Intelligent power grid system based on cloud computing

Abstract

The invention discloses an intelligent power grid system based on cloud computing, and the system comprises a user layer which comprises a plurality of intelligent ammeters, a distributed power supply, and a micro-grid; the middle layer comprises a power grid and a dispatching center, the middle layer is connected with the user layer, the power grid is suitable for carrying out bidirectional energy transfer with a distributed power supply and a micro-grid, and the dispatching center is suitable for carrying out information interaction with the power grid and the intelligent electric meters, dispatching the power grid to operate and dispatching the intelligent electric meters to execute tasks; and the cloud platform is in communication connection with the intermediate layer and the user layer, and is suitable for acquiring power data of each intelligent electric meter, each distributed power supply and each micro-grid of the user layer, processing and analyzing the power data to determine an optimal operation scheme, and controlling the operation of the power grid and the dispatching center of the intermediate layer based on the optimal operation scheme. The electric power data can be intelligently and efficiently processed by introducing the cloud platform, the development workload and the development cost are reduced, and the system operation is more stable.

Description

Technical Field

[0001] The present invention relates to the field of smart grid technology, and in particular to a smart grid system based on cloud computing. Background Art

[0002] Cloud computing can utilize the computing and storage capabilities of a large number of cheap servers, integrate these large-scale and different types of resources, and through virtualization technology, store computing and storage tasks on a powerful device (such as large servers and workstations) for execution. It can also split the tasks into several parts and distribute them across multiple distributed computers.

[0003] Most of the existing power management systems do not introduce a cloud platform and directly communicate data with terminal devices. This approach has the following problems: 1) The processing and analysis of power data is inefficient, and the intelligence level and operating efficiency are low, which cannot meet the needs of complex scenarios; 2) System developers need to work with embedded developers to build infrastructure, which increases the development workload and is difficult to support the scale of millions of devices in the architecture. When there are a large number of concurrent connections between devices, it is difficult to ensure the stability of the system. At the same time, the online and offline of a large number of devices may cause system avalanche, which poses many hidden dangers for high-concurrency scenarios; 3) Developers need to develop and deploy various security measures to ensure the security of device data; 4) It is necessary to purchase servers to build a load-balanced distributed architecture, and spend a lot of manpower and material resources to develop a complete Internet of Things system, and the implementation of device connection status, life cycle management and remote operation and maintenance is very complex.

[0004] In the future, users of cloud computing terminals will have a certain number of data computing and storage devices. As hardware speeds develop, the capabilities of these terminal devices will far exceed user demand. Therefore, these terminal devices can be considered as part of the cloud in cloud computing to provide computing and storage capabilities.

[0005] Therefore, a smart grid system based on cloud computing is needed to solve the problems existing in the above technical solutions. Summary of the invention

[0006] To this end, the present invention provides a smart grid system based on cloud computing to solve or at least alleviate the above problems.

[0007] According to one aspect of the present invention, there is provided a smart grid system based on cloud computing, comprising: a user layer, comprising a plurality of smart meters, distributed power sources and microgrids; an intermediate layer, comprising a power grid and a dispatching center, the intermediate layer being connected to the user layer, wherein the power grid is suitable for bidirectional energy transfer with the distributed power sources and the microgrid, the dispatching center being suitable for information exchange with the power grid and each smart meter, suitable for dispatching the power grid operation, and suitable for dispatching each smart meter to perform tasks; a cloud platform, being respectively communicatively connected with the intermediate layer and the user layer, suitable for acquiring power data of each smart meter, distributed power source and microgrid of the user layer, processing and analyzing the power data to determine an optimal operation plan, and controlling the operation of the power grid and the dispatching center of the intermediate layer based on the optimal operation plan, each of the smart meters being suitable for calculating and storing data as a terminal of the cloud platform, wherein the power data comprises a plurality of attribute data, and the plurality of attribute data comprises power consumption data, voltage data, current data, power data, frequency data, and power quality index data.

[0008] Optionally, in the cloud computing-based smart grid system according to the present invention, the cloud platform is suitable for generating parallel processing jobs based on the power data so as to execute the parallel processing jobs through multiple smart meters at the user layer.

[0009] Optionally, in the cloud computing-based smart grid system according to the present invention, the dispatching center is integrated with a parallel processing computing framework, which is suitable for selecting a smart meter from multiple smart meters in the user layer as a master node through the parallel processing computing framework, and selecting multiple smart meters as multiple working nodes, the multiple working nodes including multiple first working nodes for executing first tasks and multiple second working nodes for executing second tasks; the cloud platform is suitable for sending the parallel processing job to the master node; the master node is suitable for: decomposing the parallel processing job into multiple first tasks, and assigning the multiple first tasks to multiple first working nodes for execution based on the resource usage of each working node, and obtaining the intermediate results generated by each of the first working nodes after executing the task, and assigning each intermediate result as a second task to each second working node, so that each second working node merges the intermediate results to generate a final result.

[0010] Optionally, in the cloud computing-based smart grid system according to the present invention, the parallel processing jobs include: power consumption analysis parallel jobs, load forecasting parallel jobs, fault detection and diagnosis parallel jobs, power quality assessment parallel jobs, demand response analysis parallel jobs, and distributed energy management parallel jobs. One or more of the parallel jobs.

