Energy consumption monitoring, managing and adjusting system based on rule engine

Abstract

The invention provides an energy consumption monitoring, managing and adjusting system based on a rule engine, belongs to the technical field of energy consumption monitoring, and is used for solving the problem that the cost of energy consumption monitoring is relatively high in the related art. In the system, a data acquisition module is used for acquiring the energy consumption speed; the grade determination module is used for energy consumption speed grades; the management adjustment module is used for generating management adjustment information; the start control module is used for calculating the working interval duration of the data acquisition module according to the energy consumption speed and the historical energy consumption speed. According to the system, the energy consumption speed can be monitored, the energy consumption speed grade can be determined, management adjustment information can be determined according to the energy consumption speed grade, and meanwhile, the working interval duration of the data acquisition module can be reasonably controlled; according to the method, the cost of energy consumption monitoring work can be reduced on the basis of guaranteeing effective energy consumption monitoring.

Description

Technical Field

[0001] The present application relates to the technical field of energy consumption monitoring, and in particular to an energy consumption monitoring, management and regulation system based on a rule engine. Background Art

[0002] Energy consumption monitoring is an important part of energy management. Necessary monitoring and control of energy consumption is conducive to reducing unnecessary energy consumption, thereby achieving the goal of energy conservation. Generally speaking, the higher the frequency of energy consumption monitoring, the more conducive it is to accurate control of energy consumption and the more conducive it is to saving energy consumption, but at the same time, high-frequency energy consumption monitoring itself will also increase costs. Summary of the invention

[0003] The present application provides an energy consumption monitoring management and regulation system based on a rule engine, which can reasonably determine the frequency of energy consumption monitoring work, thereby reducing the cost of energy consumption monitoring work while ensuring effective energy monitoring.

[0004] The energy consumption monitoring, management and regulation system based on rule engine provided in this application specifically adopts the following technical solutions:

[0005] An energy consumption monitoring, management and regulation system based on a rule engine includes: a data acquisition module, a level determination module, a management and regulation module and a start-up control module;

[0006] The data acquisition module is used to acquire the energy consumption within a preset sampling time to calculate the energy consumption speed;

[0007] The level determination module is used to determine the energy consumption speed level according to the energy consumption speed;

[0008] The management and adjustment module is used to generate management and adjustment information according to the energy consumption speed level based on the rule engine;

[0009] The startup control module is used to control the working interval duration of the data acquisition module. The working interval duration between the last work of the data acquisition module and the previous work is obtained by substituting the energy consumption rate calculated by the data acquisition module last time and the historical energy consumption rate before the previous work into a preset calculation model.

[0010] By adopting the above technical scheme, it is possible to monitor the energy consumption rate, determine the energy consumption rate level, and determine the management and adjustment information according to the energy consumption rate level. At the same time, the working interval of the data acquisition module can be reasonably controlled. Since the level determination module and the management and adjustment module rely on the data acquisition module, the level determination module and the management and adjustment module can also be controlled synchronously. This system is conducive to reducing the cost of energy consumption monitoring work while ensuring effective energy consumption monitoring.

[0011] Furthermore, the startup control module is further configured such that the calculation method of the working interval duration includes:

[0012] Get the expected interval duration. Where, T A is the expected interval duration, v premin and v premax are the lower limit and upper limit of the energy consumption speed interval corresponding to the energy consumption speed level of the energy consumption speed, Δv is the pre-acquired energy consumption speed change per unit time, T pre is the preset interval length, z=(x,y) min Indicates that z takes the minimum value of x and y;

[0013] The working interval duration is calculated according to the expected interval duration, T J =(T A , T pre ) min , where T J The working interval duration.

[0014] Furthermore, the startup control module is further configured such that the method for calculating the energy consumption rate change per unit time includes:

[0015] Get the speed reference change per unit time, In the formula, Δv p is the speed reference change per unit time, T C is the preset sampling time, v sta is the energy consumption rate in the first half of the preset sampling time, v end is the energy consumption rate in the second half of the preset sampling time;

[0016] The energy consumption speed change per unit time is calculated based on the speed reference change per unit time, Δv = Δv p×(1+K1)×(1+K2)×(1+K3), where K1 is the first trend influence coefficient calculated from the historical energy consumption speed of the current day, K2 is the second trend influence coefficient calculated from the historical energy consumption speed within a first preset time period with a homogeneous historical moment as the midpoint in the most recent preset number of historical days, and K3 is the third trend influence coefficient calculated from the historical energy consumption speed within the first preset time period with a homogeneous historical moment as the midpoint in the most recent preset number of homogeneous historical days, the homogeneous historical day has the same category label as the current day, the category label includes a week label or a date label, and the homogeneous historical moment and the moment when the data acquisition module started working last time are the same moment on different days.

