Intelligent power protection method, system and device for security control, and storage medium

Abstract

The invention discloses an intelligent power protection method, system and device for safety control, and a storage medium, and relates to the field of intelligent power grids. The method comprises the following steps: acquiring electric power guarantee demands of a client side, and integrating the electric power guarantee demands to perform priority ranking on the electric power guarantee demands; the client side is monitored in real time to obtain power data of the client side, load prediction is performed according to the power data through an edge computing node of the client side, and a load prediction result is sent to the cloud platform; calculating the required power resource quantity according to the power guarantee demand and the load prediction result through the cloud platform, and determining a power resource allocation scheme according to the target function, the power resource quantity and the priority; a scheduling plan is generated according to the electric power resource distribution scheme, the power supply state of the client side is adjusted according to the scheduling plan, and the scheduling plan comprises power generation output, power transmission paths and power distribution loads. By implementing the technical scheme provided by the invention, diversified power guarantee requirements can be better met.

Description

Technical Field

[0001] The present application relates to the technical field of smart grids, and specifically to a safe and intelligent power protection method, system, device and storage medium. Background Art

[0002] With the rapid development of society and the advancement of science and technology, electricity has become an indispensable resource in modern society. In order to meet the power needs of various customers, especially power supply companies and key power supply protection sites, the application of smart power supply protection technology has become increasingly important.

[0003] In traditional power management systems, power resource allocation and scheduling usually rely on manual or simple automated scripts. This approach may be effective when dealing with small-scale or stable power demand, but it is difficult to cope with large-scale and dynamically changing power demand. In addition, existing systems often fail to fully consider the combined impact of multiple factors when allocating power resources, such as power supply stability, cost optimization, and customer satisfaction.

[0004] Therefore, how to effectively obtain and integrate diverse power security needs, and how to intelligently allocate and dispatch power resources based on these needs and real-time power data, have become important challenges facing current smart power security technologies. Summary of the invention

[0005] The present application provides a safe and intelligent power protection method, system, equipment and storage medium, which adopts intelligent power protection demand integration and optimization technology, can better meet the diverse power protection needs, improve the stability of the power system and customer satisfaction, and adopts real-time monitoring and load forecasting technology to make the allocation of power resources more scientific and reasonable, reduce costs and improve resource utilization efficiency.

[0006] In a first aspect of the present application, a securely managed smart power protection method is provided, which is applied to a smart power protection platform. The smart power protection platform includes a cloud platform and an edge computing node. The method includes: Obtaining the power security requirements of the customer side, integrating the power security requirements to prioritize the power security requirements, the power security requirements for preset special periods of time, and emergency response to faults, the customer side including the power supply company and preset key power security locations; The client side is monitored in real time to obtain the power data of the client side, the edge computing node of the client side performs load forecasting according to the power data, and the load forecasting result is sent to the cloud platform; The cloud platform calculates the required amount of power resources according to the power security demand and the load forecast result, and determines the power resource allocation plan according to the objective function, the power resource amount and the priority, wherein the objective function includes minimizing cost, maximizing customer satisfaction or ensuring stable power supply; A dispatching plan is generated according to the power resource allocation plan, and the power supply status of the customer side is adjusted according to the dispatching plan, wherein the dispatching plan includes power generation output, transmission path, and distribution load.

[0007] By adopting the above technical solution, the real-time monitoring and load forecasting of customer-side power data by edge computing nodes can quickly capture the changing trend of power demand, reduce the time delay of data transmission to the cloud platform, thereby speeding up the allocation of power resources and the formulation of scheduling plans, and improving the response speed of power security. The cloud platform intelligently calculates and determines the power resource allocation plan based on the power security demand and load forecast results, combined with objective functions such as cost minimization, customer satisfaction maximization or power supply stability. This method can make more effective use of limited power resources, avoid waste and over-allocation of resources, and ensure the economy and efficiency of power supply. By integrating the power security needs of the customer side, especially the power security needs and fault emergency response for preset special periods, the method can plan and prepare corresponding power security measures in advance, reduce the impact of sudden faults on power supply, and significantly improve the stability and reliability of power supply. Whether it is a power supply company or a preset key power security site, this application can flexibly respond to its diverse power security needs, and ensure that the power supply of key facilities and regions is prioritized through priority sorting and intelligent scheduling, while taking into account the basic power needs of other customers.

[0008] Optionally, the real-time monitoring of the client side to obtain the power data of the client side includes: The size of the window is set according to the periodic changes of the voltage and the current, the offset is determined according to the size and the expected data compression ratio, and the length is represented by an integer of a preset fixed length; Read data byte by byte from the power data, and for each newly read byte, search forward within the window using a hash table or a string matching algorithm to find the longest matching item; The offset and length of the longest matching item are recorded, and the offset and length are output as compressed power data.

[0009] By adopting the above technical solution, the window size is set by using the periodic variation characteristics of voltage and current, and the offset is determined in combination with the expected data compression ratio, so that redundant information in power data can be efficiently identified and compressed. The longest matching item is searched in the window using a hash table or a string matching algorithm, which ensures that the compression algorithm can accurately find the data segment that can be compressed, thereby achieving a high data compression ratio. This efficient compression method reduces the load of data transmission and storage and improves the overall efficiency of the system. Since the power data is effectively compressed, the bandwidth required during the transmission process is significantly reduced. This is particularly important for monitoring systems that need to transmit a large amount of power data in real time, because it can ensure that the power data can be transmitted to the cloud platform or other processing center in a timely and accurate manner under limited network resources. The compressed power data is faster in processing and analysis because the amount of data that the processor needs to process is reduced. This helps to speed up data processing and analysis, allowing the cloud platform to respond to power security needs, formulate scheduling plans, and adjust power supply status more quickly. The compressed power data occupies less storage space, which is an important advantage for systems that need to store a large amount of power data for a long time. It can reduce the capacity requirements of storage devices, reduce storage costs, and optimize the utilization of storage resources. Due to the improved efficiency of data compression and transmission, the system can obtain power data on the customer side in a more real-time manner. This is crucial for power protection scenarios that require real-time monitoring of power status and rapid response, because it ensures that the system can respond quickly and take appropriate measures when power anomalies or failures occur. By adjusting parameters such as window size, expected data compression ratio, and using different matching algorithms, it can be flexibly configured according to different application scenarios and requirements. This makes the method applicable to a variety of power monitoring scenarios and meets the needs of different customers for power data monitoring and compression.

[0010] Optionally, sending the load forecast result to the cloud platform includes: Encrypt the AES session key using the public key of the cloud platform to generate an encrypted session key; Encrypting the load forecast result using the AES session key to generate an encrypted load forecast result; The encrypted session key and the encrypted load forecast result are packaged to obtain a data packet, and the data packet is sent to the cloud platform through a communication channel.

[0011] By adopting the above technical solution, the AES session key is encrypted using the public key of the cloud platform, ensuring the security of the AES session key during transmission. Even if the AES session key is intercepted during transmission, it cannot be decrypted by an unauthorized third party because only the cloud platform has the corresponding private key. At the same time, the load forecasting results are encrypted using the AES session key, further ensuring the confidentiality and integrity of the load forecasting data during transmission. AES encryption is an efficient symmetric encryption algorithm, which has faster encryption and decryption speeds than public key encryption algorithms (such as RSA). Therefore, when transmitting a large amount of load forecasting data, using AES for data encryption can significantly improve transmission efficiency and reduce the time required for data transmission. The embodiment of the present application combines the advantages of public key encryption and symmetric encryption, which not only ensures the secure transmission of session keys, but also improves the efficiency of data encryption. This hybrid encryption mechanism can be flexibly adjusted according to different application scenarios and requirements to adapt to different data transmission requirements and security requirements. The load forecasting results may contain sensitive business information or customer privacy. By encrypting and transmitting these data, it can be ensured that these data are not leaked to unauthorized third parties during transmission. This helps protect user privacy and trade secrets and enhances customer trust in power service providers. The embodiments of the present application can be easily integrated into existing power monitoring and cloud platform systems without large-scale modifications to the system architecture. At the same time, by using standardized encryption protocols and algorithms, key management and encryption and decryption operations can be easily performed, reducing the maintenance cost and management difficulty of the system.

[0012] Optionally, sending the load forecast result to the cloud platform further includes: A cyclic redundancy check field is added to the data packet, the transmission path is dynamically adjusted according to the network status and transmission requirements, and the load prediction result is sent to the cloud platform through the determined transmission path. The network status includes bandwidth, delay and packet loss rate, and the transmission requirements include data importance and real-time requirements.