[0011] Optionally, in the cloud computing-based smart grid system according to the present invention, the cloud platform is suitable for processing and analyzing the power data in the following manner to determine the optimal operation plan: cleaning and formatting the power data to obtain power data in a predetermined format, and storing the power data in a predetermined format; using a statistical analysis method to analyze the power data in the predetermined format to obtain the relationship between multiple attribute data of the power data in the predetermined format and the pattern of each attribute data changing over time; based on the pattern of each attribute data changing over time, predicting the power demand of each regional load in each time period, so as to determine the power grid dispatching plan based on the power demand of each regional load in each time period; based on the pattern of each attribute data changing over time, evaluating the power quality of the power grid and predicting the power grid fault point to determine the power grid operation plan; based on the power grid operation plan and the power grid dispatching plan, combining the optimization objectives to determine the optimal operation plan.

[0012] Optionally, in the cloud computing-based smart grid system according to the present invention, a central collector is also included; the smart electric meter includes: an electric energy detection module, including an electric energy collection unit and an electric energy filtering unit, the electric energy collection unit is suitable for collecting the electric energy consumption data of the corresponding user, and the electric energy filtering unit is suitable for denoising the electric energy consumption data; an electric energy display module, including an electric energy calculation unit and an electric energy display unit, the electric energy calculation unit is suitable for calculating the denoised electric energy consumption data, and the electric energy display unit is suitable for displaying the calculated electric energy consumption data; an electric energy transmission module, including an electric energy storage unit and a data sending unit, The electric energy storage unit is suitable for storing the electricity usage data of the corresponding user at predetermined intervals, and the data sending unit is coupled to the central collector, and is suitable for sending the electricity usage data of the corresponding user to the central collector, wherein the central collector is suitable for obtaining the electricity usage data of multiple users from multiple smart meters, generating a predetermined data structure based on the electricity usage data of the multiple users, and sending the predetermined data structure to the cloud platform; the cloud platform is suitable for parsing the predetermined data structure to obtain the electricity usage data of the multiple users, and is suitable for statistics and analysis of the electricity usage data of the multiple users.

[0013] Optionally, in the cloud computing-based smart grid system according to the present invention, the electricity consumption data includes electricity metering data, current and voltage data, power data, power factor, frequency data, event record data, and meter status data.

[0014] Optionally, in the cloud computing-based smart grid system according to the present invention, the smart meter is further suitable for: monitoring the state of the power grid based on the power consumption data of the corresponding user, and determining abnormal events based on the event record data; measuring the harmonic content in the power grid based on the power consumption data of the corresponding user to evaluate the power quality of the power grid, as well as monitoring voltage fluctuations and flicker, detecting frequency deviations of the power grid, and measuring unbalanced load conditions in the three-phase system; analyzing the power consumption pattern of the corresponding user based on the power consumption data of the corresponding user, determining the peak power consumption period and the low power consumption period of the corresponding user, as well as the power consumption characteristics of the corresponding user in different time periods.

[0015] Optionally, in the cloud computing-based smart grid system according to the present invention, the smart meter is also suitable for: determining the electricity usage fee of the corresponding user according to pre-designed fee rules based on the electricity metering data in the electricity usage data of the corresponding user, generating an electricity bill based on the electricity usage fee and displaying it through the electricity display unit to present the electricity bill to the corresponding user; providing the electricity usage data of the corresponding user to a third-party server to obtain data service fees and displaying it through the electricity display unit; adjusting the electricity load of the corresponding user according to the grid demand to reduce the grid pressure and obtain corresponding benefits.

[0016] Optionally, in the cloud computing-based smart grid system according to the present invention, the cloud platform supports multiple communication protocols, including the MQTT protocol, the CoAP protocol and the HTTPS protocol.

[0017] According to the technical solution of the present invention, a cloud computing-based smart grid system is provided, including a user layer, an intermediate layer and a cloud platform, wherein the user layer includes multiple smart meters, distributed power sources and microgrids, the intermediate layer includes a power grid and a dispatching center, and information flow and energy flow can be transmitted bidirectionally between the intermediate layer and the user layer. The power grid operation can be dispatched during dispatching, and each smart meter can be dispatched to perform tasks. The cloud platform can obtain the power data of the user layer, and can process and analyze the power data to determine the optimal operation plan, so as to control the operation of the power grid and the dispatching center of the intermediate layer based on the optimal operation plan, and each smart meter can also be used as a terminal of the cloud platform to calculate and store data. It can be seen that the smart grid system of the present invention can realize efficient interaction and management of information flow and energy flow by introducing a cloud platform, and the collection, processing and analysis of power data are more intelligent and efficient, which effectively improves the intelligence level and operation efficiency of the system and can meet the needs in complex scenarios. Moreover, a variety of basic services can be provided through the cloud platform, which greatly reduces the development workload and development cost, and does not require additional development and deployment of various security measures. In addition, the concurrent processing capability is greatly improved based on the cloud platform, which can ensure the stability and reliability of the system. In addition, each smart meter can be used as a terminal of the cloud platform to calculate and store data, which can improve the scalability of the system.

