A smart grid adaptive load balancing system

Abstract

The present invention discloses a smart grid adaptive load balancing system, which relates to the field of smart grid technology, including: collecting multiple historical load overload record data of load overload occurring in the smart grid in the historical time; collecting multiple real-time power distribution demand information of multiple current power consumption ends; constructing multiple power distribution spaces of multiple power consumption ends according to multiple historical load overload record data; constructing a load balancing function to improve the current power distribution balance and the historical power distribution balance; in the power distribution space, according to the load balancing function, balancing and optimizing the real-time power distribution information of the current smart grid to multiple power consumption ends, obtaining the optimal balanced power distribution plan, and performing load-balanced power distribution. The present invention solves the technical problem of the lack of real-time and flexibility in the existing technology when processing the load balancing of the power grid, and achieves the technical effect of realizing real-time load balancing and optimizing power distribution through data collection, statistical analysis, load balancing function construction and random cross-update optimization.

Description

Technical Field

[0001] The present invention relates to the technical field of smart grids, and in particular to a smart grid adaptive load balancing system. Background Art

[0002] With the development of smart grid technology, the complexity and diversity of power system management are increasing. Smart grid achieves efficient utilization and real-time regulation of power resources by integrating modern information technology, communication technology and power technology. However, with the continuous growth of power demand and the diversification of power consumption behavior, smart grid faces huge challenges in load balancing and distribution optimization.

[0003] Especially when facing scenarios with multiple power-consuming devices, such as electric vehicle charging stations, air conditioning systems in large commercial facilities, or production equipment in industrial parks, the synchronous power demand of these devices fluctuates greatly, which can easily lead to local load overload problems. Load overload not only increases the wear and tear of power grid equipment, but may also cause power outages, seriously affecting the normal power demand of users. Traditional power grid management methods often lack real-time and flexibility when dealing with such load overloads, and are unable to meet the rapidly changing needs of modern power grids. Summary of the invention

[0004] The present application provides a smart grid adaptive load balancing system, which is used to solve the technical problem of lack of real-time performance and flexibility in the prior art when processing load balancing of power grids.

[0005] In view of the above problems, the present application provides a smart grid adaptive load balancing system.

[0006] The present application provides a smart grid adaptive load balancing system, the system comprising: A data acquisition module, wherein the data acquisition module acquires multiple historical load overload record data of load overload occurring in the history of the smart grid, wherein each historical load overload record data includes historical power distribution demand information and historical power distribution information of multiple power consumption ends in the smart grid; a real-time power distribution demand information acquisition module, wherein the real-time power distribution demand information acquisition module acquires multiple real-time power distribution demand information of the current multiple power consumption ends; a power distribution space construction module, wherein the power distribution space construction module constructs multiple power distribution spaces of multiple power consumption ends according to the multiple historical load overload record data; a load balancing function construction module, wherein the load balancing function construction module constructs a load balancing function to improve the current power distribution balance and improve the historical power distribution balance; a load balancing distribution module, wherein the load balancing distribution module performs balance optimization on the real-time power distribution information of the current smart grid to the multiple power consumption ends according to the load balancing function within the multiple power distribution spaces, obtains the optimal balanced power distribution scheme, and performs load balanced power distribution, wherein the balance optimization includes randomly cross-updating the balanced power distribution scheme for the real-time power distribution information of the multiple power consumption ends.

[0007] The technical solution provided in this application has at least the following technical effects or advantages: The present application collects multiple historical load overload record data of load overloads that occurred in the history of the smart grid, wherein each historical load overload record data includes historical power distribution demand information and historical power distribution information of multiple power consumption ends in the smart grid; collects multiple real-time power distribution demand information of multiple current power consumption ends; constructs multiple power distribution spaces of multiple power consumption ends according to multiple historical load overload record data; constructs a load balancing function to improve the current power distribution balance and the historical power distribution balance; in multiple power distribution spaces, according to the load balancing function, balances and optimizes the real-time power distribution information of the current smart grid to multiple power consumption ends, obtains the optimal balanced power distribution plan, and performs load-balanced power distribution, wherein the balance optimization includes randomly cross-updating the balanced power distribution plan for the real-time power distribution information of multiple power consumption ends. The present invention solves the technical problem of the lack of real-time and flexibility in the existing technology when processing the load balancing of the power grid, and achieves the technical effect of realizing real-time load balancing and optimizing power distribution through data collection, statistical analysis, load balancing function construction and random cross-update optimization. BRIEF DESCRIPTION OF THE DRAWINGS

[0008] In order to more clearly illustrate the technical solutions in the embodiments of the present invention, the following briefly introduces the drawings required for use in the description of the embodiments. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without creative work.

