Distribution network peak shifting self-balancing method and system based on block chain technology

Abstract

The invention relates to the technical field of power management and control, in particular to a distribution network off-peak self-balancing method and system based on a block chain technology, and provides a distribution network off-peak self-balancing method to solve the problem of secondary peak caused by off-peak power utilization in a power grid. Comprising the steps of determining a peak period of power utilization of a target area according to a power utilization condition and a distribution network capacity of the target area; obtaining the peak electricity consumption of each electricity consumption unit in the target area in the peak period, and obtaining an adjustable load unit according to the peak electricity consumption and the unit type of the electricity consumption unit; and screening the management and control plans according to the decreasing electric quantity and the increasing electric quantity to obtain an implementation scheme, feeding back the implementation scheme to the adjustable load unit, and uploading corresponding peak shifting management and control data according to the implementation scheme.

Description

Technical Field

[0001] The present invention relates to the technical field of power control platforms, and more particularly, to a distribution network peak-shaving self-balancing method and system based on blockchain technology. Background Art

[0002] In recent years, with the rapid growth of various electrical equipment, such as air conditioners and electric vehicles, the electricity consumption has also increased rapidly. Peak-shaving electricity consumption has had a profound impact on users, the power grid, and society. For example, peak-shaving electricity consumption can reduce the electricity bills of users, balance the load of the power grid, improve the stability of the power grid, promote the consumption of renewable energy, and improve the utilization rate of clean energy. However, traditional peak-shaving methods, such as administrative orders or fixed-time electricity prices, rely on centralized decision-making. Users may, due to the same incentives, such as unified valley electricity price periods, transfer loads centrally. When users lack real-time load information, they may act based on historical experience or unified notifications, resulting in the failure of negative feedback. In addition, the existing peak-valley regulation means are based on the large power grid mode, with a relatively high threshold for participation in regulation, involving a large number of objects, and a relatively cumbersome response process, resulting in low enthusiasm, interactivity, information sharing, and transparency among the participating objects. How to solve the problem of "secondary peak" caused by peak-shaving electricity consumption in the power grid has become an urgent problem to be solved in the power grid. Summary of the Invention

[0003] The problem solved by the present invention is: how to solve the problem of "secondary peak" caused by peak-shaving electricity consumption in the power grid.

[0004] To solve the above problems, an embodiment of the present invention provides a distribution network peak-shaving self-balancing method based on blockchain technology. The distribution network peak-shaving self-balancing method includes: determining the peak period of electricity consumption in the target area according to the electricity consumption situation and distribution network capacity of the target area; obtaining the peak electricity consumption of each electricity-consuming unit in the target area during the peak period, and obtaining adjustable load units according to the peak electricity consumption and the unit type of the electricity-consuming unit; obtaining the real-time electricity consumption in the target area during the peak period, and the control platform sending peak-shaving control data to the adjustable load units according to the real-time electricity consumption; the adjustable load units controlling the electrical equipment according to the peak-shaving control data and feeding back the control plan to the control platform; the control platform calculating the reduced electricity consumption and the increased electricity consumption of future electricity consumption according to the control plan; screening the control plan according to the reduced electricity consumption and the increased electricity consumption to obtain an implementation plan, feeding back the implementation plan to the adjustable load units, and uploading the corresponding peak-shaving control data according to the implementation plan.

[0005] Compared with the prior art, the technical effects achieved by adopting this technical solution are as follows: By determining the peak period according to the electricity consumption situation of the target area and the distribution network capacity, the period of tight power supply and demand can be more accurately identified. Through the peak electricity consumption and the unit type of the electricity-consuming units, the adjustable load units can be quickly determined, thereby improving the regulation efficiency. Sending peak-shifting control data to the adjustable load units according to the real-time electricity consumption can effectively prevent problems such as overload and unstable voltage in the distribution network during the peak period due to excessive load. The adjustable load units control the electrical equipment according to the peak-shifting control data, which helps to maintain the stable operation of the distribution network, reduce the occurrence probability of equipment failures and power outages, and ensure the reliability of power supply. The adjustable load units feedback the control plan to the control platform, which helps to understand the implementation situation of each adjustable load unit in real time, and timely adjust and optimize the power grid operation strategy. The peak-shifting effect can be judged by the reduced electricity consumption of the real-time electricity consumption, and whether the phenomenon of "secondary peak" will occur in the future period can be calculated by the increased electricity consumption of the future electricity consumption. Screening the control plan to obtain the implementation plan makes the control measures more scientific and accurate, improves the regulation effect and pertinence, and ensures that the power system realizes safe and efficient operation while meeting the electricity consumption needs of users.

