Underground space carbon emission and environment quality coupling optimization method

Abstract

The invention provides an underground space carbon emission and environment quality coupling optimization method. The method comprises the following steps: step 1, acquiring a data set; 2, constructing a carbon emission and environment quality coupling model based on the data set; step 3, generating a coupling optimization strategy which specifically comprises the following steps: step 3A, selecting the ventilation quantity, the illumination brightness coefficient and the operation duration of the exhaust system as optimization variables; step 3B, establishing an objective function and constraint conditions; wherein the minimization of the total carbon emission and the optimization of the environmental quality index are taken as targets; and step 3C, executing a genetic algorithm, and obtaining an optimal solution in combination with the carbon emission and environment quality coupling model. According to the invention, carbon emission management and environmental quality improvement are realized synergistically.

Description

Technical Field

[0001] The present invention belongs to the field of infrastructure carbon emissions, and in particular relates to a coupling optimization method for underground space carbon emissions and environmental quality. Background Art

[0002] Underground spaces, such as underground complexes, tunnels, underground parking lots, etc., are an essential part of the modern urbanization process. However, due to their special enclosed environment, the operation of underground spaces relies on high-energy-consuming facilities such as ventilation, lighting, and drainage, which results in significantly higher carbon emission levels than those of ground buildings. At the same time, the air quality in underground spaces is often affected by problems such as excessive carbon dioxide concentration, insufficient oxygen content, and rising concentration of particulate matter (such as PM2.5), which not only affects environmental comfort but also threatens people's health and safety.

[0003] Existing underground space management technologies usually manage carbon emission control and environmental quality improvement as independent objectives, lacking in-depth research on the coupling relationship between the two. For example, although the operation of the ventilation system can improve air quality, it will significantly increase energy consumption and carbon emissions; while reducing the operation frequency of ventilation equipment may lead to deterioration of air quality, forming a contradiction between carbon emission management and environmental quality management. In addition, due to the dynamic changes in the environmental conditions of underground spaces, traditional fixed operation parameter strategies cannot meet complex actual needs, resulting in resource waste and low management efficiency.

[0004] Therefore, there is an urgent need for an optimization method that can integrate carbon emission and environmental quality management. Based on the dynamic coupling relationship between the two, using real-time data collection and dynamic optimization technologies, while ensuring the environmental comfort of underground spaces, it can significantly reduce equipment energy consumption and carbon emission levels, providing technical support for the construction of green and low-carbon cities. Summary of the Invention

[0005] The purpose of the present invention is to provide a coupling optimization method for underground space carbon emissions and environmental quality. By constructing a dynamic coupling model of carbon emissions and environmental quality, combined with real-time data collection and optimization algorithms, it can synergistically achieve carbon emission management and environmental quality improvement. The technical solution adopted is as follows:

[0006] A coupling optimization method for underground space carbon emissions and environmental quality, comprising the following steps:

[0007] Step 1: Obtain a data set;

[0008] Among them, the input data set includes the ventilation volume of the ventilation system, the lighting brightness coefficient of the lighting system, and the operation duration of the drainage system;

[0009] The output data set includes: environmental quality, the daily carbon emissions of each system;

[0010] The environmental quality includes the concentration of carbon dioxide; the daily carbon emissions = the daily operating energy consumption * the carbon emissions generated per unit of energy consumption;

[0011] Step 2: Based on the dataset, construct a coupling model of carbon emissions and environmental quality;

[0012] Step 3: Generate a coupling optimization strategy, which specifically includes the following steps:

[0013] Step 3A: Select the ventilation volume, lighting brightness coefficient, and exhaust system operation duration as optimization variables;

[0014] Step 3B: Establish an objective function and constraints;

[0015] Among them, the minimization of the total carbon emissions and the optimization of the environmental quality are taken as the objectives;

[0016] Step 3C: Execute the genetic algorithm and combine it with the coupling model of carbon emissions and environmental quality to obtain the optimal solution.

[0017] Preferably, in Step 1, the environmental quality includes the oxygen content and the PM2.5 concentration.

