An intelligent identification method for energy efficiency services

Abstract

The present invention discloses an intelligent identification method for energy efficiency services, which includes: step S10, collecting service information of selected energy-consuming enterprises; step S11, performing energy consumption diagnosis and analysis based on the service information of the enterprises and obtaining diagnosis suggestions, where the energy consumption diagnosis and analysis at least includes: quantity, price, cost, load, equipment energy efficiency, peak-valley ratio, and power factor adjustment analysis and diagnosis; step S12, according to the diagnosis suggestion conclusion obtained above, using a preset electric energy substitution algorithm to perform replacement calculation on at least some of the energy-consuming equipment in the enterprises, analyzing the corresponding data after electric energy substitution, and forming a corresponding electric energy substitution report. Implementing the present invention can conveniently perform optimization analysis according to the energy consumption situation of enterprises and automatically obtain the expected results after electric energy substitution.

Description

Technical Field

[0001] The present invention relates to the technical field of carbon emission analysis in the power industry, and particularly to an intelligent identification method for energy efficiency services. Background Art

[0002] The year 2021 is a crucial year for promoting the work of carbon peak and carbon neutrality goals. Under the grand proposition of the "dual carbon" goals, foreign enterprises have turned their attention to China's low-carbon economy. "China is the first developing country to commit to carbon emission peaks, which is a milestone event in the global process of addressing climate change.

[0003] As the basic unit of social composition, enterprises undertake the important tasks of creating material wealth and promoting social development. At the same time, as social producers that utilize energy and emit waste, enterprises are the main bodies of energy conservation and emission reduction and also shoulder the social responsibility of energy conservation and emission reduction that cannot be shirked. How to ensure production while achieving energy conservation and emission reduction is also an important issue that enterprises are actively thinking about. How to quickly obtain an optimized electricity substitution plan based on the energy consumption situation of enterprises has become an urgent issue to be solved by enterprises. Summary of the Invention

[0004] The technical problem to be solved by the present invention is to provide an intelligent identification method for energy efficiency services, which can adopt an electricity substitution model algorithm, conveniently conduct optimization analysis according to the energy consumption situation of enterprises, and automatically obtain the expected results after electricity substitution.

[0005] To solve the above technical problem, the present invention provides an intelligent identification method for energy efficiency services, which includes the following steps:

[0006] Step S10, collecting service information of selected energy-consuming enterprises, where the service information at least includes the basic information of the enterprises, energy-consuming equipment information, and energy consumption situation information; among them, the basic information includes: ownership of housing property rights, industry category, building floor area, available roof area; the energy-consuming equipment information includes: type of energy-consuming equipment, number of energy-consuming equipment, estimated monthly and annual energy consumption; the energy consumption situation information includes energy consumption type, monthly and annual consumption of the energy consumption type;

[0007] Step S11, conducting energy consumption diagnosis and analysis based on the service information of the enterprises and obtaining a diagnosis and recommendation conclusion, where the energy consumption diagnosis and analysis at least includes: quantity-price-fee, load, equipment energy efficiency, peak-valley-flat ratio, and power adjustment analysis diagnosis;

[0008] Step S12: According to the obtained diagnostic advice conclusion mentioned above, use a preset electricity substitution algorithm to perform replacement calculations on at least some of the energy-consuming devices in the enterprise, analyze the corresponding data after electricity substitution, and form a corresponding electricity substitution report. The electricity substitution report includes at least: theoretical substitution potential, actual substitution potential, expected new installation capacity, total investment, and carbon emission data.

[0009] Preferably, step S11 further includes:

[0010] Step S110: Analyze the quantity, price, and fees, compare the power factor adjustment electricity fee, basic electricity fee, and kilowatt-hour electricity fee of this month with the corresponding fees of last month, and determine the item with the largest volatility as the item with the largest affected rate.

[0011] Step S111: Analyze the operation status and duration of the enterprise's transformers, determine the load status of the enterprise's transformers, and obtain corresponding countermeasure suggestions.

[0012] Step S112: Conduct equipment energy efficiency analysis, compare the types of energy-consuming devices involved in the enterprise with the expected annual energy consumption and the industry average level, and determine the energy consumption level description. The types of energy-consuming devices include: lighting, refrigeration, HVAC, cleaning equipment, cooking stoves, heat pumps, boilers, production equipment, office equipment, and others.

