Energy consumption adjustment management system based on electric energy substitution analysis

Abstract

The invention relates to the field of energy consumption management, and discloses an energy consumption adjustment management system based on electric energy substitution analysis, and the system comprises a data collection module which is used for collecting the energy consumption data of power equipment in real time; the electric energy substitution analysis module is used for evaluating and analyzing the electric energy substitution potential according to the collected energy consumption data; the energy consumption adjusting module is used for automatically adjusting operation parameters of the power equipment according to the result of the electric energy substitution analysis so as to realize optimization of energy consumption; the monitoring and management module is used for monitoring the running state of the system in real time and managing and analyzing the energy consumption data; according to the method, electric energy substitutability evaluation is performed on each piece of power equipment in advance, so that unnecessary energy consumption adjustment and analysis processes on the power equipment needing to be replaced in the later period are reduced, effective energy consumption management on the power equipment is realized, and the situation that operation parameters are improperly set or actual operation parameters cannot meet energy consumption management requirements is reduced; and the overall energy consumption is too high.

Description

Technical Field

[0001] The present invention relates to the field of energy consumption management, and in particular to an energy consumption adjustment and management system based on electric energy substitution analysis. Background Art

[0002] The continuous development of electric energy substitution can not only quickly increase users' electricity load, promote the development of clean energy such as wind power generation, improve power generation efficiency, and improve the level of electrification, but it is also crucial to solving the problems of abandoned wind and solar power, optimizing the energy structure, preventing and controlling air pollution, and improving the utilization level of new energy.

[0003] At present, many researchers have explored the work of electric energy substitution, but the generally recognized method of predicting the potential of electric energy substitution has not yet been finalized. The research on the potential of electric energy substitution has important implications for the development of electric energy substitution in my country. Strengthening the research on the prediction of the potential of electric energy substitution and the development strategy has an important impact on accurately grasping the potential of electric energy substitution, continuously improving the level of electric energy substitution management, and improving the technical strength of electric energy substitution.

[0004] At present, although there are some energy consumption management systems on the market, most of these systems can only realize real-time monitoring and simple analysis of energy consumption data, and cannot perform intelligent energy consumption adjustment and management according to the needs of electric energy substitution. Therefore, developing an energy consumption adjustment and management system based on electric energy substitution analysis is of great significance for improving energy utilization efficiency, reducing operating costs, and promoting sustainable development. Summary of the invention

[0005] The purpose of the present invention is to provide an energy consumption adjustment and management system based on electric energy substitution analysis to solve the above technical problems.

[0006] The purpose of the present invention can be achieved through the following technical solutions:

[0007] An energy consumption adjustment management system based on electric energy substitution analysis, comprising:

[0008] Data acquisition module, used to collect energy consumption data of power equipment in real time;

[0009] The electric energy substitution analysis module is used to evaluate and analyze the electric energy substitution potential based on the collected energy consumption data;

[0010] Energy consumption adjustment module, used to automatically adjust the operating parameters of power equipment according to the results of power substitution analysis to achieve energy consumption optimization;

[0011] The monitoring and management module is used to monitor the system operation status in real time and manage and analyze energy consumption data.

[0012] As a further technical solution, the energy consumption data includes voltage, current, active power, reactive power and electric energy consumption.

[0013] As a further technical solution, the process of evaluating and analyzing the potential of electric energy substitution is as follows:

[0014] Substitute the energy consumption data into the following formula:

[0015]

[0016] Calculate the electric energy substitution potential assessment coefficient F of the ath power equipment a ;

[0017] Where m is the total number of acquisition times in a unit time, i is the i-th acquisition time, and f i is the voltage value at the i-th acquisition time, f i0 is the standard voltage value, f c is the reference voltage value, I i0 is the standard current value, W x0 , W y0 They are standard active power and standard reactive power, I i , W x , W y are the current value, active power value, and reactive power value at the i-th acquisition time, respectively. a is the power consumption of the ath power equipment in a unit time, d a is the impact factor, Q a is the energy consumption coefficient of the ath power equipment;

[0018] The calculated electric energy substitution potential assessment coefficient F a Compared with the preset electric energy substitution potential assessment threshold F a0 Make a comparison;

[0019] If F a ≥F a0 , then it is judged that the current power equipment has great potential for electric energy substitution;

[0020] If F a <F a0 , it is judged that the current power equipment has little potential for electric energy substitution.

