049] The judgment module is used to judge whether each node of the power grid meets the power coordinated dispatching requirements according to the operation data of each node of the power grid;

[0050] The calculation module is used to calculate the total power energy consumption value to be dispatched of each node in the power grid according to each preset energy consumption value of the power grid if the power coordinated dispatch demand is met, and obtain each power dispatch emergency information of each node in the power grid;

[0051] The parsing module is used to upload the various power dispatch emergency information to each edge node for parsing, so that each edge node sends each power dispatch emergency value of each node of the power grid;

[0052] The scheduling module is used to upload the power scheduling emergency values ​​to the cloud server, so that the cloud server can calculate the scheduling order of each node in the power grid according to the power scheduling emergency values ​​and the collaborative scheduling model, and schedule the power system according to the scheduling order of each node in the power grid and the total power energy consumption value to be scheduled.

[0053] This device uses five modules to divide the work and coordinate the work to better dispatch the power system. This application can fully understand the operating status of the power grid by obtaining the operating data of each node in the power grid. On this basis, it is judged whether each node meets the power coordinated dispatching requirements, and the nodes suitable for participating in the dispatch can be screened out to ensure the rationality and feasibility of the dispatch. For nodes that meet the requirements, the total value of the power energy consumption to be dispatched is calculated and the power dispatch emergency information is obtained, which helps to accurately grasp the power resource situation and urgency of each node. The power dispatch emergency information is uploaded to the edge node for parsing to obtain the emergency value, and uploaded to the cloud, realizing efficient processing and transmission of data. The cloud calculates the node dispatching order based on these emergency values ​​and the coordinated dispatching model, and can comprehensively consider the emergency situation and importance of each node for reasonable sorting. Finally, the dispatching instructions are obtained based on the node dispatching order and the total value of the power energy consumption to be dispatched, so as to realize efficient and accurate dispatching of the power system, improve the efficiency and quality of power dispatching, and solve the problem that the data in the power Internet of Things cannot be efficiently dispatched in the prior art.

[0054] In a third aspect, the present application provides a cloud server, the cloud server comprising a receiving module and a scheduling module;

[0055] The receiving module is used to receive each power dispatch emergency value of each node of the power grid uploaded by each edge node; wherein each power dispatch emergency value of each node of the power grid is parsed by each edge node according to each power dispatch emergency information, and fed back to the cloud server; the power dispatch emergency information is determined according to the operation data of each node of the power grid when the power coordinated dispatch demand is met; the power coordinated dispatch demand is determined according to the operation data of each node of the power grid;

[0056] The scheduling module is used to calculate the scheduling order of each node in the power grid according to the power scheduling emergency values ​​and the collaborative scheduling model, and obtain the scheduling instructions of the power system according to the scheduling order of each node in the power grid and the total power energy consumption value to be scheduled.

[0057] The receiving module of the present application can receive power dispatch emergency values ​​from each edge node. These values ​​are based on the analysis results of the edge node on the real-time power grid operation data, ensuring the rapid upload and processing of emergency information. This distributed data collection and preliminary processing reduces the delay of data transmission, enabling the cloud server to respond to changes in the power grid in a timely manner. Secondly, the dispatch module uses these emergency values ​​and the collaborative dispatch model to calculate the dispatch order of each node in the power grid. This model-based calculation method can comprehensively consider the overall situation of the power grid and the specific situation of each node, thereby generating the optimal dispatch order. Then, the dispatch module combines the dispatch order and the total value of the power energy consumption to be dispatched to generate specific dispatch instructions, which ensures the accuracy and executability of the dispatch decision. Ultimately, this efficient data processing and dispatching mechanism helps to optimize the allocation of power resources and improve the stability and reliability of the power grid, so as to solve the problem that the existing technology cannot efficiently dispatch data in the power Internet of Things. BRIEF DESCRIPTION OF THE DRAWINGS

[0058] Figure 1 : A flowchart of an embodiment of the cloud-edge computing power collaborative scheduling method provided in this application;

[0059] Figure 2 : A structural diagram of an embodiment of a cloud-edge computing power collaborative scheduling device provided in this application;

[0060] Figure 3 : A structural diagram of an embodiment of a cloud server provided in this application. DETAILED DESCRIPTION

[0061] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0062] Embodiment 1

[0063] Please refer to Figure 1 , which is a cloud-edge computing power collaborative scheduling method provided by an embodiment of the present invention.

[0064] In this embodiment, the process of the cloud-edge computing power collaborative scheduling method in this application is described in detail through steps S01-S05.

[0065] S01: Obtain the operating data of each node in the power grid.

[0066] As a preferred embodiment of the first embodiment, the operation data of each node of the power grid is specifically:

[0067] The operating data of each node in the power grid includes voltage, current, temperature, humidity, vibration, etc.

[0068] S02: Based on the operating data of each node in the power grid, determine whether each node in the power grid meets the power coordinated dispatching requirements.

