Energy management system and management method for intelligent building

Abstract

The invention discloses an energy management system and management method for an intelligent building, relates to the technical field of electric energy analysis and management, and solves the problems that in electric energy management of the intelligent building, management time periods adapted to own characteristics of different intelligent buildings are neglected, and in management of electric energy according to the management time periods, the management time periods are neglected. And adaptive discharge operation is difficult to carry out on different areas. According to the method, the dynamic time periods and the management areas of the intelligent building are obtained, the electricity consumption characteristic values of the management areas in the dynamic time periods are obtained, the standard electricity consumption of the management areas in the next dynamic time period is obtained based on the electricity consumption characteristic values, and the standard electricity consumption is summed to obtain the standard total electricity consumption of the intelligent building; obtaining important factors of each management area, sending a discharge instruction based on the standard total power consumption, and performing discharge operation on each management area based on the discharge instruction and the important factors; electric energy distribution can be flexibly controlled, and the overall electric energy utilization efficiency of the intelligent building is improved.

Description

Technical Field

[0001] The present invention belongs to the field of intelligent building management, relates to electric energy analysis and management technology, and specifically is an energy management system and management method for intelligent buildings. Background Art

[0002] With the growth of the global population and economic development, energy demand continues to increase, especially electricity demand. Modern buildings consume a lot of electricity, and with the improvement of people's quality of life, the requirements for building comfort are getting higher and higher, which leads to the continuous growth of building electricity consumption. Traditional energy management methods mainly rely on manual operation or simple automation systems, which are difficult to achieve precise control and optimized management. With the development of technologies such as the Internet of Things and big data, more technical support is provided for the energy management system of smart buildings. These technologies can realize real-time monitoring and data collection of various energy equipment, optimize energy use through data analysis, and achieve efficient energy management and conservation.

[0003] At present, most energy management systems and management methods for smart buildings ignore the fact that different smart buildings have management time periods that adapt to their own characteristics in the electricity management of smart buildings. They only manage smart buildings according to manually set or fixed time periods, which will lead to rigidity in the setting of management time periods and may increase the cost of data analysis and energy management. At the same time, most energy management systems and management methods for smart buildings manage electricity according to management time periods, which makes it difficult to perform adaptive discharge operations on different areas, and it is difficult to ensure the stability of electricity consumption in important areas and the flexibility of electricity consumption in non-important areas, which reduces the practicality of the system.

[0004] Therefore, the present invention discloses an energy management system and a management method for intelligent buildings, which are used to solve the above technical problems. Summary of the invention

[0005] The present invention aims to solve at least one of the technical problems existing in the prior art; to this end, the present invention proposes an energy management system and management method for intelligent buildings, which are used to solve the technical problems that in the electric energy management of intelligent buildings, different intelligent buildings are ignored to have management time periods adapted to their own characteristics, and it is difficult to perform adaptive discharge operations on different areas when managing electric energy according to the management time periods. The present invention obtains the dynamic time periods and management areas of the intelligent building, obtains the characteristic value of power consumption of each management area in each dynamic time period, obtains the standard power consumption of each management area in the next dynamic time period based on the power consumption characteristic value, and sums the standard power consumption to obtain the standard total power consumption of the intelligent building; obtains the important factors of each management area, issues a discharge instruction based on the standard total power consumption, and performs a discharge operation on each management area based on the discharge instruction and the important factors to solve the above problems.

[0006] To achieve the above-mentioned object, a first aspect of the present invention provides an energy management system for intelligent buildings, comprising: a data collection module, and an intelligent planning module, an energy management module and a database connected thereto;

[0007] The intelligent planning module is used to plan a day into several dynamic time periods and divide the intelligent building into several management areas;

[0008] The data collection module is used to collect the power consumption of different management areas in each dynamic period;

[0009] The energy management module is used to obtain the characteristic value of power consumption of each management area in each dynamic time period, obtain the standard power consumption of each management area in the next dynamic time period based on the characteristic value of power consumption, sum up the standard power consumption of each management area to obtain the standard total power consumption of the intelligent building in the next dynamic time period; obtain the important factors of each management area, issue a discharge instruction based on the standard total power consumption, and perform a discharge operation on each management area based on the discharge instruction and the important factors.

[0010] Preferably, the planning of a day into several dynamic time periods includes:

[0011] A1: Extract the historical power consumption of the current intelligent building in each hour from the database, calculate the average value of the historical power consumption of each hour to obtain the reference power consumption CLi of each hour, and obtain the dynamic duration DSi of each hour based on the formula DSi=BS×BL / CLi; where BS is the manually set standard duration, BL is the percentile value of the reference power consumption CLi of each hour, and the percentile of the percentile value is obtained by manual setting; i is the hour sequence number, and the value of i is [1,24];

[0012] A2: Determine whether the dynamic duration DSi is greater than the duration protection value 1; if yes, use the value of the duration protection value 1 to update the dynamic duration DSi; if no, jump to A3; wherein the duration protection value 1 and the duration protection value 2 are both obtained through experience, and the duration protection value 1 is greater than the duration protection value 2;

[0013] A3: Determine whether the dynamic duration DSi is less than the duration protection value 2; if yes, update the dynamic duration DSi using the value of the duration protection value 2; if no, update the dynamic duration DSi by adding zero;

[0014] A4: Starting from the first hour, use the updated dynamic duration DS1 to divide the first hour into several dynamic time periods, and determine whether the dynamic time period of the first hour can be completely divided; if yes, use the updated dynamic duration DS2 to divide the second hour into dynamic time periods; if no, use the start time of the incomplete dynamic time period of the first hour as the start time of the second hour, and use the updated dynamic duration DS2 to divide the second hour into dynamic time periods; wherein, the incomplete dynamic time period is a dynamic time period whose duration is less than the corresponding dynamic duration DSi;

[0015] A5: Use the updated dynamic duration DSi to divide the i-th hour into several dynamic time periods, and determine whether the dynamic time period of the i-th hour can be completely divided; if yes, use the updated dynamic duration DSi+1 to divide the i+1-th hour into dynamic time periods; if no, use the start time of the incomplete dynamic time period of the i-th hour as the start time of the i+1-th hour, and use the updated dynamic duration DSi+1 to divide the i+1-th hour into dynamic time periods.