[0018] The above description is only an overview of the technical solution of the present invention. In order to more clearly understand the technical means of the present invention, it can be implemented according to the contents of the specification. In order to make the above and other purposes, features and advantages of the present invention more obvious and easy to understand, the specific implementation methods of the present invention are listed below. BRIEF DESCRIPTION OF THE DRAWINGS

[0019] To achieve the above and related purposes, certain illustrative aspects are described herein in conjunction with the following description and accompanying drawings, which indicate various ways in which the principles disclosed herein can be practiced, and all aspects and their equivalents are intended to fall within the scope of the claimed subject matter. The above and other purposes, features and advantages of the present disclosure will become more apparent by reading the following detailed description in conjunction with the accompanying drawings. Throughout the present disclosure, the same reference numerals generally refer to the same parts or elements.

[0020] Figure 1 A schematic diagram of a cloud computing-based smart grid system 100 provided according to an embodiment of the present invention is shown;

[0021] Figure 2 A schematic diagram of a smart electric meter 200 provided according to an embodiment of the present invention is shown;

[0022] Figure 3 A schematic diagram of a computing device 300 provided according to an embodiment of the present invention is shown. DETAILED DESCRIPTION

[0023] The exemplary embodiments of the present disclosure will be described in more detail below with reference to the accompanying drawings. Although the exemplary embodiments of the present disclosure are shown in the accompanying drawings, it should be understood that the present disclosure can be implemented in various forms and should not be limited by the embodiments set forth herein. On the contrary, these embodiments are provided to enable a more thorough understanding of the present disclosure and to fully convey the scope of the present disclosure to those skilled in the art.

[0024] Most of the existing power management systems do not introduce a cloud platform and directly communicate data with terminal devices. This method has low efficiency in processing and analyzing power data, and has low intelligence and operating efficiency, and cannot meet the needs of complex scenarios. In addition, the development workload of the infrastructure is large, the system stability is poor, and developers need to develop and deploy various safety measures, which requires a lot of manpower and material resources.

[0025] In order to solve the above technical problems, the embodiment of the present invention provides a smart grid system 100 based on cloud computing. By introducing a cloud platform, it is possible to achieve efficient interaction and management of information flow and energy flow, and to make the collection, processing and analysis of power data more intelligent and efficient, effectively improving the intelligence level and operation efficiency of the system, and being able to meet the needs of complex scenarios. Moreover, the cloud platform can provide a variety of basic services, greatly reducing the development workload and development costs, and there is no need to develop and deploy various security measures in addition. In addition, the cloud platform greatly improves the concurrent processing capability, which can ensure the stability and reliability of the system.

[0026] The following is an introduction to the cloud computing-based smart grid system of the present invention.

[0027] Figure 1 A schematic diagram of a smart grid system 100 based on cloud computing provided according to an embodiment of the present invention is shown.

[0028] like Figure 1 As shown, the cloud computing-based smart grid system 100 includes a user layer 110, an intermediate layer 120 and a cloud platform 130. The user layer 110 includes a plurality of smart meters 200, distributed power sources (such as power plants) and microgrids. Each smart meter 200 can correspond to a user.

[0029] The middle layer 120 includes a power grid and a dispatch center 125. The middle layer 120 is connected to the user layer 110 (based on information flow and energy flow). The power grid can perform bidirectional energy transfer with distributed power sources and microgrids (power grid outputs energy or obtains energy). The dispatch center 125 can exchange information (bidirectional data communication) with the power grid and each smart meter 200. The dispatch center 125 can dispatch the power grid to operate and dispatch each smart meter 200 to perform tasks.

[0030] The cloud platform 130 is respectively connected to the middle layer 120 and the user layer 110. The cloud platform 130 can obtain the power data of each smart meter 200, distributed power source and microgrid of the user layer 110, and can process and analyze the power data to determine the optimal operation plan. Then, the cloud platform 130 can control the operation of the power grid and the dispatching center 125 of the middle layer 120 based on the optimal operation plan.

[0031] In the embodiment of the present invention, each smart meter 200 can also be used as a terminal of the cloud platform 130 to calculate and store data, which can improve the scalability of the smart grid system of the present invention.

[0032] In an embodiment of the present invention, the power data includes multiple attribute data, and the multiple attribute data may specifically include power consumption data, voltage data, current data, power data, frequency data, and power quality index data.

[0033] In some embodiments, after the user installs the smart meter 200, the smart meter 200 can be used as a terminal (server) of the cloud platform 130 to provide computing and storage services.

[0034] In some embodiments, the cloud platform 130 may generate parallel processing jobs based on the above power data, and may execute the parallel processing jobs through multiple smart meters 200 of the user layer 110 .

[0035] In some embodiments, the dispatch center 125 is integrated with a parallel processing computing framework, and through the parallel processing computing framework, a smart meter 200 is selected from multiple smart meters 200 of the user layer 110 as a master node, and multiple smart meters 200 are selected as multiple working nodes. The multiple working nodes include multiple first working nodes for executing the first task and multiple second working nodes for executing the second task. In some embodiments, the parallel processing computing framework can be a MapReduce framework, the first task can be a Map task, and the second task can be a Reduce task.