[0021] As a further technical solution, the process of obtaining the impact factor is as follows:

[0022] Fit the time variation curve of various energy consumption data of the current power equipment within a unit time and the reference variation curve, and substitute them into the following formula:

[0023]

[0024] Calculate the impact factor d a ;

[0025] Among them, t0 and t1 are the left and right time endpoints of the unit time, f a (t) is the voltage variation curve of the current power equipment over time, I a (t) is the current curve of the current power equipment changing with time, is the active power variation curve of the current power equipment over time, μ1, μ2, and μ3 are weight coefficients.

[0026] As a further technical solution, the working process of the energy consumption adjustment module includes:

[0027] Obtain the energy consumption pattern of each power device, and determine the list of power devices that need to be adjusted according to the energy consumption pattern;

[0028] The process of obtaining the energy consumption pattern of each power device is:

[0029] Obtain the energy consumption data of each power device in real time, input the energy consumption data of each power device into the pre-trained neural network model, and output the energy consumption coefficient Q of each power device a ;

[0030] The energy consumption coefficient Q of each electrical equipment a Compared with the preset energy consumption coefficient range [Q min , Q max ] for comparison;

[0031] If Q a >Q max , it is determined that the electric equipment is in a high energy consumption mode;

[0032] If Q a ∈[Q min , Q max ], it is judged that the electric equipment is in the medium energy consumption mode;

[0033] If Q a min , it is determined that the electrical equipment is in low energy consumption mode.

[0034] As a further technical solution, the working process of the energy consumption adjustment module also includes:

[0035] A list of power equipment with low power potential and in high energy consumption mode is formed, and the power equipment in the list is marked;

[0036] Obtain various operating parameters of each marked power equipment during peak period and various operating parameters during valley period;

[0037] ​Randomly obtain the operating parameter values ​​corresponding to multiple detection time points of power equipment during peak and valley periods;

[0038] Obtain the average of each operating parameter value during the peak period and the trough period as the actual operating parameter value of each item;

[0039] Calculate the difference between the actual operating parameter values ​​of each item and the theoretical operating parameter values ​​obtained based on big data. If the difference of at least one operating parameter is greater than the preset difference warning value, adjust the operating parameter, evaluate the operating status of the adjusted power equipment, and determine whether to adjust the operating parameters of the power equipment again based on the evaluation results;

[0040] Otherwise, the operating status is evaluated directly, and the operating parameters of the power equipment are adjusted according to the evaluation results.

[0041] As a further technical solution, the process of evaluating the operating status of power equipment is as follows:

[0042] According to the actual operating parameter values ​​and theoretical operating parameter values ​​of each item, the operating state coefficient is calculated; the expression is:

[0043] Among them, z is the preset coefficient, M is the number of operating parameters, ρ k is the weight coefficient, is the difference of each operating parameter, P k is the actual operating parameter value, P k0 is the theoretical operating parameter value, S is the operating state coefficient;

[0044] The calculated operating state coefficient S is compared with a preset operating state threshold S0; if S≥S0, the operating parameters of the power equipment are adjusted, otherwise, the operating parameters are not adjusted.

[0045] As a further technical solution, the process of adjusting the operating parameters of the power equipment is as follows:

[0046] According to the difference of various operating parameters of current power equipment Sort in descending order;

[0047] The corresponding actual operating parameter values ​​are adjusted to the theoretical operating parameter values ​​in sequence until the energy consumption mode of the current power equipment is reduced to a medium energy consumption mode or a low energy consumption mode.