[0009] Figure 1A schematic diagram of the structure of a smart grid adaptive load balancing system provided in an embodiment of the present application; Figure 2 A schematic flow chart of a smart grid adaptive load balancing method provided in an embodiment of the present application.

[0010] Explanation of the reference numerals: data collection module 11 , real-time power distribution demand information collection module 12 , power distribution space construction module 13 , load balancing function construction module 14 , load balancing power distribution module 15 . DETAILED DESCRIPTION

[0011] The present application provides a smart grid adaptive load balancing system to solve the technical problems of lack of real-time performance and flexibility in the existing technology for handling load balancing of power grids. Through data collection, statistical analysis, load balancing function construction and random cross-update optimization, the technical effect of achieving real-time load balancing and optimized power distribution is achieved.

[0012] The following will be combined with the drawings in the embodiments of the present application to clearly and completely describe the technical solutions in the embodiments of the present application. Obviously, the described embodiments are only part of the embodiments of the present application, rather than all of the embodiments. Based on the embodiments in the present application, all other embodiments obtained by ordinary technicians in this field without making creative work are within the scope of protection of this application.

[0013] It should be noted that any variations of the terms "include" and "have" are intended to cover non-exclusive inclusions. For example, a process, method, system, product or server that includes a series of steps or units is not necessarily limited to those steps or units explicitly listed, but may include other steps or modules that are not explicitly listed or inherent to these processes, methods, products or devices.

[0014] Examples, such as Figure 1 As shown, the present application provides a smart grid adaptive load balancing system for performing the following Figure 2 A smart grid adaptive load balancing method is shown, the system comprising: The data collection module 11 collects a plurality of historical load overload record data of load overload occurring in the smart grid in the historical period, wherein each historical load overload record data includes historical power distribution demand information and historical power distribution information of a plurality of power consumption terminals in the smart grid.

[0015] In an embodiment of the present application, the data acquisition module acquires multiple historical load overload record data of load overload occurring in the smart grid in the historical time by collecting data from the historical database, wherein the historical load overload record data includes historical power distribution demand information and historical power distribution information of multiple power users. The historical power distribution demand information of the power user refers to the power required by each power user in a specific historical time period. For example, for power users such as charging piles, it indicates the power demand of the charging piles in a specific time period. The historical power distribution information refers to the power actually obtained by each power user in the same time period. For power users such as charging piles, this information shows the power actually distributed to the charging piles.

[0016] The real-time power distribution demand information collection module 12 collects a plurality of real-time power distribution demand information of the plurality of power consumption terminals.

[0017] In an embodiment of the present application, the real-time power distribution demand information collection module is connected to the monitoring equipment and data collection system of each power consumption end in the smart grid. These devices include smart meters, power consumption monitoring equipment, etc. Through these devices, the power distribution demand of each power consumption end is monitored and recorded in real time, and multiple real-time power distribution demand information of multiple power consumption ends are obtained.

[0018] The power distribution space construction module 13 constructs a plurality of power distribution spaces for a plurality of power consumption ends according to the plurality of historical load overload record data.

[0019] In an embodiment of the present application, the distribution space construction module performs statistical analysis on multiple historical load overload record data, determines the historical maximum distribution information and historical minimum distribution information of each power consumption end, uses the historical maximum distribution information and the minimum distribution information as intervals, and constructs multiple distribution spaces.

[0020] Furthermore, in the system provided by the embodiment of the application, multiple power distribution spaces of multiple power consumption ends are constructed according to the multiple historical load overload record data, including: The historical power distribution information of multiple power consumption ends in the multiple historical load overload record data is counted to obtain multiple historical power distribution information sets; based on the multiple historical power distribution information sets, multiple power distribution information intervals are constructed as multiple power distribution spaces.