[0036] The cloud platform 130 can send the parallel processing job to the master node. The master node can decompose the parallel processing job into multiple first tasks (Map tasks), and can assign multiple first tasks to multiple first working nodes (Map working nodes) for execution based on the resource usage of each working node. After each first working node executes the first task, a corresponding intermediate result can be generated. The master node can obtain the intermediate result generated by each first working node after executing the first task, and send the intermediate result generated by each first working node as a second task to the second working node (Reduce working node) for execution. Each second working node can merge the intermediate results, generate a final result and output it, and then send the final result to the cloud platform 130.

[0037] In some embodiments, the parallel processing jobs may include one or more of power consumption analysis jobs, load forecasting jobs, fault detection and diagnosis jobs, power quality assessment jobs, demand response analysis jobs, and distributed energy management jobs.

[0038] It should be noted that the power consumption analysis parallel job is used to represent the parallel processing of power consumption data in different regions or different time periods to quickly derive the overall energy usage. The load forecasting parallel job is used to represent the parallel calculation of power demand in the future based on historical data to optimize the operation and scheduling of the power grid. The fault detection and diagnosis parallel job is used to represent the parallel analysis of real-time data from different parts of the power grid to quickly locate faults and propose solutions. The power quality assessment parallel job is used to represent the parallel processing of power grid data to evaluate the stability and power quality of voltage and current. The demand response analysis parallel job is used to represent the parallel processing of user power consumption data, analyze the effectiveness of demand response strategies, and optimize energy distribution. The distributed energy management parallel job is used to represent the parallel management of distributed energy systems, such as solar energy, wind energy, etc., to optimize energy collection, storage and use.

[0039] In some embodiments, the cloud platform 130 may process and analyze the power data in the following manner to determine the optimal operation solution:

[0040] First, the cloud platform 130 may clean and format the power data to obtain power data in a predetermined format, and may store the power data in a predetermined format.

[0041] Next, the cloud platform 130 can use statistical analysis methods (such as regression analysis and cluster analysis methods) to analyze the power data in the predetermined format to obtain the relationship between multiple attribute data (power consumption data, voltage data, current data, power data, frequency data, power quality index data) of the power data in the predetermined format and the pattern of changes in each attribute data over time.

[0042] Furthermore, the cloud platform 130 can predict the power demand of each regional load in each time period based on the time-varying pattern of each attribute data, so as to determine the power grid dispatch plan based on the power demand of each regional load in each time period. For example, the cloud platform 130 can use a machine learning algorithm such as a decision tree, a neural network, and a support vector machine to predict the power demand of each regional load in each time period based on the time-varying pattern of each attribute data.

[0043] Furthermore, the cloud platform 130 can evaluate the power quality of the power grid (such as voltage fluctuation, frequency deviation, etc.) based on the pattern of each attribute data changing over time, and predict the fault points of the power grid to determine the power grid operation plan.

[0044] Finally, the cloud platform 130 can determine the optimal operation plan (i.e., the optimal operation plan for controlling the operation of the power grid and the dispatch center 125 of the middle layer 120) based on the power grid operation plan and the power grid dispatch plan in combination with the optimization goal. Here, the optimization goal can be, for example, minimizing cost, maximizing efficiency, ensuring power quality, etc.

[0045] In some embodiments, the cloud computing-based smart grid system 100 further includes a central collector (not shown).

[0046] According to the embodiment of the present invention, the smart meter 200 not only has all the functions of the traditional meter and the existing smart meter 200, but also has computing and storage capabilities, and can be used as a terminal (server) of the cloud platform 130 to calculate and store data, which can improve the scalability of the smart grid system of the present invention.

[0047] Figure 2 A schematic diagram of a smart electric meter 200 provided according to an embodiment of the present invention is shown.

[0048] like Figure 2 As shown, the smart electric meter 200 includes an electric energy detection module 210, an electric energy display module 220 and an electric energy transmission module 230 which are coupled in sequence.

[0049] The power detection module 210 includes a power collection unit and a power filtering unit. The power collection unit can collect power consumption data of the corresponding user, and the power filtering unit can denoise the power consumption data.

[0050] The power display module 220 includes a power calculation unit and a power display unit. The power calculation unit can calculate the denoised power consumption data, and the power display unit can display the calculated power consumption data (delayed display is possible).

[0051] The power transmission module 230 includes a power storage unit and a data transmission unit. The power storage unit can store the power consumption data of the corresponding user at predetermined intervals (for example, every 1 minute). The data transmission unit is connected to the central collector in communication and can send the power consumption data of the corresponding user to the central collector.

[0052] The central collector can be connected to the data transmission units of the smart meters 200 of multiple users in communication, and the central collector can obtain the power consumption data of multiple users from the multiple smart meters 200, generate a predetermined data structure based on the power consumption data of multiple users, and send the predetermined data structure to the cloud platform 130 (or the server of the power supply company). The cloud platform 130 can parse the predetermined data structure to obtain the power consumption data of multiple users, and can perform statistics and analysis on the power consumption data of multiple users.

[0053] In this way, the electricity consumption data of multiple users can be transmitted in batches through the central collector, thereby avoiding network jitter and server downtime that may occur during end-to-end data transmission.