[0018] Preferably, the daily operation duration of both the ventilation system and the lighting system is 24h.

[0019] Preferably, in Step 3A, the ventilation volume is 30% - 100%; the lighting brightness coefficient is 10% - 100%; the exhaust system operation duration is greater than 3h.

[0020] Preferably, the constraints in Step 3B include: equipment operation safety, environmental comfort, and energy budget.

[0021] Preferably, after Step 3C, the following steps are further included:

[0022] Step 4: Transmit the optimization strategy to the underground space management system, dynamically adjust the ventilation volume of the ventilation system, the lighting brightness of the lighting system, and the operation duration of the drainage system to achieve coupling optimization.

[0023] Preferably, after Step 4, the following steps are further included: Record the carbon emissions and environmental quality data before and after optimization, analyze the synergistic effect of the optimization strategy on environmental quality improvement and carbon emissions reduction, and generate an evaluation report.

[0024] Compared with the prior art, the advantages of the present invention are:

[0025] (1) Coupling optimization

[0026] Based on the dynamic relationship between carbon emissions and environmental quality, a coupling model is constructed to clarify the comprehensive impact of equipment operation parameters on carbon emissions and environmental quality. By balancing the minimization of carbon emissions and the optimization of environmental quality in the optimization of systems such as ventilation and lighting, the contradiction brought about by their independent management is solved.

[0027] (2) Dynamic Response and Real-time Regulation

[0028] Environmental quality and equipment operation data are collected in real time through a sensor network, and optimization strategies are generated in combination with the dynamic coupling model. According to the changes in the underground space environmental conditions, the equipment operation parameters are adjusted in real time to improve the flexibility and adaptability of management.

[0029] (3) Collaborative Emission Reduction and Environmental Improvement

[0030] On the premise of ensuring that the air quality in the underground space (such as carbon dioxide concentration, oxygen content, PM2.5 concentration, etc.) meets the standards, the operation modes of ventilation, lighting and auxiliary equipment are optimized to effectively reduce energy waste, significantly reduce the carbon emission level, and truly achieve the collaborative optimization of environmental quality and carbon emission management;

[0031] (4) Improve Resource Utilization Efficiency

[0032] By optimizing the equipment operation frequency, time and zoning strategies, the present invention minimizes the ineffective operation of high-energy-consuming equipment, optimizes resource scheduling, improves the overall operation efficiency of underground space facilities, and reduces the operation cost.

[0033] (5) Visual Evaluation and Optimization Feedback

[0034] Through the evaluation and feedback module, the present invention records the carbon emission data and environmental quality indicators before and after the implementation of the optimization strategy, intuitively displays the emission reduction effect and environmental improvement results of the collaborative optimization, and provides a scientific basis for subsequent optimization iterations. Description of the Drawings

[0035] Figure 1 It is a flow chart of the coupling optimization method for carbon emissions and environmental quality in the underground space.

[0036] Figure 2 It is a schematic diagram of the detection of carbon dioxide concentration and oxygen content.

[0037] Figure 3 It is a pie chart of the energy consumption ratio of each system after optimization.

[0038] Figure 4 It is a schematic diagram of the comprehensive evaluation of environmental indicators.

[0039] Figure 5 It is a schematic diagram of the relationship between temperature and humidity and carbon dioxide concentration. Detailed Implementation Modes

[0040] The following will describe in more detail the method for coupling and optimizing carbon emissions and environmental quality in underground spaces of the present invention with reference to schematic diagrams, in which the preferred embodiments of the present invention are shown. It should be understood that those skilled in the art can modify the present invention described herein while still achieving the advantageous effects of the present invention. Therefore, the following description should be understood as a broad guidance for those skilled in the art and not as a limitation on the present invention.