[0021] In an embodiment of the present application, a statistical analysis is performed on the historical power distribution information of multiple power consumers in multiple historical load overload record data, and the power distribution demand and actual power distribution situation of each power consumer in different time periods are summarized. By processing these data, the typical power distribution mode and demand change trend of each power consumer during the load overload period are identified, and multiple historical power distribution information sets are generated. These sets contain detailed power distribution data of each power consumer under different load conditions.

[0022] Then, based on multiple sets of historical power distribution information, the historical maximum power distribution information and minimum power distribution information of each power consumer are determined. The historical maximum power distribution information refers to the maximum power actually obtained by each power consumer in the historical records, while the historical minimum power distribution information refers to the minimum power actually obtained by each power consumer in the historical records. The historical maximum power distribution information and the minimum power distribution information of each power consumer are used as intervals to construct multiple power distribution information intervals. Each power distribution information interval represents a range from the historical maximum power distribution to the historical minimum power distribution, reflecting the power distribution situation of the power consumer under different load conditions. By constructing these power distribution information intervals, multiple power distribution spaces are formed.

[0023] The load balancing function construction module 14 constructs a load balancing function by improving the current power distribution balance and improving the historical power distribution balance.

[0024] In the embodiment of the present application, firstly, a real-time load balancing function is constructed with the goal of improving the current power distribution balance, then a historical load balancing function is constructed with the goal of improving the historical power distribution balance, and finally, the real-time load balancing function and the historical load balancing function are combined to construct a comprehensive load balancing function.

[0025] Furthermore, in the system provided in the embodiment of the application, a load balancing function is constructed to improve the current power distribution balance and the historical power distribution balance, including: In order to improve the balance of the current power distribution, a real-time load balancing function is constructed as follows: ; Among them, RTB is the real-time balance. and is the weight, M is the number of multiple power consumption terminals, To balance the real-time power distribution information of the i-th power consumption terminal in the power distribution plan, is the real-time power distribution demand information of the i-th power consumer, is the ratio of the real-time power distribution information and the real-time power distribution demand information of the i-th power user, is the average of the ratios of the real-time power distribution information and the real-time power distribution demand information of the M power consumption terminals; in order to improve the historical power distribution balance, a historical load balancing function is constructed, and a load balancing function is constructed in combination with the real-time load balancing function.

[0026] In the embodiment of the present application, a real-time load balancing function is first constructed, wherein: and The weights pre-set by technical experts are used to calculate the real-time balance degree through the above real-time load balancing function, which quantifies the balance degree of current power distribution. Next, in order to improve the balance degree of historical power distribution, a historical load balancing function is constructed, and the real-time load balancing function and the historical load balancing function are combined to obtain a load balancing function.

[0027] Furthermore, in the system provided by the embodiment of the application, in order to improve the historical power distribution balance, a historical load balancing function is constructed, and combined with the real-time load balancing function, a load balancing function is constructed, including: In order to improve the historical power distribution balance, a historical load balancing function is constructed as follows: ; Among them, HTB is the historical balance, The number of times the power distribution information of the i-th power consumption terminal is less than the power distribution demand information in the real-time balanced power distribution plan and multiple historical load overload record data, The average number of times that the power distribution information of M power consumption terminals is less than the power distribution demand information in the real-time balanced power distribution scheme and multiple historical load overload record data; a load balancing function is constructed according to the real-time load balancing function and the historical load balancing function, as shown in the following formula: ; Among them, LBF is the load balancing degree, is the real-time weight, is the historical weight.

[0028] In an embodiment of the present application, a historical load balancing function is first constructed. The historical load balancing function quantifies the degree of balance of historical power distribution by calculating the variance of the number of times the power distribution information of each power consumption end is less than the demand information in the historical records.

[0029] Next, the constructed historical load balancing function and the real-time load balancing function are combined in a weighted manner to complete the construction of the load balancing function. and The weights are pre-set by technical experts to balance the impact of current power distribution balance and historical power distribution balance.

[0030] The load balancing distribution module 15 performs a balancing optimization on the real-time distribution information of the current smart grid to the multiple power consumption ends according to the load balancing function within the multiple distribution spaces, obtains an optimal balanced distribution plan, and performs load balanced distribution, wherein the balancing optimization includes randomly cross-updating the balanced distribution plan for the real-time distribution information of the multiple power consumption ends.