[0069] As a preferred embodiment of the first embodiment, judging whether each node of the power grid meets the power coordinated dispatching demand according to the operation data of each node of the power grid is specifically:

[0070] Calculating the operation stability margin value of each node in the power grid according to the operation data of each node in the power grid;

[0071] Load the operation stability margin value threshold, and determine whether the operation stability margin value VSM exceeds the operation stability margin value threshold. If so, it is determined that the power grid node meets the requirements of power coordinated dispatching. If not, it is determined that the power grid node does not meet the requirements of power coordinated dispatching. The operation stability margin value threshold is set and stored by the cloud.

[0072] Furthermore, the operation stability margin value of each node of the power grid is calculated based on the operation data of each node of the power grid, specifically:

[0073] According to the operation data of each node in the power grid, the apparent power value of the load of the power grid node, the active output value of the power grid node, the reactive output value of the power grid node, the line impedance value and the line reactance value are obtained;

[0074] According to the obtained apparent power value of the grid node load, the active output value of the grid node, the reactive output value of the grid node, the line impedance value and the line reactance value, and the stability margin calculation formula, the operation stability margin value of each node of the grid is calculated;

[0075] Among them, the stability margin calculation formula is:

[0076]

[0077] Where R is the total resistance of the line connected to the grid node, U is the node voltage of the grid node, VSM is the operation stability margin value corresponding to the grid node, S is the apparent power value of the grid node load, P is the active output value of the grid node, Q is the reactive output value of the grid node, Z is the line impedance value, and X is the line reactance value.

[0078] In this preferred embodiment, the present application determines whether the node meets the power collaborative dispatching requirements by calculating the operation stability margin value based on the operation data of each node in the power grid, and comparing it with the preset threshold value. First of all, the present application calculates the stability margin value based on the operation data, and can quantitatively evaluate the operation stability of each node. This quantitative evaluation provides an objective basis for subsequent decision-making. When the operation stability margin value of the node is greater than the preset threshold, it is determined that the collaborative dispatching requirements are met, which means that the node is only allowed to participate in the dispatching when it has sufficient stability, thereby ensuring that the nodes participating in the dispatching have a good operation basis and avoiding the interference of unstable nodes with the entire power collaborative dispatching process. This helps to improve the reliability and stability of power collaborative dispatching, thereby ensuring the safety and efficiency of power grid operation, ensuring that electricity can be stably transmitted and distributed, and meeting the electricity needs of users.

[0079] S03: If the power coordinated dispatching requirements are met, the total power energy consumption value to be dispatched of each node in the power grid is calculated according to the preset energy consumption values ​​of the power grid, and the power dispatching emergency information of each node in the power grid is obtained.

[0080] As a preferred embodiment of the first embodiment, the total amount of power energy consumption to be dispatched of each node in the power grid is calculated according to each preset energy consumption value of the power grid, specifically:

[0081] Obtain all required power consumption L1 of the lines connected to the grid node;

[0082] Obtain the non-renewable resource energy consumption L2 required to maintain the operation of the power grid;

[0083] Obtain the renewable energy consumption L3 required to maintain the operation of the power grid;

[0084]

[0085] Where L is the total power consumption to be dispatched, N is the number of lines connected to the grid node, α is the average transmission loss of each line, L1 is the total power consumption of all lines connected to each grid node, L2 is the energy consumption of non-renewable resources, and L3 is the energy consumption of renewable resources.

[0086] In this preferred embodiment, the present application considers the total power demand energy consumption, non-renewable resource energy consumption and renewable resource energy consumption of all lines connected to each node of the power grid, and this method can comprehensively evaluate the energy consumption demand of each node of the power grid. Secondly, by introducing the average loss of line transmission, this method can more accurately predict the energy loss of the power grid during the transmission process, so as to more accurately calculate the total value of the power consumption to be dispatched. This precise energy consumption calculation helps to optimize the allocation of power resources, reduce unnecessary energy waste, and improve the operating efficiency of the power grid. In addition, this method can also provide more accurate data support for power grid operators, helping them to formulate more effective energy management strategies, thereby reducing operating costs and improving economic benefits while meeting power demand.

[0087] S04: Upload each of the power dispatch emergency information to each edge node for parsing, so that each edge node sends each power dispatch emergency value of each node in the power grid.

[0088] As a preferred embodiment of the first embodiment, the power dispatch emergency information is uploaded to the edge node for parsing to obtain the power dispatch emergency value of each node of the power grid, specifically:

[0089] According to various power dispatch emergency information, the loads of various nodes in the power grid are calculated at the edge node to exceed various values ​​of the preset load capacity;

[0090] According to various power dispatch emergency information, the failure rates of various node devices in the power grid and various external environment values ​​of various nodes in the power grid are obtained at the edge node;

[0091] Based on each external environment value, determine whether there is a natural disaster. If so, query the emergency value H corresponding to the external environmental factor. If not, the emergency value H corresponding to the external environmental factor is 0. Each natural disaster has a different emergency value H.