[0048] Beneficial effects of the present invention:

[0049] The present invention collects energy consumption data of electric equipment in real time through a data acquisition module, and evaluates and analyzes the electric energy substitution potential according to the collected energy consumption data through an electric energy substitution analysis module, thereby pre-evaluating the electric energy substitutability of each electric equipment, thereby reducing unnecessary energy consumption adjustment and analysis processes for electric equipment that needs to be replaced later, which affects the operation speed of the system. For electric equipment that does not need to be replaced, the energy consumption adjustment module automatically adjusts the operation parameters of the electric equipment according to the results of the electric energy substitution analysis to achieve energy consumption optimization. Finally, a monitoring and management module is used to monitor the system operation status in real time and manage and analyze the energy consumption data. Through the above technical solution, effective energy consumption management of electric equipment is achieved, and improper operation parameter settings or actual operation parameters that fail to meet energy consumption management requirements, resulting in excessive overall energy consumption, are reduced. BRIEF DESCRIPTION OF THE DRAWINGS

[0050] The present invention will be further described below in conjunction with the accompanying drawings.

[0051] Figure 1 It is a system structure block diagram of the present invention. DETAILED DESCRIPTION

[0052] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not 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.

[0053] See also Figure 1 As shown, the present invention is an energy consumption adjustment management system based on electric energy substitution analysis, comprising:

[0054] Data acquisition module, used to collect energy consumption data of power equipment in real time;

[0055] The electric energy substitution analysis module is used to evaluate and analyze the electric energy substitution potential based on the collected energy consumption data;

[0056] Energy consumption adjustment module, used to automatically adjust the operating parameters of power equipment according to the results of power substitution analysis to achieve energy consumption optimization;

[0057] The monitoring and management module is used to monitor the system operation status in real time and manage and analyze energy consumption data. It should be noted that the monitoring and management module is a prior art that can monitor the operation status of the entire system, and the monitoring tools used do not belong to the protection scope of the present invention.

[0058] The energy consumption data includes voltage, current, active power, reactive power and electric energy consumption.

[0059] In this embodiment, the energy consumption data of the power equipment is collected in real time through the data acquisition module, and the power substitution analysis module evaluates and analyzes the power substitution potential based on the collected energy consumption data, so as to pre-evaluate the power substitutability of each power equipment, thereby reducing unnecessary energy consumption adjustment and analysis processes for power equipment that needs to be replaced later, which affects the operation speed of the system. For power equipment that does not need to be replaced, the energy consumption adjustment module automatically adjusts the operating parameters of the power equipment according to the results of the power substitution analysis to achieve energy consumption optimization. Finally, the monitoring and management module is used to monitor the system operation status in real time and manage and analyze the energy consumption data. Through the above technical scheme, effective energy consumption management of power equipment is achieved, and improper operation parameter settings or actual operation parameters that fail to meet energy consumption management requirements, resulting in excessive overall energy consumption, are reduced.

[0060] The process of conducting an assessment and analysis of the potential for electric energy substitution is as follows:

[0061] Substitute the energy consumption data into the following formula:

[0062]

[0063] Calculate the electric energy substitution potential assessment coefficient F of the ath power equipment a ;

[0064] Where m is the total number of acquisition times in a unit time, i is the i-th acquisition time, and f i is the voltage value at the i-th acquisition time, f i0 is the standard voltage value, f c is the reference voltage value, I i0 is the standard current value, W x0 , W y0 They are standard active power and standard reactive power, I i , W x , W y are the current value, active power value, and reactive power value at the i-th acquisition time, respectively. a is the power consumption of the ath power equipment in a unit time, d a is the impact factor, Q a is the energy consumption coefficient of the ath power equipment;

[0065] The calculated electric energy substitution potential assessment coefficient F a Compared with the preset electric energy substitution potential assessment threshold F a0 Make a comparison;

[0066] If Fa ≥F a0 , then it is judged that the current power equipment has great potential for electric energy substitution;

[0067] If F a <F a0 , it is judged that the current power equipment has little potential for electric energy substitution.