[0013] Step S113: Determine the data of the peak period ratio according to the time of day when the energy is used. If it is determined that the peak period ratio is not the lowest: it is recommended to reasonably arrange the living electricity usage time, appropriately increase the electricity consumption ratio during the valley period and the normal period, and reduce the electricity consumption during the peak period, so as to save electricity expenses; when the peak period ratio is the lowest, it is recommended to maintain the living electricity usage time to save electricity expenses.

[0014] Step S114: Conduct power factor adjustment analysis, judge according to the power factor standard and the user's monthly power factor, and determine whether the enterprise does not exceed the standard or reaches the standard.

[0015] Preferably, step S111 further includes:

[0016] Determine the number of days of light load, heavy load, and normal operation of the enterprise's transformers per month.

[0017] Compare the three numbers of days. If the number of light load days is the largest, it is determined that the enterprise's transformer is in a low load state; if the number of heavy load days or normal days is the largest, it is determined that the enterprise's transformer is in a high load state.

[0018] For the enterprise in a high load state, it is recommended that the enterprise handle the capacity / demand change business online to save electricity costs; for the enterprise in a low load state, maintain the load state to maintain electricity costs.

[0019] Preferably, step S12 further includes:

[0020] Step S120, determining all non - electrical energy equipment and corresponding data in the enterprise;

[0021] Step S121, replacing the non - electrical energy equipment with electrical equipment, using a preset electrical energy substitution algorithm to calculate corresponding parameters after at least part of the equipment in the enterprise is replaced with electrical equipment, and obtaining data such as theoretical substitution potential, actual substitution potential, expected new installed capacity, total investment, and carbon emission reduction amount;

[0022] Step S122, automatically generating an electrical energy substitution report based on the calculated data.

[0023] Preferably, step S121 further includes:

[0024] Step S1210, calculating the theoretical substitution potential according to the following formula:

[0025] Theoretical substitution potential = ∑ (substitution coefficient of each type * quantity * expected annual energy consumption * replacement intention);

[0026] Among them, gasoline - to - electricity substitution potential = gasoline - to - electricity coefficient * quantity * expected annual energy consumption * replacement intention;

[0027] Diesel - to - electricity substitution potential = diesel - to - electricity coefficient * quantity * expected annual energy consumption * replacement intention;

[0028] Natural gas - to - electricity substitution potential = natural gas - to - electricity coefficient * quantity * expected annual energy consumption * replacement intention;

[0029] Purchased hot water - to - electricity substitution potential = hot water - to - electricity coefficient * quantity * expected annual energy consumption * replacement intention;

[0030] Purchased steam - to - electricity substitution potential = steam - to - electricity coefficient * quantity * expected annual energy consumption * replacement intention;

[0031] Coal - to - electricity formula substitution potential = coal - to - electricity coefficient * quantity * expected annual energy consumption * replacement intention;

[0032] The replacement intention is defaulted to 1. If a certain type of equipment does not need to be replaced, the replacement intention is 0.

[0033] Step S1211, calculating the actual substitution potential through the following formula:

[0034] Actual substitution potential = theoretical substitution potential * substitution completion degree / 100;

[0035] Step S1212, calculating the expected new installed capacity through the following formula:

[0036] Expected additional capacity = Theoretical replacement potential / (365 * 24 * Power factor);

[0037] Among them, the power factor is taken as 0.8;

[0038] Step S1213, calculate the total investment through the following formula:

[0039] Total investment: Service expansion cost + Actual replacement potential * Electricity price * 5 years

[0040] Among them, the service expansion cost = Total capacity after change * Service expansion unit price; The total capacity is the sum of the original capacity and the expected additional capacity; The service expansion unit price is obtained by querying the corresponding relationship between the service expansion unit price and the voltage level, and the corresponding relationship is pre-calibrated;

[0041] Step S1214, calculate the reduced CO2 emissions according to the following formula:

[0042] CO2 emission reduction from gasoline to electricity = Gasoline-to-oil emission reduction coefficient * Quantity * Expected annual energy consumption * Replacement intention;

[0043] CO2 emission reduction from diesel to electricity = Diesel-to-electricity emission reduction coefficient * Quantity * Expected annual energy consumption * Replacement intention;