[0017] Furthermore, the startup control module is further configured such that a method for calculating the first trend influence coefficient includes:

[0018] Get the historical energy consumption rate of the working module n times before the last working;

[0019] Based on the energy consumption speed of the previous work of the work acquisition module and n historical energy consumption speeds, n speed change data are calculated. Assume that the i-th work of the work acquisition module is farther away from the previous work moment than the i+1-th work, i=1, 2,...n-1, then the i-th speed change data Δv i =v i+1 -v i , the nth speed change data Δv n =vv n ;

[0020] Determine whether the signs of all speed change data are positive or negative;

[0021] If so, then Where v1 is the historical energy consumption rate of the first startup of the work acquisition module among n startups before the last startup of the work acquisition module;

[0022] If not, then Where p is Δv greater than 0 i The number of , q is Δv not greater than 0 i The number of , i = 1, 2, ... n.

[0023] Furthermore, the startup control module is further configured such that a method for calculating the second trend influence coefficient includes:

[0024] Obtain all historical energy consumption rates within the first preset time period with the homogeneous historical moment as the midpoint in the most recent preset number of historical days;

[0025] A historical energy consumption acceleration is calculated according to each two adjacent historical energy consumption speeds, and a historical working interval duration is determined according to the two adjacent historical energy consumption speeds;

[0026] The second trend impact coefficient is calculated based on the historical energy consumption acceleration and the historical working interval duration. In the formula, a represents the number of historical energy consumption accelerations greater than 0, b represents the number of historical energy consumption accelerations not greater than 0, T a Indicates the historical working interval duration corresponding to the historical energy consumption acceleration greater than 0, T b Represents the historical working interval duration corresponding to the historical energy consumption acceleration not greater than 0. Assuming there are z historical working interval durations, a∈[1,z], b∈[1,z], k1 represents the first preset coefficient, k2 represents the second preset coefficient, and both k1 and k2 are greater than 0.

[0027] Furthermore, the startup control module is further configured such that the calculation method of the third trend influence coefficient includes:

[0028] Obtain all historical energy consumption rates within the first preset time period with the homogenized historical moment as the midpoint in the most recent preset number of homogenized historical days;

[0029] A homogenized energy consumption acceleration is calculated according to each two adjacent historical energy consumption speeds, and a homogenized working interval duration is determined according to the two adjacent historical energy consumption speeds;

[0030] The third trend influence coefficient is calculated based on the homogenized energy consumption acceleration and the homogenized working interval duration. In the formula, p represents the number of homogenized energy consumption accelerations greater than 0, q represents the number of homogenized energy consumption accelerations not greater than 0, T p Indicates the historical working interval duration corresponding to the homogenized energy consumption acceleration greater than 0, T q Represents the historical working interval duration corresponding to the homogenized energy consumption acceleration not greater than 0. Assuming that there are g historical working interval durations, then p∈[1, g], q∈[1, g], k3 represents the third preset coefficient, k4 represents the fourth preset coefficient, and both k3 and k4 are greater than 0.

[0031] Furthermore, k1+k2=1.

[0032] Furthermore, k3+k4=1.

[0033] In summary, this application at least has the following beneficial effects:

[0034] A rule-engine-based energy consumption monitoring, management and regulation system is provided. The system can monitor the energy consumption rate and determine how to manage and regulate it. The system can also reasonably determine the frequency of monitoring the energy consumption rate, which is conducive to taking into account effective monitoring, timely discovering changes in the level of energy consumption rate, and minimizing the monitoring frequency and saving monitoring costs.