[0041] As Figures 1 to 5 , a method for coupling and optimizing carbon emissions and environmental quality in underground spaces includes the following steps:

[0042] Step 1: Obtain a data set;

[0043] Among them, the input data set includes the ventilation volume of the ventilation system, the lighting brightness coefficient of the lighting system, and the operation duration of the drainage system;

[0044] The output data set includes: the daily carbon emissions and environmental quality of each system;

[0045] The environmental quality includes the concentration of carbon dioxide; the carbon emissions = the daily operating energy consumption * the carbon emissions generated per unit of energy consumption;

[0046] The daily operating duration of both the ventilation system and the lighting system is 24 hours.

[0047] Step 2: Based on the data set, construct a coupling model of carbon emissions and environmental quality;

[0048] Furthermore, the environmental quality also includes the oxygen content and the PM2.5 concentration.

[0049] Step 3: Generate a coupling optimization strategy, which specifically includes the following steps:

[0050] Step 3A: Select the ventilation volume, the lighting brightness coefficient, and the operation duration of the exhaust system as optimization variables.

[0051] Among them, the ventilation volume is 30% - 100%; the lighting brightness coefficient is 10% - 100%; the operation duration of the exhaust system is greater than 3 hours.

[0052] Step 3B: Establish an objective function and constraint conditions.

[0053] Among them, the objective is to minimize the total carbon emissions and optimize the environmental quality;

[0054] The constraint conditions include: equipment operation safety, environmental comfort, and energy budget.

[0055] Among them, equipment operation safety:

[0056] Equipment operation safety ensures that the equipment does not operate overloaded, avoiding failures and reducing efficiency.

[0057] 1.1 Equipment load limit:

[0058] The maximum load capacity of each device (such as a ventilator, lighting system, etc.) should be based on the manufacturer's regulations. Set a "safety load factor" L max , representing the maximum operating capacity of the device. For example, assume that the maximum load of the ventilation system is 100% of its operating capacity.

[0059] Quantification constraints:

[0060]

[0061] where α is the safety factor (usually taken as 0.9 or lower) to ensure that the device always operates within the safe working range.

[0062] 1.2 Equipment start-up and stop frequency:

[0063] The start-up and stop of the equipment have an important impact on its lifespan and operating efficiency. Assume that the number of start-ups of each device does not exceed N times per day, then:

[0064] Quantification constraints: Number of equipment start-ups ≤ N

[0065] 1.3 Temperature and humidity limit:

[0066] The equipment operates most efficiently within a specific temperature and humidity range. Assume that the working environment temperature and humidity of the ventilation system are T_min to T_max and H_min to H_max respectively, then:

[0067] Quantification constraints:

[0068] Tmin ≤ T ≤ Tmax,, H min ≤ H ≤ H max

[0069] where T and H are the actual operating environment temperature and humidity of the equipment respectively.

[0070] Environmental comfort:

[0071] Environmental comfort directly affects the health and comfort of people in the underground space. When quantifying environmental comfort based on air quality and temperature and humidity control, it mainly relies on the following environmental indicators:

[0072] 2.1 Carbon dioxide concentration:

[0073] The carbon dioxide concentration should be controlled within a certain range. Assume the target range is CO2_min ≤ CO2 ≤ CO2_max (for example, (CO2_min = 400 ppm, CO2_max = 800 ppm)), then:

[0074] Quantitative constraint: 400 ppm ≤ CO2 ≤ 800 ppm

[0075] 2.2 Oxygen concentration:

[0076] The oxygen concentration should be maintained between 19% and 21%:

[0077] Quantitative constraint: 19% ≤ O2 ≤ 21%

[0078] 2.3 PM2.5 concentration:

[0079] The PM2.5 concentration should be controlled below 50 μg / m 3 (or the environmental standards of other regions), then:

[0080] Quantitative constraint: PM2.5 ≤ 50 μg / m 3

[0081] 2.4 Temperature and humidity suitability:

[0082] The temperature and humidity should be controlled within the following range:

[0083] Temperature: 22°C ≤ T ≤ 30°C; Humidity: 50% ≤ H ≤ 80%

[0084] Quantitative constraint: 22°C ≤ T ≤ 30°C, 50% ≤ H ≤ 80%

[0085] Energy budget:

[0086] 1. Equipment energy consumption limit

[0087] Assume there is a ventilation system, a lighting system, and an exhaust system, and their daily energy consumptions are E vent ,

[0088] E light and E drain , and each system has a maximum energy consumption limit.