[0044] CO2 emission reduction from natural gas to electricity = Natural gas-to-electricity emission reduction coefficient * Quantity * Expected annual energy consumption * Replacement intention;

[0045] CO2 emission reduction from purchased hot water to electricity = Hot water-to-electricity emission reduction coefficient * Quantity * Expected annual energy consumption * Replacement intention;

[0046] CO2 emission reduction from purchased steam to electricity = Steam-to-electricity emission reduction coefficient * Quantity * Expected annual energy consumption * Replacement intention;

[0047] CO2 emission reduction from coal to electricity = Coal-to-electricity emission reduction coefficient * Quantity * Expected annual energy consumption * Replacement intention;

[0048] The replacement intention is defaulted to 1. If a certain type of equipment does not need to be replaced, the replacement intention is 0.

[0049] Implementing the embodiments of the present invention has the following beneficial effects:

[0050] The present invention provides an intelligent identification method for energy efficiency services. By designing an electric energy substitution model algorithm, it can conveniently perform optimization analysis according to the energy consumption situation of enterprises and automatically obtain the expected results after electric energy substitution; Enterprises can also thereby optimally adjust the equipment that needs to perform electric energy substitution to achieve the balance between the social responsibility and cost control of the enterprise. Description of the Drawings

[0051] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the following will briefly introduce the drawings required for the description of the embodiments or the prior art. Obviously, the drawings in the following description are only some embodiments of the present invention. For those of ordinary skill in the art, without creative efforts, obtaining other drawings based on these drawings still belongs to the scope of the present invention.

[0052] Figure 1 It is a schematic diagram of the main process of an embodiment of an intelligent identification method for energy efficiency services provided by the present invention. Detailed implementation manners

[0053] To make the objectives, technical solutions and advantages of the present invention clearer, the present invention will be further described in detail below with reference to the drawings.

[0054] As Figure 1 shown, it shows a schematic diagram of the main process of an embodiment of an intelligent identification method for energy efficiency services provided by the present invention. In this embodiment, the method includes the following steps:

[0055] Step S10, collect service information of selected energy-consuming enterprises, where the service information at least includes basic information of the enterprises, energy-consuming equipment information, and energy consumption situation information; among them, the basic information includes: ownership of housing property rights, industry category, building area of the house, available area of the roof; the energy-consuming equipment information includes: type of energy-consuming equipment, number of energy-consuming equipment, estimated monthly and annual energy consumption; the energy consumption situation information includes type of energy consumption, monthly and annual consumption of the type of energy consumption;

[0056] More specifically, this collection process can be achieved by each enterprise registering and reporting through the census APP actively.

[0057] Step S11, perform energy consumption diagnosis and analysis based on the service information of the enterprise and obtain a diagnosis and suggestion conclusion, where the energy consumption diagnosis and analysis at least includes: analysis of quantity, price, and cost, load, energy efficiency of equipment, peak-valley-flat ratio, and power factor adjustment analysis and diagnosis;

[0058] In a specific example, step S11 further includes:

[0059] Step S110, analyze the quantity, price, and cost, compare the power factor adjustment electricity fee, basic electricity fee, and kilowatt-hour electricity fee this month with the corresponding fees of last month, and determine the item with the largest volatility as the item with the largest impact rate;

[0060] Step S111, analyze the operation status and duration of the enterprise's transformer, determine the load status of the enterprise's transformer, and obtain corresponding countermeasures and suggestions;

[0061] Specifically, in one example, step S111 further includes:

[0062] Determine the number of lightly loaded days, heavily loaded days, and normal days of the enterprise's transformers per month;

[0063] Compare the three numbers of days. If the number of lightly loaded days is the largest, determine that the enterprise's transformer is in a low-load state; if the number of heavily loaded days or normal days is the largest, determine that the enterprise's transformer is in a high-load state;

[0064] For the enterprise in a high-load state, it is recommended that the enterprise handle the capacity / demand change business online to save electricity costs; for the enterprise in a low-load state, establish and maintain the load state to maintain electricity costs.