[0016] It is worth noting that when the present invention manages the electric energy of intelligent buildings, when setting the time period for electric energy management, it is not set according to a fixed time period, but is personalized according to the current electricity usage characteristics of the intelligent building. In this way, the electric energy management time period can be dynamically set according to the actual electricity usage situation, and a management time period that is more suitable for the current intelligent building can be set, thereby improving the accuracy of management and the flexibility of the system.

[0017] Preferably, the intelligent building is divided into several management areas, including:

[0018] A number of manually set fixed areas are extracted from the database, and each area separated by the fixed areas in the intelligent building is marked as a control area;

[0019] Obtain the average ground area PDM of several fixed areas, obtain the ground area of ​​each control area in turn, and determine whether the ground area exceeds the average ground area PDM; if yes, mark the current control area as a management area GQj; if no, mark the current control area as a decomposed area; wherein j is the serial number of the management area;

[0020] Obtain the ground area FDM of the decomposed area in turn, based on the formula Get the decomposition number FL, and evenly divide the decomposition area into FL management areas GQj; among them, is the rounding symbol;

[0021] Each fixed area is marked as a management area GQj, all management areas GQj are extracted, and the management areas GQj are sorted based on the route distance from the center point of the management area GQj to the set position.

[0022] It is worth noting that the present invention does not conduct an overall data analysis of the intelligent building, but plans the intelligent building into several management areas and conducts separate data analysis on the management areas. This is because different areas may have different usage requirements and functions, and zoning management can make data analysis more personalized and accurate, thereby improving management efficiency.

[0023] Preferably, the collecting of power consumption of different management areas in each dynamic time period includes:

[0024] The total power consumption of different management areas in each dynamic period is obtained through a smart meter, the total power consumption is marked as the power consumption of the corresponding management area in the corresponding dynamic period, and the power consumption is stored in a database.

[0025] It is worth noting that the smart building is divided into zones to obtain information. This can avoid the impact of changes in electricity consumption in a certain area on the entire area. For example, if overtime or special circumstances in a certain area cause changes in electricity consumption in that area within an hour after get off work, at this time only the changed electricity consumption will serve the subsequent analysis of the current area, which can reduce the errors caused by analyzing data fluctuations of the entire smart building.

[0026] Preferably, the obtaining of the characteristic value of power consumption of each management area in each dynamic time period includes:

[0027] Extracting management areas in sequence based on the sequence number j, and dividing the power consumption in the extracted historical data of the management areas into a number of power groups according to dynamic time periods;

[0028] Extract the power groups in sequence, obtain the variance of the power consumption in the extracted power groups, and judge whether the variance is greater than the corresponding variance threshold; if yes, remove the power consumption in the power group that differs the most from the average power consumption of the power group, and re-judge the variance until the variance of the power group is less than the corresponding variance threshold, and retain the remaining power consumption of the power group; if no, retain the remaining power consumption of the power group; wherein the variance threshold is obtained through experience;

[0029] The minimum value XZ, the maximum value DZ and the mode SZ of the remaining power consumption of the power group are extracted, and the power consumption characteristic value DT of the power group is obtained based on the formula DT = (α1×XZ+α2×DZ+SZ) / 2; wherein α1 and α2 are both proportional adjustment coefficients greater than 0, and α1<α2, α1+α2=1.

[0030] It is worth noting that before obtaining the characteristic values ​​of electricity consumption of each management area in each dynamic time period, the present invention removes the fluctuation values ​​of the electricity consumption of each management area in each dynamic time period, and uses variance judgment to remove the abnormal values ​​in each electricity group that have a large impact on the error of calculating the characteristic values ​​of electricity consumption, so as to obtain a set of stable data. This can improve the accuracy of data analysis and provide data support for the subsequent calculation of the standard electricity consumption of each management area in the next dynamic time period.

[0031] Preferably, obtaining the standard power consumption of each management area in the next dynamic period based on the power consumption characteristic value includes:

[0032] Extract each management area in turn, obtain the average value of the power consumption characteristic value of the management area in n dynamic time periods before the current time, and mark the average value as the target characteristic value MT; wherein n is obtained by manual setting;

[0033] Obtain an average value of power consumption obtained in the management area during the n dynamic time periods before the current time, and mark the average value as the target power consumption MDL;

[0034] The power consumption characteristic value NDT of the management area in the next dynamic period is extracted, and the standard power consumption BDL of the current management area in the next dynamic period is obtained based on the formula BDL=β×MDL×NDT / MT; where β is the error adjustment coefficient, and the value range of β is (0,2).

[0035] It is worth noting that the standard total electricity consumption of the intelligent building in the next dynamic time period obtained by the present invention is obtained by summing up the standard electricity consumption of each management area. Since the electricity consumption of each management area is different in different time periods, there may be only one management area with electricity consumption in a certain time period. Therefore, each management area is analyzed separately, and the standard total electricity consumption obtained by adding up the final results has a smaller error than the electricity consumption obtained for the intelligent building as a whole, thereby improving the accuracy of system data analysis.

[0036] Preferably, the obtaining of important factors of each management area includes:

[0037] The preliminary important factors CZ set manually by the management areas are extracted from the database in turn, and the average daily number of people RS and the average daily electricity consumption RYD of the management areas are extracted. The important factor ZY of each management area is obtained based on the formula ZY=CZ+δ1×exp(RS / PRS)+δ2×exp(RYD / PRYD); wherein δ1 and δ2 are amplitude adjustment coefficients, and the value ranges of δ1 and δ2 are both (0,2); PRS is the average value of the average daily number of people RS in each management area, and PRYD is the average value of the average daily electricity consumption RYD in each management area.