[0031] In the embodiment of the present application, the load balancing function is first used to evaluate the balance of the current power distribution scheme. Then, a balance optimization is performed in multiple power distribution spaces, and the power distribution of each power user is gradually adjusted. The goal is to improve the balance of power distribution and minimize the gap between the power distribution demand of each power user and the actual power distribution.

[0032] During the optimization process, the random cross-update method is used to adjust the real-time power distribution information of multiple power users. Specifically, among multiple power users, a group of power users is randomly selected as the target of the cross-update. For the selected power users, multiple candidate balanced power distribution schemes are generated. These schemes try to improve the overall power distribution balance while meeting the needs of each power user through different power distribution strategies. The generated balanced power distribution scheme is cross-updated with the current power distribution scheme. Specifically, the power distribution information of each power user is randomly cross-linked, and a better power distribution scheme is found by exchanging power distribution strategies. According to the load balancing function, the updated power distribution scheme is evaluated, and the scheme with the highest load balancing degree is selected as the current optimal balanced power distribution scheme. Repeat the above steps, and continuously optimize the power distribution information of each power user through multiple iterations and cross-updates until the load balancing function converges, that is, the load balancing degree reaches the optimal level.

[0033] Through the above steps, the load balancing distribution module balances and optimizes the real-time distribution information of multiple power consumption terminals in the current smart grid in multiple distribution spaces according to the load balancing function, and finally obtains the optimal balanced distribution solution.

[0034] Furthermore, in the system provided by the embodiment of the application, within the multiple power distribution spaces, according to the load balancing function, the real-time power distribution information of the current smart grid to the multiple power consumption terminals is balanced and optimized, including: Randomly select a group of historical power distribution information in one of the multiple historical load overload record data as a target balanced power distribution scheme; randomly generate multiple groups of real-time power distribution information in the multiple distribution spaces as multiple generated balanced power distribution schemes, wherein the sum of each group of real-time power distribution information is the total power distribution information of the smart grid; update the multiple generated balanced power distribution schemes according to the target balanced power distribution scheme to obtain multiple updated balanced power distribution schemes; randomly cross-update the real-time power distribution information of the multiple power consumption ends in the multiple updated balanced power distribution schemes and the multiple generated balanced power distribution schemes to obtain multiple changed balanced power distribution schemes; update the target balanced power distribution scheme according to the load balancing function in the multiple generated balanced power distribution schemes, the multiple updated balanced power distribution schemes and the multiple changed balanced power distribution schemes; based on the updated target balanced power distribution scheme, iteratively optimize in the multiple distribution spaces until the optimization converges, output a balanced power distribution scheme with the maximum load balancing degree, and obtain an optimal balanced power distribution scheme.

[0035] In an embodiment of the present application, among multiple historical load overload record data, a group of historical power distribution information in a historical load overload record data is randomly selected as a target balanced power distribution scheme. This scheme reflects the power distribution situation of each power end in a certain historical time period, and serves as a reference benchmark for the current optimization. Then, in multiple power distribution spaces, multiple groups of real-time power distribution information are randomly generated as multiple generated balanced power distribution schemes. The sum of each group of real-time power distribution information is equal to the total power distribution information of the smart grid, ensuring the consistency of the total power supply, that is, the sum of the power distribution information of multiple power ends in each balanced power distribution scheme is the total power distribution information. The total power distribution information refers to the total power supply of the smart grid to all power ends in a certain time period. Afterwards, according to the target balanced power distribution scheme, multiple generated balanced power distribution schemes are adjusted, and by comparing the differences between each generated scheme and the target scheme, the power distribution information of each power end is gradually adjusted to make it closer to the target balanced power distribution scheme. Through this process, multiple updated balanced power distribution schemes are obtained.

[0036] Next, the real-time power distribution information of multiple power consumption ends in the multiple updated balanced power distribution schemes and the generated balanced power distribution schemes is randomly cross-updated to obtain multiple changed balanced power distribution schemes. Specifically, among the multiple power consumption ends, a group of power consumption ends is randomly selected as the target of cross-update. Through random selection, the optimization process is prevented from falling into local optimality. The generated balanced power distribution scheme is cross-updated with the current power distribution scheme, and the power distribution information of each power consumption end is randomly cross-linked, and the power distribution strategies are exchanged to find a better power distribution scheme.