[0092] That is: according to the various external environment values, various external environment emergency values ​​corresponding to the various external environment values ​​are calculated;

[0093] According to the values ​​of each load exceeding the preset load capacity, each failure rate, and each external environment emergency value, each power dispatch emergency value of each node in the power grid is calculated.

[0094] Furthermore, the power dispatch emergency values ​​of each node of the power grid are calculated based on the values ​​of each load exceeding the preset load capacity, each failure rate, and each external environment emergency value, specifically:

[0095] According to the values ​​of each load exceeding the preset load capacity, each failure rate, each external environment emergency value and the power dispatch emergency value calculation formula, each power dispatch emergency value of each node of the power grid is calculated;

[0096] The calculation formula of the power dispatch emergency value is:

[0097]

[0098] Where JJZ is the power dispatch emergency value of the power grid node, FHZ is the preset load capacity, H is the external environment emergency value, FH is the value of the load exceeding the preset load capacity, the value of e is 2.72, and θ is the failure rate.

[0099] In this preferred embodiment, the present application can timely understand the load pressure situation of each node by calculating the value of the load exceeding the preset load at the edge node, which is crucial for judging whether the node is facing the risk of overload. Obtaining the failure rate of the node equipment can know the possible problems of the equipment in advance, which is helpful to take preventive measures. The external environment emergency value corresponding to the external environment value is calculated, taking into account the impact of the external environment on the power grid, such as factors that may cause power grid failures, such as bad weather. Finally, the power dispatch emergency value is calculated by combining the values ​​of these load excesses, the failure rate and the external environment emergency value, which can comprehensively and accurately reflect the urgency of each node. Based on this, the power dispatch system can reasonably arrange the dispatch order according to these emergency values, give priority to nodes with serious emergencies, thereby improving the ability of the power system to respond to emergencies, ensuring the stable operation of the power grid, reducing power outages caused by untimely power dispatching, and improving the reliability and stability of power supply.

[0100] S05: Upload the power dispatch emergency values ​​to the cloud server, so that the cloud server can calculate the dispatch order of each node in the power grid according to the power dispatch emergency values ​​and the collaborative dispatch model, and dispatch the power system according to the dispatch order of each node in the power grid and the total power energy consumption value to be dispatched.

[0101] As a preferred embodiment of the first embodiment, the cloud server calculates the dispatching order of each node of the power grid according to each power dispatching emergency value and the coordinated dispatching model, specifically:

[0102] Substitute the power dispatch emergency value into the collaborative dispatch model to calculate the grid node dispatch order weight value:

[0103]

[0104] Among them, ZYZ is the weight value of the dispatch order of the power grid nodes, β is the basic weight value of the dispatch order, and n is the number of power grid nodes;

[0105] The power grid nodes are sorted according to their weight values ​​to obtain a sorting sequence, which is recorded as the power grid node dispatching sequence.

[0106] In this preferred embodiment, the present application calculates the dispatching order of each node of the power grid according to each power dispatching emergency value and the collaborative dispatching model through the cloud server, which can realize the refined management of the power grid and optimize the allocation of power resources. First, by using the power dispatching emergency value, it is possible to quickly respond to emergencies or abnormal situations in the power grid and ensure the stability and security of the power grid. Secondly, the collaborative dispatching model can comprehensively consider the global state of the power grid and the specific conditions of each node to achieve the optimal configuration of resources. The weight value calculated by the second formula not only reflects the urgency of each node, but also takes into account the overall operating status of the power grid, making the dispatching order more scientific and reasonable. The sorting process further ensures that nodes with high weight values ​​are dispatched first, thereby reducing energy loss and operating costs while meeting power demand. Finally, the generated dispatching instructions clarify the specific dispatching tasks of each power grid node, improve the executability and efficiency of the dispatching, and provide strong support for the safe and economical operation of the power grid.

[0107] As a preferred embodiment of the first embodiment, the power system is dispatched according to the dispatching order of each node of the power grid and the total value of each power energy consumption to be dispatched, specifically:

[0108] So that the cloud server generates a dispatch instruction according to the dispatch order of each node of the power grid and the total value of the power energy consumption to be dispatched;

[0109] So that the cloud server can dispatch the power system according to the dispatch instruction; wherein the dispatch instruction includes the dispatch time, dispatch amount and dispatch method of each power grid node.

[0110] In this preferred embodiment, the present application generates dispatch instructions according to the dispatch order of each node in the power grid and the total value of the power energy consumption to be dispatched by the cloud server, which can ensure the accuracy and real-time performance of power dispatch. First, the dispatch order takes into account the urgency and efficiency of the power grid operation, ensuring that high-priority nodes can be dispatched first, thereby optimizing the allocation of power resources. Secondly, the total value of the power energy consumption to be dispatched provides the energy consumption requirements of each node, so that the dispatch instructions can accurately match the actual requirements and avoid waste of resources. The dispatch instructions generated by the cloud server based on these data, including the dispatch time, dispatch amount and dispatch method, provide a clear execution guide for the operation of the power grid. This refined dispatch management not only improves the operating efficiency of the power grid and reduces energy loss, but also enhances the adaptability of the power grid to renewable energy and its ability to respond to emergencies.

