BIM-based building carbon emission monitoring system

Abstract

The present application relates to the technical field of intelligent carbon management, in particular to a building carbon emission monitoring system based on BIM, comprising a model construction module, a thermal inertia analysis module, a carbon list generation module, a carbon emission monitoring module and an energy consumption parameter optimization module.The present application generates a carbon emission parameter set by standardizing analysis of component material types, sizes and engineering quantities, in combination with IFC data structure, so that the carbon emission factor has the ability to adjust in a targeted manner.In the thermal inertia calculation, the measured ambient temperature variation sequence is introduced to correct the response difference of the heat capacity and heat conduction behavior of the component, accurately reflecting the dynamic thermal performance of the material under different environments.In the stage carbon emission calculation, the component thermal inertia response and functional period are refined, and the functional frequency and time occupancy ratio are superimposed in the carbon emission calculation, realizing the dual sensitive adjustment of carbon emission to time and component function dimension.

Description

Technical Field

[0001] This invention relates to the field of intelligent carbon management technology, and in particular to a BIM-based building carbon emission monitoring system. Background Technology

[0002] The field of intelligent carbon management technology encompasses the perception, recording, calculation, and analysis of the entire carbon emission process. It utilizes information technology to accurately acquire, dynamically monitor, and centrally manage carbon emission data, thereby achieving refined tracking and quantitative control of carbon emission behavior. The core of this technology is the integration of Building Information Modeling (BIM), IoT devices, and information systems to conduct data-driven monitoring and management of carbon emission activities throughout the entire construction and operation process of buildings.

[0003] Among them, the BIM-based building carbon emission monitoring system refers to a system built using Building Information Modeling (BIM) technology and combined with the needs of building energy consumption and carbon emission monitoring. The system interfaces with BIM data from the building design, construction, and operation and maintenance phases to monitor and analyze energy consumption and carbon emission data in real time during the building process, achieving effective management and control of building carbon emissions. This includes BIM model-based data acquisition and processing methods, the construction of calculation models for energy consumption and carbon emission monitoring, and the integration of energy efficiency data throughout the building's lifecycle. Through the combination of the BIM platform and the energy efficiency data management system, it enables full-process data tracking of building projects from design to operation and maintenance, and uses IoT technology to acquire real-time energy consumption data of various devices within the building, while leveraging a big data analytics platform to statistically analyze carbon emissions.

[0004] In building carbon emission monitoring, existing technologies largely rely on static BIM model data for carbon factor matching, lacking time-series adjustments to material thermal response behavior. This leads to the problem of applying fixed parameters in carbon emission assessments. Factor selection is primarily based on direct assignment of values ​​according to material type, ignoring the thermal conduction delays and environmental temperature changes during actual use, resulting in discrepancies between carbon emission values ​​and measured energy consumption. In carbon emission estimation, total emissions are typically divided by stage, without detailing to the frequency or duration of component functional activation, failing to reflect the dynamic contribution ratio of different components at different stages. In life cycle prediction, carbon emission change trajectories are often set according to empirical curves, lacking data-driven trend evolution logic, resulting in a lack of continuity and sensitivity in the prediction path. Furthermore, existing schemes mainly use manual correction or static regression to update carbon factors, lacking global optimization capabilities, which limits the accuracy of carbon emission control. These shortcomings not only affect the accuracy of carbon emission assessments but also make it difficult to close the loop between dynamic monitoring and parameter optimization, failing to meet the refined requirements of building life cycle carbon management. Summary of the Invention

[0005] The purpose of this invention is to address the shortcomings of existing technologies by proposing a BIM-based building carbon emission monitoring system.

[0006] To achieve the above objectives, the present invention adopts the following technical solution: a BIM-based building carbon emission monitoring system, the system comprising:

[0007] The model building module is used to acquire component composition data, including material type, size and quantity information. Based on the IFC standard, it parses BIM data as component quantity parameters and calculates preliminary carbon emission factors, which are then integrated into a carbon standard factor set and transferred to the thermal inertia analysis module.