[0006] In an embodiment of the present invention, determining the peak period of electricity consumption in the target area according to the electricity consumption situation of the target area and the distribution network capacity specifically includes: obtaining the historical electricity consumption of the target area, calculating the ratio of the historical electricity consumption to the distribution network capacity to obtain the first load rate; comparing the first load rate with the peak threshold to obtain the peak period corresponding to the target area.

[0007] Compared with the prior art, the technical effects achieved by adopting this technical solution are as follows: Comparing the first load rate with the peak threshold to obtain the peak period corresponding to the target area can dynamically adjust the division of the peak period according to the actual electricity consumption situation, realizing the accurate identification of the peak period and providing a basis for subsequent power control.

[0008] In an embodiment of the present invention, obtaining the peak electricity consumption of each electricity-consuming unit in the target area during the peak period and obtaining the adjustable load units according to the peak electricity consumption and the unit type of the electricity-consuming units specifically includes: obtaining the peak electricity consumption of each electricity-consuming unit during the peak period; obtaining the load units to be adjusted according to the peak electricity consumption and the electricity consumption threshold; judging whether there are electricity-consuming equipment that can perform peak-shifting electricity consumption in the load units to be adjusted according to the unit type of the load units to be adjusted; when there is electricity-consuming equipment that can perform peak-shifting electricity consumption in the load units to be adjusted, recording the load units to be adjusted as adjustable load units.

[0009] Compared with the prior art, the technical effects achieved by adopting this technical solution are as follows: By comparing the peak electricity consumption with the electricity consumption threshold, units with high electricity load during peak hours can be accurately identified, providing a basis for subsequent off-peak electricity consumption management. By screening adjustable load units, the load management becomes more targeted.

[0010] In an embodiment of the present invention, the real-time electricity consumption of a target area during peak hours is obtained, and the control platform sends off-peak control data to adjustable load units according to the real-time electricity consumption, which specifically includes: recording the ratio of the real-time electricity consumption to the distribution network capacity as the second load rate; judging whether to send off-peak control data to adjustable load units according to the second load rate, the load threshold, and the duration threshold.

[0011] Compared with the prior art, the technical effects achieved by adopting this technical solution are as follows: The load threshold provides an important basis for the resource allocation of the power system. By setting the duration threshold for different periods, users can be guided to consume electricity during low-load periods and avoid peak periods, thereby achieving peak shaving and valley filling of the power load.

[0012] In an embodiment of the present invention, judging whether to send off-peak control data to adjustable load units according to the second load rate, the load threshold, and the duration threshold specifically includes: when the second load rate is greater than or equal to the load threshold, sending off-peak control data to adjustable load units; counting the peak duration during which the second load rate is continuously greater than the peak threshold; when the peak duration is greater than or equal to the duration threshold, sending off-peak control data to adjustable load units.

[0013] Compared with the prior art, the technical effects achieved by adopting this technical solution are as follows: Through the off-peak control data, adjustable load units can be guided to reduce electricity consumption during peak load periods and increase electricity consumption during non-peak periods, thereby effectively balancing the supply and demand relationship of the power system.

[0014] In an embodiment of the present invention, the control platform calculates the reduced electricity consumption of the real-time electricity consumption and the increased electricity consumption of the future electricity consumption according to the control plan, which specifically includes: when an adjustable load unit controls its electrical equipment, sending the control plan to the control platform; the control platform obtains the electrical equipment turned off by the adjustable load unit according to the control plan, which is recorded as adjustable equipment, and calculates the reduced electricity consumption of the real-time electricity consumption according to the adjustable equipment; the control platform obtains the restart time of each adjustable equipment according to the control plan, and records the restarted adjustable equipment as restart equipment, and calculates the increased electricity consumption of the future electricity consumption according to the restart equipment and the restart time.

[0015] Compared with the prior art, the technical effects achieved by adopting this technical solution are as follows: The generation of the control plan helps the control platform to grasp the reduced electricity consumption due to equipment control in real time and accurately. The control platform automatically performs relevant calculations and analyses according to the control plan, reducing manual intervention and improving the processing efficiency and accuracy.