[0054] In some embodiments, the user's electricity usage data may include electricity metering data (real-time electricity consumption), current and voltage data (real-time current and voltage measurements), power data (real-time power consumption, including active power and reactive power), power factor (an indicator reflecting the efficiency of the power system), frequency data (the frequency of the power grid), event record data (for example, records of events such as power outages, overloads, and voltage anomalies), and meter status data (characterizing the working status of the smart meter 200, including fault status, battery charge status, etc.).

[0055] In some embodiments, the smart meter 200 can accurately measure electricity, monitor the state of the power grid, measure the quality of electricity, and track and analyze the user's electricity usage habits based on the collected electricity usage data of the corresponding user.

[0056] Specifically, the smart meter 200 can monitor the status of the power grid (for example, whether the voltage is stable, whether the current exceeds the limit, etc.) based on the corresponding user's electricity consumption data, and is suitable for determining abnormal events (such as power outages, overloads, voltage fluctuations, etc.) based on event record data.

[0057] The smart meter 200 can also measure the harmonic content in the power grid based on the corresponding user's electricity consumption data to evaluate the power quality of the power grid, as well as monitor voltage fluctuations and flicker (monitor short-term and long-term fluctuations in voltage, as well as rapid changes in voltage), detect the frequency deviation of the power grid (whether the frequency of the power grid deviates from the standard value), and measure the unbalanced load situation in the three-phase system.

[0058] The smart meter 200 can also analyze the electricity usage pattern of the corresponding user based on the electricity usage data of the corresponding user, determine the peak and valley periods of electricity usage of the corresponding user, and determine the electricity usage characteristics of the corresponding user in different time periods.

[0059] In some embodiments, the smart meter 200 can calculate the effective value of the current and voltage by the following formula:

[0060]

[0061] It should be noted that the effective value is one of the most important parameters of the power grid. It is used to measure the amplitude of the AC signal. The effective value of an AC signal is equal to the DC amount of the same power generated on the load. The unit of voltage is "volt", and the symbol is V; the unit of current is "ampere", and the symbol is A.

[0062] The smart meter 200 can calculate the frequency of the power grid by the following formula:

[0063]

[0064] It should be noted that frequency is the reciprocal of period, and its unit is "Hertz" and its symbol is HZ. Frequency is generally calculated by zero-crossing detection method. Let the time when the AC signal crosses zero be kt.

[0065] The smart meter 200 can calculate the power by the following formula:

[0066]

[0067] Among them, V k and I k Respectively represent the effective value of each harmonic of the voltage signal and the current signal;

[0068] and γ k Respectively represent the phase difference of each harmonic of voltage signal and current signal.

[0069] The instantaneous power is p(t)=v(t)×i(t), and the average power is shown in formula (7):

[0070]

[0071] In the formula, T represents the period, and n represents an integer number of line periods. From the above formula, it can be seen that the active power (i.e., average power) is equal to the DC component of the instantaneous power.

[0072] In some embodiments, the smart meter 200 includes a CPU, memory, IO devices, supporting software, and a real-time update module. The smart meter 200 is equivalent to a small server. After the smart meter 200 is applied to the user's home, the smart meters 200 installed by multiple users can be interconnected through high-speed communication lines to form a huge computing and storage network (user cloud).

[0073] In some embodiments, after the user installs the smart meter 200, the smart meter 200 can be used as a terminal (server) of the cloud platform 130 to provide computing and storage services. The smart meter 200 can calculate the user's electricity expenditure and the revenue obtained by the smart meter 200 from providing services through a two-way charging system.

[0074] It should be noted that the smart meter 200 in the embodiment of the present invention has a high-precision metering function. The smart meter 200 can accurately record the electricity usage data of the corresponding user (electricity metering data, that is, real-time electricity consumption) and calculate the electricity usage fee of the corresponding user according to preset billing rules.

[0075] Specifically, the smart meter 200 can determine the electricity usage fee of the corresponding user based on the electricity metering data (real-time electricity consumption) in the electricity usage data of the corresponding user according to pre-designed billing rules, and then generate an electricity bill based on the electricity usage fee, and display the electricity bill through the electricity display unit to present the electricity bill to the corresponding user.

[0076] Here, the pre-designed charging rules include electricity fee standards, which are the charging standards of local power companies and may involve basic electricity fees, peak and valley electricity prices, and tiered electricity prices.

[0077] In addition, the smart meter 200 can also provide the corresponding user's electricity consumption data to a third-party server (or power company server) to provide data support to obtain data service fees from the third-party server provider or (or power company). In addition, the smart meter 200 can display the data service fees through the power display unit to present the data service fees to the corresponding user.

[0078] The smart meter 200 can also adjust the power load of the corresponding user according to the grid demand to reduce the grid pressure and obtain corresponding benefits (incentives or compensation). In addition, the smart meter 200 can display the benefit information through the power display unit to present the benefit information to the corresponding user.

[0079] In some embodiments, the smart meter 200 can provide energy management services to users, such as energy-saving suggestions, power optimization solutions, etc., to help users reduce energy consumption and obtain service fees. In addition, if the user has distributed energy such as solar panels, the smart meter 200 can manage the input and output of these energy sources and optimize energy use. The smart meter 200 can also be used as part of a virtual power plant to provide grid regulation services and obtain market benefits by aggregating the energy resources of multiple users.