[0038] It is worth noting that the present invention first obtains the important factors according to the importance of each management area, which is an analysis indicator for the subsequent discharge operation of each management area. This helps to allocate power resources more reasonably, concentrate limited resources and energy on areas with higher importance, avoid waste of power resources, and ensure that key areas receive adequate attention and maintenance.

[0039] Preferably, the step of issuing a discharge instruction based on the standard total power consumption includes:

[0040] Extract the standard total power consumption and determine whether the standard total power consumption exceeds the maximum power supply; if yes, issue discharge instruction one; if no, issue discharge instruction two; wherein the maximum power supply is the maximum power supply obtained by the current intelligent building through the power grid in the next dynamic time period; the discharge instruction includes discharge instruction one and discharge instruction two.

[0041] Preferably, the discharging operation on each management area based on the discharging instruction and the important factor includes:

[0042] B1: Receive a discharge instruction and determine whether the received discharge instruction is discharge instruction 1; if yes, jump to B2; if no, do nothing;

[0043] B2: Extract the important factor ZY of the management area, and obtain the standardized important index BYZ of the current management area based on the formula BYZ=(ZY-PZY) / PZY; determine whether the standardized important index BYZ is greater than the important index 1; if yes, mark the current management area as a first-level management area; if no, jump to B3; wherein PZY is the average value of the important factor ZY of each management area; the important index 1 and the important index 2 are both obtained by manual setting, and the important index 1 is greater than the important index 2;

[0044] B3: Determine whether the standardized important index BYZ is less than the important index 2; if yes, mark the current management area as a third-level management area; if no, mark the current management area as a second-level management area;

[0045] B4: Mark the total standard electricity consumption required by the first-level management area as the first-level electricity consumption, and determine whether the first-level electricity consumption exceeds the maximum power supply; if yes, jump to B5; if no, jump to B6;

[0046] B5: The management area corresponding to the smallest standardized important indicator BYZ in the first-level management area is downgraded to the second-level management area in sequence, until the total power consumption of the first level does not exceed the maximum power supply, then the operation of downgrading the first-level management area to the second-level management area is stopped, and the first-level management area is powered by the grid, and the second-level and third-level management areas are powered by energy storage batteries;

[0047] B6: Calculate the difference between the maximum power supply and the first-level total power consumption to obtain the first-level spare power supply, mark the standard total power consumption required by the second-level management area as the second-level total power consumption, and determine whether the second-level total power consumption exceeds the first-level spare power supply; if yes, calculate the difference between the second-level total power consumption and the first-level spare power supply to obtain the second-level energy storage battery power supply, obtain the ratio of the first-level spare power supply to the second-level energy storage battery power supply, and based on the ratio, supply power to the second-level management area through the power grid and the energy storage battery, and supply power to the third-level management area through the energy storage battery; if no, supply power to the second-level management area through the power grid, and jump to B7;

[0048] B7: Calculate the difference between the first-level spare power supply and the second-level total power consumption to obtain the second-level spare power supply, mark the standard total power consumption required for the third-level management area as the third-level total power consumption, and determine whether the third-level total power consumption exceeds the second-level spare power supply; if yes, calculate the difference between the third-level total power consumption and the second-level spare power supply to obtain the third-level energy storage battery power supply, obtain the ratio of the second-level spare power supply to the third-level energy storage battery power supply, and supply power to the third-level management area through the power grid and the energy storage battery based on the ratio; if no, supply power to the third-level management area through the power grid.

[0049] It is worth noting that the present invention does not directly use important factors when classifying management areas, but rather calculates standardized important indicators based on important factors. The obtained standardized important indicators can express the important conditions of each management area unique to the current building. Since the important factors of different intelligent buildings are of different sizes, if the important factors are directly used to divide the levels of each management area, it is necessary to set the important indicators one and two of each intelligent building according to the characteristics of the building, which will result in a large amount of data resource analysis. However, by standardizing important indicators, the important indicators one and two of different intelligent buildings can be set to the same value, so that different intelligent building data can be analyzed using the same set of standards, reducing the situation where the system needs to set important indicators one and two for each intelligent building, thereby improving the adaptability of the system.

[0050] It is worth noting that when the total standard electricity consumption required in the first-level management area exceeds the maximum power supply, the present invention does not supply electricity to the first-level management area through proportional power supply, but downgrades the management area corresponding to the smallest standardized important indicator in the first-level management area to the second-level management area until the first-level electricity consumption does not exceed the maximum power supply, then stops downgrading the first-level management area to the second-level management area, and then supplies electricity to the first-level management area with the power grid, and supplies electricity to the second-level and third-level management areas with energy storage batteries; this can maximize the stability of power supply to important areas with high standardized important indicators, and reduce the risk of power failures or operation interruptions in important areas with high standardized important indicators due to unstable proportional power supply.

[0051] A second aspect of the present invention provides an energy management method for an intelligent building, comprising the following steps:

[0052] S1: Plan a day into several dynamic time periods and divide the intelligent building into several management areas;

[0053] S2: Collect the power consumption of different management areas in each dynamic period;

[0054] S3: Obtain the characteristic value of electricity consumption of each management area in each dynamic time period, obtain the standard electricity consumption of each management area in the next dynamic time period based on the characteristic value of electricity consumption, sum up the standard electricity consumption of each management area to obtain the standard total electricity consumption of the intelligent building in the next dynamic time period; obtain the important factors of each management area, issue a discharge instruction based on the standard total electricity consumption, and perform a discharge operation on each management area based on the discharge instruction and the important factors.

[0055] Compared with the prior art, the present invention has the following beneficial effects:

[0056] 1. The present invention obtains the dynamic time period and management area of ​​the intelligent building, obtains the characteristic value of power consumption of each management area in each dynamic time period, obtains the standard power consumption of each management area in the next dynamic time period based on the characteristic value of power consumption, and sums the standard power consumption to obtain the standard total power consumption of the intelligent building; obtains the important factors of each management area, issues a discharge instruction based on the standard total power consumption, and performs a discharge operation on each management area based on the discharge instruction and the important factors, thereby solving the technical problems of ignoring the fact that different intelligent buildings have management time periods adapted to their own characteristics in the power management of intelligent buildings, and being difficult to perform adaptive discharge operations on different areas when managing power according to the management time period; the present invention can flexibly control power distribution, thereby improving the overall power utilization efficiency of intelligent buildings.