[0111] Furthermore, the architecture of the grid-wide IoT includes the perception layer, network layer, platform layer, and application layer;

[0112] Perception layer: Through various sensors, RFID tags, cameras and other equipment, various data in power grid operation, such as voltage, current, temperature, humidity, vibration, etc., are collected in real time.

[0113] Network layer: Use wireless communication technologies (such as Wi-Fi, Zigbee, LoRa, NB-I oT, etc.) and wired communication technologies (such as optical fiber, Ethernet, etc.) to transmit the data collected by the perception layer to the platform layer for processing.

[0114] Platform layer: provides data processing, storage, analysis and management functions, including the application of cloud computing, big data, artificial intelligence and other technologies, to achieve comprehensive perception of the operating status of the power grid and intelligent decision-making.

[0115] Application layer: Various application services for users and developers, such as intelligent inspection, fault warning, energy efficiency management, demand response, etc., to improve the operation and maintenance efficiency of the power grid and user satisfaction.

[0116] This application can fully understand the operating status of the power grid by obtaining the operating data of each node in the power grid. On this basis, it is judged whether each node meets the needs of power coordinated dispatching, and the nodes suitable for participating in the dispatching can be screened out to ensure the rationality and feasibility of the dispatching. For nodes that meet the needs, the total value of the power energy consumption to be dispatched is calculated and the emergency information of power dispatching is obtained, which helps to accurately grasp the power resource situation and urgency of each node. The emergency information of power dispatching is uploaded to the edge node for parsing to obtain the emergency value, and then uploaded to the cloud, so as to realize efficient processing and transmission of data. The cloud calculates the node dispatching order according to these emergency values ​​and the coordinated dispatching model, and can comprehensively consider the emergency situation and importance of each node for reasonable sorting. Finally, the dispatching instructions are obtained according to the node dispatching order and the total value of the power energy consumption to be dispatched, so as to realize efficient and accurate dispatching of the power system, improve the efficiency and quality of power dispatching, and solve the problem that the data in the power Internet of Things cannot be efficiently dispatched in the prior art.

[0117] Embodiment 2

[0118] Please refer to Figure 2 , which is a cloud-edge computing power collaborative scheduling device provided in an embodiment of the present application.

[0119] In this embodiment, the cloud-edge computing power collaborative scheduling device includes an acquisition module 10, a judgment module 20, a calculation module 30, an analysis module 40 and a scheduling module 50.

[0120] The acquisition module 10 is used to acquire the operation data of each node in the power grid.

[0121] As a preferred embodiment of the second embodiment, the operation data of each node of the power grid is specifically:

[0122] The operating data of each node in the power grid includes voltage, current, temperature, humidity, vibration, etc.

[0123] The judgment module 20 is used to judge whether each node in the power grid meets the power coordinated dispatching requirements according to the operation data of each node in the power grid.

[0124] As a preferred embodiment of the second embodiment, judging whether each node of the power grid meets the power coordinated dispatching demand according to the operation data of each node of the power grid is specifically:

[0125] Calculating the operation stability margin value of each node in the power grid according to the operation data of each node in the power grid;

[0126] Load the operation stability margin value threshold, and determine whether the operation stability margin value VSM exceeds the operation stability margin value threshold. If so, it is determined that the power grid node meets the requirements of power coordinated dispatching. If not, it is determined that the power grid node does not meet the requirements of power coordinated dispatching. The operation stability margin value threshold is set and stored by the cloud.

[0127] Furthermore, the operation stability margin value of each node of the power grid is calculated based on the operation data of each node of the power grid, specifically:

[0128] According to the operation data of each node in the power grid, the apparent power value of the load of the power grid node, the active output value of the power grid node, the reactive output value of the power grid node, the line impedance value and the line reactance value are obtained;

[0129] According to the obtained apparent power value of the grid node load, the active output value of the grid node, the reactive output value of the grid node, the line impedance value and the line reactance value, and the stability margin calculation formula, the operation stability margin value of each node of the grid is calculated;

[0130] The stability margin calculation formula is:

[0131]

[0132] Where R is the total resistance of the line connected to the grid node, U is the node voltage of the grid node, VSM is the operation stability margin value corresponding to the grid node, S is the apparent power value of the grid node load, P is the active output value of the grid node, Q is the reactive output value of the grid node, Z is the line impedance value, and X is the line reactance value.