[0080] In some embodiments, the cloud platform 130 supports multiple communication protocols, including, for example, the MQTT protocol, the CoAP protocol, and the HTTPS protocol. Based on multiple communication protocols, it can adapt to different types of power equipment and network environments, ensuring efficient exchange of data between terminal devices (such as the smart meter 200) and the cloud platform 130.

[0081] The cloud platform 130 in the embodiment of the present invention can provide a variety of basic services, including data analysis services, security maintenance services, data flow services, etc. Based on these services, the collection, cleaning and storage of power data can be efficiently processed. Through strict security measures, the integrity and confidentiality of power data during transmission and storage are ensured.

[0082] The cloud platform 130 in the embodiment of the present invention supports the connection of hundreds of millions of devices and the concurrent processing of millions of messages, which is particularly important for processing a large amount of power data. At the same time, it has a strong DDoS attack protection capability, which can ensure the stability and reliability of the system and ensure the real-time reception and processing of power data.

[0083] In addition, the cloud platform 130 in the embodiment of the present invention uses cloud services for system development and deployment, which not only simplifies the management of infrastructure, but also improves the flexibility and scalability of the system. Users can easily operate through a browser, which is convenient for subsequent system upgrades and maintenance, ensuring the stability and sustainable development capabilities of the system in long-term operation.

[0084] According to the cloud computing-based smart grid system 100 provided in the embodiment of the present invention, it includes a user layer, an intermediate layer and a cloud platform, wherein the user layer includes a plurality of smart meters, distributed power sources and microgrids, the intermediate layer includes a power grid and a dispatching center, and information flow and energy flow can be transmitted bidirectionally between the intermediate layer and the user layer, and the power grid operation can be dispatched during dispatching, and each smart meter can be dispatched to perform tasks. The cloud platform can obtain the power data of the user layer, and can process and analyze the power data to determine the optimal operation plan, so as to control the operation of the power grid and the dispatching center of the intermediate layer based on the optimal operation plan, and each smart meter can also be used as a terminal of the cloud platform to calculate and store data. It can be seen that the smart grid system of the present invention can realize efficient interaction and management of information flow and energy flow by introducing the cloud platform, and the collection, processing and analysis of power data are more intelligent and efficient, which effectively improves the intelligence level and operation efficiency of the system and can meet the needs in complex scenarios. Moreover, a variety of basic services can be provided through the cloud platform, which greatly reduces the development workload and development cost, and does not require additional development and deployment of various security measures. In addition, the concurrent processing capability is greatly improved based on the cloud platform, which can ensure the stability and reliability of the system. In addition, each smart meter can be used as a terminal of the cloud platform to calculate and store data, which can improve the scalability of the system.

[0085] In some embodiments, the cloud platform, dispatch center, and smart meter of the present invention can be implemented as a computing device 300 described below.

[0086] Figure 3 FIG. 3 is a schematic diagram of a computing device 300 provided according to an embodiment of the present invention. Figure 3 As shown, in a basic configuration, computing device 300 includes at least one processing unit 302 and system memory 304. According to one aspect, depending on the configuration and type of computing device, processing unit 302 can be implemented as a processor. System memory 304 includes, but is not limited to, volatile storage (e.g., random access memory), non-volatile storage (e.g., read-only memory), flash memory, or any combination of such memories. According to one aspect, system memory 304 includes operating system 305.

[0087] According to one aspect, operating system 305 is suitable for controlling the operation of computing device 300, for example. Furthermore, examples are practiced in conjunction with graphics libraries, other operating systems, or any other application programs, and are not limited to any particular application or system. Figure 3The basic configuration is shown in FIG. 3 by those components within the dashed lines. According to one aspect, computing device 300 has additional features or functionality. For example, according to one aspect, computing device 300 includes additional data storage devices (removable and / or non-removable), such as magnetic disks, optical disks, or tapes. Such additional storage Figure 3 3 is illustrated by a removable storage device 309 and a non-removable storage device 310.

[0088] As stated above, according to one aspect, a program module 303 is stored in the system memory 304. According to one aspect, the program module 303 may include one or more application programs, and the present invention does not limit the type of application program, for example, the application program may include: a data analysis application program, a word processing application program, a spreadsheet application program, a database application program, a web browser application program, etc.

[0089] According to one aspect, the examples may be practiced on a circuit comprising discrete electronic components, a packaged or integrated electronic chip containing logic gates, a circuit utilizing a microprocessor, or a single chip containing electronic components or a microprocessor. Figure 3 Each or many components shown in can be integrated into a system on a chip (SOC) on a single integrated circuit to practice examples. According to one aspect, such a SOC device may include one or more processing units, a graphics unit, a communication unit, a system virtualization unit, and various application functions, all of which are integrated (or "burned") into a chip substrate as a single integrated circuit. When operated via SOC, the functions described in this article can be operated via a dedicated logic integrated with other components of the computing device 300 on a single integrated circuit (chip). Other technologies that can perform logical operations (such as AND, OR, and NOT) can also be used to practice embodiments of the present invention, including but not limited to mechanical, optical, fluid, and quantum technologies. In addition, embodiments of the present invention can be practiced in a general-purpose computer or in any other circuit or system.