[0016] In one embodiment of the present invention, the control plan is screened according to the reduced power consumption and the increased power consumption to obtain an implementation plan, and the implementation plan is fed back to the adjustable load unit, and the corresponding peak-shaving control data is uploaded according to the implementation plan, specifically including: judging whether there is a situation exceeding the peak threshold value during the off-peak period according to the increased power consumption, historical power consumption and peak threshold value; if so, determining the power consumption that can be increased during the off-peak period according to the historical power consumption and the peak threshold value, which is recorded as the target increment, and obtaining the target reduced power consumption according to the real-time power consumption and the peak threshold value, which is recorded as the target reduction; screening the control plan according to the target increment and the target reduction to obtain an implementation plan; feeding back the implementation plan to the adjustable load unit, and uploading the corresponding peak-shaving control data according to the implementation plan.

[0017] Compared with the prior art, the technical effects achieved by adopting this technical solution are as follows: by analyzing the increased power consumption, historical power consumption and peak threshold value, it is possible to accurately judge whether there is a situation exceeding the peak threshold value during the off-peak period, and accordingly determine the target increment and the target reduction. By real-time monitoring and dynamically adjusting the peak-shaving control plan, it is possible to effectively avoid the overload of the power grid load, help enhance the stability of the power grid operation, reduce the occurrence of power outages, and ensure the reliability of power supply.

[0018] In one embodiment of the present invention, the implementation plan is fed back to the adjustable load unit, and the corresponding peak-shaving control data is uploaded according to the implementation plan, specifically including: obtaining the real-time power consumption of the target area, and judging the implementation situation of the implementation plan according to the real-time power consumption; when the implementation situation meets the expectation, sending a statement to the adjustable load unit; when the implementation situation does not meet the expectation, the control platform re-sends the peak-shaving control data to the adjustable load unit.

[0019] Compared with the prior art, the technical effects achieved by adopting this technical solution are as follows: by obtaining the real-time power consumption of the target area, it is possible to monitor the implementation of the peak-shaving control measures in real time, ensure the dynamic grasp of the power grid operation state, and be able to discover problems in time and take measures.

[0020] In one embodiment of the present invention, a self-balancing system based on blockchain technology is further provided. The distribution network peak-shaving self-balancing method recorded in the above embodiment is applied to the self-balancing system. The self-balancing system includes: a data acquisition module for acquiring real-time power consumption; a data communication module for the control platform to send peak-shaving control data to the adjustable load unit and for the adjustable load unit to feedback the control plan to the control platform; a data calculation module for calculating the reduced power consumption and the increased power consumption; and a data analysis module for screening the control plan. BRIEF DESCRIPTION OF THE DRAWINGS

[0021] To more clearly illustrate the technical solutions of the embodiments of the present invention, the following will briefly introduce the accompanying drawings to be used in the description of the embodiments. Obviously, the accompanying drawings in the following description are only some embodiments of the present invention. For those skilled in the art, without creative efforts, other drawings can be obtained based on these drawings; Figure 1 It is one of the flowcharts of the distribution network peak-shaving self-balancing method based on blockchain technology of the present invention; Figure 2 It is the second flowchart of the distribution network peak-shaving self-balancing method based on blockchain technology of the present invention; Figure 3 It is the third flowchart of the distribution network peak-shaving self-balancing method based on blockchain technology of the present invention; Figure 4 It is the fourth flowchart of the distribution network peak-shaving self-balancing method based on blockchain technology of the present invention; Figure 5 It is the fifth flowchart of the distribution network peak-shaving self-balancing method based on blockchain technology of the present invention; Figure 6 It is the sixth flowchart of the distribution network peak-shaving self-balancing method based on blockchain technology of the present invention; Figure 7 It is the module diagram of the self-balancing system based on blockchain technology of the present invention.

[0022] Explanation of reference numerals: 100 - Self-balancing system; 110 - Data acquisition module; 120 - Data communication module; 130 - Data calculation module; 140 - Data analysis module. Detailed implementation manners

[0023] To make the above objects, features, and advantages of the present invention more obvious and understandable, the following will describe the specific embodiments of the present invention in detail with reference to the accompanying drawings.

[0024]

First Embodiment

[0025] In step S100, the target area refers to the area that needs to conduct power consumption management and analysis. For example, areas such as factories, commercial and residential power consumption, etc. The power consumption situation includes, but is not limited to, data such as equipment operation status, peak power consumption period, low power consumption period, flat power consumption period, and power consumption. Usually, the power consumption law of the target area can be obtained according to the historical power consumption of the target area. For example, the power consumption of an office building in winter and summer is larger than that in spring and autumn. For factories, the power consumption in the off-season is less than that in the peak season.

[0026] Generally speaking, due to the differences in load demand and power grid structure, etc., the distribution network capacities of different regions have certain differences. In order to ensure the stable operation of the power control platform, it is necessary to determine the peak period of the target area according to the distribution network capacity and power consumption situation. For example, the period when the load is greater than or equal to 80% of the distribution network capacity is recorded as the peak period.