[0013] By adopting the above technical solution, adding a CRC field to the data packet can perform integrity check on the transmitted data. After receiving the data packet, the receiver can check the data in the data packet according to the CRC field to ensure that the data has not been tampered with or damaged during the transmission process. This mechanism can significantly improve the reliability of data transmission and reduce decision-making errors or system abnormalities caused by data errors. Dynamically adjusting the transmission path according to network status (such as bandwidth, delay and packet loss rate) and transmission requirements (such as data importance and real-time requirements) can ensure that the load forecast results can be transmitted to the cloud platform in the most appropriate path. In a network environment with low bandwidth or high delay, a path with lower delay or lower packet loss rate can be selected; for data with high real-time requirements, a faster transmission path can be selected. This way of dynamically adjusting the transmission path can optimize data transmission efficiency and ensure that key data can arrive in time. The network environment is complex and changeable, including bandwidth fluctuations, delay changes, increased packet loss rate, etc. By dynamically adjusting the transmission path, the embodiment of the present application can adaptively respond to these changes and ensure the stability and reliability of data transmission. This adaptive capability enables the system to maintain efficient operation in different network environments. By dynamically adjusting the transmission path, network resources can be reasonably utilized to avoid waste of network resources. When bandwidth is limited, key data can be transmitted first; when bandwidth is sufficient, more data can be transmitted. This intelligent resource allocation method can improve the utilization of network resources and reduce overall operating costs. The addition of CRC check and dynamic adjustment of transmission path mechanisms make the system more flexible and scalable in design. With the development of technology and the continuous expansion of applications, the system can easily add new functions or optimize existing functions to adapt to new needs and challenges.

[0014] Optionally, the calculating the required amount of electric power resources according to the electric power guarantee demand and the load forecast result by the cloud platform includes: Analyze the power security demand to determine a first time period and a second time period, wherein the first time period refers to a time period in which basic power resources are required, and the second time period refers to a time period in which basic power resources and additional power resources are required; For the first time period, using the load forecast result as the required amount of electric power resources; For the second time period, a first value of the additional power resources is determined according to the power guarantee demand, and the required amount of power resources is taken as the sum of the first value and the load forecast result.

[0015] By adopting the above technical solution and conducting a detailed analysis of the power security demand, the cloud platform can distinguish between the time period (first time period) when basic power resources are required and the time period (second time period) when basic power resources and additional power resources are required. This distinction makes the allocation of power resources more accurate, avoids waste or shortage of resources, and ensures the stability and reliability of power supply. When the power demand changes, especially when additional power resources are required in the second time period, the cloud platform can calculate and determine the required amount of additional power resources in real time according to the power security demand. This dynamic response capability enables the power system to quickly adapt to fluctuations in power demand and improves the flexibility and efficiency of power supply. Using load forecasting results as the basis for power resource demand and determining the required amount of power resources in combination with power security demand helps to optimize the configuration of power resources. By predicting power demand in advance and planning the allocation of power resources, it can be ensured that there are sufficient power resources available during peak power demand periods, thereby reducing the risk of power shortage or overload. By accurately calculating the required amount of power resources, the cloud platform can ensure that the power system maintains a stable operating state while meeting the power security demand. This helps to reduce power failures and accidents caused by insufficient or excessive power supply and improves the safety and reliability of the power system. The cloud platform calculates the required amount of power resources based on power security needs and load forecast results, providing strong data support for power dispatch and management. This enables power dispatchers to make intelligent decisions based on accurate data, optimize the dispatch and use of power resources, and improve the overall efficiency of the power system.

[0016] Optionally, determining a first value of additional power resources according to the power guarantee requirement includes: Obtaining special conditions in the power supply demand, wherein the special conditions include power supply demand caused by weather, power supply demand caused by activities, and emergency power supply demand; Determining an additional increase in electricity demand based on the special conditions and historical data, wherein the historical data includes electricity usage characteristics, electricity usage habits and rated power of equipment of different users, wherein the different users include residential users, commercial users and industrial users; The first value is determined according to the additional increase and influencing factors, where the influencing factors include equipment efficiency, power grid transmission capacity and spare capacity.

[0017] By adopting the above technical solution, the system can more accurately assess the increase in power demand by obtaining special conditions in power security demand, such as power supply demand caused by weather, activities or emergencies. This accurate assessment helps to ensure that the required additional power resources can be provided in a timely and accurate manner during peak power demand or emergencies. When determining the additional increase in power demand, the system not only considers the power consumption characteristics and habits of different users in historical data, but also combines the rated power of the equipment. This comprehensive consideration makes the evaluation result more comprehensive and accurate. At the same time, by further considering influencing factors such as equipment efficiency, grid transmission capacity and spare capacity, the system can more finely calculate the required additional power resources, thereby improving the reliability and stability of power supply. The first value determined according to the additional increase in power demand and the influencing factors provides a scientific basis for the optimal allocation of power resources. The system can reasonably allocate power resources according to this value to ensure that it can respond quickly and provide sufficient power support during peak power demand or emergencies. This helps to reduce the risk of power shortage or overload and improve the overall efficiency of the power system. For emergency power supply needs, the system can quickly assess the required additional power resources and take corresponding emergency measures. This efficient emergency response capability helps reduce the impact of emergencies on the power system and ensure the continuity and stability of power supply. By comprehensively considering multiple factors to determine the first value of additional power resources, the system provides strong data support for power dispatchers and managers. This helps them make intelligent decisions based on accurate data, optimize the dispatch and use of power resources, and improve the intelligence level of the power system.

[0018] Optionally, determining the power resource allocation scheme according to the objective function, the power resource amount and the priority includes: determining whether a maximum amount of electric power resources provided by the electric power system is greater than the amount of electric power resources; When the maximum amount of electric power resources provided by the electric power system is greater than the amount of electric power resources, determining the source of the electric power resources and the corresponding second value according to the objective function; When the maximum amount of electric power resources provided by the electric power system is equal to or less than the amount of electric power resources, a second value of the electric power resources that can be allocated to each customer side is determined according to the priority, and the source of the electric power resources is determined according to the objective function.

[0019] By adopting the above technical solution, by judging whether the maximum amount of power resources provided by the power system is greater than the required amount of power resources, the system can ensure that there is sufficient power supply to meet the overall demand before allocating power resources. This avoids the problem of power shortage caused by insufficient power supply and ensures the stable operation of the power system. When the power resources are sufficient, the system determines the source of power resources and the corresponding allocation value (second value) according to the objective function. The objective function may be designed based on factors such as cost minimization, efficiency maximization, and environmental protection. By solving the optimization algorithm, the reasonable allocation of power resources can be achieved and the overall efficiency of the power system can be improved. When power resources are tight (that is, the maximum amount of power resources provided by the power system is equal to or less than the required amount of power resources), the system can determine the amount of power resources that can be allocated to each customer side according to the priority. This priority-based allocation method ensures that the power needs of key users or important areas are met and improves the reliability and stability of power supply. The allocation scheme combines the actual power supply capacity of the power system with customer needs, taking into account both the adequacy of resources and the priority of customer needs. This flexibility and adaptability enable the power resource allocation scheme to cope with changes in power demand in different scenarios and ensure the smooth operation of the power system. By giving priority to meeting the power needs of high-priority customers, this allocation scheme helps improve customer satisfaction. At the same time, by optimizing resource allocation, reducing power costs and improving power supply efficiency, it can also indirectly improve customers' overall satisfaction with power services. The entire allocation process makes decisions based on objective functions and priorities, realizing the intelligent allocation of power resources. This not only improves the scientificity and accuracy of decision-making, but also reduces the impact of human factors on the allocation results, making the allocation of power resources more fair, reasonable and efficient.

[0020] In a second aspect of the present application, a safe and controlled intelligent power protection system is provided, including a demand module, a monitoring module, a calculation module and an execution module, wherein: A demand module is configured to obtain the power security requirements of the customer side, integrate the power security requirements to prioritize the power security requirements, the power security requirements include power supply stability requirements, power security requirements for preset special time periods and fault emergency response, and the customer side includes power supply companies and preset key power security locations; A monitoring module is configured to monitor the client side in real time to obtain power data of the client side, perform load forecasting based on the power data through the edge computing node of the client side, and send the load forecasting result to the cloud platform; A calculation module configured to calculate the required amount of power resources according to the power guarantee demand and the load forecast result through the cloud platform, and determine the power resource allocation plan according to the objective function, the power resource amount and the priority, wherein the objective function includes minimizing cost, maximizing customer satisfaction or ensuring stable power supply; The execution module is configured to generate a scheduling plan according to the power resource allocation plan and adjust the power supply status of the customer side according to the scheduling plan, wherein the scheduling plan includes power generation output, transmission path, and distribution load.