[0090] According to one aspect, computing device 300 may also have one or more input devices 312, such as a keyboard, a mouse, a pen, a voice input device, a touch input device, etc. Output devices 314 may also be included, such as a display, a speaker, a printer, etc. The aforementioned devices are examples and other devices may also be used. Computing device 300 may include one or more communication connections 316 that allow communication with other computing devices 318. Examples of suitable communication connections 316 include, but are not limited to: RF transmitter, receiver and / or transceiver circuits; Universal Serial Bus (USB), parallel and / or serial ports.

[0091] The term computer-readable medium as used herein includes computer storage media. Computer storage media may include volatile and non-volatile, removable and non-removable media implemented in any method or technology for storing information (e.g., computer-readable instructions, data structures, or program modules). System memory 304, removable storage device 309, and non-removable storage device 310 are all examples of computer storage media (i.e., memory storage). Computer storage media may include random access memory (RAM), read-only memory (ROM), electrically erasable read-only memory (EEPROM), flash memory or other memory technology, CD-ROM, digital versatile disk (DVD) or other optical storage, cassettes, tapes, disk storage or other magnetic storage devices, or any other products that can be used to store information and can be accessed by computing device 300. According to one aspect, any such computer storage medium may be a part of computing device 300. Computer storage media do not include carrier waves or other propagated data signals.

[0092] According to one aspect, communication media is implemented by computer readable instructions, data structures, program modules, or other data in a modulated data signal (e.g., a carrier wave or other transport mechanism), and includes any information delivery media. According to one aspect, the term "modulated data signal" describes a signal that has one or more characteristics set or changed in a manner that encodes information in the signal. By way of example and not limitation, communication media includes wired media such as a wired network or direct-wired connection, and wireless media such as acoustic, radio frequency (RF), infrared, and other wireless media.

[0093] The various techniques described herein may be implemented in combination with hardware or software, or a combination thereof. Thus, the method and apparatus of the present invention, or some aspects or parts of the method and apparatus of the present invention may be in the form of program codes (i.e., instructions) embedded in a tangible medium, such as a removable hard disk, a USB flash drive, a floppy disk, a CD-ROM, or any other machine-readable storage medium, wherein when the program is loaded into a machine such as a computer and executed by the machine, the machine becomes a device for practicing the present invention.

[0094] In the case where the program code is executed on a programmable computer, the mobile terminal generally includes a processor, a storage medium readable by the processor (including volatile and non-volatile memory and / or storage elements), at least one input device, and at least one output device. The memory is configured to store the program code; the processor is configured to execute the program code according to the instructions in the program code stored in the memory.

[0095] By way of example and not limitation, readable media include readable storage media and communication media. Readable storage media stores information such as computer readable instructions, data structures, program modules or other data. Communication media generally embody computer readable instructions, data structures, program modules or other data in a modulated data signal such as a carrier wave or other transmission mechanism, and include any information transfer medium. Any combination of the above is also included within the scope of readable media.

[0096] In the description provided herein, algorithms and displays are not inherently related to any particular computer, virtual system or other device. Various general purpose systems can also be used together with the examples of the present invention. According to the above description, it is obvious that the structure required for constructing such systems. In addition, the present invention is not directed to any specific programming language either. It should be understood that various programming languages ​​can be utilized to implement the content of the present invention described herein, and the above description of specific languages ​​is for the purpose of disclosing the best mode of the present invention.

[0097] In the description provided herein, a large number of specific details are described. However, it is understood that embodiments of the present invention can be practiced without these specific details. In some instances, well-known methods, structures and techniques are not shown in detail so as not to obscure the understanding of this description.

[0098] Similarly, it should be understood that in order to streamline the present disclosure and aid in understanding one or more of the various inventive aspects, in the above description of exemplary embodiments of the present invention, various features of the present invention are sometimes grouped together into a single embodiment, figure, or description thereof.

[0099] Those skilled in the art will appreciate that the modules or units or components of the devices in the examples disclosed herein may be arranged in the devices described in the embodiment, or alternatively may be located in one or more devices different from the devices in the examples. The modules in the foregoing examples may be combined into one module or may be divided into multiple submodules.

[0100] Unless otherwise specified, the use of ordinal numbers "first", "second", "third", etc. to describe common objects merely indicates that different instances of similar objects are involved and is not intended to imply that the objects so described must have a given order in time, space, order or in any other manner.

Claims

1. A smart grid system based on cloud computing, comprising: The user layer includes multiple smart meters, distributed power sources, and microgrids; The middle layer includes a power grid and a dispatching center, wherein the middle layer is connected to the user layer, wherein the power grid is suitable for bidirectional energy transmission with the distributed power source and the microgrid, and the dispatching center is suitable for information exchange with the power grid and each smart meter, and is suitable for dispatching the power grid operation and dispatching each smart meter to perform tasks; The cloud platform is respectively communicated with the middle layer and the user layer, and is suitable for obtaining power data of each smart meter, distributed power source and microgrid of the user layer, processing and analyzing the power data to determine the optimal operation plan, and controlling the operation of the power grid and dispatching center of the middle layer based on the optimal operation plan. Each of the smart meters is suitable for calculating and storing data as a terminal of the cloud platform, wherein the power data includes a variety of attribute data, and the various attribute data include power consumption data, voltage data, current data, power data, frequency data, and power quality index data.