[0065] Step S112, conduct equipment energy efficiency analysis, compare the types of energy-consuming equipment involved in the enterprise with the expected annual energy consumption and the industry average level, and determine the described energy consumption grade; the types of energy-consuming equipment include: lighting, refrigeration, HVAC, cleaning equipment, cooking appliances, heat pumps, boilers, production equipment, office equipment, and others;

[0066] Step S113, determine the data of the peak period proportion according to the time of day when the energy is used. If it is determined that the peak period proportion is not the lowest: it is recommended to reasonably arrange the time of domestic electricity use, appropriately increase the electricity consumption proportion during the valley period and the normal period, and reduce the electricity consumption during the peak period, so as to save electricity expenses; when the peak period proportion is the lowest, it is recommended to maintain the time of domestic electricity use to save electricity expenses.

[0067] Step S114, conduct power factor adjustment analysis, judge according to the power factor standard and the user's monthly power factor, and determine whether the enterprise does not exceed the standard or reaches the standard.

[0068] Step S12, according to the obtained diagnosis and recommendation conclusions, use a pre-set electric energy substitution algorithm to perform replacement calculations on at least some of the energy-consuming equipment in the enterprise, analyze the corresponding data after electric energy substitution, and form a corresponding electric energy substitution report. The electric energy substitution report at least includes: theoretical substitution potential, actual substitution potential, expected new installed capacity, total investment, and carbon emission data.

[0069] In a specific example, step S12 further includes:

[0070] Step S120, determine all non-electric energy equipment in the enterprise and the corresponding data;

[0071] Step S121: Replace the non-electric energy equipment with electric equipment, and use a pre-set electric energy substitution algorithm to calculate the corresponding parameters after at least partial replacement of the enterprise's equipment with electric equipment, so as to obtain data on theoretical substitution potential, actual substitution potential, expected new installation capacity, total investment, and carbon emission reduction volume.

[0072] More specifically, step S121 further includes:

[0073] Step S1210: Calculate the theoretical substitution potential according to the following formula:

[0074] Theoretical substitution potential = ∑ (substitution coefficient of each type * quantity * expected annual average energy consumption * replacement intention);

[0075] Among them, the unit of the theoretical substitution potential is 10,000 kWh / year. The substitution coefficients of each type are the conversion coefficients between various non-electric energy equipment replaced with electric energy equipment. The quantity is the quantity of the equipment, and the expected annual average energy consumption is the expected annual average energy consumption of the first equipment, which is derived from the corresponding historical data (such as the average). Specifically, the following introduces the calculation methods for the substitution potential of various non-electric energy equipment:

[0076] Among them, the substitution potential of gasoline to electricity = gasoline-to-electricity coefficient * quantity * expected annual average energy consumption * replacement intention; among them, the gasoline-to-electricity coefficient is: 1 * 1.4714 / (1355 * 1.229); it can be understood that 1 ton of gasoline is equal to 1.4714 tons of standard coal, and 1 ton of gasoline is equal to 1355 liters; 10,000 kWh of electricity is equivalent to 1.229 tons of standard coal, that is, the 1.229 is the equivalent value (the same below);

[0077] The substitution potential of diesel to electricity = diesel-to-electricity coefficient * quantity * expected annual average energy consumption * replacement intention; among them, the diesel-to-electricity coefficient is: 1 * 1.4714 / (1176 * 1.229); it can be understood that 1 ton of diesel is equal to 1.4571 tons of standard coal, and 1 ton of diesel is equal to 1176 liters;

[0078] The substitution potential of natural gas to electricity = natural gas-to-electricity coefficient * quantity * expected annual average energy consumption * replacement intention, where the natural gas-to-electricity coefficient is: 1 * 1.4571 / (1176 * 1.229); it can be understood that 1 thousand cubic meters is equal to 1.33 tons of standard coal;

[0079] The substitution potential of purchased hot water to electricity = hot water-to-electricity coefficient * quantity * expected annual average energy consumption * replacement intention; the hot water-to-electricity coefficient is: 1 * 0.9 / (0.15 * 1.229); it can be understood that 1 ton of standard coal generates 150 kg of hot water (70° hot water);

[0080] The potential for replacing purchased steam with electricity = steam - to - electricity coefficient * quantity * estimated annual energy consumption * replacement intention; among which, the steam - to - electricity coefficient is: 1 * 0.83 * 0.9 / (1000 * 7 * 1.229); it can be understood that the density of water vapor is 0.8035 kg / m³, 1 ton of steam = 1000 / 0.8035 = 1244.6 m³, and 1 ton of coal generates 7 tons of steam.