[0133] In this preferred embodiment, the present application determines whether the node meets the power collaborative dispatching requirements by calculating the operation stability margin value based on the operation data of each node in the power grid, and comparing it with the preset threshold value. First of all, the present application calculates the stability margin value based on the operation data, and can quantitatively evaluate the operation stability of each node. This quantitative evaluation provides an objective basis for subsequent decision-making. When the operation stability margin value of the node is greater than the preset threshold, it is determined that the collaborative dispatching requirements are met, which means that the node is only allowed to participate in the dispatching when it has sufficient stability, thereby ensuring that the nodes participating in the dispatching have a good operation basis and avoiding the interference of unstable nodes with the entire power collaborative dispatching process. This helps to improve the reliability and stability of power collaborative dispatching, thereby ensuring the safety and efficiency of power grid operation, ensuring that electricity can be stably transmitted and distributed, and meeting the electricity needs of users.

[0134] Calculation module 30: If the power coordinated dispatching requirements are met, the total power energy consumption value to be dispatched of each node in the power grid is calculated according to each preset energy consumption value of the power grid, and each power dispatching emergency information of each node in the power grid is obtained.

[0135] As a preferred embodiment of the second embodiment, the total amount of power energy consumption to be dispatched of each node in the power grid is calculated according to each preset energy consumption value of the power grid, specifically:

[0136] Obtain all required power consumption L1 of the lines connected to the grid node;

[0137] Obtain the non-renewable resource energy consumption L2 required to maintain the operation of the power grid;

[0138] Obtain the renewable energy consumption L3 required to maintain the operation of the power grid;

[0139]

[0140] Where L is the total power consumption to be dispatched, N is the number of lines connected to the grid node, α is the average transmission loss of each line, L1 is the total power consumption of all lines connected to each grid node, L2 is the energy consumption of non-renewable resources, and L3 is the energy consumption of renewable resources.

[0141] In this preferred embodiment, the present application considers the total power demand energy consumption, non-renewable resource energy consumption and renewable resource energy consumption of all lines connected to each node of the power grid, and this method can comprehensively evaluate the energy consumption demand of each node of the power grid. Secondly, by introducing the average loss of line transmission, this method can more accurately predict the energy loss of the power grid during the transmission process, so as to more accurately calculate the total value of the power consumption to be dispatched. This precise energy consumption calculation helps to optimize the allocation of power resources, reduce unnecessary energy waste, and improve the operating efficiency of the power grid. In addition, this method can also provide more accurate data support for power grid operators, helping them to formulate more effective energy management strategies, thereby reducing operating costs and improving economic benefits while meeting power demand.

[0142] The parsing module 40 is used to upload the various power dispatch emergency information to each edge node for parsing, so that each edge node sends each power dispatch emergency value of each node in the power grid.

[0143] As a preferred embodiment of the second embodiment, the power dispatch emergency information is uploaded to the edge node for parsing to obtain the power dispatch emergency value of each node of the power grid, specifically:

[0144] According to various power dispatch emergency information, the loads of various nodes in the power grid are calculated at the edge node to exceed various values ​​of the preset load capacity;

[0145] According to various power dispatch emergency information, the failure rates of various node devices in the power grid and various external environment values ​​of various nodes in the power grid are obtained at the edge node;

[0146] Based on each external environment value, determine whether there is a natural disaster. If so, query the emergency value H corresponding to the external environmental factor. If not, the emergency value H corresponding to the external environmental factor is 0. Each natural disaster has a different emergency value H.

[0147] That is: according to the various external environment values, various external environment emergency values ​​corresponding to the various external environment values ​​are calculated;

[0148] According to the values ​​of each load exceeding the preset load capacity, each failure rate, and each external environment emergency value, each power dispatch emergency value of each node in the power grid is calculated.

[0149] Furthermore, the power dispatch emergency values ​​of each node of the power grid are calculated based on the values ​​of each load exceeding the preset load capacity, each failure rate, and each external environment emergency value, specifically:

[0150] According to the values ​​of each load exceeding the preset load capacity, each failure rate, each external environment emergency value and the power dispatch emergency value calculation formula, each power dispatch emergency value of each node of the power grid is calculated;

[0151] The calculation formula of the power dispatch emergency value is:

[0152]

[0153] Where JJZ is the power dispatch emergency value of the power grid node, FHZ is the preset load capacity, H is the external environment emergency value, FH is the value of the load exceeding the preset load capacity, the value of e is 2.72, and θ is the failure rate.

[0154] In this preferred embodiment, the present application can timely understand the load pressure situation of each node by calculating the value of the load exceeding the preset load at the edge node, which is crucial for judging whether the node is facing the risk of overload. Obtaining the failure rate of the node equipment can know the possible problems of the equipment in advance, which is helpful to take preventive measures. The external environment emergency value corresponding to the external environment value is calculated, taking into account the impact of the external environment on the power grid, such as factors that may cause power grid failures, such as bad weather. Finally, the power dispatch emergency value is calculated by combining the values ​​of these load excesses, the failure rate and the external environment emergency value, which can comprehensively and accurately reflect the urgency of each node. Based on this, the power dispatch system can reasonably arrange the dispatch order according to these emergency values, give priority to nodes with serious emergencies, thereby improving the ability of the power system to respond to emergencies, ensuring the stable operation of the power grid, reducing power outages caused by untimely power dispatching, and improving the reliability and stability of power supply.