[0027] Usually, the target area has a certain power consumption regularity. Taking the determination of the peak period of the current natural day as an example, the peak period of the current natural day can be predicted through the power consumption of adjacent natural days. For example, the peak power consumption period of an industrial park from March 24th, March 25th, and March 26th, 2025 is from 9 o'clock to 11 o'clock, and it can be inferred that the peak period from 9 o'clock to 11 o'clock is the peak period of March 27th, 2025.

[0028] For residential areas, due to the power consumption of residents and seasonal changes, the peak period in summer usually concentrates from 18:00 to 22:00, while the peak period in winter may appear from 7:00 to 9:00 and from 18:00 to 21:00.

[0029] It should be noted that when there are special periods such as holidays and shutdown for maintenance, etc., then, the power consumption situation during this period cannot be used as a reference standard for determining the peak period.

[0030] In step S200, electricity-consuming entities include, but are not limited to, industrial electricity-consuming entities, agricultural electricity-consuming entities, commercial electricity-consuming entities, and residential electricity consumption, etc. Generally, whether peak shaving can be carried out during peak electricity consumption periods is related to the type of the electricity-consuming entity. For example, residents can carry out activities such as doing laundry and charging after 23:00. When irrigating farmland, the irrigation time can be arranged during low electricity consumption periods. Additionally, during industrial production, some equipment such as cold chain equipment, life safety guarantee equipment, and high-speed production line equipment cannot carry out peak shaving.

[0031] In step S300, generally, the real-time electricity consumption of the target area can be obtained in real time through smart electricity meters and a power monitoring and control platform. The control platform analyzes the real-time electricity consumption data in combination with the distribution network capacity, evaluates the current electricity load situation, and generates peak shaving control data according to the comparison result between the real-time electricity consumption and the distribution network capacity. Among them, the peak shaving control data includes, but is not limited to, instructions such as adjusting the electricity consumption time, reducing the electricity consumption power, or switching to a backup power supply.

[0032] In step S400, generally, electricity-consuming entities can plan their electricity consumption on the current working day according to the needs of production and life. Taking a large factory as an example, the large factory will formulate a detailed electricity consumption plan based on production orders and equipment operation parameters to ensure the smooth progress of the production process and avoid damage to equipment caused by insufficient power or overload. When adjustable load entities receive the peak shaving control data, they control the electricity-consuming equipment according to the electricity consumption plan. Taking a shopping mall as an example, the shopping mall will reasonably plan the electricity consumption of equipment such as lighting, air conditioning, and elevators according to business hours, promotional activity arrangements, and the flow of people in different areas. When the adjustable load entity receives the peak shaving control data, it can control the electricity-consuming equipment according to its electricity consumption plan.

[0033] For example, when the peak period of the target area is from 10:00 to 11:00, a certain factory receives the peak shaving control data at 10:00. According to its electricity consumption plan, it intends to turn off 20 electricity-consuming equipment at 10:00 until they are restarted at 17:00. Then this factory generates a control plan based on the quantity, model, shutdown time, and restart time of the turned-off electricity-consuming equipment, and feeds this control plan back to the control platform.

[0034] For example, when an adjustable load entity receives the peak shaving control data, it does not control the electricity-consuming equipment due to production requirements. When not controlling the electricity-consuming equipment, it does not need to feed back the control plan to the control platform.

[0035] In step S500, according to the start-stop or power regulation measures of electrical equipment in the control plan, calculate the total load amount turned off by the adjustable load unit during the current period to obtain the reduced power consumption of the real-time power consumption. According to the restart time and power magnitude of the electrical equipment that is turned off in the control plan, calculate the increased power consumption of the future power consumption. For example, according to the control plan, it is obtained that the electrical equipment with a total power of 100KW starts to be turned off at 14:00 and ends at 15:00, and the electrical equipment with a total power of 90KW starts to restart at 21:00. Then, at 14:00, the reduced power consumption of the real-time power consumption in the target area is 100KW, and at 21:00, the increased power consumption is 90KW.

[0036] In addition, when the adjustable load unit receives the peak-shaving control data, some electrical equipment that was originally planned to start during the peak period but did not start in the end should also be included in the reduced power consumption of the real-time power consumption. When calculating the increased power consumption of the future power consumption, only consider whether the electrical equipment that is turned off in the control plan will restart in the future period.