[0089] Energy consumption limit of the ventilation system:

[0090] E vent = V vent × P vent ≤ E vent,max

[0091] Where:

[0092] V vent - Ventilation volume (such as %);

[0093] P vent -- Power consumption per unit ventilation volume (kWh / m 3 )

[0094] Event,max - Maximum energy consumption limit (kWh) of the ventilation system.

[0095] Energy consumption limit of the lighting system:

[0096] E light = L light × P light ≤ E light,max

[0097] Where:

[0098] L light - Lighting brightness coefficient (%),

[0099] P light - Power consumption per unit brightness (kWh / m 2 ),

[0100] E light,max - Maximum energy consumption limit (kWh) of the lighting system.

[0101] Energy consumption limit of the drainage system:

[0102] E drain = T drain × P drain ≤ E drain,max

[0103] Where:

[0104] T drain - Operating duration (hours) of the exhaust system,

[0105] P drain - Energy consumption per unit time (kWh / h),

[0106] E drain,max - Maximum energy consumption limit (kWh) of the drainage system.

[0107] 2. Equipment energy efficiency requirements

[0108] Assume that each device has a specified energy efficiency upper limit (unit energy consumption). Quantified by the following formula: Energy efficiency requirements of the ventilation system:

[0109]

[0110] Where: is the maximum unit energy efficiency (kWh / m 3 ) of the ventilation system.

[0111] Energy efficiency requirements of the lighting system:

[0112]

[0113] is the maximum unit energy efficiency of the lighting system (kWh / m 2 ).

[0114] Energy efficiency requirements for the drainage system:

[0115]

[0116] Among them: is the maximum unit energy efficiency of the exhaust system (kWh / h).

[0117] 3. Comprehensive energy consumption budget

[0118] For the entire underground space, set the budget limit E total,max of the total energy consumption. Then the constraint condition:

[0119] E total = E vent + E light + E drain ≤ E total,max

[0120] Among them:

[0121] E total is the total energy consumption of all systems in the underground space (kWh),

[0122] E total,max is the total energy consumption budget (kWh).

[0123] 4. Peak load limit

[0124] Assume that during the peak period, there is a peak limit on the energy consumption of the equipment. Set the maximum energy consumption ratio during the peak period to be α peak (for example, 80%). Then there is:

[0125]

[0126] Among them:

[0127] is the energy consumption of the ventilation system during the peak period,

[0128] is the energy consumption of the lighting system during the peak period,

[0129] is the energy consumption of the drainage system during the peak period,

[0130] α peak is the peak load limit ratio.

[0131] 5. Energy consumption ratio limit

[0132]

[0133] Among them: r vent / r light / r drain is the proportion of the energy consumption of each system in the total energy consumption.

[0134] Step 3C: Execute the genetic algorithm and combine it with the carbon emission and environmental quality coupling model to obtain the optimal solution.

[0135] Step 3C1: Adjust the values of the optimization variables within the range of the constraint conditions;

[0136] Step 3C2: Based on the carbon emission and environmental quality coupling model, obtain the carbon emission prediction value and the environmental quality prediction value;

[0137] Step 3C3: Generate a coupling optimization strategy composed of the optimization variables;

[0138] Step 4: Transmit the optimization strategy to the underground space management system, dynamically adjust the ventilation volume of the ventilation system, the lighting brightness of the lighting system, and the operation duration of the drainage system to achieve coupling optimization.

[0139] Step 5: Record the carbon emission and environmental quality data before and after optimization, analyze the synergistic effect of the optimization strategy on environmental quality improvement and carbon emission reduction, and generate an evaluation report.

[0140] Taking an underground parking lot as an example, demonstrate how to apply the coupling optimization method for underground space carbon emission and environmental quality of the present invention to jointly achieve carbon emission management and environmental quality improvement.