[0155] The scheduling module 50 is used to upload the above-mentioned power scheduling emergency values ​​to the cloud server, so that the cloud server can calculate the scheduling order of each node in the power grid according to the above-mentioned power scheduling emergency values ​​and the collaborative scheduling model, and schedule the power system according to the scheduling order of each node in the power grid and the total power energy consumption value to be scheduled.

[0156] As a preferred embodiment of the second embodiment, the cloud server calculates the dispatching order of each node of the power grid according to each power dispatching emergency value and the coordinated dispatching model, specifically:

[0157] Substitute the power dispatch emergency value into the collaborative dispatch model to calculate the grid node dispatch order weight value:

[0158]

[0159] Among them, ZYZ is the weight value of the dispatch order of the power grid nodes, β is the basic weight value of the dispatch order, and n is the number of power grid nodes;

[0160] The power grid nodes are sorted according to their weight values ​​to obtain a sorting sequence, which is recorded as the power grid node dispatching sequence.

[0161] In this preferred embodiment, the present application calculates the dispatching order of each node of the power grid according to each power dispatching emergency value and the collaborative dispatching model through the cloud server, which can realize the refined management of the power grid and optimize the allocation of power resources. First, by using the power dispatching emergency value, it is possible to quickly respond to emergencies or abnormal situations in the power grid and ensure the stability and security of the power grid. Secondly, the collaborative dispatching model can comprehensively consider the global state of the power grid and the specific conditions of each node to achieve the optimal configuration of resources. The weight value calculated by the second formula not only reflects the urgency of each node, but also takes into account the overall operating status of the power grid, making the dispatching order more scientific and reasonable. The sorting process further ensures that nodes with high weight values ​​are dispatched first, thereby reducing energy loss and operating costs while meeting power demand. Finally, the generated dispatching instructions clarify the specific dispatching tasks of each power grid node, improve the executability and efficiency of the dispatching, and provide strong support for the safe and economical operation of the power grid.

[0162] As a preferred embodiment of the second embodiment, the power system is dispatched according to the dispatching order of each node of the power grid and the total value of each power energy consumption to be dispatched, specifically:

[0163] So that the cloud server generates a dispatch instruction according to the dispatch order of each node of the power grid and the total value of the power energy consumption to be dispatched;

[0164] So that the cloud server can dispatch the power system according to the dispatch instruction; wherein the dispatch instruction includes the dispatch time, dispatch amount and dispatch method of each power grid node.

[0165] In this preferred embodiment, the present application generates dispatch instructions according to the dispatch order of each node in the power grid and the total value of the power energy consumption to be dispatched by the cloud server, which can ensure the accuracy and real-time performance of power dispatch. First, the dispatch order takes into account the urgency and efficiency of the power grid operation, ensuring that high-priority nodes can be dispatched first, thereby optimizing the allocation of power resources. Secondly, the total value of the power energy consumption to be dispatched provides the energy consumption requirements of each node, so that the dispatch instructions can accurately match the actual requirements and avoid waste of resources. The dispatch instructions generated by the cloud server based on these data, including the dispatch time, dispatch amount and dispatch method, provide a clear execution guide for the operation of the power grid. This refined dispatch management not only improves the operating efficiency of the power grid and reduces energy loss, but also enhances the adaptability of the power grid to renewable energy and its ability to respond to emergencies.

[0166] Furthermore, the architecture of the grid-wide IoT includes the perception layer, network layer, platform layer, and application layer;

[0167] Perception layer: Through various sensors, RFID tags, cameras and other equipment, various data in power grid operation, such as voltage, current, temperature, humidity, vibration, etc., are collected in real time.

[0168] Network layer: Use wireless communication technologies (such as Wi-Fi, Zigbee, LoRa, NB-I oT, etc.) and wired communication technologies (such as optical fiber, Ethernet, etc.) to transmit the data collected by the perception layer to the platform layer for processing.

[0169] Platform layer: provides data processing, storage, analysis and management functions, including the application of cloud computing, big data, artificial intelligence and other technologies, to achieve comprehensive perception of the operating status of the power grid and intelligent decision-making.

[0170] Application layer: Various application services for users and developers, such as intelligent inspection, fault warning, energy efficiency management, demand response, etc., to improve the operation and maintenance efficiency of the power grid and user satisfaction.

[0171] This application can fully understand the operating status of the power grid by obtaining the operating data of each node in the power grid. On this basis, it is judged whether each node meets the needs of power coordinated dispatching, and the nodes suitable for participating in the dispatching can be screened out to ensure the rationality and feasibility of the dispatching. For nodes that meet the needs, the total value of the power energy consumption to be dispatched is calculated and the emergency information of power dispatching is obtained, which helps to accurately grasp the power resource situation and urgency of each node. The emergency information of power dispatching is uploaded to the edge node for parsing to obtain the emergency value, and then uploaded to the cloud, so as to realize efficient processing and transmission of data. The cloud calculates the node dispatching order according to these emergency values ​​and the coordinated dispatching model, and can comprehensively consider the emergency situation and importance of each node for reasonable sorting. Finally, the dispatching instructions are obtained according to the node dispatching order and the total value of the power energy consumption to be dispatched, so as to realize efficient and accurate dispatching of the power system, improve the efficiency and quality of power dispatching, and solve the problem that the data in the power Internet of Things cannot be efficiently dispatched in the prior art.