[0037] Then, among the multiple generated balanced power distribution schemes, the multiple updated balanced power distribution schemes and the multiple changed balanced power distribution schemes, the target balanced power distribution scheme is updated according to the load balancing function, and the optimal power distribution scheme is selected by evaluating the load balancing degree of each scheme.

[0038] Finally, based on the updated target balanced power distribution scheme, iterative optimization is performed in multiple power distribution spaces. Repeat the above steps, through multiple iterations and cross-updates, continuously optimize the power distribution information of each power consumption end until the preset number of iterations is reached. At this time, it is considered that the optimization convergence is achieved, that is, the load balance is optimal. The optimal balanced power distribution scheme is obtained through the above process.

[0039] Furthermore, in the system provided by the embodiment of the application, the multiple generated balanced power distribution schemes are updated according to the target balanced power distribution scheme to obtain multiple updated balanced power distribution schemes, including: Taking multiple historical power distribution information within the target balanced power distribution scheme as multiple update directions; using the power distribution update step, updating the multiple real-time power distribution information within the multiple generated balanced power distribution schemes to obtain multiple groups of adjusted power distribution information; allocating the total power distribution information according to the ratio of multiple adjusted power distribution information within the multiple groups of adjusted power distribution information to obtain multiple groups of updated power distribution information as multiple updated balanced power distribution schemes.

[0040] In the embodiment of the present application, firstly, multiple historical power distribution information in the target balanced power distribution scheme is used as multiple update directions. Specifically, the historical power distribution information of multiple power consumption ends is extracted from the randomly selected target balanced power distribution scheme, and this information reflects the power distribution situation of each power consumption end in a specific historical time period. These historical power distribution information are used as update directions to guide the generated balanced power distribution scheme to be adjusted towards the target direction.

[0041] Then, the multiple real-time power distribution information in the multiple generated balanced power distribution schemes are updated using the preset power distribution update step. The power distribution update step is the increase or decrease in the power distribution information at each adjustment, for example, the step is set to 5%. Specifically, according to the preset power distribution update step, the real-time power distribution information of each power consumption end is gradually adjusted in the update direction of the historical power distribution information, so that it gradually approaches the target balanced power distribution scheme. Through multiple small adjustments, it is ensured that the generated balanced power distribution scheme gradually approaches the target scheme, and multiple sets of adjusted power distribution information are obtained.

[0042] Then, the total power distribution information is distributed according to the adjustment ratio of each power consumption end in multiple groups of adjusted power distribution information. The adjustment ratio refers to the proportion of the adjusted power distribution information of each power consumption end relative to the adjusted power distribution information of this group. This step ensures that the total power distribution amount remains unchanged, so that the power distribution of the entire system remains consistent during the adjustment process. Specifically, the adjustment ratio of each power consumption end in each group of adjusted power distribution information is calculated, and the total power distribution information is redistributed according to these adjustment ratios to ensure that the distributed power distribution information meets the requirements of the total power distribution, and obtain multiple groups of updated power distribution information.

[0043] Finally, the reallocated multiple groups of updated power distribution information are used as new balanced power distribution solutions.

[0044] Furthermore, in the system provided by the embodiment of the application, the real-time power distribution information of the multiple power consumption ends in the multiple updated balanced power distribution schemes and the multiple generated balanced power distribution schemes are randomly cross-updated to obtain multiple changed balanced power distribution schemes, including: A plurality of cross power terminals are randomly selected from the plurality of power terminals as the first group of cross power terminals; a corresponding first updated balanced power distribution scheme and a first generated balanced power distribution scheme are randomly selected from the plurality of updated balanced power distribution schemes and the plurality of generated balanced power distribution schemes; the power distribution information of the first group of cross power terminals in the first group of cross power terminals is cross-updated, and the total power distribution information is allocated based on the proportion of the power distribution information of the plurality of power terminals after the cross-update to obtain a first changed balanced power distribution scheme; a plurality of cross power terminals are continuously randomly selected from the plurality of power terminals as the second group of cross power terminals; a corresponding second updated balanced power distribution scheme and a second generated balanced power distribution scheme are randomly selected from the plurality of updated balanced power distribution schemes and the plurality of generated balanced power distribution schemes, and the power distribution information of the second group of cross power terminals is cross-updated to obtain a second changed balanced power distribution scheme; other updated balanced power distribution schemes and generated balanced power distribution schemes are continuously cross-updated to obtain a plurality of changed balanced power distribution schemes.