[0057] 2. The present invention adopts a flexible time period setting method for intelligent building power management. It no longer follows a fixed setting mode, but customizes the configuration according to the current power usage characteristics of the intelligent building. This approach allows the power management time period to be dynamically set according to the actual power usage mode, thereby ensuring that the set management period matches the real-time needs of the intelligent building, effectively improving the accuracy of management and the adaptability of the system.

[0058] 3. The present invention adopts a standardized method for classifying management areas. It does not rely directly on important factors, but calculates standardized key indicators through important factors. These standardized indicators can accurately reflect the relative importance of each management area in a specific building. Due to the differences in important factors of different intelligent buildings, if the management area level is directly divided by important factors, it is necessary to set important indicators one and two for each intelligent building, which will lead to a lot of data analysis and configuration work. On the contrary, by adopting standardized indicators, important indicators one and two of different buildings can be unified into the same value, thereby allowing the use of unified standards to analyze the data of various intelligent buildings. This method reduces the need for personalized setting of important indicators and enhances the versatility and adaptability of the system. BRIEF DESCRIPTION OF THE DRAWINGS

[0059] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. 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 paying creative work.

[0060] Figure 1 It is a schematic diagram of the operation steps of the present invention;

[0061] Figure 2 It is a schematic diagram of the system module of the present invention;

[0062] Figure 3 The figure is a schematic diagram of the operation steps for obtaining a dynamic time period according to the present invention. DETAILED DESCRIPTION

[0063] The technical solution of the present invention will be clearly and completely described below in conjunction with the embodiments. Obviously, the described embodiments are only part of the embodiments of the present invention, rather than all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0064] See also Figure 1-Figure 2 , a first aspect of the present invention provides an energy management system for intelligent buildings, comprising: a data collection module, and an intelligent planning module, an energy management module and a database connected thereto;

[0065] Intelligent planning module: used to plan a day into several dynamic time periods and divide the intelligent building into several management areas;

[0066] Data collection module: used to collect the power consumption of different management areas in each dynamic period;

[0067] Energy management module: used to obtain the characteristic value of electricity consumption of each management area in each dynamic time period, obtain the standard electricity consumption of each management area in the next dynamic time period based on the characteristic value of electricity consumption, sum up the standard electricity consumption of each management area to obtain the standard total electricity consumption of the intelligent building in the next dynamic time period; obtain the important factors of each management area, issue a discharge instruction based on the standard total electricity consumption, and perform discharge operations on each management area based on the discharge instruction and important factors.

[0068] See also Figure 3 , in this application, a day is planned into several dynamic time periods, including:

[0069] A1: Extract the historical power consumption of the current intelligent building in each hour from the database, calculate the average value of the historical power consumption of each hour to obtain the reference power consumption CLi of each hour, and obtain the dynamic duration DSi of each hour based on the formula DSi=BS×BL / CLi; where BS is the manually set standard duration, BL is the percentile value of the reference power consumption CLi of each hour, and the percentile of the percentile value is obtained by manual setting; i is the hour sequence number, and the value of i is [1,24];

[0070] A2: Determine whether the dynamic duration DSi is greater than the duration protection value 1; if yes, use the value of the duration protection value 1 to update the dynamic duration DSi; if no, jump to A3; wherein the duration protection value 1 and the duration protection value 2 are both obtained through experience, and the duration protection value 1 is greater than the duration protection value 2;

[0071] A3: Determine whether the dynamic duration DSi is less than the duration protection value 2; if yes, use the value of the duration protection value 2 to update the dynamic duration DSi; if no, add zero to the dynamic duration DSi for update;

[0072] A4: Starting from the first hour, use the updated dynamic duration DS1 to divide the first hour into several dynamic time periods, and determine whether the dynamic time period of the first hour can be completely divided; if yes, use the updated dynamic duration DS2 to divide the second hour into dynamic time periods; if no, use the start time of the incomplete dynamic time period of the first hour as the start time of the second hour, and use the updated dynamic duration DS2 to divide the second hour into dynamic time periods; wherein, the incomplete dynamic time period is a dynamic time period whose duration is less than the corresponding dynamic duration DSi;

[0073] A5: Use the updated dynamic duration DSi to divide the i-th hour into several dynamic time periods, and determine whether the dynamic time period of the i-th hour can be completely divided; if yes, use the updated dynamic duration DSi+1 to divide the i+1-th hour into dynamic time periods; if no, use the start time of the incomplete dynamic time period of the i-th hour as the start time of the i+1-th hour, and use the updated dynamic duration DSi+1 to divide the i+1-th hour into dynamic time periods.

[0074] It should be noted that, in this embodiment, BL is the percentile of the percentile value of the reference power consumption CLi of each hour, which is 62.5%. The specific method of obtaining BL is as follows:

[0075] Arrange the reference power consumption Cli from small to large, extract the reference power consumption Cli at 62.5% of the position, and mark the reference power consumption Cli at 62.5% as the percentile value BL of the reference power consumption CLi of each hour.

[0076] It should be noted that, if there is no reference power consumption Cli at the 62.5% position from small to large, the reference power consumption Cli closest to the 62.5% position is marked as the percentile value BL of the reference power consumption CLi of each hour.