[0008] The thermal inertia analysis module is used to call the component engineering quantity parameters and the carbon standard factor set, combine them with the statistical environmental temperature change sequence, perform correction calculations on the material heat capacity coefficient and thermal conduction delay time, and output the component thermal inertia characteristic parameters to the carbon list generation module.

[0009] The carbon list generation module is used to calculate the carbon emissions for each stage by referring to the thermal inertia characteristic parameters of the component and the carbon standard factor set, and to adjust the carbon emission factors for the construction and operation stages by referring to the carbon emissions, and to generate a phased carbon emission list and transmit it to the carbon emission monitoring module.

[0010] The carbon emission monitoring module is used to input the phased carbon emission list into the LEAP model, construct the carbon emission intensity change path, obtain the carbon emission prediction sequence for each stage of the life cycle, analyze the peak carbon emission time, component type and component contribution rate, and output the carbon emission change trend monitoring results.

[0011] The present invention is improved in that the component engineering quantity parameters include component quality indicators, size combination form, and engineering quantity structural hierarchy; the component thermal inertia characteristic parameters specifically include heat capacity adjustment coefficient, thermal conductivity delay factor, and temperature change response coefficient; the phased carbon emission list includes an initial construction period carbon emission list, an operation and maintenance period carbon emission list, and carbon emission factor adjustment records; and the carbon emission change trend monitoring results specifically include carbon intensity evolution curve, predicted carbon peak time, and component contribution ranking list.

[0012] The present invention is improved in that the model building module includes:

[0013] The component data extraction submodule obtains the material type, size and quantity information from the component composition data, classifies and numbers the material types, constructs a component size structure table based on the size and quantity information, and combines the component size structure table with the classification and numbering results to generate a component code list.

[0014] The parameter calculation and aggregation submodule, based on the component code list, calls the geometric parameters and physical information of the corresponding components in the IFC standard data structure, parses and obtains the volume, quantity and material density of the components, combines the three parameters to perform data merging processing to form single component engineering quantity parameters, aggregates and calculates the engineering quantity data of all components, and generates a set of total component engineering quantity values.

[0015] The carbon factor generation submodule selects basic carbon emission factor data matching the component material properties based on the total value set of component engineering quantities, compares the component material density with the standard factor density benchmark, adjusts the carbon factor according to the deviation ratio, maps the adjusted carbon factor to the component engineering quantity parameters and integrates them to generate a carbon standard factor set.

[0016] The standard factor density benchmark was obtained by consulting the component material classification item in the industry carbon emission database.

[0017] The present invention is improved in that the thermal inertia analysis module includes:

[0018] The component data linkage submodule calls the component engineering quantity parameters and the component number, material name and total component engineering quantity value in the carbon standard factor set. It performs matching processing based on the component number, filters out component items with complete material and size information, and performs data linkage processing with the matching results and the statistical environmental temperature change sequence to generate the component thermal response input set.

[0019] The thermal parameter correction submodule, based on the component thermal response input set, calls the initial value of the material's thermal capacity coefficient and the initial time of thermal conduction delay, combines the hourly temperature gradient in the ambient temperature change sequence, compares the deviation difference between the measured temperature difference and the theoretical temperature difference of the component's thermal response, and adjusts the original thermal capacity coefficient and thermal conduction delay time according to the deviation difference to obtain the thermal parameter correction coefficient pair.

[0020] The inertial parameter output submodule calculates the thermal flux response amplitude, temperature transfer time interval, and reaction rate range of each component in parallel based on the thermal parameter correction coefficients for the heat capacity and thermal conductivity correction coefficients of each component, combined with the component material type and size structure parameters, to obtain the component's thermal inertial characteristic parameters.

