A method and system for early warning of overall energy consumption in urban tunnels

Abstract

The present invention relates to a method and system for early warning of overall energy consumption in urban tunnels. The method comprises: obtaining structural parameters of the urban tunnel, constructing a reasonable electricity consumption prediction model to obtain reasonable electricity consumption, and obtaining a reasonable electricity consumption index based on actual tunnel electricity consumption, and determining a reasonable electricity consumption score through threshold division; selecting a meter to be tested from various meters within the urban tunnel; obtaining the unit basic electricity charge and peak, flat, and valley comprehensive unit price of all the meters to be tested, and determining a power consumption distribution balance score based on threshold division; obtaining a comprehensive energy consumption score for the urban tunnel based on the obtained reasonable electricity consumption score and power consumption distribution balance score, setting an early warning threshold, and optimizing energy consumption in the urban tunnel. Compared with existing technologies, the present invention considers both the tunnel's electricity consumption and electricity consumption behavior, achieving a comprehensive assessment of urban tunnel energy consumption, and can promptly identify energy consumption issues in urban tunnels and implement timely optimization.

Description

Technical Field

[0001] The present invention relates to the technical field of energy consumption in urban tunnels, and in particular to an overall energy consumption early warning method and system for urban tunnels. Background Art

[0002] At present, domestic and international research on energy conservation and emission reduction in road tunnels mainly focuses on structural energy conservation and technical energy conservation. These include the application of technologies such as solar fiber optic lighting, solar photovoltaic power generation, and wind-solar hybrid power generation to adjust the energy structure of road tunnels during operation, and the reduction of energy consumption during road tunnel operation by optimizing ventilation and lighting system design parameters, using energy-saving lighting sources, and adopting intelligent control facilities. However, relatively little attention has been paid to managerial energy conservation, especially with regard to the long-term monitoring, analysis, and evaluation of energy consumption during road tunnel operation.

[0003] Traditional tunnel operation and maintenance practices employ a relatively extensive approach to energy consumption management. Mechanical and electrical equipment activation is often based on regulatory requirements and empirical evidence. Tunnels vary significantly in length, area, and mechanical and electrical equipment capacity, making it difficult to directly compare energy consumption across tunnels. Consequently, there is a lack of reasonable, quantitative tunnel energy consumption evaluation indicators. To scientifically and rationally reflect energy consumption levels and energy efficiency during tunnel operation and provide information and a basis for macroeconomic decision-making and management, a rational energy consumption evaluation scheme for tunnel operation is necessary. Summary of the Invention

[0004] The purpose of the present invention is to provide an urban tunnel overall energy consumption early warning method and system in order to overcome the defects of the above-mentioned prior art that lacks reasonable and quantitative tunnel energy consumption evaluation indicators and cannot timely optimize energy consumption.

[0005] The purpose of the present invention can be achieved by the following technical solutions:

[0006] A method for early warning of overall energy consumption in urban tunnels, comprising the following steps:

[0007] The structural parameters of urban tunnels are obtained, and a reasonable electricity consumption prediction model is constructed based on these structural parameters to obtain the reasonable electricity consumption under the current structural parameters. Based on the reasonable electricity consumption under the current structural parameters and the corresponding actual tunnel electricity consumption, an electricity consumption rationality index is obtained, and then threshold division is performed to determine the electricity consumption rationality score of the urban tunnel.

[0008] From the various electricity meters within the urban tunnel, meters with electricity rate policies including basic electricity rate, peak electricity rate, normal electricity rate, and off-peak electricity rate were selected as the meters to be tested. The basic electricity rate and the combined peak, flat, and off-peak unit price of all the meters to be tested were obtained, and thresholds were used to determine the electricity distribution balance score of the urban tunnel.

[0009] Based on the obtained power consumption rationality score and power distribution balance score, the comprehensive energy consumption score of the urban tunnel is obtained. If the score is lower than the preset warning threshold, the energy consumption of the urban tunnel is optimized.

[0010] Furthermore, the reasonable electricity consumption prediction model includes the sum, square sum and product sum of each variable in the structural parameters.

[0011] Furthermore, the structural parameters include tunnel length, cross-sectional area and installation capacity, and the expression of the reasonable power consumption prediction model is:

[0012]

[0013] Where y is the predicted result of reasonable electricity consumption, x1 is the tunnel length, x2 is the cross-sectional area, x3 is the connection capacity, and a, b, …, j are all model parameters. All model parameters are adjustable parameters and are set based on big data analysis.