[0077] It should be noted that it is determined whether the dynamic time period of the first hour can be completely divided; if yes, the updated dynamic time length DS2 is used to divide the dynamic time period of the second hour; if no, the start time of the incomplete dynamic time period of the first hour is used as the start time of the second hour, and the updated dynamic time length DS2 is used to divide the dynamic time period of the second hour. It can be understood as follows:

[0078] The time range for the first hour of the day is 0:00-1:00;

[0079] If the dynamic duration DS1 is 10 minutes, it can be completely divided into one hour, because 60 minutes divided by 10 minutes equals 6, which means that the first hour can be completely divided into 6 dynamic time periods, and the duration of each dynamic time period is 10 minutes; then the dynamic time periods of the first hour are 0:00-0:10, 0:10-0:20, 0:20-0:30, 0:30-0:40, 0:40-0:50, 0:50-1:00;

[0080] If the dynamic duration DS1 is 9 minutes, it cannot completely divide an hour, because 60 minutes divided by 9 minutes is approximately equal to 6.67. This means that the first hour cannot be completely divided into several dynamic time periods, but can only be divided into 6 dynamic time periods and one incomplete dynamic time period. The dynamic time periods of the first hour are 0:00-0:09, 0:09-0:18, 0:18-0:27, 0:27-0:36, 0:36-0:45, 0:45-0:54, and the incomplete dynamic time period of the first hour is 0:54-1:00. Therefore, the time range of the second hour is 0:54-2:00, and the updated dynamic duration DS2 is used to divide the second hour into dynamic time periods.

[0081] It should be noted that in step A5, when i is 24, after the 24th hour is divided into several dynamic time periods using the updated dynamic duration DS24, no subsequent judgment and division of the 25th hour into dynamic time periods are performed.

[0082] It should be noted that if the 24th hour cannot be completely divided into several dynamic time periods, the incomplete dynamic time period of the 24th hour will be regarded as the last dynamic time period of the day;

[0083] For example: the dynamic time period of the 23rd hour can be completely divided, and the dynamic duration DS24 of the 24th hour is 9 minutes, so the incomplete dynamic time period of the 24th hour is 23:54-24:00, and the last dynamic time period of the day is 23:54-24:00.

[0084] In this application, the intelligent building is divided into several management areas, including:

[0085] A number of manually set fixed areas are extracted from the database, and each area separated by the fixed areas in the intelligent building is marked as a control area;

[0086] Obtain the average ground area PDM of several fixed areas, obtain the ground area of ​​each control area in turn, and determine whether the ground area exceeds the average ground area PDM; if yes, mark the current control area as the management area GQj; if no, mark the current control area as the decomposition area; where j is the serial number of the management area;

[0087] Obtain the ground area FDM of the decomposed area in turn, based on the formula Get the decomposition number FL, and evenly divide the decomposition area into FL management areas GQj; among them, is the rounding symbol;

[0088] Each fixed area is marked as a management area GQj, all management areas GQj are extracted, and the management areas GQj are sorted based on the route distance from the center point of the management area GQj to the set position.

[0089] It should be noted that the fixed area is a relatively important area, or an area owned by the same property owner or the same user such as the same company or family.

[0090] It should be noted that the decomposed area is evenly divided into FL management areas GQj as follows: the division is performed based on equal areas, such as FL=2, and the decomposed area is evenly divided into 2 management areas GQj with equal areas.

[0091] It should be noted that the sorting is based on the route distance from the center point of the management area GQj to the set location, and the sorting is from small to large according to the route distance. The set location includes the entrance and exit of the intelligent building or the elevator entrance on the first floor of the intelligent building.

[0092] This application collects the electricity consumption of different management areas in each dynamic period, including:

[0093] The total power consumption of different management areas in each dynamic period is obtained through smart meters, the total power consumption is marked as the power consumption of the corresponding management area in the corresponding dynamic period, and the power consumption is stored in the database.

[0094] In this application, the power consumption characteristic values ​​of each management area in each dynamic period are obtained, including:

[0095] Extracting management areas in sequence based on the sequence number j, and dividing the power consumption in the extracted historical data of the management areas into a number of power groups according to dynamic time periods;

[0096] Extract the electricity groups in sequence, obtain the variance of the electricity consumption in the extracted electricity groups, and judge whether the variance is greater than the corresponding variance threshold; if yes, remove the electricity consumption in the electricity group that is most different from the average electricity consumption of the electricity group, and re-judge the variance until the variance of the electricity group is less than the corresponding variance threshold, and retain the remaining electricity consumption of the electricity group; if no, retain the remaining electricity consumption of the electricity group; wherein the variance threshold is obtained through experience;

[0097] The minimum value XZ, the maximum value DZ and the mode SZ of the remaining power consumption of the power group are extracted, and the power consumption characteristic value DT of the power group is obtained based on the formula DT = (α1×XZ+α2×DZ+SZ) / 2; wherein α1 and α2 are both proportional adjustment coefficients greater than 0, and α1<α2, α1+α2=1.

[0098] In this application, the standard power consumption of each management area in the next dynamic period is obtained based on the power consumption characteristic value, including:

[0099] Extract each management area in turn, obtain the average value of the power consumption characteristic value of the management area in n dynamic time periods before the current time, and mark the average value as the target characteristic value MT; wherein n is obtained by manual setting;

[0100] Obtain an average value of power consumption obtained in the management area during the n dynamic time periods before the current time, and mark the average value as the target power consumption MDL;

[0101] The power consumption characteristic value NDT of the management area in the next dynamic period is extracted, and the standard power consumption BDL of the current management area in the next dynamic period is obtained based on the formula BDL=β×MDL×NDT / MT; where β is the error adjustment coefficient, and the value range of β is (0,2).

[0102] It should be noted that the error adjustment coefficient β is obtained based on the characteristic values ​​of electricity consumption and the comprehensive discreteness of electricity consumption in the previous n dynamic time periods. The stronger the discreteness of a set of data, the greater the difference between the values ​​of the data set and the more violent the fluctuation. Therefore, the greater the characteristic values ​​of electricity consumption and the comprehensive discreteness of electricity consumption in the current n dynamic time periods, the larger the value of the error adjustment coefficient β, and the smaller the characteristic values ​​of electricity consumption and the comprehensive discreteness of electricity consumption in the current n dynamic time periods, the smaller the value of the error adjustment coefficient β.

[0103] It should be noted that the comprehensive discreteness is obtained by proportionally summing the discreteness of the power consumption characteristic values ​​of the first n dynamic time periods and the discreteness of the power consumption of the first n dynamic time periods.