[0021] In the third aspect of the present application, an electronic device is provided, including a processor, a memory, a user interface and a network interface, the memory is used to store instructions, the user interface and the network interface are both used to communicate with other devices, and the processor is used to execute the instructions stored in the memory so that the electronic device executes any one of the methods described above.

[0022] In a fourth aspect of the present application, a computer-readable storage medium is provided, wherein the computer-readable storage medium stores instructions, and when the instructions are executed, any of the methods described above is executed.

[0023] In summary, one or more technical solutions provided in the embodiments of the present application have at least the following technical effects or advantages: 1. By acquiring and integrating the power security needs of customers, including power supply stability requirements, power security needs during preset special periods, and emergency response to faults, it is possible to predict and respond to potential power supply risks in advance. At the same time, it monitors customer power data in real time and conducts load forecasting, providing data support for the precise scheduling of power resources, thereby ensuring the stability and reliability of power supply; 2. The cloud platform calculates the required amount of power resources based on power security requirements and load forecast results, and optimizes the allocation of power resources based on objective functions (such as minimizing costs, maximizing customer satisfaction, or ensuring stable power supply). This optimization strategy not only helps to reduce the cost of power supply, but also improves customer satisfaction and achieves efficient use of power resources. 3. For emergencies such as fault emergency response, the power resource allocation plan can be quickly adjusted according to the power guarantee demand and real-time power data, and the corresponding dispatch plan can be generated. This rapid response mechanism helps to reduce the impact of faults on power supply and improve the emergency response capability of the power system; 4. By integrating the cloud platform and edge computing nodes, real-time processing and analysis of power data, as well as intelligent dispatch and management of power resources, are realized. This intelligent management method not only improves the efficiency and accuracy of power supply, but also reduces the cost and risk of manual intervention; 5. It can prioritize and personalize the power supply guarantee needs of different customers to meet the needs of various customer groups such as power supply companies and preset key power supply guarantee sites. This flexibility helps to improve the quality and level of power services and enhance customer satisfaction and loyalty; 6. In the process of data transmission and processing, safe and reliable communication protocols and encryption technologies are used to ensure the security and privacy of power data. This helps to build customers' trust in power services and ensure the stable operation of the power system. BRIEF DESCRIPTION OF THE DRAWINGS

[0024] Figure 1 It is a flowchart of the intelligent power protection method for safety management disclosed in the embodiment of the present application; Figure 2 It is a module schematic diagram of the intelligent power protection system for safety management disclosed in the embodiment of the present application; Figure 3 It is a structural schematic diagram of an electronic device disclosed in an embodiment of the present application.

[0025] Explanation of the reference numerals: 201, requirement module; 202, monitoring module; 203, calculation module; 204, execution module; 301, processor; 302, communication bus; 303, user interface; 304, network interface; 305, memory. DETAILED DESCRIPTION

[0026] In order to enable technicians in this field to better understand the technical solutions in this specification, the technical solutions in the embodiments of this specification will be clearly and completely described below in conjunction with the drawings in the embodiments of this specification. Obviously, the described embodiments are only part of the embodiments of this application, not all of the embodiments.

[0027] In the description of the embodiments of the present application, words such as "for example" or "for example" are used to indicate examples, illustrations or explanations. Any embodiment or design described as "for example" or "for example" in the embodiments of the present application should not be interpreted as being more preferred or more advantageous than other embodiments or designs. Specifically, the use of words such as "for example" or "for example" is intended to present related concepts in a specific way.

[0028] In the description of the embodiments of the present application, the meaning of the term "multiple" refers to two or more. For example, multiple systems refer to two or more systems, and multiple screen terminals refer to two or more screen terminals. In addition, the terms "first" and "second" are used for descriptive purposes only and cannot be understood as indicating or implying relative importance or implicitly indicating the indicated technical features. Thus, the features defined as "first" and "second" may explicitly or implicitly include one or more of the features. The terms "include", "comprise", "have" and their variations all mean "including but not limited to", unless otherwise specifically emphasized.

[0029] This embodiment discloses a safe and intelligent power protection method, which is applied to the intelligent power protection platform. Figure 1 is a flow chart of the intelligent power protection method for safety management disclosed in the embodiment of the present application, such as Figure 1 As shown, the smart power conservation method includes the following steps: S110, obtaining power security requirements on the customer side, integrating the power security requirements to prioritize the power security requirements, the power security requirements including power supply stability requirements, power security requirements during preset special periods, and fault emergency response, the customer side including the power supply company and preset key power security locations; As the manager and maintainer of the power network, the power supply company's power supply guarantee needs usually involve requirements for the stability, reliability, economy and sustainable development of the entire power grid. These needs may include but are not limited to grid structure optimization, intelligent upgrades, energy efficiency improvement, etc. Preset key power supply sites, such as hospitals, data centers, government agencies, transportation hubs, etc., have extremely high dependence and special requirements on power supply. Their power supply guarantee needs usually include power supply stability requirements, power supply guarantee needs during preset special periods, and fault emergency response. Power supply stability requirements: Ensure uninterrupted power supply and quickly restore power supply even in extreme weather or power grid failures. Preset power supply guarantee needs during special periods: During major events, holidays, emergency rescue, etc., additional power guarantee measures are required to ensure the smooth progress of activities or the continuous provision of key services. Fault emergency response: Establish a rapid response mechanism to deal with possible power failures or interruptions, including fault warning, rapid location, emergency repair and restoration, and subsequent analysis. Demands are classified and summarized according to types (such as stability, special periods, emergency response), locations (such as hospitals, data centers), time scales (long-term, medium-term, short-term), etc. for subsequent processing. Combined with the power supply company's overall strategy, resource allocation, technical capabilities, and specific needs of key power supply sites, conduct a comprehensive assessment of each demand to determine its feasibility and priority. Evaluate the criticality of each demand based on the urgency of the demand and the degree of impact on public safety and socio-economics. Consider the degree of match between currently available resources (such as human, material, financial, and technical resources) and demand, and ensure that needs with sufficient resources and significant impact are met first. Predict possible risks, such as natural disasters, equipment aging, and human errors, and give higher priority to needs with higher risks. Based on the above assessment results, formulate a priority ranking plan for power supply security needs, and clarify the priority order and implementation plan of each need.

[0030] S120, real-time monitoring of the client side to obtain power data of the client side, performing load forecasting according to the power data through the edge computing node of the client side, and sending the load forecasting result to the cloud platform; Real-time monitoring is to obtain real-time power usage data on the customer side (such as factories, commercial buildings, residential areas, etc.). These data include but are not limited to current, voltage, power factor, active power, reactive power, total power consumption, etc. These data can be collected in real time through smart meters, sensors and Internet of Things (IoT) devices installed on the customer side, and transmitted to the data collection system by wireless or wired means. Real-time monitoring is the basis of energy management and optimization. It provides real-time and accurate power usage information, which provides a basis for subsequent load forecasting and decision support. Edge computing refers to data processing and analysis close to the data source (i.e., the customer side) to reduce data transmission delays and bandwidth consumption and improve response speed. On the edge computing node, the collected power data is combined with historical data, weather information, holidays, economic indicators and other factors, and load forecasting is performed using machine learning, time series analysis and other technologies. The forecast results can help understand the power demand in the future (such as hours, days, weeks, and months). Load forecasting on edge computing nodes can generate forecast results faster, reduce the burden of data transmission to the cloud platform, and protect customer privacy data. The load forecast results generated by the edge computing nodes are sent to the cloud platform for further analysis, storage, display and sharing. The cloud platform has powerful data processing and storage capabilities, which can support more complex analysis and larger-scale data management. The forecast results can be transmitted to the cloud platform through a secure network protocol (such as HTTPS). During the transmission process, the security and integrity of the data should be ensured to prevent data leakage or tampering. On the cloud platform, the load forecast results from multiple client sides can be summarized and analyzed to form a more comprehensive load forecast report. These reports can be used in multiple fields such as energy scheduling, demand side management, and power market transactions to provide decision support for governments, power grid companies, and energy users.