[0037] In step S600, usually, it can be determined whether the peak shaving is effective based on the reduced power consumption. When the reduced power consumption meets the peak shaving demand, judge whether the increased power consumption of the future power consumption will cause a "secondary peak". If the increased power consumption of the future power consumption does not cause a "secondary peak", stop sending the peak-shaving control data to the adjustable load unit. If the increased power consumption of the future power consumption causes a "secondary peak", it is necessary to screen each control plan to obtain a reasonable implementation plan. When the reduced power consumption does not meet the peak shaving demand, it is necessary to continue sending the peak-shaving control data.

[0038] When the increased power consumption of the future power consumption causes a "secondary peak", adjust the control plans of each adjustable load unit. For example, adjust the power consumption time of some adjustable load units. For example, the target area is a non-peak period after 15:00. Due to peak-shaving power consumption, the power consumption between 16:00 and 17:00 increases sharply, resulting in the phenomenon of a "secondary peak". According to the control plan, reasonably distribute the increased power consumption between 16:00 and 17:00 to other non-peak periods to relieve the power consumption pressure between 16:00 and 17:00.

[0039] Real-time monitor the power consumption of the target area and the power consumption of the adjustable load unit. According to the real-time power consumption of the target area, judge whether the implementation plan of the target area is effective. When the implementation plan is effective, stop sending the peak-shaving control data to the adjustable load unit. According to the power consumption of the adjustable load unit, judge whether the adjustable load unit uses electricity according to the control plan.

[0040] It should be noted that in order to improve data transparency and trust, the electricity consumption data of the target area, the electricity consumption data of adjustable load units, control plans, and peak-shaving control data can be stored through blockchain technology.

[0041] By determining the peak hours according to the electricity consumption situation of the target area and the distribution network capacity, it is possible to more accurately identify the hours when the power supply and demand are tense. By using the peak electricity consumption and the unit type of the electricity-consuming unit, the adjustable load units can be quickly determined, thus improving the regulation efficiency. Sending peak-shaving control data to the adjustable load units according to the real-time electricity consumption can effectively prevent problems such as overload and voltage instability of the distribution network due to excessive load during peak hours. The adjustable load units control the electrical equipment according to the peak-shaving control data, which helps to maintain the stable operation of the distribution network, reduce the probability of equipment failures and power outages, and ensure the reliability of power supply. The adjustable load units feedback the control plan to the control platform, which helps to understand the implementation situation of each adjustable load unit in real time, and timely adjust and optimize the power grid operation strategy. The effect of peak shaving can be judged by the reduced electricity consumption of the real-time electricity consumption, and whether the phenomenon of "secondary peak" will occur in the future period can be calculated by the increased electricity consumption of the future electricity consumption. Screening the control plan to obtain the implementation plan makes the control measures more scientific and accurate, improves the effect and pertinence of regulation, and ensures that the power system operates safely and efficiently while meeting the electricity consumption needs of users.

[0042]

Second Embodiment

[0043] In step S120, the setting of the peak threshold needs to comprehensively consider the peak-valley difference, the duration of each period, and the peak-shaving potential of users. The calculation formula of the peak threshold is as follows: ; D = P÷C.

[0044] Among them, D is the peak threshold, C is the distribution network capacity, is the load threshold, is the maximum safe load of the power grid, is the peak-valley difference, is the total duration of the peak hours; T is the total duration of the peak hours, flat hours, and valley hours added together, The user response coefficient refers to the ratio of the peak load that can be transferred during peak hours by electricity-consuming units in the target area during peak periods to the total load. For example, k = 0.3 means that the electricity-consuming unit can transfer 30% of the peak load.

[0045] For example, in a certain area = 900 MW, = 600 MW, = 6 h, T = 24 h, k = 0.4. Then, P = 900 - 600×6 / 24×1 / (1 + 0.4) = 792.9 MW. That is, when the real-time load is close to or exceeds 792.9 MW, it is the peak period corresponding to the target area.

[0046] Generally, to determine the peak period of the current natural day, it is necessary to obtain at least the peak periods of three consecutive adjacent natural days, and obtain the peak period of the current working day based on the peak periods of adjacent natural days.

[0047] For example, to determine the peak period of an industrial park on March 26, 2025, it is necessary to obtain the peak periods of March 23, 2025, March 24, 2025, and March 25, 2025, and use a machine learning model to predict the peak period of March 26, 2025.

[0048] Comparing the first load factor with the peak threshold to obtain the peak period corresponding to the target area can dynamically adjust the division of the peak period according to the actual electricity consumption situation, achieving accurate identification of the peak period and providing a basis for subsequent power control.