[0104] Important factors for obtaining each management area in this application include:

[0105] The preliminary important factors CZ set manually by the management areas are extracted from the database in turn, and the average daily number of people RS and the average daily electricity consumption RYD of the management areas are extracted. The important factor ZY of each management area is obtained based on the formula ZY=CZ+δ1×exp(RS / PRS)+δ2×exp(RYD / PRYD); wherein δ1 and δ2 are amplitude adjustment coefficients, and the value ranges of δ1 and δ2 are both (0,2); PRS is the average value of the average daily number of people RS in each management area, and PRYD is the average value of the average daily electricity consumption RYD in each management area.

[0106] It should be noted that the preliminary importance factor CZ is used to identify those management areas that require special attention, such as data centers, server rooms, control centers, and other areas.

[0107] It should be noted that by customizing the preliminary important factor CZ, resource allocation and safety management can be carried out in a more targeted manner, thereby improving the intelligence level and overall performance of the building.

[0108] In this application, a discharge instruction is issued based on the standard total power consumption, including:

[0109] Extract the standard total power consumption and determine whether the standard total power consumption exceeds the maximum power supply; if yes, issue discharge instruction one; if not, issue discharge instruction two; wherein the maximum power supply is the maximum power supply obtained by the current intelligent building through the power grid in the next dynamic period; the discharge instructions include discharge instruction one and discharge instruction two.

[0110] In this application, discharge operations are performed on each management area based on discharge instructions and important factors, including:

[0111] B1: Receive a discharge instruction and determine whether the received discharge instruction is discharge instruction 1; if yes, jump to B2; if no, do nothing;

[0112] B2: Extract the important factor ZY of the management area, and obtain the standardized important index BYZ of the current management area based on the formula BYZ=(ZY-PZY) / PZY; determine whether the standardized important index BYZ is greater than the important index 1; if yes, mark the current management area as a first-level management area; if no, jump to B3; wherein PZY is the average value of the important factor ZY of each management area; the important index 1 and the important index 2 are both obtained by manual setting, and the important index 1 is greater than the important index 2;

[0113] B3: Determine whether the standardized important index BYZ is less than the important index 2; if yes, mark the current management area as the third-level management area; if no, mark the current management area as the second-level management area;

[0114] B4: Mark the total standard electricity consumption required by the first-level management area as the first-level electricity consumption, and determine whether the first-level electricity consumption exceeds the maximum power supply; if yes, jump to B5; if no, jump to B6;

[0115] B5: The management area corresponding to the smallest standardized important indicator BYZ in the first-level management area is downgraded to the second-level management area in sequence, until the total power consumption of the first level does not exceed the maximum power supply, then the operation of downgrading the first-level management area to the second-level management area is stopped, and the first-level management area is powered by the grid, and the second-level and third-level management areas are powered by energy storage batteries;

[0116] B6: Calculate the difference between the maximum power supply and the first-level total power consumption to obtain the first-level spare power supply, mark the standard total power consumption required by the second-level management area as the second-level total power consumption, and determine whether the second-level total power consumption exceeds the first-level spare power supply; if yes, calculate the difference between the second-level total power consumption and the first-level spare power supply to obtain the second-level energy storage battery power supply, obtain the ratio of the first-level spare power supply to the second-level energy storage battery power supply, and based on the ratio, supply power to the second-level management area through the power grid and the energy storage battery, and supply power to the third-level management area through the energy storage battery; if no, supply power to the second-level management area through the power grid, and jump to B7;

[0117] B7: Calculate the difference between the first-level spare power supply and the second-level total power consumption to obtain the second-level spare power supply, mark the standard total power consumption required for the third-level management area as the third-level total power consumption, and determine whether the third-level total power consumption exceeds the second-level spare power supply; if yes, calculate the difference between the third-level total power consumption and the second-level spare power supply to obtain the third-level energy storage battery power supply, obtain the ratio of the second-level spare power supply to the third-level energy storage battery power supply, and supply power to the third-level management area through the power grid and the energy storage battery based on the ratio; if no, supply power to the third-level management area through the power grid.

[0118] It should be noted that important indicator 1 and important indicator 2 are judgment thresholds used to distinguish the levels of management areas.

[0119] It should be noted that, based on the proportion value, the secondary management area or the tertiary management area is powered by the power grid and the energy storage battery. The power supply time can be divided according to the proportion value, and the power grid and the energy storage battery are powered by dividing the power supply time; or the power supply amount can be divided according to the proportion value, and the power grid and the energy storage battery are powered by dividing the power supply amount.

[0120] It should be noted that the difference between the maximum power supply and the total power consumption at level one is calculated to obtain the first-level spare power supply as follows: the first-level spare power supply is obtained by subtracting the total power consumption at level one from the maximum power supply.

[0121] It should be noted that the difference between the total secondary power consumption and the primary spare power supply is calculated to obtain the secondary energy storage battery power supply: the secondary energy storage battery power supply is obtained by subtracting the primary spare power supply from the total secondary power consumption.

[0122] It should be noted that the difference between the primary spare power supply and the secondary total power consumption is calculated to obtain the secondary spare power supply as follows: the secondary spare power supply is obtained by subtracting the secondary total power consumption from the primary spare power supply.

[0123] It should be noted that the power supply of the third-level energy storage battery is obtained by performing a difference calculation on the total power consumption of the third level and the spare power supply of the second level: the power supply of the third-level energy storage battery is obtained by subtracting the spare power supply of the second level from the total power consumption of the third level.

[0124] It should be noted that the power supply of the secondary energy storage battery is the power supply required by the energy storage battery in the secondary management area, and the power supply of the tertiary energy storage battery is the power supply required by the energy storage battery in the tertiary management area.

[0125] A second aspect of the present invention provides an energy management method for an intelligent building, comprising the following steps:

[0126] S1: Plan a day into several dynamic time periods and divide the intelligent building into several management areas;

[0127] S2: Collect the power consumption of different management areas in each dynamic period;

[0128] S3: Obtain the characteristic value of electricity consumption of each management area in each dynamic time period, obtain the standard electricity consumption of each management area in the next dynamic time period based on the characteristic value of electricity consumption, sum up the standard electricity consumption of each management area to obtain the standard total electricity consumption of the intelligent building in the next dynamic time period; obtain the important factors of each management area, issue a discharge instruction based on the standard total electricity consumption, and perform a discharge operation on each management area based on the discharge instruction and the important factors.