[0068] The process of obtaining the impact factor is as follows:

[0069] Fit the time variation curve of various energy consumption data of the current power equipment within a unit time and the reference variation curve, and substitute them into the following formula:

[0070]

[0071] Calculate the impact factor d a ;

[0072] Among them, t0 and t1 are the left and right time endpoints of the unit time, f a (t) is the voltage variation curve of the current power equipment over time, I a (t) is the current curve of the current power equipment changing with time, is the active power variation curve of the current power equipment over time, μ1, μ2, and μ3 are weight coefficients.

[0073] In this embodiment, a specific electric energy substitution analysis method is provided. Specifically, the energy consumption data of each electric device is obtained and then substituted into the formula Calculate the electric energy substitution potential assessment coefficient F of the ath power equipment a According to the above formula, the deviation between the actual energy consumption data and the expected standard value is reflected by the ratio of each energy consumption data to the expected standard value. Obviously, the larger the deviation, the more unstable the energy consumption data is, which means that there are more problems. Therefore, the overall energy consumption must be higher, and the electric energy substitution potential assessment coefficient F a Combined with the electricity consumption, it is obvious that the greater the electricity consumption, the greater the electricity substitution potential assessment coefficient F a , so the calculated electric energy substitution potential assessment coefficient F a Compared with the preset electric energy substitution potential assessment threshold F a0 For comparison, if F a ≥F a0 , then it is judged that the current power equipment has great potential for electric energy substitution. If F a <F a0 , it is judged that the electric energy substitution potential of the current power equipment is small, thereby realizing the pre-division of the electric energy substitution potential and avoiding unnecessary analysis of subsequent energy consumption adjustment;

[0074] In order to improve the accuracy of energy consumption data analysis, the change values ​​of current, voltage and active power per unit time are combined for analysis, and the formula is used It can be expressed in the form of a (t)-f a0 (t), I a (t)-I a0 (t) The larger the deviation, the poorer the stability of the above three parameters per unit time. Therefore, the higher the demand for electric energy replacement for the power equipment is, so as to achieve overall energy saving.

[0075] The working process of the energy consumption adjustment module includes:

[0076] Obtain the energy consumption pattern of each power device, and determine the list of power devices that need to be adjusted according to the energy consumption pattern;

[0077] The process of obtaining the energy consumption pattern of each power device is:

[0078] Obtain the energy consumption data of each power device in real time, input the energy consumption data of each power device into the pre-trained neural network model, and output the energy consumption coefficient Q of each power device a ;

[0079] The energy consumption coefficient Q of each electrical equipment a Compared with the preset energy consumption coefficient range [Q min , Q max ] for comparison;

[0080] If Q a >Q max , it is determined that the electric equipment is in a high energy consumption mode;

[0081] If Q a ∈[Q min , Q max ], it is judged that the electric equipment is in the medium energy consumption mode;

[0082] If Q a min , it is determined that the electrical equipment is in low energy consumption mode.

[0083] In this embodiment, the energy consumption of the power equipment that does not replace electric energy is adjusted by the above technical solution, so as to reduce the energy consumption of the overall system. Specifically, the energy consumption mode of the power equipment is calculated, and the energy consumption coefficient of each power equipment is obtained by a pre-trained neural network model, and then the energy consumption coefficient Q of each power equipment is calculated. a Compared with the preset energy consumption coefficient range [Q min ​, Q max ] to compare, if Q a >Q max , then the power equipment is judged to be in high energy consumption mode; if Q a ∈[Q min , Q max ], then the power equipment is judged to be in the medium energy consumption mode; if Q a min , then determine whether the power equipment is in low energy consumption mode, so as to accurately and quickly determine the power equipment for energy consumption adjustment and improve the overall efficiency of energy consumption adjustment.