[0045] In the embodiment of the present application, firstly, a plurality of cross power terminals are randomly selected from a plurality of power terminals by using a random selection method as a first group of cross power terminals. Then, a corresponding first updated balanced power distribution scheme and a first generated balanced power distribution scheme are randomly selected from a plurality of updated balanced power distribution schemes and a plurality of generated balanced power distribution schemes. Through random selection, the diversity between different power distribution schemes is increased, and the optimization effect is improved.

[0046] Then, the power distribution information of the first group of cross-power terminals in the first group of cross-power terminals is cross-updated. Specifically, the power distribution information of the first group of cross-power terminals in the first updated balanced power distribution scheme and the first generated balanced power distribution scheme is exchanged, and through this exchange operation, a new combination of power distribution strategies is explored. Based on the proportion of the power distribution information of multiple power terminals after the cross-update, the total power distribution information is allocated to ensure that the sum of the power distribution information of multiple power terminals in each balanced power distribution scheme remains unchanged. Through the above operations, the first changed balanced power distribution scheme is obtained.

[0047] Next, continue to randomly select multiple cross-power terminals from the multiple power terminals as the second group of cross-power terminals. Similarly, through random selection, the diversity of the optimization process is increased. Among the multiple updated balanced power distribution schemes and the multiple generated balanced power distribution schemes, randomly select the corresponding second updated balanced power distribution scheme and the second generated balanced power distribution scheme. The power distribution information of the second group of cross-power terminals is cross-updated, and the specific steps are similar to the operations of the first group of cross-power terminals, by exchanging the power distribution information of the second group of cross-power terminals in the second updated balanced power distribution scheme and the second generated balanced power distribution scheme. Then, based on the proportion of the power distribution information of the multiple power terminals after the cross-update, the total power distribution information is allocated, and the second changed balanced power distribution scheme is obtained through the above operations.

[0048] Finally, other updated balanced power distribution schemes and generated balanced power distribution schemes are cross-updated. New cross-power consumption terminals are randomly selected to select the corresponding updated balanced power distribution schemes and generated balanced power distribution schemes. Cross-updates are performed, power distribution information is exchanged, and the total power distribution information is redistributed based on the cross-updated ratio. By repeating this process, multiple changed balanced power distribution schemes are obtained.

[0049] Further, in the system provided by the embodiment of the application, among the multiple generated balanced power distribution schemes, the multiple updated balanced power distribution schemes and the multiple changed balanced power distribution schemes, the target balanced power distribution scheme is updated according to the load balancing function, including: Based on the load balancing function, according to the power distribution information of multiple power users in the multiple generated balanced power distribution schemes, multiple updated balanced power distribution schemes and multiple changed balanced power distribution schemes, combined with the multiple historical load overload record data, multiple load balancing degrees are calculated; and the balanced power distribution scheme corresponding to the largest load balancing degree is selected as the target balanced power distribution scheme.

[0050] In the embodiment of the present application, the real-time power distribution information of each power consumption end is extracted from multiple generated balanced power distribution schemes, multiple updated balanced power distribution schemes, and multiple changed balanced power distribution schemes, and the corresponding load overload data is extracted from the historical records. Next, the load balancing function is used to calculate the load balancing degree of each scheme. Then, all the calculation results are compared, and the scheme with the highest load balancing degree is selected as the target balanced power distribution scheme.

[0051] In the embodiments of the present application, in summary, the embodiments of the present application have at least the following technical effects: The present application collects multiple historical load overload record data of load overloads that occurred in the history of the smart grid, wherein each historical load overload record data includes historical power distribution demand information and historical power distribution information of multiple power consumption ends in the smart grid; collects multiple real-time power distribution demand information of multiple current power consumption ends; constructs multiple power distribution spaces of multiple power consumption ends according to multiple historical load overload record data; constructs a load balancing function to improve the current power distribution balance and the historical power distribution balance; in multiple power distribution spaces, according to the load balancing function, balances and optimizes the real-time power distribution information of the current smart grid to multiple power consumption ends, obtains the optimal balanced power distribution plan, and performs load-balanced power distribution, wherein the balance optimization includes randomly cross-updating the balanced power distribution plan for the real-time power distribution information of multiple power consumption ends. The present invention solves the technical problem of the lack of real-time and flexibility in the existing technology when processing the load balancing of the power grid, and achieves the technical effect of realizing real-time load balancing and optimizing power distribution through data collection, statistical analysis, load balancing function construction and random cross-update optimization.