[0014] Furthermore, the reasonable electricity consumption prediction model further includes correcting the monthly reasonable electricity consumption prediction result y according to the monthly basis, and the calculation expression of the corrected reasonable electricity consumption is:

[0015] y p =k0*y

[0016] Where y p is the corrected reasonable electricity consumption, and k0 is the monthly correction coefficient.

[0017] Furthermore, the calculation expression of the power consumption rationality index is:

[0018]

[0019] Where, ECI is the electricity consumption rationality index, y a This is the actual electricity consumption of urban tunnels.

[0020] Furthermore, the calculation expression of the unit basic electricity fee is:

[0021] z1=a0.y0

[0022] y0=x0 / x

[0023] x=x1+x2+x3

[0024] Where z1 is the unit basic electricity charge, a0 is the basic weight coefficient, y0 is the unit basic electricity consumption, x0 is the basic electricity consumption, the basic electricity consumption is the sum of the basic electricity consumption of all the meters to be tested, x is the total electricity, x1 is the peak electricity, which is the sum of the peak electricity of all the meters to be tested; x2 is the average electricity, which is the sum of the average electricity of all the meters to be tested; x3 is the valley electricity, which is the sum of the valley electricity of all the meters to be tested.

[0025] Furthermore, the calculation expression of the peak, flat and valley comprehensive unit price is:

[0026] z2=a1.y1+a2.y2+a3.y3

[0027]

[0028]

[0029]

[0030] Wherein, z2 is the comprehensive unit price of peak, flat and valley electricity; a1, a2 and a3 are comprehensive weight coefficients; y1 is the unit peak converted electricity; y2 is the unit flat converted electricity; y3 is the unit valley converted electricity; k1, k2 and k3 are seasonal reduction coefficients, which are adjusted according to the season; x1 is the peak electricity, which is the sum of the peak electricity of all the meters to be tested; x2 is the flat electricity, which is the sum of the flat electricity of all the meters to be tested; x3 is the valley electricity, which is the sum of the valley electricity of all the meters to be tested.

[0031] Furthermore, after obtaining the unit basic electricity fee and the peak-flat-valley comprehensive unit price, thresholds are set for the unit basic electricity fee and the peak-flat-valley comprehensive unit price, respectively, to determine the unit basic electricity fee score and the peak-flat-valley comprehensive unit price score. The weights of the unit basic electricity fee score and the peak-flat-valley comprehensive unit price score are then obtained to obtain the electricity consumption distribution balance score of the urban tunnel.

[0032] The calculation expression for the weight of the unit basic electricity fee score and the peak, flat and valley comprehensive unit price score is:

[0033] W1=z1 / (z1+z2)

[0034] W2=z2 / (z1+z2)

[0035] Where W1 is the unit basic electricity charge score weight, W2 is the peak-flat-valley comprehensive unit price score weight, z1 is the unit basic electricity charge, and z2 is the peak-flat-valley comprehensive unit price;

[0036] The calculation expression of the electricity distribution balance score is:

[0037] EDI=z1*W1+z2*W2

[0038] Where EDI is the electricity distribution balance score.

[0039] Furthermore, the comprehensive energy consumption score is a weighted sum of a reasonable electricity consumption score and a balanced electricity consumption distribution score.

[0040] The present invention also provides an urban tunnel overall energy consumption early warning system, comprising a memory and a processor, wherein the memory stores a computer program, and the processor calls the computer program to execute the steps of the above-mentioned method.

[0041] Compared with the prior art, the present invention has the following advantages:

[0042] (1) The present invention predicts reasonable electricity consumption based on the structural parameters of urban tunnels, and compares it with the actual tunnel electricity consumption to conduct electricity consumption rationality analysis; based on the basic electricity fee that can reflect the degree of concentrated opening of high-power equipment in the tunnel, and the peak, flat and valley electricity fees that reflect the electricity distribution of the tunnel, the electricity balance analysis is conducted; from a holistic perspective, both the tunnel electricity consumption and the electricity consumption behavior are taken into account, and an overall assessment of the energy consumption of urban tunnels is achieved, which can timely discover the energy consumption problems of urban tunnels and make timely optimization.