[0084] The working process of the energy consumption adjustment module also includes:

[0085] A list of power equipment with low power potential and in high energy consumption mode is formed, and the power equipment in the list is marked;

[0086] Obtain various operating parameters of each marked power equipment during peak period and various operating parameters during valley period;

[0087] Randomly obtain the operating parameter values ​​corresponding to multiple detection time points of power equipment during peak and valley periods;

[0088] Obtain the average of each operating parameter value during the peak period and the trough period as the actual operating parameter value of each item;

[0089] Calculate the difference between the actual operating parameter values ​​of each item and the theoretical operating parameter values ​​obtained based on big data. If the difference of at least one operating parameter is greater than the preset difference warning value, adjust the operating parameter, evaluate the operating status of the adjusted power equipment, and determine whether to adjust the operating parameters of the power equipment again based on the evaluation results;

[0090] Otherwise, the operating status is evaluated directly, and the operating parameters of the power equipment are adjusted according to the evaluation results.

[0091] The process of evaluating the operating status of power equipment is as follows:

[0092] According to the actual operating parameter values ​​and theoretical operating parameter values ​​of each item, the operating state coefficient is calculated; the expression is:

[0093] Among them, z is the preset coefficient, M is the number of operating parameters, ρ k is the weight coefficient, is the difference of each operating parameter, P k is the actual operating parameter value, P k0 is the theoretical operating parameter value, S is the operating status coefficient; z defaults to 1.

[0094] ​The calculated operating state coefficient S is compared with a preset operating state threshold S0; if S≥S0, the operating parameters of the power equipment are adjusted, otherwise, the operating parameters are not adjusted.

[0095] In this embodiment, the operating status of the power equipment is evaluated using the formula The calculated operating status coefficient, obviously, the greater the difference between the operating parameters, the worse the operating status of the power equipment; the greater the ratio of the actual operating parameter value to the theoretical operating parameter value, the greater the deviation of the power equipment during operation. Through the accumulation and multiplication of various parameters, the overall operating status evaluation of each power equipment is obtained, which provides a basis for judging whether the subsequent operating parameters of the power equipment need to be adjusted. Finally, the calculated operating status coefficient S is compared with the preset operating status threshold S0; if S≥S0, the operating parameters of the power equipment are adjusted, otherwise, the operating parameters are not adjusted.

[0096] The process of adjusting the operating parameters of power equipment is as follows:

[0097] According to the difference of various operating parameters of current power equipment Sort in descending order;

[0098] The corresponding actual operating parameter values ​​are adjusted to the theoretical operating parameter values ​​in sequence until the energy consumption mode of the current power equipment is reduced to a medium energy consumption mode or a low energy consumption mode.

[0099] It should be noted that the calculation formulas and various parameters involved in the calculation in the present invention have been dimensionally processed in advance, and the process of dimensionless processing is well known in the industry and will not be described here.

[0100] The above is a detailed description of an embodiment of the present invention, but the content is only a preferred embodiment of the present invention and cannot be considered to limit the scope of implementation of the present invention. All equivalent changes and improvements made within the scope of the present invention should still fall within the scope of the patent coverage of the present invention.

Claims

1. An energy consumption adjustment and management system based on electric energy substitution analysis, characterized in that: include: Data acquisition module, used to collect energy consumption data of power equipment in real time; The electric energy substitution analysis module is used to evaluate and analyze the electric energy substitution potential based on the collected energy consumption data; Energy consumption adjustment module, used to automatically adjust the operating parameters of power equipment according to the results of power substitution analysis to achieve energy consumption optimization; The monitoring and management module is used to monitor the system operation status in real time and manage and analyze energy consumption data.

2. The energy consumption adjustment and management system based on electric energy substitution analysis according to claim 1 is characterized in that: The energy consumption data includes voltage, current, active power, reactive power and electric energy consumption.

3. The energy consumption adjustment and management system based on electric energy substitution analysis according to claim 2 is characterized in that: The process of conducting an assessment and analysis of the potential for electric energy substitution is as follows: Substitute the energy consumption data into the following formula: Calculate the electric energy substitution potential assessment coefficient F of the ath power equipment a ; Where m is the total number of acquisition times in a unit time, i is the i-th acquisition time, and f i is the voltage value at the i-th acquisition time, f i0 is the standard voltage value, f c is the reference voltage value, I i0 is the standard current value, W x0 , W y0 They are standard active power and standard reactive power, I i , W x , W y are the current value, active power value, and reactive power value at the i-th acquisition time, respectively. a is the power consumption of the ath power equipment in a unit time, d a is the impact factor, Q a is the energy consumption coefficient of the ath power equipment; The calculated electric energy substitution potential assessment coefficient F a Compared with the preset electric energy substitution potential assessment threshold F a0 Make a comparison; If F a ≥F a0 , then it is judged that the current power equipment has great potential for electric energy substitution; If F a <F a0 , it is judged that the current power equipment has little potential for electric energy substitution.