[0172] Embodiment 3

[0173] Please refer to Figure 3

[0174] In this embodiment, the cloud server includes a receiving module 101 and a scheduling module 102 .

[0175] The receiving module 101 is used to receive each power dispatch emergency value of each node of the power grid uploaded by each edge node; wherein each power dispatch emergency value of each node of the power grid is parsed by each edge node according to each power dispatch emergency information, and fed back to the cloud server; the power dispatch emergency information is determined according to the operation data of each node of the power grid when the power coordinated dispatch demand is met; the power coordinated dispatch demand is determined according to the operation data of each node of the power grid;

[0176] The scheduling module 102 is used to calculate the scheduling order of each node in the power grid according to the power scheduling emergency values ​​and the collaborative scheduling model, and obtain the scheduling instructions of the power system according to the scheduling order of each node in the power grid and the total power energy consumption value to be scheduled.

[0177] The receiving module of the present application can receive power dispatch emergency values ​​from each edge node. These values ​​are based on the analysis results of the edge node on the real-time power grid operation data, ensuring the rapid upload and processing of emergency information. This distributed data collection and preliminary processing reduces the delay of data transmission, enabling the cloud server to respond to changes in the power grid in a timely manner. Secondly, the dispatch module uses these emergency values ​​and the collaborative dispatch model to calculate the dispatch order of each node in the power grid. This model-based calculation method can comprehensively consider the overall situation of the power grid and the specific situation of each node, thereby generating the optimal dispatch order. Then, the dispatch module combines the dispatch order and the total value of the power energy consumption to be dispatched to generate specific dispatch instructions, which ensures the accuracy and executability of the dispatch decision. Ultimately, this efficient data processing and dispatching mechanism helps to optimize the allocation of power resources and improve the stability and reliability of the power grid, so as to solve the problem that the existing technology cannot efficiently dispatch data in the power Internet of Things.

[0178] The specific embodiments described above further illustrate the purpose, technical solutions and beneficial effects of the present invention. It should be understood that the above description is only a specific embodiment of the present invention and is not intended to limit the scope of protection of the present invention. It is particularly pointed out that for those skilled in the art, any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present invention should be included in the scope of protection of the present invention.

Claims

1. A cloud-edge computing power collaborative scheduling method, characterized in that: include: Obtain operation data of each node in the power grid; According to the operation data of each node of the power grid, judging whether each node of the power grid meets the power coordinated dispatching requirements; If the power coordinated dispatching requirements are met, the total power energy consumption value to be dispatched of each node in the power grid is calculated according to the preset energy consumption values ​​of the power grid, and the power dispatching emergency information of each node in the power grid is obtained; Uploading each power dispatch emergency information to each edge node for parsing, so that each edge node sends each power dispatch emergency value of each node of the power grid; The power dispatch emergency values ​​are uploaded to the cloud server so that the cloud server can calculate the dispatch order of each node in the power grid according to the power dispatch emergency values ​​and the collaborative dispatch model, and dispatch the power system according to the dispatch order of each node in the power grid and the total power energy consumption value to be dispatched.

2. The cloud-edge computing power collaborative scheduling method according to claim 1 is characterized in that: The step of judging whether each node of the power grid meets the power coordinated dispatching requirements according to the operation data of each node of the power grid is as follows: Calculating the operation stability margin value of each node in the power grid according to the operation data of each node in the power grid; If the operating stability margin value of each node in the power grid is greater than a preset threshold, it is determined that each node in the power grid meets the power coordinated dispatching requirements.

3. The cloud-edge computing power collaborative scheduling method according to claim 2 is characterized in that: The operation stability margin value of each node of the power grid is calculated based on the operation data of each node of the power grid, specifically: According to the operation data of each node in the power grid, the apparent power value of the load of the power grid node, the active output value of the power grid node, the reactive output value of the power grid node, the line impedance value and the line reactance value are obtained; According to the obtained apparent power value of the grid node load, the active output value of the grid node, the reactive output value of the grid node, the line impedance value and the line reactance value, and the stability margin calculation formula, the operation stability margin value of each node of the grid is calculated; Among them, the stability margin calculation formula is: Where R is the total resistance of the line connected to the grid node, U is the node voltage of the grid node, VSM is the operation stability margin value corresponding to the grid node, S is the apparent power value of the grid node load, P is the active output value of the grid node, Q is the reactive output value of the grid node, Z is the line impedance value, and X is the line reactance value.