[0021] The present invention is improved in that the carbon list generation module includes:

[0022] The phase carbon emission calculation submodule is based on the thermal inertia characteristic parameters of the components and the heat capacity, heat conduction time and unit carbon emission of the components in the carbon standard factor. It divides the environmental response cycle of each component in the construction, operation and operation phases. After matching the thermal inertia and carbon factor data within the cycle, it calculates the carbon emission of each component within a specified time and sums them up to obtain the total phase carbon emission.

[0023] The factor value adjustment submodule detects the usage frequency and functional status of components in each stage based on the difference between the carbon emission values ​​and carbon factor values ​​of components in the construction stage and the operation stage in the total carbon emission of the stage. It uses the thermal inertia response cycle of the component as a reference to perform coefficient supplementation processing on the adjusted carbon emission factor value to obtain the stage factor adjustment coefficient group.

[0024] The emission list construction submodule calls the correction value of each component in the stage factor adjustment coefficient group and the initial carbon factor value to combine them numerically. It then redistributes the carbon emission factor according to the stage in which the component is located, and combines the number of components in each stage with the corresponding carbon emission value to collect and output the adjusted data by stage, thus establishing a staged carbon emission list.

[0025] The present invention improves upon this by performing a coefficient supplementation process on the adjusted carbon emission factor value, using the following formula:

[0026] ;

[0027] Calculation components In the cycle Factor offset adjustment value ;

[0028] in, It is a cycle Actual carbon emission factors were observed. It is a reference benchmark factor for the same period. It is a cycle Thermal inertial response time It is a component In all The sum of thermal response times over each cycle It is a cycle Function runtime It is a component Total duration of functionality across all cycles.

[0029] The present invention is improved in that the carbon emission monitoring module includes:

[0030] The emission path construction submodule is based on the carbon emission of components and the information of the stage in the phased carbon emission list. It inputs the stage carbon emission value into the LEAP model, arranges and integrates the corresponding time nodes, normalizes the total carbon emission value of multiple stages according to the building area, and extracts the change slope and fluctuation density in the time series to generate the carbon emission intensity change path.

[0031] The stage sequence prediction submodule calls the change trend and stage boundary information in the carbon emission intensity change path, and based on the life cycle segmentation setting in the LEAP model, performs time series filling and trend extrapolation for multiple stages such as construction, delivery and operation, continuously calculates the change nodes and superimposes the stage effect factors to obtain the life cycle carbon emission sequence.

[0032] The peak contribution analysis submodule extracts the total carbon emission value of components and component number during the peak period based on the peak node of carbon emission in each stage of the life cycle carbon emission sequence, calculates the proportion of carbon emission of components, classifies components, summarizes the emission contribution of components in the peak interval, and outputs the carbon emission change trend monitoring results.

[0033] The present invention improves upon this by using the following formula for the stage effect factor:

[0034] ;

[0035] Calculation components In the stage Stage effect factor ;

[0036] in, It is a component In the stage The actual average carbon emissions, It is a component In the stage Industry reference carbon emission values, It is the component's functional utilization factor, indicating the component's performance at a given stage. The activation frequency in It is the component time occupancy factor, indicating the component's time occupancy during the stage. The ratio of usage time to standard time.

[0037] The present invention is improved by further including an energy consumption parameter optimization module. Based on the carbon emission change trend monitoring results, the energy consumption parameter optimization module uses a particle swarm optimization algorithm to iteratively adjust the parameters of the carbon emission factors, outputs a carbon factor optimization list, updates the carbon emission parameters, and obtains the energy consumption parameter optimization results.

[0038] The carbon factor optimization list includes a set of correction coefficients, a set of optimization and adaptation parameters, and update and iteration records. The energy consumption parameter optimization results specifically refer to the carbon factor correction table, life cycle energy consumption index, and optimized carbon emission benchmark.