[0031] Optionally, the real-time monitoring of the client side to obtain the power data of the client side includes: The size of the window is set according to the periodic changes of the voltage and the current, the offset is determined according to the size and the expected data compression ratio, and the length is represented by an integer of a preset fixed length; Read data byte by byte from the power data, and for each newly read byte, search forward within the window using a hash table or a string matching algorithm to find the longest matching item; The offset and length of the longest matching item are recorded, and the offset and length are output as compressed power data.

[0032] According to the periodic variation characteristics of voltage and current (such as waveform frequency, cycle length, etc.), set a suitable window size. This window is used to find repeated patterns in the data. The window size should be large enough to capture repeated patterns in the data, but not too large to increase the complexity of the search and memory consumption. The offset is determined based on the window size and the expected data compression ratio, which indicates the farthest position where a repeated pattern may be found before the current position. The determination of the offset needs to consider the balance between compression efficiency and search efficiency. Using a preset fixed-length integer to represent length information (such as the length or offset of a match) helps to quickly and accurately restore the original data when decompressing.

[0033] The data compression process is based on reading data byte by byte from the power data. For each newly read byte, a hash table or string matching algorithm is used to search forward within the window to find the longest match. A hash table can improve search efficiency because it allows checking whether a particular value exists in constant time; while a string matching algorithm (such as KMP, Boyer-Moore, etc.) can find the longest repeating substring in the data. When the longest match is found, the offset and length of the match are recorded. The offset indicates the offset of the starting position of the match within the window relative to the current position; the length indicates the length of the match. The recorded offset and length are output as compressed power data. These data are much smaller than the original power data because they only contain information about the location and size of the repeating pattern, not the entire data itself.

[0034] The compression efficiency of this method depends on the number and size of repeated patterns in the data. If there are a large number of repeated patterns in the data, this method can achieve a high compression ratio. Since power data usually has a certain periodicity (such as waveform data), this method is particularly suitable for real-time monitoring and compression of customer-side power data. However, it may also be affected by data noise, fluctuations, and non-periodic changes, so it needs to be adjusted and optimized according to actual conditions when applied.

[0035] Optionally, sending the load forecast result to the cloud platform includes: Encrypt the AES session key using the public key of the cloud platform to generate an encrypted session key; Encrypting the load forecast result using the AES session key to generate an encrypted load forecast result; The encrypted session key and the encrypted load forecast result are packaged to obtain a data packet, and the data packet is sent to the cloud platform through a communication channel.

[0036] This step is to ensure that the AES session key (the key used to encrypt the load forecast results later) cannot be intercepted or tampered with by unauthorized third parties during transmission. Public key encryption is an asymmetric encryption technology that uses a pair of keys: a public key (disclosed to everyone) and a private key (only held by the recipient). In this scenario, the cloud platform's public key is used to encrypt the AES session key. The AES session key encrypted with the public key becomes the encrypted session key, and only the recipient holding the cloud platform's private key can decrypt it. The load forecast results are encrypted using the AES (Advanced Encryption Standard) algorithm to ensure the confidentiality of the data during transmission. AES is a symmetric encryption technology, which means that the same key (in this case, the AES session key) is used for encryption and decryption. This encryption method is fast and suitable for encrypting large amounts of data. The load forecast results encrypted by AES become encrypted load forecast results, and only the recipient holding the correct AES session key can decrypt and view the original data. The encrypted session key and the encrypted load forecast results are packaged into a data packet to be sent to the cloud platform through the communication channel. A data packet is a collection of data that contains all necessary information (such as encrypted session keys and encrypted load forecast results), which is organized in a standardized format for easy transmission and reception. The communication channel can be any secure communication protocol established over the Internet, such as HTTPS, TLS / SSL, etc. These protocols provide encryption and integrity verification of data during transmission to prevent data leakage or tampering. When the data packet is ready, it can be sent to the cloud platform through the selected communication channel. At the receiving end, the cloud platform will use its private key to decrypt the encrypted session key, and then use the decrypted AES session key to decrypt the encrypted load forecast results, thereby restoring the original load forecast data.

[0037] The AES session key is encrypted using the cloud platform's public key, ensuring the security of the session key during transmission. Even if the session key is intercepted during transmission, it cannot be decrypted by unauthorized parties because only the cloud platform has the corresponding private key. The load forecast results are encrypted using the AES session key, providing high-strength data encryption protection. AES is a widely used symmetric encryption algorithm that can effectively resist various attack methods. Compared with public key encryption, symmetric encryption (such as AES) has higher encryption and decryption speeds. This means that when transmitting large amounts of data, using AES encryption can significantly reduce the time required for encryption and decryption, thereby improving the efficiency of data transmission. Through encryption, the amount of data in the load forecast results is compressed before transmission (although not directly through encryption compression, encryption generally means a more compact data representation), which helps reduce network bandwidth consumption, especially when the amount of data is large. From generating the AES session key, to using the key to encrypt the load forecast results, and finally sending the encrypted data to the cloud platform, the entire process achieves end-to-end encryption protection. This ensures that the load forecast results remain confidential throughout the entire transmission process, and only the intended recipient (i.e., the cloud platform) can decrypt and view the data. Even if there is a potential risk of monitoring or interception during network transmission, since the data has been encrypted, unauthorized parties cannot obtain useful information, thus effectively preventing the risk of data leakage. By using the public key to encrypt the AES session key, the complexity of key management is simplified. The cloud platform can easily manage and distribute public keys without worrying about the transmission security of session keys. The process can adapt to different data transmission scenarios, whether it is small-scale real-time data transmission or large-scale data backup and recovery, the encryption algorithm and key length can be adjusted to meet different security requirements.

[0038] Optionally, sending the load forecast result to the cloud platform further includes: A cyclic redundancy check field is added to the data packet, the transmission path is dynamically adjusted according to the network status and transmission requirements, and the load prediction result is sent to the cloud platform through the determined transmission path. The network status includes bandwidth, delay and packet loss rate, and the transmission requirements include data importance and real-time requirements.

[0039] Cyclic Redundancy Check (CRC) is a technology used to detect errors that may occur during data transmission or storage. By adding a CRC field to a data packet, the received data can be checked at the receiving end to confirm whether the data has been changed or damaged during transmission. Before sending a data packet, a CRC value is calculated based on the content of the data packet and added to the data packet as an additional field. After receiving the data packet, the receiving end recalculates the CRC value using the same algorithm and compares it with the CRC value in the data packet. If the two are consistent, it is considered that no error has occurred during the data transmission process; if they are inconsistent, an error may have occurred and appropriate error handling measures need to be taken.

[0040] Network status (such as bandwidth, latency, and packet loss rate) is constantly changing. In order to ensure the reliability and efficiency of data transmission, the transmission path needs to be dynamically adjusted according to the current network status. Network status information, including bandwidth usage, latency, and packet loss rate, is obtained in real time through network monitoring tools or protocols (such as SNMP, ICMP, etc.). Evaluate the demand for transmission paths based on the importance and real-time requirements of the data. For example, for data with high real-time requirements, you may need to choose a path with low latency and low packet loss rate; while for data with high importance but not so real-time, you may pay more attention to transmission reliability and bandwidth utilization. Based on the network status and transmission requirements, select the most appropriate transmission path. This may require a comprehensive trade-off of multiple factors to ensure the overall performance of data transmission. Different data has different importance. For critical business data or sensitive information, more stringent security measures and higher transmission priorities are required to ensure data integrity and confidentiality. Some data have high requirements for real-time performance, such as load forecasting results in smart grids. These data need to be transmitted to the cloud platform as soon as possible for processing and analysis, so as to respond and make decisions in a timely manner.

[0041] Adding a CRC field to a data packet ensures the integrity of the data during transmission. CRC is a method for detecting errors that may occur after data transmission or storage. The receiver can verify whether the data has been tampered with or damaged during transmission by calculating the CRC value of the received data and comparing it with the CRC value provided by the sender. If the two CRC values ​​do not match, the receiver can request to resend the data, thereby improving the reliability of data transmission. Dynamically adjusting the transmission path according to network status (such as bandwidth, latency, and packet loss rate) and transmission requirements (such as data importance and real-time requirements) can ensure that data is transmitted to the cloud platform in the best way. This dynamic adjustment mechanism helps to optimize data transmission efficiency and reduce unnecessary transmission delays and data loss. By dynamically adjusting the transmission path, it can adapt to different network environments and transmission requirements. Whether it is a real-time monitoring system with high real-time requirements or a backup system with strict requirements on data integrity but low real-time requirements, the transmission strategy can be adjusted to meet its specific needs. This flexibility enables the system to be more widely used in various smart grid and energy management scenarios. By optimizing the transmission path and reducing the risk of data loss, users can receive the required load forecasting results faster, thereby reducing waiting time and improving user experience.