[0141] Step 1: Environmental and equipment data collection

[0142] 1.1 Data collection content

[0143] 1.1.1 Environmental quality data: Collect the environmental parameters in the underground parking lot through sensors, including:

[0144] Carbon dioxide concentration: 400 ppm to 1200 ppm;

[0145] Oxygen content: 19% to 21%;

[0146] PM2.5 concentration: 10 μg / m 3 ~50 μg / m 3 ;

[0147] Temperature and humidity: Temperature 22°C to 30°C, humidity 50% to 80%.

[0148] 1.1.2 Equipment operation data: Collect the operation status of the ventilation system, lighting system, and drainage system in the parking lot, including:

[0149] Ventilation system air volume: 30% to 100% operation;

[0150] Illumination system power: Zoned brightness range 10% - 100%;

[0151] Operation time and frequency of the drainage system;

[0152] 1.2 Acquisition method

[0153] Deploy an environmental sensor network in the parking lot with a spacing of 10 meters, and record data every 5 minutes; obtain the equipment operation parameters and energy consumption data in real time through the monitoring system and upload them to the cloud data platform;

[0154] Step 2: Construction of the carbon emission and environmental quality coupling model

[0155] 2.1 Data analysis

[0156] Adopt the multivariate regression analysis method to quantify the combined effects of ventilation volume, illumination brightness, and other equipment operation parameters on carbon emissions and environmental quality.

[0157] For example, when the ventilation volume increases by 10%, the carbon dioxide concentration decreases by 100 ppm, but the equipment energy consumption increases by 15%.

[0158] 2.2 Model construction

[0159] Through coupling analysis, construct a dynamic relationship model of carbon dioxide concentration, oxygen content, and ventilation system operation parameters; construct an impact model of PM2.5 concentration on the operation parameters of the illumination system and the drainage system;

[0160] The model output includes the predicted values of carbon emissions and environmental quality indicators under different combinations of operation parameters;

[0161] Step 3: Generation of coupling optimization strategies

[0162] 3.1 Optimization objectives

[0163] On the premise of ensuring that the carbon dioxide concentration is lower than 800 ppm, the oxygen content is higher than 20%, and the PM2.5 concentration is lower than 30 μg / m 3 , minimize the equipment operation energy consumption, that is, the total carbon emissions.

[0164] 3.2 Algorithm implementation

[0165] Use the genetic algorithm to generate optimization strategies, and set the optimization variables including ventilation volume, illumination brightness, and drainage system operation time;

[0166] 3.3 Example of optimization results:

[0167] The air volume of the ventilation system is reduced to 60%; the partition brightness of the lighting system is set at 80% for busy areas and 20% for vacant areas; the operation frequency of the drainage system is reduced to 2 times a day, with each operation lasting 1.5 hours.

[0168] Step 4: Implementation and regulation of optimization strategies

[0169] 4.1 Implementation plan

[0170] Input the optimization strategies into the parking lot management system to dynamically adjust the operation parameters of ventilation, lighting, and drainage equipment.

[0171] The air volume of the ventilation system is dynamically adjusted according to the carbon dioxide concentration, running at 70% during peak hours and 50% during low-flow hours; the lighting system is partition-controlled, maintaining 80% brightness in the parking area, 100% in the entrance and exit areas, and reducing to 10% in the vacant areas; the drainage system dynamically regulates the operation duration according to humidity and drainage requirements.

[0172] 4.2 Regulation mechanism

[0173] Real-time monitor environmental data through sensors. When the carbon dioxide concentration approaches 800 ppm, automatically increase the air volume of the ventilation system; when the PM2.5 concentration is below 20 μg / m 3 Reduce the ventilation frequency to save energy. The environmental data is refreshed every 10 minutes to ensure that the optimization strategies adapt to dynamic changes.

[0174] Step 5: Evaluation and feedback of optimization effects

[0175] 5.1 Data before optimization

[0176] The daily operation energy consumption of the ventilation system is 600 kWh; the daily operation energy consumption of the lighting system is 300 kWh; the daily operation energy consumption of the drainage system is 50 kWh; total carbon emissions: 950 kWh × 0.6 kg CO2 / kWh = 570 kg CO2.

