An energy consumption adjustment management system based on electric energy substitution analysis

Abstract

The present invention relates to the field of energy consumption management and discloses an energy consumption adjustment and management system based on electric energy substitution analysis, comprising: a data acquisition module for real-time acquisition of energy consumption data of electric equipment; an electric energy substitution analysis module for evaluating and analyzing electric energy substitution potential based on the acquired energy consumption data; an energy consumption adjustment module for automatically adjusting operating parameters of electric equipment based on the results of the electric energy substitution analysis to optimize energy consumption; a monitoring and management module for real-time monitoring of the system operating status and management and analysis of energy consumption data; the present invention pre-evaluates 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, achieving effective energy consumption management of the electric equipment, and reducing the situation where the overall energy consumption is too high due to improper operation parameter settings or actual operation parameters failing to meet energy consumption management requirements.

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 wind and solar power abandonment, optimizing the energy structure, preventing and controlling air pollution, and improving the utilization level of new energy.

[0003] Many researchers are currently exploring the potential of electric energy substitution, but a widely accepted method for predicting its potential has yet to be established. Research on its potential is crucial for the development of electric energy substitution in my country. Strengthening research on its potential prediction and development strategies is crucial for accurately understanding its potential, continuously improving its management, and enhancing its technological capabilities.

[0004] Although there are some energy consumption management systems on the market, most of these systems can only achieve real-time monitoring and simple analysis of energy consumption data, and are unable to intelligently adjust and manage energy consumption based on 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 and 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, which is used to automatically adjust the operating parameters of power equipment according to the results of electric energy 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 evaluation coefficient F of the a-th 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, standard reactive power, I i 、W x 、W y are the current value, active power value, and reactive power value of the i-th acquisition time, respectively. a is the energy 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 evaluation 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-varying curves of various energy consumption data of the current power equipment within a unit time and the reference change 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 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 as follows:

[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 power 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 power equipment is in high energy consumption mode;

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

[0033] If Q a min , it is determined that the power 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 created, and the power equipment on 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 off-peak periods;

[0038] Obtain the average of the operating parameter values during the peak period and the valley 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. After the adjustment, evaluate the operating status of the power equipment. Based on the evaluation results, determine whether to adjust the operating parameters of the power equipment again.

[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 status 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 the medium energy consumption mode or the 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 the data acquisition module, and evaluates and analyzes the electric energy substitution potential based on the collected energy consumption data through the 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, affecting the operation speed of the system. For electric equipment that does not need to be replaced, the energy consumption adjustment module automatically adjusts the operating parameters of the electric equipment according to the results of the electric energy 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 solution, effective energy consumption management of electric equipment is achieved, and the situation of improper operation parameter settings or actual operation parameters failing to meet energy consumption management requirements, resulting in excessive overall energy consumption, is reduced. BRIEF DESCRIPTION OF THE DRAWINGS

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

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

[0052] The following will clearly and completely describe the technical solutions in the embodiments of the present invention in conjunction with the accompanying drawings. 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 making any creative efforts shall fall within the scope of protection of the present invention.

[0053] See also Figure 1 As shown, the present invention is an energy consumption adjustment and 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, which is used to automatically adjust the operating parameters of power equipment according to the results of electric energy substitution analysis to achieve energy consumption optimization;

[0057] The monitoring and management module is used to monitor the system's operating 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 technology that can only monitor the operating status of the entire system. The monitoring tools used are not within the scope of protection of this 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 is used to evaluate and analyze 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 in the future, 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 solution, effective energy consumption management of the 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 evaluation coefficient F of the a-th 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, standard reactive power, I i 、W x 、W y are the current value, active power value, and reactive power value of the i-th acquisition time, respectively. a is the energy 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 evaluation 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-varying curves of various energy consumption data of the current power equipment within a unit time and the reference change 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 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 evaluation coefficient F of the a-th power equipment a According to the above formula, we can see that 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 is a greater risk of problems. Therefore, the overall energy consumption is definitely higher. The electric energy substitution potential assessment coefficient F is 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 evaluation 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 eliminating unnecessary analysis of subsequent energy consumption adjustment;

[0074] In addition, 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, from the above formula we can see that if f 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, thereby achieving 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 as follows:

[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 power 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 power equipment is in high energy consumption mode;

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

[0082] If Q a min , it is determined that the power 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, thereby reducing the energy consumption of the entire system. Specifically, the energy consumption pattern of the power equipment is first calculated, and the energy consumption coefficient of each power equipment is obtained through a pre-trained neural network model. Then, the energy consumption coefficient Q of each power equipment is converted into a Compared with the preset energy consumption coefficient range [Q min ​, Q max ] to compare, if Q a >Q max , then it is determined that the power equipment is in high energy consumption mode; if Q a ∈[Q min , Q max ], it is judged that the power equipment is 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 created, and the power equipment on 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 off-peak periods;

[0088] Obtain the average of the operating parameter values during the peak period and the valley 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. After the adjustment, evaluate the operating status of the power equipment. Based on the evaluation results, determine whether to adjust the operating parameters of the power equipment again.

[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 status 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 shows that 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 pre-set 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 the medium energy consumption mode or the low energy consumption mode.

[0099] It should be noted that the calculation formulas and various parameters involved in the calculations 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. However, the content described is only a preferred embodiment of the present invention and should not be considered to limit the scope 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, which is used to automatically adjust the operating parameters of power equipment according to the results of electric energy substitution analysis to achieve energy consumption optimization; Monitoring and management module, used to monitor the system operation status in real time and manage and analyze energy consumption data; 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 evaluation coefficient F of the a-th 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, standard reactive power, I i 、W x 、W y are the current value, active power value, and reactive power value of the i-th acquisition time, respectively. a is the energy 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 evaluation 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 electric energy substitution potential of the current power equipment is small; The process of obtaining the impact factor is as follows: Fit the time-varying curves of various energy consumption data of the current power equipment within a unit time and the reference change 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 curve of the current power equipment over time, I a (t) is the current curve of the current power equipment changing with time, W xa (t) is the active power variation curve of the current power equipment over time, and μ1, μ2, and μ3 are weight coefficients.

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 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 as follows: 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 power 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 power equipment is in high energy consumption mode; If Q a ∈[Q min , Q max ], it is determined that the power equipment is in the medium energy consumption mode; If Q a min , it is determined that the power equipment is in low energy consumption mode.​ 4. The energy consumption adjustment and management system based on electric energy substitution analysis according to claim 3 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 created, and the power equipment on 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 off-peak periods; Obtain the average of the operating parameter values during the peak period and the valley 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. After the adjustment, evaluate the operating status of the power equipment. Based on the evaluation results, determine whether to adjust the operating parameters of the power equipment again. Otherwise, the operating status is evaluated directly and the operating parameters of the power equipment are adjusted according to the evaluation results.

5. The energy consumption adjustment and management system based on electric energy substitution analysis according to claim 4 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 status 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.

6. The energy consumption adjustment and management system based on electric energy substitution analysis according to claim 5 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 the medium energy consumption mode or the low energy consumption mode.

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