[0042] S130, calculating the required amount of power resources according to the power guarantee demand and the load forecast result through the cloud platform, and determining a power resource allocation plan according to an objective function, the amount of power resources and a priority, wherein the objective function includes minimizing costs, maximizing customer satisfaction or ensuring stable power supply; The cloud platform uses mathematical models and algorithms to calculate the amount of power resources required in the future based on the power security demand and load forecast results. This process may involve detailed analysis of different time periods, different regions, and different types of loads to ensure the accuracy and reliability of the calculation results. After determining the required amount of power resources, the cloud platform needs to formulate a power resource allocation plan based on a series of goals and constraints. These goals and constraints usually include objective functions, power resource quantities, and priorities. The objective function is the main optimization goal when formulating an allocation plan. It may include minimizing costs (such as fuel costs, operation and maintenance costs, etc.), maximizing customer satisfaction (such as improving user satisfaction by reducing the number and duration of power outages), or ensuring stable power supply (such as maintaining sufficient spare capacity to cope with emergencies). Different objective functions reflect different decision preferences and value orientations. Power resource quantity: This is the material basis for formulating an allocation plan, that is, the total amount of power resources available for allocation in the system. Priority: When formulating an allocation plan, the priorities of different power users or loads must also be considered. For example, critical infrastructure (such as hospitals, data centers, etc.) may have a higher priority and need to give priority to ensuring their power supply. The cloud platform uses optimization algorithms (such as linear programming, genetic algorithms, simulated annealing, etc.) and expert systems to reasonably allocate power resources to meet different goals and constraints. These allocation plans may include power generation plans, transmission scheduling, distribution strategies, etc., aiming to achieve optimal configuration and efficient use of power resources.

[0043] Optionally, the calculating the required amount of electric power resources according to the electric power guarantee demand and the load forecast result by the cloud platform includes: Analyze the power security demand to determine a first time period and a second time period, wherein the first time period refers to a time period in which basic power resources are required, and the second time period refers to a time period in which basic power resources and additional power resources are required; For the first time period, using the load forecast result as the required amount of electric power resources; For the second time period, a first value of the additional power resources is determined according to the power guarantee demand, and the required amount of power resources is taken as the sum of the first value and the load forecast result.

[0044] The cloud platform first conducts an in-depth analysis of the power security demand to identify the first time period and the second time period. The first time period refers to those time periods that only basic power resources are needed to meet the demand. Basic power resources usually refer to the minimum amount of power required to maintain the normal operation of the power grid or system, and it does not include additional resources required to deal with emergencies or peak loads. The second time period is different from the first time period. The second time period requires not only basic power resources, but also additional power resources to meet specific power security needs. These additional resources may be used to meet peak loads, respond to emergencies, or ensure the stable operation of critical facilities. For the first time period: the cloud platform directly uses the load forecast result as the amount of power resources required in this time period. This is because during this time period, the power demand is relatively stable and there is no additional power security demand, so the load forecast result can accurately reflect the amount of power resources required. For the second time period: the cloud platform first determines the first value of additional power resources based on the power security demand. This value is based on a detailed analysis of the power security demand, which may involve a review of historical data, a forecast of future trends, and an assessment of specific events (such as natural disasters, large-scale events, etc.). After determining the first value of the additional power resources, the cloud platform will add it to the load forecast result to obtain the total amount of power resources required during the time period. This process ensures that the system has sufficient power resources to cope with various possible power security needs even during the period of high power demand. During the calculation process, the cloud platform will also take into account other factors, such as the availability of power resources, power generation costs, environmental protection requirements, etc. These factors may affect the final calculation results of the amount of power resources, making the allocation plan more in line with the actual situation and sustainable development requirements. It is worth noting that power demand and security requirements may change over time. Therefore, the cloud platform needs to monitor the changes in power demand and load forecast results in real time, and adjust the calculation method and allocation plan of the required amount of power resources in real time as needed. This helps to ensure the effective allocation and efficient use of power resources.

[0045] By identifying the first time period and the second time period, the cloud platform can more accurately grasp the changing pattern of power demand, thus avoiding a one-size-fits-all allocation method. The cloud platform adopts different calculation strategies for different time periods. In the first time period, the load forecast results are directly used as the power resource amount to ensure the sufficient supply of basic power resources; in the second time period, the additional power resource amount is determined according to the power guarantee demand and added to the load forecast results to ensure the power supply in peak load and emergency situations. By accurately calculating the required power resource amount, the cloud platform can ensure that power resources are fully utilized and avoid waste and idleness of resources. In the case of tight power resources or high costs, the cloud platform can reduce unnecessary power consumption and cost expenditure by optimizing the allocation plan. In the second time period, the cloud platform can ensure sufficient power resources to cope with peak loads, thereby avoiding risks such as grid overload and power outages. In the event of an emergency or emergency, the cloud platform can quickly adjust the power resource allocation plan to ensure that the power supply of key facilities and regions is not affected, thereby improving the stability and reliability of the power grid. By optimizing the configuration of power resources, the cloud platform helps to reduce unnecessary power consumption and emissions, and promotes the realization of environmental protection and energy-saving goals. Based on accurate load forecasting and power resource demand calculation, the cloud platform can provide strong support for the long-term planning and construction of power grids, and help achieve sustainable development of the power industry.

[0046] Optionally, determining a first value of additional power resources according to the power guarantee requirement includes: Obtaining special conditions in the power supply demand, wherein the special conditions include power supply demand caused by weather, power supply demand caused by activities, and emergency power supply demand; Determining an additional increase in electricity demand based on the special conditions and historical data, wherein the historical data includes electricity usage characteristics, electricity usage habits and rated power of equipment of different users, wherein the different users include residential users, commercial users and industrial users; The first value is determined according to the additional increase and influencing factors, where the influencing factors include equipment efficiency, power grid transmission capacity and spare capacity.

[0047] Identify the special conditions that may exist in the power supply demand. These special conditions are the key factors that cause the power demand to exceed the normal range. Special conditions mainly include three categories: (1) power supply demand caused by weather. For example, extremely high or low temperatures will lead to a significant increase in the use of air conditioning and heating equipment, thereby increasing power demand; (2) power supply demand caused by activities. Large-scale activities (such as sports events, music festivals, exhibitions, etc.) will attract a large number of people to gather, and the power demand of related facilities (such as lighting, audio, video equipment, etc.) will also increase significantly; (3) emergency power supply demand. In the event of natural disasters (such as earthquakes, floods), emergencies (such as large-scale power outages), etc., emergency power resources need to be quickly deployed to ensure the operation of key facilities and the basic living needs of residents. Once special conditions are identified, it is necessary to evaluate the additional increase in power demand based on these conditions and historical data. Historical data plays a vital role here. It records the power consumption characteristics, power consumption habits and equipment rated power of different users under various circumstances. These data usually include: (1) Electricity consumption characteristics of different users: Residential users, commercial users and industrial users have different electricity consumption behaviors. For example, residential users' electricity consumption is mainly concentrated in the evening and weekends, while commercial users and industrial users may have higher electricity demand during the day on weekdays; (2) Electricity usage habits: Different user groups may have different electricity usage habits. For example, household users may prefer to use electrical appliances for cooking, entertainment and other activities, while commercial users may need a large amount of lighting and air-conditioning equipment; (3) Rated power of equipment: Different equipment has different power consumption. Knowing the rated power of equipment can help to estimate power demand more accurately. By analyzing historical data and combining special conditions, the additional increase in power demand can be calculated. The additional increase in power demand is combined with a series of influencing factors to determine the first value of additional power resources. These influencing factors include: (1) equipment efficiency: the actual operating efficiency of the equipment may be lower than its rated power, which will affect the calculation results of power demand; (2) grid transmission capacity: the transmission capacity of the grid limits the actual supply of power resources, and the capacity and stability of the grid need to be considered; (3) backup capacity: in order to ensure the stability and reliability of power supply, it is usually necessary to retain a certain amount of backup capacity to deal with emergencies.