[0052] It should be noted that the above-mentioned sequence of the embodiments of the present application is only for description and does not represent the advantages and disadvantages of the embodiments. And the above-mentioned specific embodiments of this specification are described. The processes depicted in the accompanying drawings do not necessarily require the specific order and continuous order shown to achieve the desired results. In some embodiments, multitasking and parallel processing are also possible or may be advantageous.

[0053] The above description is only a preferred embodiment of the present application and is not intended to limit the present application. Any modifications, equivalent substitutions, improvements, etc. made within the spirit and principles of the present application shall be included in the protection scope of the present application.

[0054] This specification and drawings are merely exemplary illustrations of the present application and are deemed to cover any and all modifications, variations, combinations or equivalents within the scope of the present application. Obviously, a person skilled in the art may make various modifications and variations to the present application without departing from the scope of the present application. Thus, if these modifications and variations of the present application fall within the scope of the present application and its equivalents, the present application intends to include these modifications and variations.

Claims

1. A smart grid adaptive load balancing system, characterized in that: The system comprises: A data collection module, wherein the data collection module collects a plurality of historical load overload record data of load overload occurring in the smart grid in the historical time, wherein each historical load overload record data includes historical power distribution demand information and historical power distribution information of a plurality of power consumption terminals in the smart grid; A real-time power distribution demand information collection module, which collects a plurality of real-time power distribution demand information of the plurality of power consumption terminals; A power distribution space construction module, wherein the power distribution space construction module constructs a plurality of power distribution spaces of a plurality of power consumption ends according to the plurality of historical load overload record data; A load balancing function construction module, wherein the load balancing function construction module is used to improve the current power distribution balance and improve the historical power distribution balance to construct a load balancing function; A load balancing distribution module, wherein the load balancing distribution module performs a balancing optimization on the real-time distribution information of the current smart grid to the multiple power consumption ends according to the load balancing function within the multiple distribution spaces, obtains an optimal balanced distribution plan, and performs load balanced distribution, wherein the balancing optimization includes randomly cross-updating the balanced distribution plan for the real-time distribution information of the multiple power consumption ends.

2. The smart grid adaptive load balancing system according to claim 1, characterized in that: According to the plurality of historical load overload record data, a plurality of power distribution spaces of a plurality of power consumption ends are constructed, including: Collecting statistics on historical power distribution information of multiple power consumption terminals in the multiple historical load overload record data to obtain multiple historical power distribution information sets; Based on the multiple historical power distribution information sets, multiple power distribution information intervals are constructed as multiple power distribution spaces.

3. The smart grid adaptive load balancing system according to claim 1, characterized in that: To improve the current power distribution balance and the historical power distribution balance, a load balancing function is constructed, including: In order to improve the balance of the current power distribution, a real-time load balancing function is constructed as follows: ； Among them, RTB is the real-time balance. and is the weight, M is the number of multiple power consumption terminals, To balance the real-time power distribution information of the i-th power consumption terminal in the power distribution plan, is the real-time power distribution demand information of the i-th power consumer, is the ratio of the real-time power distribution information and the real-time power distribution demand information of the i-th power user, is the average value of the ratio of the real-time power distribution information to the real-time power distribution demand information of the M power consumption terminals; In order to improve the historical power distribution balance, a historical load balancing function is constructed, and combined with the real-time load balancing function, a load balancing function is constructed.

4. The smart grid adaptive load balancing system according to claim 3, characterized in that: In order to improve the historical power distribution balance, a historical load balancing function is constructed, and combined with the real-time load balancing function, a load balancing function is constructed, including: In order to improve the historical power distribution balance, a historical load balancing function is constructed as follows: ； Among them, HTB is the historical balance, The number of times the power distribution information of the i-th power consumption terminal is less than the power distribution demand information in the real-time balanced power distribution plan and multiple historical load overload record data, To find the average number of times that the power distribution information of M power consumption terminals is less than the power distribution demand information within the real-time balanced power distribution plan and multiple historical load overload record data; According to the real-time load balancing function and the historical load balancing function, a load balancing function is constructed as follows: ； Among them, LBF is the load balancing degree, is the real-time weight, is the historical weight.