[0129] Part of the data in the above formula is calculated by removing the dimension and taking its numerical value. The formula is a formula closest to the actual situation obtained by software simulation of a large amount of collected data; the preset parameters and preset thresholds in the formula are set by technical personnel in this field according to actual conditions or obtained through simulation of a large amount of data.

[0130] Working principle of the present invention:

[0131] A day is planned into several dynamic time periods, and the intelligent building is divided into several management areas. In this step, the power management time period can be dynamically set according to the actual power consumption situation, and the management time period that is more suitable for the current intelligent building can be set to improve the accuracy of management and the flexibility of the system; the power consumption of different management areas in each dynamic time period is collected; the power consumption characteristic value of each management area in each dynamic time period is obtained, and the standard power consumption of each management area in the next dynamic time period is obtained based on the power consumption characteristic value, and the standard power consumption of each management area is summed to obtain the standard total power consumption of the intelligent building in the next dynamic time period. In this step, each management area is analyzed separately, and the standard total power consumption obtained by adding the final results is smaller than the error caused by the power consumption obtained by the intelligent building as a whole, which improves the accuracy of system data analysis; the important factors of each management area are obtained. The important factors in this step are an analysis indicator for subsequent discharge operations on each management area. This helps to allocate power resources more reasonably, and can concentrate limited resources and energy on more important areas to avoid waste of power resources, while ensuring that key areas are fully concerned and maintained; a discharge instruction is issued based on the standard total power consumption, and a discharge operation is performed on each management area based on the discharge instruction and the important factors.

[0132] The above embodiments are only used to illustrate the technical method of the present invention rather than to limit it. Although the present invention has been described in detail with reference to the preferred embodiments, those skilled in the art should understand that the technical method of the present invention may be modified or replaced by equivalents without departing from the spirit and scope of the technical method of the present invention.

Claims

1. An energy management system for smart buildings, characterized in that: include: Data collection module, and the connected intelligent planning module, energy management module and database; The intelligent planning module is used to plan a day into several dynamic time periods and divide the intelligent building into several management areas; The data collection module is used to collect the power consumption of different management areas in each dynamic period; The energy management module is used to obtain the power consumption characteristic value of each management area in each dynamic period, obtain the standard power consumption of each management area in the next dynamic period based on the power consumption characteristic value, and sum the standard power consumption of each management area to obtain the standard total power consumption of the intelligent building in the next dynamic period; Obtain important factors of each management area, issue a discharge instruction based on the standard total power consumption, and perform a discharge operation on each management area based on the discharge instruction and the important factors.

2. An energy management system for intelligent buildings according to claim 1, characterized in that: The day is planned into several dynamic time periods, including: A1: Extract the historical power consumption of the current intelligent building in each hour from the database, calculate the average value of the historical power consumption of each hour to obtain the reference power consumption CLi of each hour, and obtain the dynamic duration DSi of each hour based on the formula DSi=BS×BL / CLi; where BS is the standard duration, BL is the percentile value of the reference power consumption CLi of each hour; i is the hour sequence number, and the value of i is [1,24]; A2: Determine whether the dynamic duration DSi is greater than duration protection value 1; if yes, use the value of duration protection value 1 to update the dynamic duration DSi; if no, jump to A3; wherein duration protection value 1 is greater than duration protection value 2; A3: Determine whether the dynamic duration DSi is less than the duration protection value 2; if yes, update the dynamic duration DSi using the value of the duration protection value 2; if no, update the dynamic duration DSi by adding zero; A4: Starting from the first hour, use the updated dynamic duration DS1 to divide the first hour into several dynamic time periods, and determine whether the dynamic time period of the first hour can be completely divided; if yes, use the updated dynamic duration DS2 to divide the second hour into dynamic time periods; if no, use the start time of the incomplete dynamic time period of the first hour as the start time of the second hour, and use the updated dynamic duration DS2 to divide the second hour into dynamic time periods; wherein, the incomplete dynamic time period is a dynamic time period whose duration is less than the corresponding dynamic duration DSi; A5: Use the updated dynamic duration DSi to divide the i-th hour into several dynamic time periods, and determine whether the dynamic time period of the i-th hour can be completely divided; if yes, use the updated dynamic duration DSi+1 to divide the i+1-th hour into dynamic time periods; if no, use the start time of the incomplete dynamic time period of the i-th hour as the start time of the i+1-th hour, and use the updated dynamic duration DSi+1 to divide the i+1-th hour into dynamic time periods.

3. An energy management system for intelligent buildings according to claim 1, characterized in that: The intelligent building is divided into several management areas, including: A number of manually set fixed areas are extracted from the database, and each area separated by the fixed areas in the intelligent building is marked as a control area; Obtain the average ground area PDM of several fixed areas, obtain the ground area of ​​each control area in turn, and determine whether the ground area exceeds the average ground area PDM; if yes, mark the current control area as a management area GQj; if no, mark the current control area as a decomposed area; wherein j is the serial number of the management area; Obtain the ground area FDM of the decomposed area in turn, based on the formula Get the decomposition number FL, and evenly divide the decomposition area into FL management areas GQj; among them, is the rounding symbol; Each fixed area is marked as a management area GQj, all management areas GQj are extracted, and the management areas GQj are sorted based on the route distance from the center point of the management area GQj to the set position.

4. The energy management system for intelligent buildings according to claim 1, characterized in that: The collecting of power consumption of different management areas in each dynamic period includes: The total power consumption of different management areas in each dynamic period is obtained through a smart meter, the total power consumption is marked as the power consumption of the corresponding management area in the corresponding dynamic period, and the power consumption is stored in a database.