[0043] (2) In the analysis of the rationality of electricity consumption, the present invention comprehensively considers factors such as tunnel length, cross-sectional area, service life, equipment capacity, personnel, vehicles, and management room area, and conducts correlation analysis to extract key influencing factors. For the key influencing factors, the quadratic polynomial fitting method is adopted, taking into account the sum of multiple variables, the sum of products between multiple variables, and the sum of squares of multiple variables, and comprehensively measures the overall level of multiple variables, the interaction between variables, and the degree of discreteness of variables, so as to achieve accurate prediction of reasonable electricity consumption. BRIEF DESCRIPTION OF THE DRAWINGS

[0044] Figure 1 The figure is a flow chart of a method for early warning of overall energy consumption in urban tunnels provided in an embodiment of the present invention. DETAILED DESCRIPTION

[0045] To make the objectives, technical solutions, and advantages of the embodiments of the present invention more clear, the technical solutions of the embodiments of the present invention will be clearly and completely described below in conjunction with the accompanying drawings of 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. Generally, the components of the embodiments of the present invention described and shown in the drawings herein can be arranged and designed in various different configurations.

[0046] Therefore, the following detailed description of the embodiments of the present invention provided in the accompanying drawings is not intended to limit the scope of the invention as claimed, but rather merely represents selected embodiments of the present invention. All other embodiments derived by persons of ordinary skill in the art based on the embodiments of the present invention without creative effort shall fall within the scope of protection of the present invention.

[0047] It should be noted that similar reference numerals and letters denote similar items in the following drawings, and therefore, once an item is defined in one drawing, it does not need to be further defined or explained in subsequent drawings.

[0048] Example 1

[0049] like Figure 1 As shown, this embodiment provides a method for early warning of overall energy consumption in urban tunnels, comprising the following steps:

[0050] S1: Collect and summarize the structural parameters of urban tunnels, then build a reasonable power consumption prediction model based on these structural parameters to obtain the reasonable power consumption under the current structural parameters. Based on the reasonable power consumption under the current structural parameters and the corresponding actual tunnel power consumption, the power consumption rationality index is obtained, and then thresholds are divided to determine the power consumption rationality score of the urban tunnel.

[0051] S2: Based on the electricity billing data types of existing electricity consumption policies (data sourced from State Grid electricity bills), the data is divided into basic electricity charges, peak-hour electricity charges, normal-hour electricity charges, and off-peak electricity charges. Meters from various devices using these electricity billing data types are used as test meters. Meter electricity usage data is collected to obtain the overall basic electricity charge and peak-, normal-, and off-peak combined unit prices for all test meters. This is used to determine thresholds and determine the electricity distribution balance score for urban tunnels.

[0052] S3: Based on the obtained power consumption rationality score and power distribution balance score, the comprehensive energy consumption score of the urban tunnel is obtained. If the score is lower than the preset warning threshold, the energy consumption of the urban tunnel is optimized.

[0053] Step S1 is used to analyze the rationality of power consumption, and the specific process includes:

[0054] 1.1 Analysis of factors affecting electricity consumption

[0055] Tunnels vary significantly in length, area, and electromechanical equipment capacity, making it difficult to directly compare energy consumption across different tunnels. To facilitate this comparison, comprehensive consideration should be given to factors such as tunnel length, cross-sectional area, service life, equipment capacity, personnel, vehicles, and administrative space. By considering these key factors, a reasonable electricity consumption prediction model was developed to estimate reasonable electricity consumption for different tunnels. The predicted reasonable electricity consumption was then compared with actual electricity consumption to quantitatively determine the reasonableness of the tunnel's electricity consumption.

[0056] Regarding factors influencing electricity consumption, we considered that electricity consumption may be related to factors such as the installed capacity of tunnel equipment, total length, cross-sectional area, traffic volume, number of vehicles, personnel, design flow rate, and service life. Correlation analysis of these factors revealed a significant correlation between equipment capacity, length, cross-sectional area, and electricity consumption. Therefore, these three parameters were selected for further regression analysis.

[0057] 1.2 Reasonable electricity consumption forecast

[0058] After eliminating abnormal fluctuations, the monthly electricity consumption of the 12 tunnels in 2020 was plotted against tunnel length, cross-sectional area, and equipment capacity. Polynomial fitting was used to better reflect the changing trend of the scatter plot. Therefore, a quadratic polynomial fitting was used to construct a reasonable electricity consumption prediction model:

[0059]

[0060] Where y is the predicted result of reasonable electricity consumption, x1 is the tunnel length, x2 is the cross-sectional area, x3 is the connection capacity, and a, b, …, j are all model parameters. All model parameters are adjustable parameters and are set based on big data analysis.