2. The system of claim 1, wherein: The cloud platform is suitable for generating parallel processing jobs based on the power data so as to execute the parallel processing jobs through a plurality of smart meters at the user layer.

3. The system of claim 2, wherein: The dispatch center is integrated with a parallel processing computing framework, and is suitable for selecting a smart meter from the multiple smart meters in the user layer as a master node through the parallel processing computing framework, and selecting multiple smart meters as multiple working nodes, wherein the multiple working nodes include multiple first working nodes for executing the first task and multiple second working nodes for executing the second task; The cloud platform is adapted to send the parallel processing job to the master node; The master node is suitable for: decomposing the parallel processing job into multiple first tasks, and assigning the multiple first tasks to multiple first work nodes for execution based on the resource usage of each work node, and obtaining the intermediate results generated after each of the first work nodes executes the task, and assigning each intermediate result as a second task to each second work node, so that each second work node merges the intermediate results to generate a final result.

4. A system as claimed in claim 2 or 3, wherein: The parallel processing jobs include: one or more of: power consumption analysis parallel jobs, load forecasting parallel jobs, fault detection and diagnosis parallel jobs, power quality assessment parallel jobs, demand response analysis parallel jobs, and distributed energy management parallel jobs.

5. The system according to any one of claims 1 to 4, wherein: The cloud platform is suitable for processing and analyzing the power data in the following manner to determine the optimal operation plan: Cleaning and formatting the power data to obtain power data in a predetermined format, and storing the power data in the predetermined format; Analyzing the power data in the predetermined format by using a statistical analysis method to obtain a relationship between multiple attribute data of the power data in the predetermined format and a pattern of changes of each attribute data over time; Based on the time-varying pattern of each attribute data, predict the power demand of each regional load in each time period, so as to determine the power grid dispatching plan based on the power demand of each regional load in each time period; Based on the time-varying patterns of each attribute data, the power quality of the power grid is evaluated, and the power grid fault points are predicted to determine the power grid operation plan; Based on the power grid operation plan and the power grid dispatch plan, the optimal operation plan is determined in combination with the optimization target.

6. The system of any one of claims 1 to 5, wherein: It also includes a central collector; The smart electric meter comprises: The power detection module includes a power collection unit and a power filtering unit, wherein the power collection unit is suitable for collecting power consumption data of a corresponding user, and the power filtering unit is suitable for denoising the power consumption data; The electric energy display module comprises an electric energy calculation unit and an electric energy display unit, wherein the electric energy calculation unit is adapted to calculate the denoised electric energy data, and the electric energy display unit is adapted to display the calculated electric energy data; The electric energy transmission module comprises an electric energy storage unit and a data transmission unit, wherein the electric energy storage unit is adapted to store the electric energy consumption data of the corresponding user at predetermined intervals, and the data transmission unit is coupled to a central collector and is adapted to send the electric energy consumption data of the corresponding user to the central collector, wherein the central collector is adapted to obtain the electric energy consumption data of multiple users from multiple smart meters, generate a predetermined data structure based on the electric energy consumption data of the multiple users, and send the predetermined data structure to the cloud platform; The cloud platform is suitable for parsing the predetermined data structure to obtain the electricity usage data of the multiple users, and is suitable for performing statistics and analysis on the electricity usage data of the multiple users.

7. The system of claim 6, wherein: The electricity consumption data includes electric energy metering data, current and voltage data, power data, power factor, frequency data, event record data, and meter status data.

8. The system of claim 7, wherein: The smart meter is further adapted to: Based on the power consumption data of the corresponding user, monitoring the state of the power grid, and being adapted to determine abnormal events based on the event record data; Based on the electricity consumption data of the corresponding user, measure the harmonic content in the power grid to evaluate the power quality of the power grid, monitor voltage fluctuations and flickers, detect frequency deviations of the power grid, and measure unbalanced load conditions in the three-phase system; Based on the electricity consumption data of the corresponding user, the electricity consumption pattern of the corresponding user is analyzed to determine the peak electricity consumption period and the valley electricity consumption period of the corresponding user, as well as the electricity consumption characteristics of the corresponding user in different time periods.

9. The system of claim 7 or 8, wherein: The smart meter is also suitable for: Based on the electric energy metering data in the electric energy usage data of the corresponding user, determining the electric energy usage fee of the corresponding user according to the pre-designed fee rule, generating an electric energy bill based on the electric energy usage fee and displaying it through the electric energy display unit to present the electric energy bill to the corresponding user; Providing the electricity consumption data of the corresponding user to a third-party server to obtain data service fees and displaying the data through an electric energy display unit; Adjust the electricity load of corresponding users according to the grid demand to reduce the pressure on the grid and obtain corresponding benefits.

10. The system of any one of claims 1 to 9, wherein: The cloud platform supports multiple communication protocols, including MQTT protocol, CoAP protocol and HTTPS protocol.

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