[0039] The present invention is improved in that the energy consumption parameter optimization module includes:

[0040] The factor variable initialization submodule extracts the initial value and change range of carbon emission factors for the corresponding stage of the component based on the component carbon emission intensity change path, peak interval and component category contribution in the carbon emission change trend monitoring results, performs interval division processing on the change range, sets the initial position of the optimization particles and assigns stage labels, and generates a carbon emission factor variable group.

[0041] The emission factor iteration submodule calls the carbon emission factor parameter values ​​and variation ranges of each stage component in the carbon emission factor variable group, compares the difference between the carbon emission factor value corresponding to the current position of each particle and the target carbon emission value in the life cycle carbon emission sequence, adjusts the particle position proportionally according to the difference and records the optimal position, and obtains the carbon factor optimization list.

[0042] The energy consumption parameter update submodule compares the adjusted carbon emission factor parameters of components in the carbon factor optimization list with the original carbon emission factor parameters, and replaces the optimized carbon emission factor parameters with the parameter table according to the category and stage of the components, thus establishing the energy consumption parameter optimization results.

[0043] Compared with the prior art, the advantages and positive effects of the present invention are as follows:

[0044] In this invention, a set of carbon emission parameters is generated by standardizing the analysis of component material types, dimensions, and engineering quantities, combined with the IFC data structure, enabling targeted adjustment of carbon emission factors. The measured environmental temperature change sequence is incorporated into the thermal inertia calculation to correct the response difference in the component's heat capacity and thermal conductivity, accurately reflecting the dynamic thermal performance of the material under different environments. In the staged carbon emission calculation, the component's thermal inertia response and functional time periods are integrated for detailed stage segmentation, and functional frequency and time occupancy ratio are superimposed in the carbon emission calculation, achieving dual sensitive adjustment of carbon emissions based on time and component function dimensions. During the establishment of the life cycle prediction path, a carbon emission evolution path covering the entire process is generated by jointly fitting the time series change trend and stage boundary conditions, and peak nodes are extracted for component contribution ranking, effectively identifying the core sources of carbon emissions. At the parameter optimization level, a particle swarm optimization algorithm is used to dynamically optimize the carbon factors, incorporating peak intervals, contributing components, and other elements into the factor adjustment logic to ensure the continuity and control accuracy of carbon emission parameters. The construction of the aforementioned multi-dimensional input and feedback loops enables carbon emission monitoring to have adjustable structural levels, sensitive response to time-series rhythms, dynamic optimization of prediction accuracy, and system linkage of factor adjustments, thus promoting carbon emission management from static indicator verification to dynamic process control. Attached Figure Description

[0045] Figure 1 This is a system module diagram proposed in this invention;

[0046] Figure 2This is a system framework diagram proposed in this invention;

[0047] Figure 3 This is a schematic diagram of the model construction module of the present invention;

[0048] Figure 4 This is a schematic diagram of the thermal inertia analysis module of the present invention;

[0049] Figure 5 This is a schematic diagram of the carbon list generation module of the present invention;

[0050] Figure 6 This is a schematic diagram of the carbon emission monitoring module of the present invention;

[0051] Figure 7 This is a schematic diagram of the energy consumption parameter optimization module of the present invention. Detailed Implementation

[0052] To make the objectives, technical solutions, and advantages of this invention clearer, the invention will be further described in detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative and not intended to limit the invention.

[0053] In the description of this invention, it should be understood that the terms "length," "width," "upper," "lower," "front," "rear," "left," "right," "vertical," "horizontal," "top," "bottom," "inner," and "outer," etc., indicating orientation or positional relationships, are based on the orientation or positional relationships shown in the accompanying drawings and are only for the convenience of describing the invention and simplifying the description, and do not indicate or imply that the device or element referred to must have a specific orientation, or be constructed and operated in a specific orientation, and therefore should not be construed as a limitation of the invention. Furthermore, in the description of this invention, "a plurality of" means two or more, unless otherwise explicitly specified.