[0061] This embodiment performs multivariate nonlinear regression and obtains the parameters shown in Table 1, R 2 It is 0.893, indicating that these three parameters can accurately fit 89.3% of all electricity consumption data, and the multivariate nonlinear fitting effect is good.

[0062] Table 1 Parameter estimates

[0063]

[0064] The formula after multivariate nonlinear fitting is as follows:

[0065] Y=-181608*X1-220.474*X2-50.466*X3+19177.31*X1 2 +0.92*X2 2 -0.007*X 32 -177.372*X1*X2+11.045*X1*X3+0.034*X2*X3+907202.2

[0066] Considering that the electricity consumption of tunnels in different months is slightly different, the predicted value obtained by the above formula does not take into account the difference between months. Therefore, based on the actual difference in electricity consumption in different months of the year, a monthly reduction coefficient k is introduced. The reasonable electricity consumption after considering seasonal factors is taken as the reasonable electricity consumption y of each tunnel. p , the calculation expression of the corrected reasonable power consumption is:

[0067] y p =k0*y

[0068] Where y p is the corrected reasonable electricity consumption, and k0 is the monthly correction coefficient, as shown in Table 2.

[0069] Table 2

[0070]

[0071] 1.3. Electricity consumption evaluation

[0072] Based on the actual conditions of different tunnels, a relatively reasonable electricity consumption forecast value is customized, and the actual electricity consumption each month is compared with the reasonable forecast value. Different electricity consumption scores are given according to the distribution of actual deviations.

[0073] An electricity consumption index (ECI) is established to determine whether a tunnel's electricity consumption is low or high. An ECI greater than 0 indicates that actual electricity consumption is less than a reasonable forecast, presumably indicating low electricity consumption. An ECI equal to 0 indicates that actual electricity consumption is equal to a reasonable forecast. An ECI less than 0 indicates that actual electricity consumption is greater than a reasonable forecast, presumably indicating high electricity consumption.

[0074] The calculation expression of the reasonable power consumption index is:

[0075]

[0076] Where, ECI is the electricity consumption rationality index, y a This is the actual electricity consumption of urban tunnels.

[0077] According to the above formula, the ECI index of all tunnels is calculated.

[0078] Step S2 is used to perform power consumption balance analysis, and the specific process includes:

[0079] 2.1 Analysis of electricity fee structure

[0080] The main consideration is the two-part electricity billing method, where the total electricity bill = basic electricity bill + peak electricity bill + normal electricity bill + off-peak electricity bill + adjusted electricity bill.

[0081] The basic electricity charge can reflect the extent to which high-power equipment is concentratedly turned on in the tunnel, and the peak, flat and valley electricity charges can reflect the electricity distribution and staggered electricity consumption in the tunnel during peak, flat and valley periods.

[0082] Considering the significant variations in electricity consumption across tunnels, a unified evaluation standard was established, taking into account the differences between the basic electricity fee and peak, flat, and off-peak electricity rates per unit of electricity consumption. This means the rationality and balance of electricity consumption across tunnels is measured using the basic unit electricity fee (basic electricity fee / electricity consumption) and the combined peak, flat, and off-peak electricity price (peak, flat, and off-peak electricity fee / electricity consumption). The sum of the basic unit electricity fee and the combined peak, flat, and off-peak electricity price gives the unit price per kilowatt-hour (total electricity fee / total electricity consumption), reflecting the combined price taking into account the basic unit electricity fee and peak, flat, and off-peak electricity rates.

[0083] 2.2. Basic electricity fee per unit

[0084] The unit basic electricity fee (basic electricity fee / electricity consumption) reflects the concentration of high-power equipment in each tunnel. The lower the unit basic electricity fee, the less high-power equipment is concentrated in the tunnel under the same electricity consumption.

[0085] The calculation expression of unit basic electricity cost is:

[0086] z1=a0·y0

[0087] y0=x0 / x

[0088] x=x1+x2+x3

[0089] Where z1 is the unit basic electricity charge, a0 is the basic weight coefficient, y0 is the unit basic electricity consumption, x0 is the basic electricity consumption, the basic electricity consumption is the sum of the basic electricity consumption of all the meters to be tested, x is the total electricity, x1 is the peak electricity, which is the sum of the peak electricity of all the meters to be tested; x2 is the average electricity, which is the sum of the average electricity of all the meters to be tested; x3 is the valley electricity, which is the sum of the valley electricity of all the meters to be tested.