[0081] The potential for replacing coal with electricity in the formula = coal - to - electricity coefficient * quantity * estimated annual energy consumption * replacement intention, among which, the coal - to - electricity coefficient is: 1 / 1.229 * 0.9; it can be understood that 10,000 kWh of electricity is equivalent to 1.229 tons of standard coal, and the equivalent coefficient of 0.1229 is uniformly adopted, 0.9 tons of standard coal / ton.

[0082] Among which, the replacement intention is defaulted to 1. If a certain type of equipment does not need to be replaced, the replacement intention is 0.

[0083] Step S1211, calculate the actual replacement potential (unit: 10,000 kWh / year) through the following formula:

[0084] Actual replacement potential = theoretical replacement potential * replacement completion rate / 100.

[0085] Step S1212, calculate the expected new capacity (unit: 10,000 kVA) through the following formula:

[0086] Expected new capacity = theoretical replacement potential / (365 * 24 * power factor);

[0087] Among which, it is statistically calculated according to 365 days and 24 hours of electricity consumption in a year, and the power factor is taken as 0.8.

[0088] Step S1213, calculate the total investment (unit: 10,000 yuan) through the following formula:

[0089] Total investment: service expansion cost + actual replacement potential * electricity price * 5 years

[0090] Among which, the service expansion cost = changed total capacity * service expansion unit price; the total capacity is the sum of the original capacity and the expected new capacity; the service expansion unit price is obtained by querying the corresponding relationship between the service expansion unit price and the voltage level, and the corresponding relationship is pre - calibrated.

[0091] In an example, the corresponding relationship is shown in the following table:

[0092] Voltage level Unit price (yuan) 10kV 168 20kV 138 35kV 94.5 110kV 52.5 220kV 21 0.38kV 231

[0093] Step S1214, calculate the reduced CO₂ emissions (unit: ton) according to the following formula:

[0094] Gasoline-to-electricity CO2 emission reduction = gasoline-to-oil emission reduction coefficient * quantity * expected annual energy consumption * replacement intention, where the gasoline-to-oil emission reduction coefficient is: 1 * 2.254 / 1000; it can be understood that one liter of gasoline emits 2.254 kilograms of carbon dioxide; the unit of CO2 emission reduction is tons (the same below);

[0095] Diesel-to-electricity CO2 emission reduction = diesel-to-electricity emission reduction coefficient * quantity * expected annual energy consumption * replacement intention; where the diesel-to-electricity emission reduction coefficient is: 1 * 2.6765 / 1000; it can be understood that one liter of diesel emits 2.6765 kilograms of carbon dioxide;

[0096] Natural gas-to-electricity CO2 emission reduction = gas-to-electricity emission reduction coefficient * quantity * expected annual energy consumption * replacement intention; where the gas-to-electricity emission reduction coefficient is: 1 * 1.96 / 1000; it can be understood that the carbon emission generated by 1 cubic meter of natural gas is 1.96 kilograms;

[0097] Purchased hot water-to-electricity CO2 emission reduction = water-to-electricity emission reduction coefficient * quantity * expected annual energy consumption * replacement intention; where the water-to-electricity emission reduction coefficient is: 2.66 * 0.9 * 1 / 0.15; it can be understood that 1 ton of standard coal generates 150 kilograms of hot water (70° hot water);

[0098] Purchased steam-to-electricity CO2 emission reduction = steam-to-electricity emission reduction coefficient * quantity * expected annual energy consumption * replacement intention; where the steam-to-electricity emission reduction coefficient is: 1 * 0.8035 * 2.62 * 0.9 / (1000 * 7); it can be understood that the steam density is 0.8035 kilograms per cubic meter, 1 ton of steam = 1000 / 0.8035 = 1244.6 cubic meters, and 1 ton of coal generates 7 tons of steam;

[0099] Coal-to-electricity CO2 emission reduction = coal-to-electricity emission reduction coefficient * quantity * expected annual energy consumption * replacement intention; the coal-to-electricity emission reduction coefficient is: 1 * 2.62 * 0.9; it can be understood that 1 ton of standard coal generates 2.66 tons of carbon dioxide;

[0100] Replacement intention: By default, it is 1. If a certain type of equipment does not need to be replaced, the replacement intention is 0.