[0054] Please see Figure 1 This invention provides a technical solution: a BIM-based building carbon emission monitoring system, the system comprising:

[0055] The model building module is used to acquire component composition data, including material type, size and quantity information. Based on the IFC standard, it parses BIM data as component quantity parameters and calculates preliminary carbon emission factors, which are then integrated into a carbon standard factor set and transferred to the thermal inertia analysis module.

[0056] The thermal inertia analysis module is used to call the component engineering quantity parameters and carbon standard factor set, combine them with the statistical environmental temperature change sequence, perform correction calculations on the material heat capacity coefficient and thermal conduction delay time, and output the component thermal inertia characteristic parameters to the carbon list generation module.

[0057] The carbon list generation module is used to calculate the carbon emissions at each stage by referring to the thermal inertia characteristic parameters of the components and the carbon standard factor set. The carbon emission factors at the construction and operation stages are adjusted based on the carbon emissions, and a phased carbon emission list is generated and transmitted to the carbon emission monitoring module.

[0058] The carbon emission monitoring module is used to input the phased carbon emission list into the LEAP model, construct the carbon emission intensity change path, obtain the carbon emission prediction sequence for each stage of the life cycle, analyze the peak time of carbon emissions, component type and component contribution rate, and output the carbon emission change trend monitoring results.

[0059] The component engineering quantity parameters include component quality indicators, size combination form, and engineering quantity structural hierarchy. The component thermal inertia characteristic parameters specifically include heat capacity adjustment coefficient, thermal conductivity delay factor, and temperature change response coefficient. The phased carbon emission list includes the initial construction period carbon emission list, the operation and maintenance period carbon emission list, and carbon emission factor adjustment records. The carbon emission change trend monitoring results specifically include carbon intensity evolution curve, carbon peak time prediction value, and component contribution ranking list. The carbon factor optimization list includes correction coefficient set, optimization adaptation parameter set, and update iteration record. The energy consumption parameter optimization results specifically refer to the carbon factor correction table, life cycle energy consumption index, and optimized carbon emission benchmark.

[0060] Please see Figure 2 and Figure 3 The model building module includes:

[0061] The component data extraction submodule obtains the material type, size and quantity information from the component composition data, classifies and numbers the material types, constructs a component size structure table based on the size and quantity information, and combines the component size structure table with the classification and numbering results to generate a component code list.

[0062] The process of acquiring material type, size, and quantity information from component composition data requires accessing the standard component list database within the Building Information Modeling (BIM) system. This involves retrieving the unique identifier of each component and its corresponding material field. After obtaining the material type data, it is categorized by material type (e.g., concrete, steel, bricks, insulation materials). Each material type is then further subdivided by material type (e.g., steel is further subdivided into HRB400 rebar, Q235 steel plate, etc.). Each material type is then uniformly coded according to system rules, with a coding structure like "MT-01" and "MT-02," where "MT" represents MaterialType and "01" and "02" are classification numbers. A material type number table is generated based on the classification numbering results. Finally, the geometric information associated with the component, including its length, is extracted. ,width ,high The volume of the component can be obtained using the following formula: ,in: Component volume (unit: ), Component length (unit: m) Component width (unit: m) Component height (unit: m). For example, the length of a component... ,Width ,high Then its volume is Retrieve the number of individual components from the component list data. Construct project quantity information: ,in: Total quantity of components (unit: ), : Quantity of components (unit: pieces). If the quantity of components is... One, then Based on the component ID and geometric dimensions, a dimension structure table is constructed in the system. The structure table lists fields such as component ID, dimension combination, volume, quantity, and material number. Combining the component dimension structure table with the aforementioned material number table, the data is combined by merging fields. In the data table, the dimension combinations and material numbers of the same component ID are matched and arranged to form a complete list of components, and finally, a component code list is generated.