[0035] It should be understood that the contents described in the Summary of the Invention are not intended to limit the key or important features of the embodiments of the present application, nor are they intended to limit the scope of the present application. Other features of the present application will become easily understood through the following description. BRIEF DESCRIPTION OF THE DRAWINGS

[0036] The above and other features, advantages and aspects of the embodiments of the present application will become more apparent with reference to the following detailed description in conjunction with the accompanying drawings. In the accompanying drawings, the same or similar reference numerals represent the same or similar elements, wherein:

[0037] Figure 1 A block diagram of an energy consumption monitoring, management and regulation system based on a rule engine in an embodiment of the present application is shown. DETAILED DESCRIPTION

[0038] In order to make the purpose, technical solution and advantages of the embodiments of the present application clearer, the technical solution in the embodiments of the present application will be clearly and completely described below in conjunction with the drawings in the embodiments of the present application. Obviously, the described embodiments are part of the embodiments of the present application, not all of the embodiments. Based on the embodiments in the present application, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of this application.

[0039] In addition, the term "and / or" in this article is only a description of the association relationship between the associated objects, indicating that there can be three relationships. For example, A and / or B can represent: A exists alone, A and B exist at the same time, and B exists alone. In addition, the character " / " in this article generally indicates that the associated objects before and after are in an "or" relationship.

[0040] The present application provides an energy consumption monitoring, management and regulation system based on a rule engine, which can effectively monitor energy consumption and reduce the monitoring cost of energy consumption.

[0041] Figure 1 A block diagram of an energy consumption monitoring, management and regulation system based on a rule engine in an embodiment of the present application is shown.

[0042] Reference Figure 1 The system includes a data acquisition module 110 , a level determination module 120 , a management and adjustment module 130 and a startup control module 140 .

[0043] Among them, the data acquisition module 110 is used to obtain the energy consumption within a preset sampling time to calculate the energy consumption rate; the level determination module 120 is used to determine the energy consumption rate level according to the energy consumption rate; the management and adjustment module 130 is used to generate management and adjustment information according to the energy consumption rate level based on the rule engine; the start control module 140 is used to control the working interval duration of the data acquisition module 110, and the working interval duration between the last work of the data acquisition module 110 and the previous work is obtained by substituting the energy consumption rate calculated by the data acquisition module 110 last time and the historical energy consumption rate before the previous work into the preset calculation model.

[0044] Specifically, the system is connected to an external terminal device for collecting energy consumption, such as a water meter, an electric meter, a heat meter, etc. The terminal device generally collects energy consumption in real time and uploads the energy consumption to the system in real time. For simplicity of description, the present application embodiment takes electric energy consumption monitoring as an example for explanation.

[0045] The action of the data acquisition module 110 in the system to obtain energy consumption is actually the action of retrieving the energy consumption uploaded to the system by the terminal device. When the data acquisition module 110 is working, it obtains the energy consumption within the preset sampling time. Here, the preset sampling time ends at the time when the data acquisition module 110 is working and the duration is preset. The length of the preset sampling time can be adaptively adjusted according to the monitoring requirements, and is specifically set to 5min, 10min, 30min, 1h, etc. In the embodiment of the present application, the preset sampling duration can be specifically selected as 10min. The energy consumption rate calculated by the data acquisition module 110 is the average energy consumption rate within the preset sampling duration, and the calculation method is to divide the energy consumption within the preset sampling time by the duration of the preset sampling time. For example, if the preset sampling duration is 10min and the energy consumption is f degrees, the energy consumption rate is 0.1f degrees / min.

[0046] A pre-constructed energy consumption speed indicator system is stored in the registration determination module. The energy consumption speed indicator system can be set according to industry standards, monitoring requirements or human experience. The energy consumption speed indicator system includes multiple energy consumption speed intervals, each energy consumption speed interval includes a lower limit and an upper limit, and all energy consumption speed intervals constitute all possible sets of energy consumption speeds, that is, the energy consumption speed must fall within an energy consumption speed interval, and an energy consumption speed interval corresponds to an energy consumption speed level. For example, there can be five energy consumption speed levels, which are level one, level two, level three, level four, and level five according to the energy consumption speed from slow to fast.

[0047] The energy consumption speed level is stored in the level determination module 120. The energy consumption speed level itself is an indicator system, which can be set according to industry standards, monitoring requirements or human experience. The energy consumption speed level includes multiple energy consumption speed intervals, each energy consumption speed interval includes a lower limit and an upper limit, and all energy consumption speed intervals constitute all possible sets of energy consumption speeds, that is, the energy consumption speed must fall within an energy consumption speed interval.