[0101] Furthermore, in the method of the present invention, the return on investment (in percentage) can also be calculated through the following formula:

[0102] Return on investment = (1 - total investment / last year's total cost * 5) * 100;

[0103] Among them, the last year's total cost is fixed as the first year.

[0104] Step S122: Automatically generate an electric energy substitution report based on the calculated data. It should be understood that the data obtained in Steps S11 and S12 need to be included in the electric energy substitution report.

[0105] Implementing the embodiments of the present invention has the following beneficial effects:

[0106] The present invention provides an intelligent identification method for energy efficiency services. By designing an electric energy substitution model algorithm, it is convenient to perform optimization analysis based on the energy consumption situation of enterprises and automatically obtain the expected results after electric energy substitution. Enterprises can also thereby optimally adjust the equipment that needs to undergo electric energy substitution to achieve a balance between the enterprise's social responsibility and cost control.

[0107] Those skilled in the art should understand that the embodiments of the present invention can be provided as a method, apparatus, or computer program product. Therefore, the present invention can take the form of a completely hardware embodiment, a completely software embodiment, or an embodiment combining software and hardware aspects. Moreover, the present invention can take the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0108] The present invention is described with reference to the flowcharts and / or block diagrams of methods, devices (systems), and computer program products according to the embodiments of the present invention. It should be understood that each process and / or block in the flowchart and / or block diagram, as well as the combination of processes and / or blocks in the flowchart and / or block diagram, can be implemented by computer program instructions. These computer program instructions can be provided to the processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing devices to generate a machine, such that the instructions executed by the processor of the computer or other programmable data processing devices generate means for implementing the functions specified in one Figure 1 one process or multiple processes and / or blocks Figure 1 one block or multiple blocks.

[0109] The above-disclosed is only a preferred embodiment of the present invention, and of course, it cannot be used to limit the scope of the rights of the present invention. Therefore, equivalent changes made according to the claims of the present invention still fall within the scope covered by the present invention.

Claims

1. An intelligent identification method for energy efficiency services, characterized in that, It includes the following steps: Step S10, collect the service information of selected energy-consuming enterprises, where the service information at least includes the basic information of the enterprises, energy-consuming equipment information, and energy consumption situation information; among them, the basic information includes: house property ownership, industry category, building floor area of the house, available roof area; the energy-consuming equipment information includes: type of energy-consuming equipment, quantity of energy-consuming equipment, expected monthly and annual energy consumption; the energy consumption situation information includes energy consumption type, monthly and annual consumption of the energy consumption type; Step S11, conduct energy consumption diagnosis and analysis based on the service information of the enterprise and obtain diagnosis suggestions, where the energy consumption diagnosis and analysis at least includes: analysis of quantity, price, and fee, load, equipment energy efficiency, peak-valley-flat ratio, and power factor adjustment analysis and diagnosis; Step S12, according to the diagnosis suggestion conclusion obtained above, adopt a preset electric energy substitution algorithm to perform replacement calculation on some energy-consuming equipment in the enterprise, analyze the corresponding data after electric energy substitution, and form a corresponding electric energy substitution report, where the electric energy substitution report at least includes: theoretical substitution potential, actual substitution potential, expected new installed capacity, total investment, and carbon emission data; Among them, step S11 further includes: Step S110, analyze the quantity, price, and fee, compare the power factor adjustment electricity fee, basic electricity fee, and kilowatt-hour electricity fee of this month with the corresponding fees of last month, and determine the item with the largest volatility as the item with the largest affected rate; Step S111, analyze the operation status and duration of the enterprise's transformer, determine the load status of the enterprise's transformer, and obtain corresponding countermeasures; Step S112, conduct equipment energy efficiency analysis, compare the type of energy-consuming equipment involved in the enterprise and the expected annual energy consumption with the industry average level, and determine the energy consumption level description; the types of energy-consuming equipment include: lighting, refrigeration, heating, ventilation, cleaning equipment, cooking utensils, heat pumps, boilers, production equipment, office equipment, and others; Step S113, according to the time of day when the energy is used, determine the data of the peak period ratio; if it is judged that the peak period ratio is not the lowest: it is recommended to reasonably arrange the living electricity consumption time, appropriately increase the electricity consumption ratio during the valley period and the normal period, and reduce the electricity consumption during the peak period, so as to save electricity expenses; when the peak period ratio is the lowest, it is recommended to maintain the living electricity consumption time and save electricity expenses; Step S114, conduct power factor adjustment analysis, judge according to the power factor standard and the user's power factor of the current month, and determine whether the enterprise does not exceed the standard or reaches the standard.