5. The energy management system for intelligent buildings according to claim 1, characterized in that: The obtaining of the characteristic value of power consumption of each management area in each dynamic time period includes: Extracting management areas in sequence based on the sequence number j, and dividing the power consumption in the extracted historical data of the management areas into a number of power groups according to dynamic time periods; Extract the power groups in sequence, obtain the variance of the power consumption in the extracted power groups, and judge whether the variance is greater than the corresponding variance threshold; if yes, remove the power consumption in the power group that differs the most from the average power consumption of the power group, and re-judge the variance until the variance of the power group is less than the corresponding variance threshold, and retain the remaining power consumption of the power group; if no, retain the remaining power consumption of the power group; The minimum value XZ, the maximum value DZ and the mode SZ of the remaining power consumption of the power group are extracted, and the power consumption characteristic value DT of the power group is obtained based on the formula DT = (α1×XZ+α2×DZ+SZ) / 2; wherein α1 and α2 are both proportional adjustment coefficients greater than 0, and α1<α2, α1+α2=1.

6. An energy management system for intelligent buildings according to claim 5, characterized in that: The method of obtaining the standard power consumption of each management area in the next dynamic period based on the power consumption characteristic value includes: Extract each management area in turn, obtain the average value of the power consumption characteristic value of the management area in n dynamic time periods before the current time, and mark the average value as the target characteristic value MT; Obtain an average value of power consumption obtained in the management area during the n dynamic time periods before the current time, and mark the average value as the target power consumption MDL; The power consumption characteristic value NDT of the management area in the next dynamic period is extracted, and the standard power consumption BDL of the current management area in the next dynamic period is obtained based on the formula BDL=β×MDL×NDT / MT; where β is the error adjustment coefficient, and the value range of β is (0,2).

7. The energy management system for intelligent buildings according to claim 1, characterized in that: The important factors of obtaining each management area include: The preliminary important factors CZ set manually by the management areas are extracted from the database in turn, and the average daily number of people RS and the average daily electricity consumption RYD of the management areas are extracted. The important factor ZY of each management area is obtained based on the formula ZY=CZ+δ1×exp(RS / PRS)+δ2×exp(RYD / PRYD); wherein δ1 and δ2 are amplitude adjustment coefficients, and the value ranges of δ1 and δ2 are both (0,2); PRS is the average value of the average daily number of people RS in each management area, and PRYD is the average value of the average daily electricity consumption RYD in each management area.

8. An energy management system for intelligent buildings according to claim 7, characterized in that: The issuing of a discharge instruction based on the standard total power consumption includes: Extract the standard total power consumption and determine whether the standard total power consumption exceeds the maximum power supply; if yes, issue discharge instruction one; if no, issue discharge instruction two; wherein the maximum power supply is the maximum power supply obtained by the current intelligent building through the power grid in the next dynamic time period; the discharge instruction includes discharge instruction one and discharge instruction two.

9. An energy management system for intelligent buildings according to claim 8, characterized in that: The discharging operation on each management area based on the discharging instruction and the important factor includes: B1: Receive a discharge instruction and determine whether the received discharge instruction is discharge instruction 1; if yes, jump to B2; if no, do nothing; B2: Extract the important factor ZY of the management area, and obtain the standardized important index BYZ of the current management area based on the formula BYZ=(ZY-PZY) / PZY; determine whether the standardized important index BYZ is greater than the important index 1; if yes, mark the current management area as a first-level management area; if no, jump to B3; wherein PZY is the average value of the important factor ZY of each management area; the important index 1 is greater than the important index 2; B3: Determine whether the standardized important index BYZ is less than the important index 2; if yes, mark the current management area as a third-level management area; if no, mark the current management area as a second-level management area; B4: Mark the total standard electricity consumption required by the first-level management area as the first-level electricity consumption, and determine whether the first-level electricity consumption exceeds the maximum power supply; if yes, jump to B5; if no, jump to B6; B5: The management area corresponding to the smallest standardized important indicator BYZ in the first-level management area is downgraded to the second-level management area in sequence, until the total power consumption of the first level does not exceed the maximum power supply, then the operation of downgrading the first-level management area to the second-level management area is stopped, and the first-level management area is powered by the grid, and the second-level and third-level management areas are powered by energy storage batteries; B6: Calculate the difference between the maximum power supply and the first-level total power consumption to obtain the first-level spare power supply, mark the standard total power consumption required by the second-level management area as the second-level total power consumption, and determine whether the second-level total power consumption exceeds the first-level spare power supply; if yes, calculate the difference between the second-level total power consumption and the first-level spare power supply to obtain the second-level energy storage battery power supply, obtain the ratio of the first-level spare power supply to the second-level energy storage battery power supply, and based on the ratio, supply power to the second-level management area through the power grid and the energy storage battery, and supply power to the third-level management area through the energy storage battery; if no, supply power to the second-level management area through the power grid, and jump to B7; B7: Calculate the difference between the first-level spare power supply and the second-level total power consumption to obtain the second-level spare power supply, mark the standard total power consumption required for the third-level management area as the third-level total power consumption, and determine whether the third-level total power consumption exceeds the second-level spare power supply; if yes, calculate the difference between the third-level total power consumption and the second-level spare power supply to obtain the third-level energy storage battery power supply, obtain the ratio of the second-level spare power supply to the third-level energy storage battery power supply, and supply power to the third-level management area through the power grid and the energy storage battery based on the ratio; if no, supply power to the third-level management area through the power grid.

10. An energy management method for intelligent buildings, based on the energy management system for intelligent buildings according to claims 1 to 9, characterized in that: S1: Plan a day into several dynamic time periods and divide the intelligent building into several management areas; S2: Collect the power consumption of different management areas in each dynamic period; S3: Obtain the characteristic value of power consumption of each management area in each dynamic period, obtain the standard power consumption of each management area in the next dynamic period based on the characteristic value of power consumption, and sum the standard power consumption of each management area to obtain the total standard power consumption of the intelligent building in the next dynamic period; Obtain important factors of each management area, issue a discharge instruction based on the standard total power consumption, and perform a discharge operation on each management area based on the discharge instruction and the important factors.

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