[0049]

Third Embodiment

[0050] In step S210, the peak power consumption of each electricity-consuming unit during the peak period is obtained through an intelligent electricity meter or a power company, and different electricity-usage thresholds are set according to the magnitudes of the peak power consumptions of each electricity-consuming unit during the peak period. For example, for some high-load industries such as steel manufacturing and power-intensive industries, higher electricity-usage thresholds are set, while for some low-load industries, lower electricity-usage thresholds are set.

[0051] For example, the electricity-usage threshold for industrial users can be set at 5% of the peak power consumption of the target area during the peak period, and for commercial users, it can be set at 3%. When the peak power consumption of an electricity-consuming unit during the peak period is greater than the electricity-usage threshold, the electricity-consuming unit is recorded as a load unit to be adjusted.

[0052] In step S220, the electricity consumption, usage time period, and power demand of all the main power-consuming equipment of the load unit to be adjusted are obtained through an intelligent electricity meter or a power company. By analyzing the equipment usage pattern and production process of the load unit to be adjusted, it is judged whether the electricity-consuming equipment has flexibility in electricity-usage time. Some electricity-consuming equipment is crucial for production or operation and cannot be adjusted arbitrarily in terms of operation time, while the operation time of some electricity-consuming equipment can be postponed or advanced without seriously affecting production or operation. The electricity-consuming equipment that can shift peak electricity usage is recorded as peak-shiftable equipment.

[0053] The units with high electricity loads during the peak period can be accurately identified through the peak power consumption and the electricity-usage threshold, providing a basis for subsequent peak-shift electricity-usage management. By screening the load units to be adjusted, the load management becomes more targeted.

[0054]

Fourth Embodiment

[0055] In step S320, the load threshold refers to the ratio of the maximum load that the power grid can operate normally to the distribution network capacity, which can usually be obtained from the State Grid or local government departments. The duration threshold refers to the reference value of the continuous time length when the second load rate exceeds the peak threshold. The duration threshold can be set according to the control requirements. Based on historical electricity consumption data, methods such as regression analysis, time series analysis, or machine learning models can be used to establish a load prediction model. According to the load prediction model, predict the duration of the peak period of the current natural day. For example, assume that the peak threshold in a certain area is 80%, and the average continuous duration of the peak period is 50 minutes. If the duration threshold is set to 70% of 50 minutes, that is, 35 minutes, when the continuous time length when the second load rate exceeds the peak threshold is greater than or equal to 35 minutes, send peak-shifting control data. In addition, if the power grid load pressure is relatively large, the duration threshold can be appropriately reduced.

[0056] The load threshold provides an important basis for the resource allocation of the power system. By setting the duration threshold for different periods, users can be guided to use electricity during the low-load period and avoid the peak period, thereby achieving peak shaving and valley filling of the power load.

[0057]

Fifth Embodiment

[0058] In steps S321 and S323, based on historical electricity consumption data, methods such as regression analysis, time series analysis, or machine learning models are used to establish a load prediction model. According to the load prediction model, predict the duration of the peak period of the current natural day and the electricity consumption fluctuation situation during the peak period. Calculate the electricity consumption power that needs to be reduced according to the second load rate and the electricity consumption fluctuation situation during the peak period. Obtain the peak-shifting start and end times based on the peak duration and the duration threshold. Generate peak-shifting control data with the above-obtained data.

[0059] For example, if the peak threshold of a certain area is 70%, the average continuous duration during the peak period is 100 minutes, the load threshold is 80%, and the duration threshold is 40 minutes. When the second load rate is 80%, according to the second load rate and the peak threshold, it is necessary to reduce the second load rate by 10%. When the second load rate is 75% and the peak duration is greater than or equal to 40 minutes, according to the second load rate and the peak threshold, it is necessary to reduce the second load rate by 5%.

[0060] It should be noted that usually, there may be inaccurate prediction of the peak period. Therefore, it is necessary to monitor the electricity consumption of the target area and each electricity-consuming unit in real time. When the prediction of the peak period is inaccurate and a new peak period appears, send peak-shifting control data to the adjustable load unit.

[0061] In step S322, the continuous duration of the load exceeding the load threshold can be recorded in real time through the monitoring system. For example, a timer can be set to start timing when the load exceeds the load threshold and stop timing until the load is lower than the threshold.

[0062] It should be noted that when the second load rate is less than the load threshold or the peak duration is less than the duration threshold, there is no need to send peak-shifting control data to the adjustable load unit.