[0048] The function of management and adjustment information is to generate control instructions for adjusting the energy consumption speed or to prompt relevant personnel to adjust the energy consumption speed. The rule engine contains the judgment rules for the energy consumption speed level. By substituting the energy consumption speed level into the rule engine, the result of whether the current energy consumption speed level is appropriate can be obtained. If the energy consumption speed level is high or low, management and adjustment information with different contents can be generated to adjust the energy consumption speed level to the appropriate level, so as to realize the monitoring, management and adjustment of the energy consumption speed. Of course, this is an introduction to the simplest function of the rule engine. The rule engine can also include other functions, such as real-time intelligent determination of the appropriate energy consumption speed level in the energy consumption speed indicator system based on the time label, attribute label, permission label, etc. of the energy consumption path. Since the rule engine does not belong to the key invention point of this application, the rule engine is not disclosed too much here.

[0049] Since each energy consumption speed level corresponds to an energy consumption speed interval, and the rule engine works based on the energy consumption speed level, the system is actually concerned with changes in the energy consumption speed level rather than changes in the energy consumption speed. In this way, the traditional working mode of timed energy consumption speed collection obviously lacks certain intelligence. Therefore, the system adds a startup control module 140 to control the working interval of the data acquisition module 110, so as to calculate the energy consumption speed in a timely manner when the energy consumption speed level changes. In this way, the monitoring frequency can be reduced on the basis of ensuring effective monitoring of energy consumption, thereby saving costs.

[0050] In an embodiment of the present application, the startup control module 140 is used to control the working interval duration of the data acquisition module 110. The working interval duration between the last work of the data acquisition module 110 and the previous work is obtained by substituting the energy consumption rate calculated by the data acquisition module 110 last time and the historical energy consumption rate before the previous work into a preset calculation model.

[0051] When actually determining the working time interval, the current work (also called the work at the current moment) is generally performed at the end of the preset sampling time, and the working interval between the next work and the current work is calculated based on the energy consumption rate of the current work and the historical energy consumption rate, that is, the time of the next work is determined.

[0052] In the start control module 140, the method for calculating the working interval duration includes:

[0053] Get the expected interval duration. Where, T A is the expected interval duration, v premin and v premax are the lower limit and upper limit of the energy consumption speed interval corresponding to the energy consumption speed level of the energy consumption speed, Δv is the pre-acquired energy consumption speed change per unit time, T pre is the preset interval length, z=(x,y) min Indicates that z takes the minimum value of x and y;

[0054] The working interval duration is calculated according to the expected interval duration, T J =(T A , T pre ) min , where T J The working interval duration.

[0055] The preset interval duration is set manually, that is, the longest working interval duration cannot exceed the preset interval duration to avoid the working interval duration being too long.

[0056] Furthermore, the method for calculating the energy consumption rate change per unit time includes:

[0057] Get the speed reference change per unit time, In the formula, Δv p is the speed reference change per unit time, T C is the preset sampling time, v sta is the energy consumption rate in the first half of the preset sampling time, v end is the energy consumption rate in the second half of the preset sampling time;

[0058] The energy consumption speed change per unit time is calculated based on the speed reference change per unit time, Δv = Δv p ×(1+K1)×(1+K2)×(1+K3), where K1 is the first trend influence coefficient calculated from the historical energy consumption speed of the current day, K2 is the second trend influence coefficient calculated from the historical energy consumption speed within a first preset time period with a homogeneous historical moment as the midpoint in the most recent preset number of historical days, and K3 is the third trend influence coefficient calculated from the historical energy consumption speed within the first preset time period with a homogeneous historical moment as the midpoint in the most recent preset number of homogeneous historical days, the homogeneous historical day has the same category label as the current day, the category label includes a week label or a date label, and the homogeneous historical moment and the moment when the data acquisition module 110 started working last time are the same moment on different days.

[0059] It should be understood that, based on the previous work being the current work, assuming that the current day is December 22, 2023 (Friday), and the preset sampling time start time of the current work is 20:00, the week label of the current day is Friday, the date label is the 22nd, and the month label is December. The homogenized historical time is 22:00.

[0060] Furthermore, the calculation method of the first trend influence coefficient includes:

[0061] Get the historical energy consumption rate of the working module n times before the last working;

[0062] Based on the energy consumption speed of the previous work of the work acquisition module and n historical energy consumption speeds, n speed change data are calculated. Assume that the i-th work of the work acquisition module is farther away from the previous work moment than the i+1-th work, i=1,2,...n-1, then the i-th speed change data Δv i =v i+1 -v i , the nth speed change data Δv n =vv n ;

[0063] Determine whether the signs of all speed change data are positive or negative;

[0064] If so, then Where v1 is the historical energy consumption rate of the first startup of the work acquisition module among n startups before the last startup of the work acquisition module;

[0065] If not, then Where p is Δv greater than 0 i The number of , q is Δv not greater than 0 i The number of , i = 1, 2, ... n.