4. The energy consumption adjustment and management system based on electric energy substitution analysis according to claim 3 is characterized in that: The process of obtaining the impact factor is as follows: Fit the time variation curve of various energy consumption data of the current power equipment within a unit time and the reference variation curve, and substitute them into the following formula: Calculate the impact factor d a ; Among them, t0 and t1 are the left and right time endpoints of the unit time, f a (t) is the voltage variation curve of the current power equipment over time, I a (t) is the current curve of the current power equipment changing with time, is the active power variation curve of the current power equipment over time, μ1, μ2, and μ3 are weight coefficients.

5. The energy consumption adjustment and management system based on electric energy substitution analysis according to claim 1 is characterized in that: The working process of the energy consumption adjustment module includes: Obtain the energy consumption pattern of each power device, and determine the list of power devices that need to be adjusted according to the energy consumption pattern; The process of obtaining the energy consumption pattern of each power device is: Obtain the energy consumption data of each power device in real time, input the energy consumption data of each power device into the pre-trained neural network model, and output the energy consumption coefficient Q of each power device a ; The energy consumption coefficient Q of each electrical equipment a Compared with the preset energy consumption coefficient range [Q min , Q max ] for comparison; If Q a >Q max , it is determined that the electric equipment is in a high energy consumption mode; If Q a ∈[Q min , Q max ], it is judged that the electric equipment is in the medium energy consumption mode; If Q a min , it is determined that the electrical equipment is in low energy consumption mode.​ 6. The energy consumption adjustment and management system based on electric energy substitution analysis according to claim 5 is characterized in that: The working process of the energy consumption adjustment module also includes: A list of power equipment with low power potential and in high energy consumption mode is formed, and the power equipment in the list is marked; Obtain various operating parameters of each marked power equipment during peak period and various operating parameters during valley period; Randomly obtain the operating parameter values ​​corresponding to multiple detection time points of power equipment during peak and valley periods; Obtain the average of each operating parameter value during the peak period and the trough period as the actual operating parameter value of each item; Calculate the difference between the actual operating parameter values ​​of each item and the theoretical operating parameter values ​​obtained based on big data. If the difference of at least one operating parameter is greater than the preset difference warning value, adjust the operating parameter, evaluate the operating status of the adjusted power equipment, and determine whether to adjust the operating parameters of the power equipment again based on the evaluation results; Otherwise, the operating status is evaluated directly, and the operating parameters of the power equipment are adjusted according to the evaluation results.

7. The energy consumption adjustment and management system based on electric energy substitution analysis according to claim 6 is characterized in that: The process of evaluating the operating status of power equipment is as follows: According to the actual operating parameter values ​​and theoretical operating parameter values ​​of each item, the operating state coefficient is calculated; the expression is: Among them, z is the preset coefficient, M is the number of operating parameters, ρ k is the weight coefficient, is the difference of each operating parameter, P k is the actual operating parameter value, P k0 is the theoretical operating parameter value, S is the operating state coefficient; The calculated operating state coefficient S is compared with a preset operating state threshold S0; if S≥S0, the operating parameters of the power equipment are adjusted, otherwise, the operating parameters are not adjusted.

8. The energy consumption adjustment and management system based on electric energy substitution analysis according to claim 7 is characterized in that: The process of adjusting the operating parameters of power equipment is as follows: According to the difference of various operating parameters of current power equipment Sort in descending order; The corresponding actual operating parameter values ​​are adjusted to the theoretical operating parameter values ​​in sequence until the energy consumption mode of the current power equipment is reduced to a medium energy consumption mode or a low energy consumption mode.

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