[0063] Through the peak-shifting control data, the adjustable load unit can be guided to reduce electricity consumption during the load peak period and increase electricity consumption during the non-peak period, thereby effectively balancing the supply and demand relationship of the power system.

[0064]

Sixth Embodiment

[0065] In step S510, when the adjustable load unit receives the peak-shaving control data, generally there are two possible situations as follows. The first: controlling the electrical equipment according to the peak-shaving control data and the production plan. The second: not controlling the electrical equipment. When the adjustable load unit controls the electrical equipment, set the subsequent restart time and the duration after restart of the controlled electrical equipment according to the production plan, and generate a control plan.

[0066] In step S530, usually, when the adjustable equipment restarts and runs during the non-peak period, record the adjustable equipment as a restart equipment, and obtain the increased power consumption in the future through the power of the restart equipment.

[0067] It should be noted that when the control plan changes, the new control plan needs to be sent to the control platform.

[0068] The generation of the control plan helps the control platform to accurately and timely grasp the power consumption reduced due to equipment control. The control platform automatically performs relevant calculations and analyses according to the control plan, reducing manual intervention and improving the processing efficiency and accuracy.

[0069]

Seventh Embodiment

[0070] In step S610, through the historical power consumption, use the load forecasting model to obtain the future power consumption, compare the sum of the increased power consumption in the future and the future power consumption with the peak threshold, and judge whether there is a situation exceeding the peak threshold during the non-peak period.

[0071] In step S620, usually, when the power of the devices restarted simultaneously during off-peak hours is relatively large, there may be a situation where the peak threshold is exceeded. In this case, generally, there are the following two options. First, when the reduced power is greater than the target reduction, sort the priorities of the control plans, and screen out the adjustable load units that do not require power control. Second, when the reduced power is greater than or equal to the target reduction, screen the control plans according to the target increase and the increased power, and screen out the adjustable load units that need to change the restart time. Generate an implementation plan based on the screened results.

[0072] It should be noted that when there is no situation where the peak threshold is exceeded, send a statement to the adjustable load unit, informing the adjustable load unit to control the electrical equipment according to the control plan.

[0073] By analyzing the increased power, historical power consumption, and peak threshold, it is possible to accurately judge whether there is a situation where the peak threshold is exceeded during off-peak hours, and accordingly determine the target increase and target reduction. By real-time monitoring and dynamically adjusting the peak-shifting control plan, it is possible to effectively avoid the situation of grid load overload, contribute to enhancing the stability of grid operation, reduce the occurrence of power outages, and ensure the reliability of power supply.

[0074]

Eighth Embodiment

[0075] In step S632, when the real-time power consumption after control is not greater than the peak threshold, or the continuous duration greater than the peak threshold is less than the duration threshold, it can be considered that the implementation situation meets the expectation. When the implementation situation meets the expectation, send a statement to the adjustable load unit, informing the adjustable load unit to control the electrical equipment according to the implementation plan. When the implementation situation does not meet the expectation, the control platform re-sends the peak-shifting control data to the adjustable load unit.

[0076] By obtaining the real-time power consumption of the target area, it is possible to monitor the implementation of the peak-shifting control measures in real time, ensure the dynamic grasp of the grid operation status, and be able to discover problems in time and take measures.

[0077]

Ninth Embodiment

[0078] Although the present invention is disclosed as above, the present invention is not limited thereto. Any person skilled in the art can make various changes and modifications without departing from the spirit and scope of the present invention. Therefore, the protection scope of the present invention should be subject to the scope defined by the claims.

Claims

1. A method for self - balancing of distribution network peak - shaving based on blockchain technology, characterized in that, The distribution network peak shaving self - balancing method includes: Determine the peak power consumption period of the target area according to the power consumption situation and distribution network capacity of the target area; Obtain the peak power consumption of each electricity - consuming unit in the target area during the peak power consumption period, and obtain adjustable load units according to the peak power consumption and the unit type of the electricity - consuming unit; Obtain the real - time power consumption of the target area during the peak power consumption period, and the control platform sends peak shaving control data to the adjustable load units according to the real - time power consumption; The adjustable load units control the electrical equipment according to the peak shaving control data and feedback the control plan to the control platform; The control platform calculates the reduced power consumption of the real - time power consumption and the increased power consumption of future power consumption according to the control plan; Screen the control plan according to the reduced power consumption and the increased power consumption to obtain an implementation plan, feedback the implementation plan to the adjustable load units, and upload the corresponding peak shaving control data according to the implementation plan.