[0090] 2.3. Comprehensive unit price for peak, flat and valley periods

[0091] The comprehensive unit price of peak, flat and valley periods can reflect the electricity distribution of each tunnel during peak, flat and valley periods. The smaller the comprehensive unit price of peak, flat and valley periods, the better the staggered electricity consumption in the tunnel and the more reasonable the electricity consumption.

[0092] Considering the different total durations of peak, flat, and off-peak periods in summer and non-summer, even if peak, flat, and off-peak electricity consumption are the same and electricity consumption is balanced, the combined peak, flat, and off-peak price in summer is higher than in non-summer. Therefore, the scoring criteria have been adjusted accordingly based on actual conditions.

[0093] The calculation expression of the peak, flat and valley comprehensive unit price is:

[0094] z2=a1.y1+a2.y2+a3.y3

[0095]

[0096]

[0097]

[0098] Wherein, z2 is the comprehensive unit price of peak, flat and valley electricity; a1, a2 and a3 are comprehensive weight coefficients; y1 is the unit peak converted electricity; y2 is the unit flat converted electricity; y3 is the unit valley converted electricity; k1, k2 and k3 are seasonal reduction coefficients, which are adjusted according to the season; x1 is the peak electricity, which is the sum of the peak electricity of all the meters to be tested; x2 is the flat electricity, which is the sum of the flat electricity of all the meters to be tested; x3 is the valley electricity, which is the sum of the valley electricity of all the meters to be tested.

[0099] 2.4. Electricity Consumption Balance Evaluation

[0100] On the one hand, the degree of concentrated activation of high-power equipment needs to be considered in the balance of electricity consumption. On the other hand, the staggered electricity consumption during peak, flat and valley periods needs to be considered. Therefore, the basic unit electricity charge score and the comprehensive unit price score during peak, flat and valley periods are used to measure the balance of electricity consumption in the tunnel.

[0101] After obtaining the basic unit electricity fee and the peak-, flat-, and valley-level combined unit price, thresholds are applied to each of these two prices, determining the basic unit electricity fee score and the peak-, flat-, and valley-level combined unit price score. The weights of these scores are then used to determine the electricity consumption distribution balance score for urban tunnels.

[0102] Considering that different tunnels have different proportions of basic electricity charges and peak, flat, and off-peak electricity charges, and thus have different impacts on electricity charges, dynamic weights W1 and W2 are set. The weights are dynamically adjusted based on the actual electricity consumption structure of the tunnel that month:

[0103] W1=z1 / (z1+z2)

[0104] W2=z2 / (z1+z2)

[0105] Where W1 is the unit basic electricity charge score weight, W2 is the peak-flat-valley comprehensive unit price score weight, z1 is the unit basic electricity charge, and z2 is the peak-flat-valley comprehensive unit price;

[0106] The calculation expression of the electricity distribution balance score is:

[0107] EDI=z1*W1+z2*W2

[0108] Where EDI is the electricity distribution balance score.

[0109] Step S3 is used to evaluate the power consumption, and the specific process includes:

[0110] A comprehensive evaluation index for electricity consumption was established by comprehensively considering both the rationality and balance of electricity consumption. Rationality reflects the tunnel's electricity consumption, while balance reflects electricity usage behavior. Comprehensive energy consumption evaluation was performed using the following formula.

[0111] The comprehensive score of electricity consumption = 0.6*electricity consumption rationality score + 0.4*electricity consumption balance score.

[0112] Example 2

[0113] This embodiment provides an urban tunnel overall energy consumption early warning system, including a memory and a processor. The memory stores a computer program, and the processor calls the computer program to execute the steps of the method described in Example 1.

[0114] The above describes in detail the preferred embodiments of the present invention. It should be understood that those skilled in the art can make numerous modifications and variations based on the concepts of the present invention without inventive effort. Therefore, any technical solutions that can be derived by those skilled in the art through logical analysis, reasoning, or limited experimentation based on the concepts of the present invention and the prior art should be within the scope of protection defined by the claims.