[0066] Furthermore, the calculation method of the second trend influence coefficient includes:

[0067] Obtain all historical energy consumption rates within the first preset time period with the homogeneous historical moment as the midpoint in the most recent preset number of historical days;

[0068] A historical energy consumption acceleration is calculated according to each two adjacent historical energy consumption speeds, and a historical working interval duration is determined according to the two adjacent historical energy consumption speeds;

[0069] The second trend impact coefficient is calculated based on the historical energy consumption acceleration and the historical working interval duration. In the formula, a represents the number of historical energy consumption accelerations greater than 0, b represents the number of historical energy consumption accelerations not greater than 0, Ta Indicates the historical working interval duration corresponding to the historical energy consumption acceleration greater than 0, T b Represents the historical working interval duration corresponding to the historical energy consumption acceleration not greater than 0. Assuming there are z historical working interval durations, a∈[1,z], b∈[1,z], k1 represents the first preset coefficient, k2 represents the second preset coefficient, and both k1 and k2 are greater than 0.

[0070] Among them, k1+k2=1.

[0071] Furthermore, the calculation method of the third trend influence coefficient includes:

[0072] Obtain all historical energy consumption rates within the first preset time period with the homogenized historical moment as the midpoint in the most recent preset number of homogenized historical days;

[0073] A homogenized energy consumption acceleration is calculated according to each two adjacent historical energy consumption speeds, and a homogenized working interval duration is determined according to the two adjacent historical energy consumption speeds;

[0074] The third trend influence coefficient is calculated based on the homogenized energy consumption acceleration and the homogenized working interval duration. In the formula, p represents the number of homogenized energy consumption accelerations greater than 0, q represents the number of homogenized energy consumption accelerations not greater than 0, T p Indicates the historical working interval duration corresponding to the homogenized energy consumption acceleration greater than 0, T q Represents the historical working interval duration corresponding to the homogenized energy consumption acceleration not greater than 0. Assuming that there are g historical working interval durations, then p∈[1, g], q∈[1, g], k3 represents the third preset coefficient, k4 represents the fourth preset coefficient, and both k3 and k4 are greater than 0.

[0075] Among them, k3+k4=1.

[0076] In combination with the above description, the startup control module 140 can reasonably determine the next working time of the data acquisition module 110 based on the current energy consumption rate and the historical energy consumption rate. This working time is conducive to timely discovering changes in the energy consumption rate level, thereby facilitating effective monitoring of energy consumption and reducing monitoring costs.

[0077] The above description is only a preferred embodiment of the present application and an explanation of the technical principles used. Those skilled in the art should understand that the scope of disclosure involved in the present application is not limited to the technical solution formed by a specific combination of the above technical features, but should also cover other technical solutions formed by any combination of the above technical features or their equivalent features without departing from the aforementioned disclosed concept. For example, the above features are replaced with the technical features with similar functions disclosed in this application (but not limited to) by each other to form a technical solution.

Claims

1. An energy consumption monitoring, management and regulation system based on a rule engine, characterized in that: include: A data acquisition module (110), a level determination module (120), a management and adjustment module (130) and a start control module (140); The data acquisition module (110) is used to acquire the energy consumption within a preset sampling time to calculate the energy consumption speed; The level determination module (120) is used to determine the energy consumption speed level according to the energy consumption speed; The management and adjustment module (130) is used to generate management and adjustment information according to the energy consumption speed level based on a rule engine; The startup control module (140) is used to control the working interval duration of the data acquisition module (110), and the working interval duration between the last working of the data acquisition module (110) and the previous working of the data acquisition module (110) is obtained by substituting the energy consumption speed calculated by the data acquisition module (110) last time and the historical energy consumption speed before the previous working into a preset calculation model.

2. The system according to claim 1, characterized in that The startup control module (140) is further configured such that the method for calculating the working interval duration includes: Get the expected interval duration. Where, T A is the expected interval duration, v premin and v premax are the lower limit and upper limit of the energy consumption speed interval corresponding to the energy consumption speed level of the energy consumption speed, Δv is the pre-acquired energy consumption speed change per unit time, T pre is the preset interval length, z=(x,y) min Indicates that z takes the minimum value of x and y; The working interval duration is calculated according to the expected interval duration, T J =(T A ,T pre ) min , where T J The working interval duration.