[0063] The parameter calculation and aggregation submodule is based on the component code list. It calls the geometric parameters and physical information of the corresponding components in the IFC standard data structure, parses and obtains the volume, quantity and material density of the components, combines the three parameters to perform data merging and processing to form the single component engineering quantity parameters, aggregates and calculates the engineering quantity data of all components, and generates the total value set of component engineering quantities.

[0064] Based on the component code list, the component geometric parameters and physical information in the IFC standard data structure are called. Fields such as `<body>` are retrieved under the entity in the IFC file structure to extract the component volume. ,quantity With density For example, volume ,quantity If the material is HRB400 steel reinforcement, the density is... Then construct quality parameters for: ,in: Component mass (unit: kg) Component volume (unit: ), Material density (unit: Substituting the data yields... This forms a set of individual engineering quantity parameters for the components. This information is recorded in the structure list; all components are summarized, component-dimensional aggregation is performed, and the quantity data of all components is summed. ,in: Total quantity of all components (unit: ), : No. The quantity of work for each component Total number of components. For example, the total quantity of all HRB400 steel components is... The components are grouped and summarized according to their categories to generate a statistical table of total component quantities and a set of total component quantities.

[0065] The carbon factor generation submodule selects basic carbon emission factor data matching the component material properties based on the total value set of component engineering quantities, compares the component material density with the standard factor density benchmark, adjusts the carbon factor according to the deviation ratio, maps the adjusted carbon factor to the component engineering quantity parameters and integrates them to generate a carbon standard factor set.

[0066] The standard factor density benchmark was obtained by consulting the component material classification items in the industry carbon emission database.

[0067] Based on the total value set of component quantities, basic carbon emission factor data matching the component material properties are selected. The material type and standard carbon emission factor lookup table in the construction industry carbon database is then used to map the component material classification results to the codes in the carbon database. For example, HRB400 corresponds to a carbon emission factor of... The density benchmark for HRB400, as found in the carbon database, is... If the actual density of a certain component is The density deviation ratio is calculated as follows: ,in: Density deviation rate (dimensionless). Actual material density of the component (unit: ), Carbon factor standard density benchmark (unit: Substituting the values ​​into the equation yields: Then, the original carbon emission factors Make corrections: ,in: Adjusted carbon emission factor (unit: ), Basic carbon emission factor (unit: Substituting into the calculation, we get... Then, the adjusted carbon emission factor and component mass will be used to further refine the calculation. Combined, calculate the total carbon emissions of the components: ,in: Total carbon emissions of components (unit: ), Component mass (unit: kg) Adjusted carbon factor (unit: Substituting into the calculation, we get: The carbon emission value of the component is recorded under the material number and matched with the component code list. All component carbon emission data are integrated to form a carbon standard factor set.

[0068] Please see Figure 2 and Figure 4 The thermal inertia analysis module includes:

[0069] The component data linkage submodule calls the component engineering quantity parameters and the component number, material name and total component engineering quantity in the carbon standard factor set. It performs matching processing based on the component number, filters the component items with complete material and size information, and performs data linkage processing with the matching results and the statistical environmental temperature change sequence to generate the component thermal response input set.

[0070] The process involves calling upon the component quantity parameters and the component number, material name, and total component quantity from the carbon standard factor set. First, the corresponding number field for each component is extracted from the parsed component parameter database. The component number is then compared item by item with the component code in the carbon standard factor set. Entries existing in both databases and with matching codes are registered and retained as valid items. Simultaneously, the material name field in the matching items is verified; components with empty material names or marked as "unknown" are excluded. For the remaining items, their dimensional parameters are checked for completeness, including volume, size combinations, and quantity. Only components that simultaneously meet the conditions of component code, material name, and dimensional completeness are retained for subsequent calculations. Based on this, the component number is obtained... The time series data corresponding to the building number is imported, along with hourly temperature change data for the area where the building is located. This data is a daily distribution sequence of the annual average temperature, recorded in a 24-hour × 365-day matrix. Meteorological data of the building's location is used as the input source. For example, if a project is located in Guangzhou, the daily average temperature value for the corresponding year is read from the local meteorological database, one set per hour, forming a yearly temperature change sequence with a total length of 8760 sets of data. This temperature change data is then linked with the component quantity information according to the component number. Each component record corresponds to an hourly temperature sequence segment, constructing a unified data structure table. The columns include component number, material type, volume, quantity, total quantity, and 8760 rows of hourly temperature record entries. Finally, these are integrated to form the component thermal response input set.