Claims

1. A method for early warning of overall energy consumption in urban tunnels, characterized in that: The following steps are involved: Obtain the structural parameters of urban tunnels, and build a reasonable power consumption prediction model based on the structural parameters to obtain the reasonable power consumption under the current structural parameters; Based on the reasonable power consumption under the current structural parameters and the corresponding actual tunnel power consumption, the power consumption rationality index is obtained, and then threshold division is performed to determine the power consumption rationality score of the urban tunnel; From the various electricity meters within the urban tunnel, meters with electricity rate policies including basic electricity rate, peak electricity rate, normal electricity rate, and off-peak electricity rate were selected as the meters to be tested. The basic electricity rate and the combined peak, flat, and off-peak unit price of all the meters to be tested were obtained, and thresholds were used to determine the electricity distribution balance score of the urban tunnel. Based on the obtained power consumption rationality score and power distribution balance score, the comprehensive energy consumption score of the urban tunnel is obtained. If the score is lower than the preset warning threshold, the energy consumption of the urban tunnel is optimized; The structural parameters include tunnel length, cross-sectional area and connection capacity. The expression of the reasonable power consumption prediction model is: Where, For reasonable power consumption prediction results, is the tunnel length, is the cross-sectional area, For the installation capacity, 、 、…、 These are all model parameters. Each model parameter is an adjustable parameter and is set based on big data analysis. The reasonable electricity consumption prediction model also includes the monthly reasonable electricity consumption prediction results based on the monthly After correction, the calculation expression of reasonable power consumption is: Where, is the corrected reasonable electricity consumption, is the monthly correction factor; The calculation expression of the reasonable power consumption index is: Where, is the reasonable index of electricity consumption, This is the actual electricity consumption of urban tunnels.

2. The method for early warning of overall energy consumption in urban tunnels according to claim 1, characterized in that: The reasonable electricity consumption prediction model includes the sum, square sum and product sum of each variable in the structural parameters.

3. The method for early warning of overall energy consumption in urban tunnels according to claim 1, characterized in that: The calculation expression of the unit basic electricity fee is: = / x x= + + Where, The basic electricity fee for the unit, is the basic weight coefficient, is the basic electricity consumption of the unit, is the basic power consumption, which is the sum of the basic power consumption of all the meters to be tested, x is the total power consumption, is the peak power, which is the sum of the peak power of all the meters to be tested; is the average power, which is the sum of the average power of all the meters to be tested; is the valley power, which is the sum of the valley power of all the meters to be tested.

4. The method for early warning of overall energy consumption in urban tunnels according to claim 1, characterized in that: The calculation expression of the peak, flat and valley comprehensive unit price is: Where, The comprehensive unit price of peak, flat and valley, 、 、 is the comprehensive weight coefficient, is the unit peak converted electricity, The unit is the converted electricity quantity. is the unit valley electricity conversion, 、 、 is the seasonal reduction factor, which is adjusted according to the season. is the peak power, which is the sum of the peak power of all the meters to be tested; is the average power, which is the sum of the average power of all the meters to be tested; is the valley power, which is the sum of the valley power of all the meters to be tested.

5. The method for early warning of overall energy consumption in urban tunnels according to claim 1, characterized in that: After obtaining the basic unit electricity fee and the peak-, flat-, and valley-level combined unit price, thresholds are applied to each of these two prices, determining the basic unit electricity fee score and the peak-, flat-, and valley-level combined unit price score. The weights of these scores are then used to determine the electricity consumption distribution balance score for urban tunnels. The calculation expression for the weight of the unit basic electricity fee score and the peak, flat and valley comprehensive unit price score is: W1= / ( + ) W2= / ( + ) Where W1 is the unit basic electricity fee score weight, W2 is the peak, flat and valley comprehensive unit price score weight, The basic electricity fee for the unit, The comprehensive unit price of peak, flat and valley; The calculation expression of the electricity distribution balance score is: Where, Score for the balance of electricity distribution.

6. The method for early warning of overall energy consumption in urban tunnels according to claim 1, characterized in that: The comprehensive energy consumption score is the weighted sum of the reasonable electricity consumption score and the balanced electricity distribution score.

7. An urban tunnel overall energy consumption early warning system, characterized in that: The method comprises a memory and a processor, wherein the memory stores a computer program, and the processor calls the computer program to execute the steps of any one of the methods according to claims 1 to 6.

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