2. The method for peak load shifting and self - balancing in a distribution network according to claim 1, wherein, The step of determining the peak power consumption period of the target area according to the power consumption situation and distribution network capacity of the target area specifically includes: Obtain the historical power consumption of the target area, calculate the ratio of the historical power consumption to the distribution network capacity to obtain the first load factor; Compare the first load factor with the peak threshold to obtain the peak power consumption period corresponding to the target area.

3. The method for self - balancing of peak - load shifting in the distribution network according to claim 2, wherein The step of obtaining the peak power consumption of each electricity - consuming unit in the target area during the peak power consumption period and obtaining adjustable load units according to the peak power consumption and the unit type of the electricity - consuming unit specifically includes: Obtain the peak power consumption of each electricity - consuming unit during the peak power consumption period, and obtain the load units to be adjusted according to the peak power consumption and the power consumption threshold; Judge whether there are electrical equipment that can perform peak shaving power consumption in the load units to be adjusted according to the unit type of the load units to be adjusted; When there are electrical equipment that can perform peak shaving power consumption in the load units to be adjusted, record the load units to be adjusted as the adjustable load units.

4. The method for self - balancing of peak - load shifting in a distribution network according to claim 3, wherein, The step of obtaining the real - time power consumption of the target area during the peak power consumption period, and the control platform sends peak shaving control data to the adjustable load units according to the real - time power consumption specifically includes: Record the ratio of the real - time power consumption to the distribution network capacity as the second load factor; Judge whether to send the peak shaving control data to the adjustable load units according to the second load factor, the load threshold, and the duration threshold.

5. The method for self-balancing of peak load shifting in distribution network according to claim 4, wherein The step of obtaining the peak shaving control data according to the second load factor, the load threshold, and the duration threshold specifically includes: When the second load factor is greater than or equal to the load threshold, send the peak shaving control data to the adjustable load units; Count the peak duration when the second load factor is continuously greater than the peak threshold; When the peak duration is greater than or equal to the duration threshold, send the peak shaving control data to the adjustable load units.

6. The distribution network peak-shifting self-balancing method according to claim 5, wherein, The step of the control platform calculating the reduced power consumption of the real - time power consumption and the increased power consumption of future power consumption according to the control plan specifically includes: When the adjustable load units control the electrical equipment, send the control plan to the control platform; The control platform obtains the electrical equipment to be shut down by the adjustable load unit according to the control plan, which is denoted as the adjustable equipment, and calculates the reduced power consumption of the real-time power consumption according to the adjustable equipment; The control platform obtains the restart time of each adjustable equipment according to the control plan, and denotes the restarted adjustable equipment as the restart equipment, and calculates the increased power consumption of the future power consumption according to the restart equipment and the restart time.

7. The distribution network peak-shifting self-balancing method according to claim 6, characterized in that, The control plan is screened according to the reduced power consumption and the increased power consumption to obtain an implementation plan, and the implementation plan is fed back to the adjustable load unit, and the corresponding peak-shaving control data is uploaded according to the implementation plan, specifically including: Judging whether there is a situation exceeding the peak threshold during the off-peak period according to the increased power consumption, the historical power consumption and the peak threshold; If so, determine the power consumption that can be increased during the off-peak period according to the historical power consumption and the peak threshold, which is denoted as the target increment, and obtain the target reduced power consumption according to the real-time power consumption and the peak threshold, which is denoted as the target reduction; Screen the control plan according to the target increment and the target reduction to obtain the implementation plan; Feed back the implementation plan to the adjustable load unit, and upload the corresponding peak-shaving control data according to the implementation plan.

8. The method for self-balancing of peak load shifting in distribution network according to claim 7, characterized in that The feedback of the implementation plan to the adjustable load unit and the uploading of the corresponding peak-shaving control data according to the implementation plan specifically include: Obtain the real-time power consumption of the target area, and judge the implementation situation of the implementation plan according to the real-time power consumption; When the implementation situation meets the expectation, send a statement to the adjustable load unit; When the implementation situation does not meet the expectation, the control platform resends the peak-shaving control data to the adjustable load unit.

9. A self-balancing system based on blockchain technology, characterized in that, As described in any one of claims 1 to 8, the distribution network peak-shaving self-balancing method is applied to the self-balancing system, and the self-balancing system includes: A data acquisition module for acquiring the real-time power consumption; A data communication module for the control platform to send the peak-shaving control data to the adjustable load unit and for the adjustable load unit to feedback the control plan to the control platform; A data calculation module for calculating the reduced power consumption and the increased power consumption; A data analysis module for screening the control plan.

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