[0048] By obtaining special conditions (such as weather, activities, emergencies, etc.) in the power security demand, the cloud platform can quickly identify factors that may cause a surge in power demand and prepare in advance. Based on the analysis of special conditions and historical data, the cloud platform can quickly calculate the additional increase in power demand and adjust the power resource allocation plan accordingly to ensure the flexibility and response speed of power supply. When determining the first value of additional power resources, not only the additional increase in power demand is considered, but also a variety of influencing factors such as equipment efficiency, grid transmission capacity and spare capacity are comprehensively considered. This comprehensive consideration approach helps to ensure the reliability and stability of power supply and reduce the risk of power outages caused by equipment failure, grid congestion or insufficient spare capacity. By preparing and allocating sufficient additional power resources in advance, the cloud platform can effectively respond to emergencies and emergencies, alleviate power supply pressure, and reduce the impact of power outages on residents' lives, commercial operations and industrial production. Based on the analysis of historical data and user characteristics, the cloud platform can more accurately predict the changes in power demand of different users, thereby realizing the precise allocation of power resources. This helps to avoid waste and idleness of power resources and improve the efficiency of power resource use. By optimizing the allocation of power resources, the cloud platform can reduce unnecessary power consumption and cost expenditure. At the same time, during peak hours of electricity demand, equipment damage and increased maintenance costs caused by grid overload can be avoided by rationally dispatching and allocating additional power resources. This process reflects the core concept of smart grids, which is to improve the flexibility, reliability and economy of power systems through information, automation and intelligent technologies. As an important part of smart grids, cloud platforms provide strong support for the refined management of power supply through real-time data analysis and intelligent decision support. By optimizing the allocation of power resources and reducing unnecessary power consumption, cloud platforms help reduce carbon emissions and environmental pollution in the power industry and promote the sustainable development of the power industry. At the same time, by improving the reliability and stability of power supply, cloud platforms also provide strong guarantees for the sustainable development of the economy and society.

[0049] Optionally, determining the power resource allocation scheme according to the objective function, the power resource amount and the priority includes: determining whether a maximum amount of electric power resources provided by the electric power system is greater than the amount of electric power resources; When the maximum amount of electric power resources provided by the electric power system is greater than the amount of electric power resources, determining the source of the electric power resources and the corresponding second value according to the objective function; When the maximum amount of electric power resources provided by the electric power system is equal to or less than the amount of electric power resources, a second value of the electric power resources that can be allocated to each customer side is determined according to the priority, and the source of the electric power resources is determined according to the objective function.

[0050] Identify the maximum amount of power resources that the current power system can provide. The maximum amount of power resources is affected by many factors, including the power generation capacity of the power plant, the transmission capacity of the power grid, the spare capacity, and the current power load. This key information can be obtained through real-time monitoring and data analysis. Compare the maximum amount of power resources provided by the power system with the given amount of power resources. The purpose of this step is to determine whether the current system has enough power resources to meet all or part of the customer's needs.

[0051] If the maximum amount of power resources provided by the power system is greater than the given amount of power resources, it means that the system has enough power resources to meet the demand, but it may be necessary to optimize the allocation of resources according to certain strategies (such as minimum cost, maximum efficiency, etc.). At this time, the source of power resources and the specific amount that each source should provide (i.e., the second value) will be determined according to the objective function (such as minimizing costs, minimizing emissions, maximizing customer satisfaction, etc.). This helps to achieve efficient use of power resources and cost savings. For example, when the objective function is cost minimization, low-cost power resources can be used first.

[0052] If the maximum amount of power resources provided by the power system is equal to or less than the given amount of power resources, it means that the system cannot meet the needs of all customers. In this case, it is necessary to determine the second value of the power resources that can be allocated to each customer based on the priority. The priority can be determined based on a variety of factors such as the importance of the customer, historical power usage, contractual agreements, etc. Once the allocation amount for each customer is determined, the specific source of these power resources is determined based on the objective function. This helps to ensure that the needs of key customers are met when resources are limited and minimize the impact on other customers.

[0053] For example, the power system allocates power resources to three customers (customer A, customer B, and customer C). Each customer has different power requirements and priorities. At the same time, the power system has a maximum power resource limit. The maximum power resource of the power system: 1000 units; customer A requires 300 units, priority 1 (highest); customer B: requires 400 units, priority 2; customer C: requires 500 units, priority 3 (lowest). Assume that the objective function is to minimize the cost, that is, to obtain power from low-cost power resource sources (such as renewable energy, low-cost fossil fuels, etc.) as much as possible. The maximum power resource provided by the power system is 1000 units, while the total demand of the three customers is 1200 units. Obviously, the maximum power resource is not enough to meet the needs of all customers. Due to insufficient power resources, power resources need to be allocated according to priority. Customer A has the highest priority, and the 300 units of power it needs are allocated first. Customer B is allocated 400 units because its priority is higher than that of customer C. Customer C has the lowest priority and the remaining power resources are not enough to meet all its needs, so it can only be allocated the remaining 300 units of power. After the second value of electricity resources is allocated, the specific sources of these electricity need to be determined according to the objective function (lowest cost). Assume that there are two sources of electricity resources: one is renewable energy (lower cost) and the other is fossil fuel (higher cost). In order to reduce costs, electricity can be obtained from renewable energy sources first until its supply limit is reached or all demands are met. If renewable energy is not enough to meet all allocated electricity needs, the remaining electricity is obtained from fossil fuels. The allocation results are as follows: Customer A: 300 units of electricity are allocated, all from renewable energy. Customer B: 400 units of electricity are allocated, most of which come from renewable energy, and the rest comes from fossil fuels (if renewable energy is insufficient). Customer C: 300 units of electricity are allocated, mainly from fossil fuels (because renewable energy has been allocated to customers with higher priority).

[0054] By judging whether the maximum amount of power resources provided by the power system is greater than the required amount of power resources, it is possible to ensure efficient allocation when resources are sufficient, avoid overproduction or procurement of power resources, thereby saving costs and reducing resource waste. If resources are insufficient, the priority allocation mode is directly entered to ensure that key needs are met. Different allocation strategies are adopted according to the actual situation of power system resources (sufficient or insufficient), which reflects a high degree of flexibility and adaptability. When resources are sufficient, the source and allocation of resources are optimized through objective functions (such as cost minimization, efficiency maximization, etc.), while when resources are tight, the power supply of key customers or services is ensured according to priority, thereby ensuring the stable operation of the power system and customer satisfaction. When resources are limited, the amount of power resources that can be allocated to each customer side is determined by setting priorities, ensuring the fairness of power allocation and the priority of key needs. This mechanism helps to reduce disputes, improve customer satisfaction, and maintain social stability when resources are tight. The application of objective functions provides a scientific decision-making basis for power resource allocation. Through the calculation of objective functions, indicators such as cost and efficiency of different resource sources and allocation schemes can be quantified, so as to select the optimal scheme. This helps to improve the efficiency and accuracy of power resource allocation and reduce decision-making risks. Considering objective functions (such as environmental protection, renewable energy utilization, etc.) in the resource allocation process will help promote the development of the power system in a greener and more sustainable direction. By optimizing resource sources and allocation, we can reduce dependence on fossil fuels, increase the utilization rate of renewable energy, reduce carbon emissions, and contribute to environmental protection and sustainable development.

[0055] S140, generating a scheduling plan according to the power resource allocation plan, and adjusting the power supply status of the customer side according to the scheduling plan, wherein the scheduling plan includes power generation output, transmission path, and distribution load.

[0056] According to the power resource allocation plan, the power output of each power plant is determined. This includes considering factors such as the power generation capacity, fuel supply, maintenance plan, and environmental protection requirements of the power plant. The power output arrangement needs to ensure that the stability and economy of the power system are maintained while meeting the power demand. For example, by optimizing the output combination of different power plants, the power generation cost can be reduced and the energy utilization efficiency can be improved. According to the power demand and the distribution of power output, a reasonable transmission path is planned. This includes determining the starting point, end point, voltage level, and transmission capacity of the transmission line. Transmission path planning needs to ensure the safety and reliability of power transmission, while considering the topology and operation constraints of the power grid. For example, avoid overloaded lines, reduce transmission losses, and improve the fault recovery capability of the power grid. According to the power resource allocation plan and transmission path planning, power resources are allocated to various distribution areas and customer sides. This includes determining the load demand, power supply reliability, and economy requirements of each distribution area. Distribution load allocation needs to ensure the fairness and priority of power supply, while considering factors such as load balance and voltage stability of the power grid. For example, by adjusting the load distribution ratio of different distribution areas, the load curve of the power grid can be optimized and the power supply quality can be improved. According to the dispatch plan, the power supply status on the customer side is adjusted. This includes controlling the power consumption equipment on the customer side and adjusting parameters such as power supply voltage and frequency to ensure that the power demand on the customer side is met and meets the requirements of safe, reliable and economical operation. During the adjustment process, it is necessary to monitor the power consumption on the customer side and the operating status of the power grid in real time, and promptly detect and handle abnormal situations such as overload, short circuit, voltage fluctuation, etc.