3. The system according to claim 2, characterized in that The startup control module (140) is further configured such that the method for calculating the energy consumption rate change per unit time includes: Get the speed reference change per unit time, In the formula, Δv p is the speed reference change per unit time, T C is the preset sampling time, v sta is the energy consumption rate in the first half of the preset sampling time, v end is the energy consumption rate in the second half of the preset sampling time; The energy consumption speed change per unit time is calculated based on the speed reference change per unit time, Δv = Δv p ×(1+K1)×(1+K2)×(1+K3), wherein K1 is a first trend influence coefficient calculated from the historical energy consumption speed of the current day, K2 is a second trend influence coefficient calculated from the historical energy consumption speed within a first preset time period with a homogeneous historical moment as the midpoint in the most recent preset number of historical days, and K3 is a third trend influence coefficient calculated from the historical energy consumption speed within a first preset time period with a homogeneous historical moment as the midpoint in the most recent preset number of homogeneous historical days, wherein the homogeneous historical day has the same category label as the current day, wherein the category label includes a week label or a date label, and the homogeneous historical moment and the moment when the data acquisition module (110) started working last time are the same moment on different days.

4. The system according to claim 3, characterized in that The startup control module (140) is further configured such that a method for calculating the first trend influence coefficient includes: Get the historical energy consumption rate of the working module n times before the last working; Based on the energy consumption speed of the previous work of the work acquisition module and n historical energy consumption speeds, n speed change data are calculated. Assume that the i-th work of the work acquisition module is farther away from the previous work moment than the i+1-th work, i=1,2,...n-1, then the i-th speed change data Δv i =v i+1 -v i , the nth speed change data Δv n =vv n ; Determine whether the signs of all speed change data are positive or negative; If so, then Where v1 is the historical energy consumption rate of the first startup of the work acquisition module among n startups before the last startup of the work acquisition module; If not, then Where p is Δv greater than 0 i The number of , q is Δv not greater than 0 i The number of , i = 1, 2, ... n.

5. The system according to claim 4, characterized in that The startup control module (140) is further configured such that a method for calculating the second trend influence coefficient includes: Obtain all historical energy consumption rates within the first preset time period with the homogeneous historical moment as the midpoint in the most recent preset number of historical days; A historical energy consumption acceleration is calculated according to each two adjacent historical energy consumption speeds, and a historical working interval duration is determined according to the two adjacent historical energy consumption speeds; The second trend impact coefficient is calculated based on the historical energy consumption acceleration and the historical working interval duration. In the formula, a represents the number of historical energy consumption accelerations greater than 0, b represents the number of historical energy consumption accelerations not greater than 0, T a Indicates the historical working interval duration corresponding to the historical energy consumption acceleration greater than 0, T b Represents the historical working interval duration corresponding to the historical energy consumption acceleration not greater than 0. Assuming there are z historical working interval durations, a∈[1,z], b∈[1,z], k1 represents the first preset coefficient, k2 represents the second preset coefficient, and both k1 and k2 are greater than 0.

6. The system according to claim 5, characterized in that The startup control module (140) is further configured such that a method for calculating the third trend influence coefficient includes: Obtain all historical energy consumption rates within the first preset time period with the homogenized historical moment as the midpoint in the most recent preset number of homogenized historical days; A homogenized energy consumption acceleration is calculated according to each two adjacent historical energy consumption speeds, and a homogenized working interval duration is determined according to the two adjacent historical energy consumption speeds; The third trend influence coefficient is calculated based on the homogenized energy consumption acceleration and the homogenized working interval duration. In the formula, p represents the number of homogenized energy consumption accelerations greater than 0, q represents the number of homogenized energy consumption accelerations not greater than 0, T p Indicates the historical working interval duration corresponding to the homogenized energy consumption acceleration greater than 0, T p Represents the historical working interval duration corresponding to the homogenized energy consumption acceleration not greater than 0. Assuming that there are g historical working interval durations, then p∈[1, g], q∈[1, g], k3 represents the third preset coefficient, k4 represents the fourth preset coefficient, and both k3 and k4 are greater than 0.

7. The system according to claim 6, characterized in that k1+k2=1.

8. The system according to claim 7, characterized in that k3+k4=1.

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