[0177] Environmental quality: The average carbon dioxide concentration is 1000 ppm, and the average PM2.5 concentration is 40 μg / m 3 ;

[0178] 5.2 Data after optimization

[0179] The energy consumption of the ventilation system is reduced to 450 kWh; the energy consumption of the lighting system is reduced to 200 kWh; the energy consumption of the drainage system is reduced to 30 kWh; total carbon emissions: 680 kWh × 0.6 kg CO2 / kWh = 408 kg CO2;

[0180] Environmental quality: The carbon dioxide concentration is reduced to 750 ppm, and the PM2.5 concentration is reduced to 25 μg / m 3 ;

[0181] 5.3 Emission Reduction and Improvement Effects

[0182] Carbon emission reduction: 570 kgCO2 - 408 kgCO2 = 162 kgCO2, with an emission reduction rate of 28.4%; Environmental quality improvement: the carbon dioxide concentration decreased by 25%, and the PM2.5 concentration decreased by 37.5%.

[0183] 5.4 Evaluation Report

[0184] Generate a collaborative optimization evaluation report, including the carbon emission contribution of each device, the trend of environmental quality improvement, and the comparative analysis before and after optimization, visually demonstrating the optimization effect.

[0185] The above are only the preferred embodiments of the present invention and do not impose any limitation on the present invention. Any person skilled in the art, without departing from the technical solution of the present invention, makes any form of equivalent substitution or modification and other changes to the technical solutions and technical contents disclosed in the present invention, which are still within the content of the technical solution of the present invention and still fall within the protection scope of the present invention.

Claims

1. A coupling optimization method for underground space carbon emissions and environmental quality, characterized in that: The following steps are involved: Step 1: Get the data set; The input data sets include the ventilation volume of the ventilation system, the lighting brightness coefficient of the lighting system, and the operation time of the drainage system; The output datasets include: environmental quality, daily carbon emissions per system; The environmental quality includes the concentration of carbon dioxide; daily carbon emissions = daily operating energy consumption * carbon emissions generated by unit energy consumption; Step 2: Based on the data set, build a coupling model of carbon emissions and environmental quality; Step 3: Generate a coupling optimization strategy, which specifically includes the following steps: Step 3A, selecting ventilation volume, lighting brightness coefficient and exhaust system operation time as optimization variables; Step 3B, establish objective function and constraints; Among them, the goal is to minimize the total carbon emissions and optimize the environmental quality; Step 3C: Execute the genetic algorithm and combine the carbon emission and environmental quality coupling model to obtain the optimal solution.

2. The method for coupling optimization of underground space carbon emissions and environmental quality according to claim 1 is characterized in that: In step 1, environmental quality includes oxygen content and PM2.5 concentration.

3. The method for coupling optimization of underground space carbon emissions and environmental quality according to claim 1 is characterized in that: The ventilation and lighting systems operate 24 hours a day.

4. The method for coupling optimization of underground space carbon emissions and environmental quality according to claim 1 is characterized in that: In step 3A, the ventilation volume is 30% to 100%; the lighting brightness coefficient is 10% to 100%; and the exhaust system operates for more than 3 hours.

5. The method for coupling optimization of underground space carbon emissions and environmental quality according to claim 1 is characterized in that: The constraints in step 3B include: equipment operation safety, environmental comfort, and energy budget.

6. The method for coupling optimization of underground space carbon emissions and environmental quality according to claim 1 is characterized in that: Step 3C may be followed by the following steps: Step 4: Transfer the optimization strategy to the underground space management system to dynamically adjust the ventilation volume of the ventilation system, the lighting brightness of the lighting system, and the operating time of the drainage system to achieve coupled optimization.

7. The method for coupling optimization of underground space carbon emissions and environmental quality according to claim 6 is characterized in that: After step 4, the following steps are included: Record carbon emissions and environmental quality data before and after optimization, analyze the synergistic effects of optimization strategies on environmental quality improvement and carbon emissions reduction, and generate an evaluation report.

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