[0057] The smart power supply platform adopts an architecture that combines cloud platforms and edge computing nodes to achieve cloud-edge collaboration. The cloud platform is responsible for big data processing, intelligent algorithm analysis, and global scheduling decisions, while the edge computing nodes are responsible for real-time data processing and preliminary analysis on the client side, reducing data transmission delays and improving response speed. This architecture not only ensures the flexibility and scalability of the system, but also ensures the rapid processing and decision support of key data. In response to the needs of long-distance reliable transmission and diversified data transmission, a variety of information interaction technologies and communication networking technologies are studied and applied. This includes but is not limited to optical fiber communication, wireless communication (such as 4G / 5G, Wi-Fi 6, etc.), satellite communication, etc., as well as optimization of network communication protocols (such as TCP / IP protocol optimization, QoS guarantee, etc.) and data transmission mechanisms (such as data compression, breakpoint continuation, etc.), thereby improving the efficiency and reliability of data transmission. In view of the high requirements for security and confidentiality of power supply guarantee tasks, the system adopts advanced encryption technologies (such as AES, RSA, etc.) and access control mechanisms (such as role-based access control RBAC, multi-factor authentication, etc.) to ensure security during data transmission and storage. At the same time, a complete data backup and recovery mechanism is established to prevent data loss or damage and ensure the continuous and stable operation of the system. The smart power protection platform integrates real-time online monitoring, hidden danger identification, intelligent early warning, online inspection and other functions. It uses intelligent algorithms to analyze and process power data in real time to promptly discover and deal with potential power hidden dangers. This intelligent management and control method has greatly improved the efficiency and accuracy of power protection work.

[0058] This embodiment also discloses a safe and intelligent power protection system. Figure 2 Schematic diagram of the module of the intelligent power protection system for safety management disclosed in the embodiment of the present application, such as Figure 2 As shown, the system includes a demand module 201, a monitoring module 202, a calculation module 203 and an execution module 204, wherein: The demand module 201 is configured to obtain the power security demand of the customer side, integrate the power security demand to prioritize the power security demand, the power security demand includes the power supply stability requirement, the power security demand in the preset special period and the fault emergency response, and the customer side includes the power supply company and the preset key power security location; A monitoring module 202 is configured to monitor the client side in real time to obtain power data of the client side, perform load forecasting based on the power data through the edge computing node of the client side, and send the load forecasting result to the cloud platform; A calculation module 203 is configured to calculate the required amount of power resources according to the power guarantee demand and the load forecast result through the cloud platform, and determine the power resource allocation plan according to the objective function, the power resource amount and the priority, wherein the objective function includes minimizing cost, maximizing customer satisfaction or ensuring stable power supply; The execution module 204 is configured to generate a scheduling plan according to the power resource allocation plan, and adjust the power supply status of the customer side according to the scheduling plan, wherein the scheduling plan includes power generation output, transmission path, and distribution load.

[0059] Optionally, the monitoring module 202 is configured to: The size of the window is set according to the periodic changes of the voltage and the current, the offset is determined according to the size and the expected data compression ratio, and the length is represented by an integer of a preset fixed length; Read data byte by byte from the power data, and for each newly read byte, search forward within the window using a hash table or a string matching algorithm to find the longest matching item; The offset and length of the longest matching item are recorded, and the offset and length are output as compressed power data.

[0060] Optionally, the monitoring module 202 is configured to: Encrypt the AES session key using the public key of the cloud platform to generate an encrypted session key; Encrypting the load forecast result using the AES session key to generate an encrypted load forecast result; The encrypted session key and the encrypted load forecast result are packaged to obtain a data packet, and the data packet is sent to the cloud platform through a communication channel.

[0061] Optionally, the monitoring module 202 is further configured to: A cyclic redundancy check field is added to the data packet, the transmission path is dynamically adjusted according to the network status (such as etc.) and the transmission demand, and the load prediction result is sent to the cloud platform through the determined transmission path. The network status includes bandwidth, delay and packet loss rate, and the transmission demand includes data importance and real-time requirements.

[0062] Optionally, the calculation module 203 is configured to: Analyze the power security demand to determine a first time period and a second time period, wherein the first time period refers to a time period in which basic power resources are required, and the second time period refers to a time period in which basic power resources and additional power resources are required; For the first time period, using the load forecast result as the required amount of electric power resources; For the second time period, a first value of the additional power resources is determined according to the power guarantee demand, and the required amount of power resources is taken as the sum of the first value and the load forecast result.

[0063] Optionally, the calculation module 203 is further configured to: Obtaining special conditions in the power supply demand, wherein the special conditions include power supply demand caused by weather, power supply demand caused by activities, and emergency power supply demand; Determining an additional increase in electricity demand based on the special conditions and historical data, wherein the historical data includes electricity usage characteristics, electricity usage habits and rated power of equipment of different users, wherein the different users include residential users, commercial users and industrial users; The first value is determined according to the additional increase and influencing factors, where the influencing factors include equipment efficiency, power grid transmission capacity and spare capacity.

[0064] Optionally, the calculation module 203 is configured to: determining whether a maximum amount of electric power resources provided by the electric power system is greater than the amount of electric power resources; When the maximum amount of electric power resources provided by the electric power system is greater than the amount of electric power resources, determining the source of the electric power resources and the corresponding second value according to the objective function; When the maximum amount of electric power resources provided by the electric power system is equal to or less than the amount of electric power resources, a second value of the electric power resources that can be allocated to each customer side is determined according to the priority, and the source of the electric power resources is determined according to the objective function.

[0065] It should be noted that: when the device provided in the above embodiment realizes its function, only the division of the above functional modules is used as an example. In actual application, the above functions can be assigned to different functional modules as needed, that is, the internal structure of the device is divided into different functional modules to complete all or part of the functions described above. In addition, the device and method embodiments provided in the above embodiment belong to the same concept, and the specific implementation process is detailed in the method embodiment, which will not be repeated here.

[0066] This embodiment also discloses an electronic device, referring to Figure 3 The electronic device may include: at least one processor 301 , at least one communication bus 302 , a user interface 303 , a network interface 304 , and at least one memory 305 .

[0067] The communication bus 302 is used to realize the connection and communication between these components.

[0068] The user interface 303 may include a display screen (Display) and a camera (Camera). Optionally, the user interface 303 may also include a standard wired interface and a wireless interface.

[0069] The network interface 304 may optionally include a standard wired interface or a wireless interface (such as a WI-FI interface).

[0070] Among them, the processor 301 may include one or more processing cores. The processor 301 uses various interfaces and lines to connect various parts in the entire server, and executes various functions of the server and processes data by running or executing instructions, programs, code sets or instruction sets stored in the memory 305, and calling data stored in the memory 305. Optionally, the processor 301 can be implemented in at least one hardware form of digital signal processing (Digital Signal Processing, DSP), field programmable gate array (Field-Programmable Gate Array, FPGA), and programmable logic array (Programmable Logic Array, PLA). The processor 301 can integrate one or a combination of a central processing unit (Central Processing Unit, CPU), a graphics processing unit (Graphics Processing Unit, GPU) and a modem. Among them, the CPU mainly processes the operating system, user interface and application programs; the GPU is responsible for rendering and drawing the content to be displayed on the display screen; the modem is used to process wireless communications. It can be understood that the above-mentioned modem may not be integrated into the processor 301, and it can be implemented separately through a chip.

[0071] Among them, the memory 305 may include a random access memory (Random Access Memory, RAM) and may also include a read-only memory (Read-Only Memory). Optionally, the memory 305 includes a non-transitory computer-readable storage medium. The memory 305 can be used to store instructions, programs, codes, code sets or instruction sets. The memory 305 may include a program storage area and a data storage area, wherein the program storage area may store instructions for implementing an operating system, instructions for at least one function (such as a touch function, a sound playback function, an image playback function, etc.), instructions for implementing the above-mentioned various method embodiments, etc.; the data storage area may store data involved in the above-mentioned various method embodiments, etc. The memory 305 may also be optionally at least one storage device located away from the aforementioned processor 301. As Figure 3As shown, the memory 305 as a computer storage medium may include an operating system, a network communication module, a user interface module, and an application program for a smart power conservation method for safety management.