5. The smart grid adaptive load balancing system according to claim 4, characterized in that: In the multiple power distribution spaces, according to the load balancing function, the real-time power distribution information of the current smart grid to the multiple power consumption terminals is balanced and optimized, including: Randomly selecting a set of historical power distribution information in the plurality of historical load overload record data as a target balanced power distribution scheme; In the plurality of power distribution spaces, a plurality of groups of real-time power distribution information are randomly generated as a plurality of generated balanced power distribution schemes, wherein the sum of each group of real-time power distribution information is the total power distribution information of the smart grid; According to the target balanced power distribution scheme, the multiple generated balanced power distribution schemes are updated to obtain multiple updated balanced power distribution schemes; Randomly cross-update the real-time power distribution information of the multiple power consumption terminals in the multiple updated balanced power distribution schemes and the multiple generated balanced power distribution schemes to obtain multiple changed balanced power distribution schemes; Among the multiple generated balanced power distribution schemes, the multiple updated balanced power distribution schemes and the multiple changed balanced power distribution schemes, updating the target balanced power distribution scheme according to the load balancing function; Based on the updated target balanced power distribution scheme, iterative optimization is performed in the multiple power distribution spaces until the optimization converges, and a balanced power distribution scheme with the maximum load balancing degree is output to obtain an optimal balanced power distribution scheme.

6. The smart grid adaptive load balancing system according to claim 5, characterized in that: According to the target balanced power distribution scheme, the multiple generated balanced power distribution schemes are updated to obtain multiple updated balanced power distribution schemes, including: Using multiple historical power distribution information in the target balanced power distribution scheme as multiple update directions; Adopting a power distribution update step, updating a plurality of real-time power distribution information in the plurality of generated balanced power distribution schemes, and obtaining a plurality of sets of adjusted power distribution information; The total power distribution information is distributed according to the ratio of multiple adjusted power distribution information in the multiple groups of adjusted power distribution information to obtain multiple groups of updated power distribution information as multiple updated balanced power distribution schemes.

7. The smart grid adaptive load balancing system according to claim 5, characterized in that: The real-time power distribution information of the multiple power consumption terminals in the multiple updated balanced power distribution schemes and the multiple generated balanced power distribution schemes are randomly cross-updated to obtain multiple changed balanced power distribution schemes, including: Randomly selecting a plurality of cross power terminals from the plurality of power terminals as a first group of cross power terminals; Randomly selecting a corresponding first updated balanced power distribution scheme and a first generated balanced power distribution scheme from among the plurality of updated balanced power distribution schemes and the plurality of generated balanced power distribution schemes; Cross-update the power distribution information of the first group of cross power terminals in the first group of cross power terminals, and distribute the total power distribution information based on the proportion of the power distribution information of the plurality of power terminals after the cross-update, to obtain a first change balanced power distribution plan; Continue to randomly select multiple cross power terminals from the multiple power terminals as a second group of cross power terminals; Randomly select a corresponding second updated balanced power distribution scheme and a second generated balanced power distribution scheme from the multiple updated balanced power distribution schemes and the multiple generated balanced power distribution schemes, cross-update the power distribution information of the second group of cross power consumption terminals, and obtain a second changed balanced power distribution scheme; Continue to cross-update other updated balanced power distribution plans and generated balanced power distribution plans to obtain multiple changed balanced power distribution plans.

8. The smart grid adaptive load balancing system according to claim 5, characterized in that: In the plurality of generated balanced power distribution schemes, the plurality of updated balanced power distribution schemes and the plurality of changed balanced power distribution schemes, updating the target balanced power distribution scheme according to the load balancing function includes: Based on the load balancing function, according to the power distribution information of multiple power consumption ends in the multiple generated balanced power distribution schemes, the multiple updated balanced power distribution schemes and the multiple changed balanced power distribution schemes, combined with the multiple historical load overload record data, multiple load balancing degrees are calculated; The balanced power distribution scheme corresponding to the maximum load balancing degree is selected as the target balanced power distribution scheme.

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