2. The method according to claim 1, characterized in that, Step S111 further includes: Determine the number of lightly loaded days, heavily loaded days, and normal days of the enterprise's transformer per month; Compare the three numbers of days. If the number of lightly loaded days is the largest, it is determined that the enterprise's transformer is in a low load state; if the number of heavily loaded days or normal days is the largest, it is determined that the enterprise's transformer is in a high load state; For the enterprise in a high load state, it is recommended that the enterprise handle the capacity / demand change business online to save electricity costs; for the enterprise in a low load state, maintain the load state to maintain electricity costs.

3. The method according to claim 2, characterized in that, Step S12 further includes: Step S120, determine all non-electric energy equipment in the enterprise and the corresponding data; Step S121: Replace the non-electric energy equipment with electric energy equipment, and use a pre-set electric energy substitution algorithm to calculate the corresponding parameters for at least part of the enterprise's replacement with electric energy equipment, so as to obtain data such as theoretical substitution potential, actual substitution potential, expected new installed capacity, total investment, and carbon emission reduction amount; Step S122: Automatically generate an electric energy substitution report based on the calculated data.

4. The method according to claim 3, characterized in that, The said step S121 further includes: Step S1210: Calculate the theoretical substitution potential according to the following formula: Theoretical substitution potential = ∑(substitution coefficients of various types * quantity * expected annual average energy consumption * replacement intention); Among them, gasoline-to-electric substitution potential = gasoline-to-electric coefficient * quantity * expected annual average energy consumption * replacement intention; Diesel-to-electric substitution potential = diesel-to-electric coefficient * quantity * expected annual average energy consumption * replacement intention; Natural gas-to-electric substitution potential = natural gas-to-electric coefficient * quantity * expected annual average energy consumption * replacement intention; Purchased hot water-to-electric substitution potential = hot water-to-electric coefficient * quantity * expected annual average energy consumption * replacement intention; Purchased steam-to-electric substitution potential = steam-to-electric coefficient * quantity * expected annual average energy consumption * replacement intention; Coal-to-electric formula substitution potential = coal-to-electric coefficient * quantity * expected annual average energy consumption * replacement intention; The replacement intention is defaulted to 1. If a certain type of equipment does not need to be replaced, the replacement intention is 0; Step S1211: Calculate the actual substitution potential through the following formula: Actual substitution potential = theoretical substitution potential * substitution completion degree / 100; Step S1212: Calculate the expected new installed capacity through the following formula: Expected new installed capacity = theoretical substitution potential / (365 * 24 * power factor); Among them, the power factor takes a value of 0.8; Step S1213: Calculate the total investment through the following formula: Total investment: service expansion cost + actual substitution potential * electricity price * 5 years Among them, the service expansion cost = changed total capacity * service expansion unit price; the total capacity is the sum of the original capacity and the expected new installed capacity; the service expansion unit price is obtained by querying the corresponding relationship between the service expansion unit price and the voltage level, and the corresponding relationship is pre-calibrated; Step S1214: Calculate the reduced CO2 emissions according to the following formula: Gasoline-to-electric CO2 emission reduction amount = gasoline-to-oil emission reduction coefficient * quantity * expected annual average energy consumption * replacement intention; Diesel-to-electric CO2 emission reduction amount = diesel-to-electric emission reduction coefficient * quantity * expected annual average energy consumption * replacement intention; Natural gas-to-electric CO2 emission reduction amount = natural gas-to-electric emission reduction coefficient * quantity * expected annual average energy consumption * replacement intention; Purchased hot water-to-electric CO2 emission reduction amount = hot water-to-electric emission reduction coefficient * quantity * expected annual average energy consumption * replacement intention; Purchased steam-to-electric CO2 emission reduction amount = steam-to-electric emission reduction coefficient * quantity * expected annual average energy consumption * replacement intention; Coal-to-electric CO2 emission reduction amount = coal-to-electric emission reduction coefficient * quantity * expected annual average energy consumption * replacement intention; The replacement intention is defaulted to 1. If a certain type of equipment does not need to be replaced, the replacement intention is 0.

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