4. The cloud-edge computing power collaborative scheduling method according to claim 1 is characterized in that: The power dispatch emergency information is uploaded to the edge node for parsing to obtain the power dispatch emergency value of each node in the power grid, specifically: According to various power dispatch emergency information, the values ​​of various loads of various nodes in the power grid exceeding the preset load capacity are calculated at the edge node; According to various power dispatch emergency information, the failure rates of various node devices in the power grid and various external environment values ​​of various nodes in the power grid are obtained at the edge node; According to the external environment values, each external environment emergency value corresponding to each external environment value is calculated; According to the values ​​of each load exceeding the preset load capacity, each failure rate, and each external environment emergency value, each power dispatch emergency value of each node in the power grid is calculated.

5. The cloud-edge computing power collaborative scheduling method according to claim 4 is characterized in that: The power dispatch emergency values ​​of each node of the power grid are calculated based on the values ​​of each load exceeding the preset load capacity, each failure rate, and each external environment emergency value, specifically: According to the values ​​of each load exceeding the preset load capacity, each failure rate, each external environment emergency value and the power dispatch emergency value calculation formula, each power dispatch emergency value of each node of the power grid is calculated; The calculation formula of the power dispatch emergency value is: Where JJZ is the power dispatch emergency value of the power grid node, FHZ is the preset load capacity, H is the external environment emergency value, FH is the value of the load exceeding the preset load capacity, e is the preset value, and θ is the failure rate.

6. The cloud-edge computing power collaborative scheduling method according to claim 1 is characterized in that: The total amount of power energy consumption to be dispatched of each node in the power grid is calculated according to each preset energy consumption value of the power grid, specifically: According to the total power demand energy consumption of all lines connected to each node of the power grid, the non-renewable resource energy consumption, the renewable resource energy consumption and the first formula, the total value of each power energy consumption to be dispatched of each node of the power grid is calculated; The first formula is Where L is the total power consumption to be dispatched, N is the number of lines connected to the grid node, α is the average transmission loss of each line, L1 is the total power consumption of all lines connected to each grid node, L2 is the energy consumption of non-renewable resources, and L3 is the energy consumption of renewable resources.

7. The cloud-edge computing power collaborative scheduling method according to claim 1 is characterized in that: The cloud server calculates the dispatching order of each node of the power grid according to the power dispatching emergency values ​​and the coordinated dispatching model, specifically: The cloud server calculates the weight values ​​of the dispatching order of each node in the power grid according to the power dispatching emergency values, the coordinated dispatching model and the second formula, and sorts the weight values ​​to obtain the dispatching order of each node in the power grid; The second formula is Where ZYZ is the weight value of the grid node dispatch order, β is the basic weight value of the dispatch order, and n is the number of grid nodes.

8. The cloud-edge computing power collaborative scheduling method according to claim 1 is characterized in that: The power system is dispatched according to the dispatching order of each node of the power grid and the total value of each power energy consumption to be dispatched, specifically: So that the cloud server generates a dispatch instruction according to the dispatch order of each node of the power grid and the total value of the power energy consumption to be dispatched; So that the cloud server can dispatch the power system according to the dispatch instruction; wherein the dispatch instruction includes the dispatch time, dispatch amount and dispatch method of each power grid node.

9. A cloud-edge computing power collaborative scheduling device, characterized in that: It includes acquisition module, judgment module, calculation module, analysis module and scheduling module; The acquisition module is used to obtain the operation data of each node in the power grid; The judgment module is used to judge whether each node of the power grid meets the power coordinated dispatching requirements according to the operation data of each node of the power grid; The calculation module is used to calculate the total power energy consumption value to be dispatched of each node in the power grid according to each preset energy consumption value of the power grid if the power coordinated dispatch demand is met, and obtain each power dispatch emergency information of each node in the power grid; The parsing module is used to upload the various power dispatch emergency information to each edge node for parsing, so that each edge node sends each power dispatch emergency value of each node of the power grid; The scheduling module is used to upload the power scheduling emergency values ​​to the cloud server, so that the cloud server can calculate the scheduling order of each node in the power grid according to the power scheduling emergency values ​​and the collaborative scheduling model, and schedule the power system according to the scheduling order of each node in the power grid and the total power energy consumption value to be scheduled.

10. A cloud server, comprising: Receiving module and scheduling module; The receiving module is used to receive each power dispatch emergency value of each node of the power grid uploaded by each edge node; wherein each power dispatch emergency value of each node of the power grid is parsed by each edge node according to each power dispatch emergency information, and fed back to the cloud server; the power dispatch emergency information is determined according to the operation data of each node of the power grid when the power coordinated dispatch demand is met; the power coordinated dispatch demand is determined according to the operation data of each node of the power grid; The scheduling module is used to calculate the scheduling order of each node in the power grid according to the power scheduling emergency values ​​and the collaborative scheduling model, and obtain the scheduling instructions of the power system according to the scheduling order of each node in the power grid and the total power energy consumption value to be scheduled.

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