[0072] exist Figure 3 In the electronic device shown, the user interface 303 is mainly used to provide an input interface for the user and obtain data input by the user; and the processor 301 can be used to call the application program of the intelligent power preservation method for security management stored in the memory 305. When executed by one or more processors 301, the electronic device executes one or more methods in the above-mentioned embodiments.

[0073] It should be noted that, for the aforementioned method embodiments, for the sake of simplicity, they are all described as a series of action combinations, but those skilled in the art should be aware that the present application is not limited by the order of the actions described, because according to the present application, certain steps can be performed in other orders or simultaneously. Secondly, those skilled in the art should also be aware that the embodiments described in the specification are all preferred embodiments, and the actions and modules involved are not necessarily required for the present application.

[0074] In the above embodiments, the description of each embodiment has its own emphasis. For parts that are not described in detail in a certain embodiment, reference can be made to the relevant descriptions of other embodiments.

[0075] In the several embodiments provided in this application, it should be understood that the disclosed devices can be implemented in other ways. For example, the device embodiments described above are only schematic, such as the division of units, which is only a logical function division. There may be other division methods in actual implementation, such as multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the mutual coupling or direct coupling or communication connection shown or discussed can be through some service interfaces, and the indirect coupling or communication connection of devices or units can be electrical or other forms.

[0076] The units described as separate components may or may not be physically separated, and the components shown as units may or may not be physical units, that is, they may be located in one place or distributed on multiple network units. Some or all of the units may be selected according to actual needs to achieve the purpose of the solution of this embodiment.

[0077] In addition, each functional unit in each embodiment of the present application may be integrated into one processing unit, or each unit may exist physically separately, or two or more units may be integrated into one unit. The above-mentioned integrated unit may be implemented in the form of hardware or in the form of software functional units.

[0078] If the integrated unit is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a computer-readable memory. Based on this understanding, the technical solution of the present application, or the part that contributes to the prior art, or all or part of the technical solution can be embodied in the form of a software product, which is stored in a memory 305 and includes several instructions for a computer device (which can be a personal computer, server or network device, etc.) to execute all or part of the steps of the various embodiments of the present application. The aforementioned memory 305 includes: various media that can store program codes, such as a USB flash drive, a mobile hard disk, a magnetic disk or an optical disk.

[0079] The above is only an exemplary embodiment of the present disclosure and cannot be used to limit the scope of the present disclosure. That is, any equivalent changes and modifications made according to the teachings of the present disclosure are still within the scope of the present disclosure. After considering the disclosure of the specification, those skilled in the art will easily think of other embodiments of the present disclosure. This application is intended to cover any modification, use or adaptation of the present disclosure, which follows the general principles of the present disclosure and includes common knowledge or customary technical means in the technical field that are not recorded in the present disclosure. The description and examples are only regarded as exemplary, and the scope and spirit of the present disclosure are defined by the claims.

Claims

1. A safe and intelligent power protection method, characterized in that: Applied to a smart power protection platform, the smart power protection platform includes a cloud platform and an edge computing node, and the method includes: Obtaining the power security requirements of the customer side, integrating the power security requirements to prioritize the power security requirements, the power security requirements for preset special periods of time, and emergency response to faults, the customer side including the power supply company and preset key power security locations; The client side is monitored in real time to obtain the power data of the client side, the edge computing node of the client side performs load forecasting according to the power data, and the load forecasting result is sent to the cloud platform; The cloud platform calculates the required amount of power resources according to the power security demand and the load forecast result, and determines the power resource allocation plan according to the objective function, the power resource amount and the priority, wherein the objective function includes minimizing cost, maximizing customer satisfaction or ensuring stable power supply; A dispatching plan is generated according to the power resource allocation plan, and the power supply status of the customer side is adjusted according to the dispatching plan, wherein the dispatching plan includes power generation output, transmission path, and distribution load.

2. The intelligent power conservation method for safety management and control according to claim 1 is characterized in that: The real-time monitoring of the client side to obtain the power data of the client side includes: The size of the window is set according to the periodic changes of the voltage and the current, the offset is determined according to the size and the expected data compression ratio, and the length is represented by an integer of a preset fixed length; Read data byte by byte from the power data, and for each newly read byte, search forward within the window using a hash table or a string matching algorithm to find the longest matching item; The offset and length of the longest matching item are recorded, and the offset and length are output as compressed power data.

3. The intelligent power conservation method for safety management and control according to claim 1 is characterized in that: The sending of the load forecast result to the cloud platform includes: Encrypt the AES session key using the public key of the cloud platform to generate an encrypted session key; Encrypting the load forecast result using the AES session key to generate an encrypted load forecast result; The encrypted session key and the encrypted load forecast result are packaged to obtain a data packet, and the data packet is sent to the cloud platform through a communication channel.

4. The intelligent power conservation method for safety management and control according to claim 3 is characterized in that: The sending of the load forecast result to the cloud platform further includes: A cyclic redundancy check field is added to the data packet, the transmission path is dynamically adjusted according to the network status and transmission requirements, and the load prediction result is sent to the cloud platform through the determined transmission path. The network status includes bandwidth, delay and packet loss rate, and the transmission requirements include data importance and real-time requirements.

5. The intelligent power conservation method for safety management and control according to claim 1 is characterized in that: The calculation of the required amount of power resources by the cloud platform according to the power guarantee demand and the load forecast result includes: Analyze the power security demand to determine a first time period and a second time period, wherein the first time period refers to a time period in which basic power resources are required, and the second time period refers to a time period in which basic power resources and additional power resources are required; For the first time period, using the load forecast result as the required amount of electric power resources; For the second time period, a first value of the additional power resources is determined according to the power guarantee demand, and the required amount of power resources is taken as the sum of the first value and the load forecast result.

6. The intelligent power conservation method for safety management and control according to claim 5 is characterized in that: Determining a first value of the additional power resource according to the power guarantee requirement includes: Obtaining special conditions in the power supply demand, wherein the special conditions include power supply demand caused by weather, power supply demand caused by activities, and emergency power supply demand; Determining an additional increase in electricity demand based on the special conditions and historical data, wherein the historical data includes electricity usage characteristics, electricity usage habits and rated power of equipment of different users, wherein the different users include residential users, commercial users and industrial users; The first value is determined according to the additional increase and influencing factors, where the influencing factors include equipment efficiency, power grid transmission capacity and spare capacity.

7. The intelligent power conservation method for safety management and control according to claim 1 is characterized in that: Determining the power resource allocation scheme according to the objective function, the power resource amount and the priority includes: determining whether a maximum amount of electric power resources provided by the electric power system is greater than the amount of electric power resources; When the maximum amount of electric power resources provided by the electric power system is greater than the amount of electric power resources, determining the source of the electric power resources and the corresponding second value according to the objective function; When the maximum amount of electric power resources provided by the electric power system is equal to or less than the amount of electric power resources, a second value of the electric power resources that can be allocated to each customer side is determined according to the priority, and the source of the electric power resources is determined according to the objective function.

8. A safe and intelligent power protection system, characterized in that: It includes demand module, monitoring module, calculation module and execution module, among which: A demand module is configured to obtain the power security requirements of the customer side, integrate the power security requirements to prioritize the power security requirements, the power security requirements include power supply stability requirements, power security requirements for preset special time periods and fault emergency response, and the customer side includes power supply companies and preset key power security locations; A monitoring module is configured to monitor the client side in real time to obtain power data of the client side, perform load forecasting based on the power data through the edge computing node of the client side, and send the load forecasting result to the cloud platform; A calculation module configured to calculate the required amount of power resources according to the power guarantee demand and the load forecast result through the cloud platform, and determine the power resource allocation plan according to the objective function, the power resource amount and the priority, wherein the objective function includes minimizing cost, maximizing customer satisfaction or ensuring stable power supply; The execution module is configured to generate a scheduling plan according to the power resource allocation plan and adjust the power supply status of the customer side according to the scheduling plan, wherein the scheduling plan includes power generation output, transmission path, and distribution load.

9. An electronic device, characterized in that: It includes a processor, a memory, a user interface and a network interface, the memory is used to store instructions, the user interface and the network interface are both used to communicate with other devices, and the processor is used to execute the instructions stored in the memory so that the electronic device executes the method as described in any one of claims 1-7.

10. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores instructions, and when the instructions are executed, the method according to any one of claims 1 to 7 is executed.

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