[0071] The thermal parameter correction submodule is based on the component thermal response input set. It calls the initial value of the material's thermal capacity coefficient and the initial time of thermal conduction delay. It combines the hourly temperature gradient in the ambient temperature change sequence, compares the deviation between the measured temperature difference and the theoretical temperature difference of the component's thermal response, and adjusts the original thermal capacity coefficient and thermal conduction delay time according to the deviation difference to obtain the thermal parameter correction coefficient pair.

[0072] Based on the component thermal response input set, the initial thermal capacity coefficient and thermal conduction delay time value corresponding to the material name identified by the component are read. This initial value is referenced from the value table provided in the building materials thermal performance specification standard. For example, the initial thermal capacity value of concrete is set as follows: The initial thermal conduction delay time is set to The system then extracts hourly temperature records for each component from the component thermal response input set. The temperature difference between any two consecutive time points is calculated as the temperature gradient. For example, if the temperature of a component at hour 101 and hour 100 are 29.6°C and 28.9°C respectively, the gradient is 0.7°C. This temperature gradient value, along with previously recorded total component volume and unit density values, is used to simulate the thermal response. The system records a measured temperature difference of 1.8°C between the outer surface and inner core of the component, compared to a theoretical temperature difference estimated based on initial thermal parameters of 2.3°C. The deviation is 0.5°C. Corrections are made based on this deviation. If the deviation exceeds a set difference threshold of 0.3°C, a coefficient adjustment operation is triggered. In this case, the corrected heat capacity value is reduced by 6% from the original value, i.e., the heat capacity correction value is adjusted to... The thermal conduction delay time is also increased by 8%, that is, adjusted to The corrected values ​​are recorded in the component thermal parameter structure table, and the differences between the original values ​​and the adjusted values ​​are archived to generate thermal parameter correction coefficient pairs.

[0073] The inertial parameter output submodule calculates the thermal flux response amplitude, temperature transfer time interval, and reaction rate range of each component in parallel based on the thermal parameter correction coefficient and the thermal capacity and thermal conductivity correction coefficient of each component, combined with the component material type and size structure parameters, to obtain the component thermal inertial characteristic parameters.

[0074] Based on the thermal parameter correction factors, the heat capacity and thermal conductivity correction factors for each component are first matched. Then, the material type of the component is matched, and its reference range for heat flux per unit volume is retrieved from the material standard heat flux table. For example, the reference range for steel components is set as follows: Then, combining the component's geometric parameters such as volume and thickness, estimate its heated surface area and heat transfer path length. Based on the adjusted values ​​of heat capacity and heat conduction time, re-estimate the temperature rise time and amplitude at the component's center point after a unit heat input, thereby calculating the temperature transfer time interval. Taking a concrete wall as an example, with a thickness of 30cm and an area of... Quality is Correct the heat capacity to The unit heat input is Enter by hour Heat, the temperature rise at the center point of the component is approximately Based on the variation in heat transfer rate, this time is adjusted to In the range, the surface temperature rise time was measured to be 1 hour, so the temperature transfer time interval was constructed to be 4.3–4.8 hours. The temperature response rate of different materials in this range was further recorded, classified and summarized, and finally a list of components containing indicators such as heat capacity correction value, thermal conduction delay, heat transfer rate, and response time was constructed to obtain the thermal inertia characteristic parameters of the components.

[0075] Please see Figure 2 and Figure 5 The carbon list generation module includes:

[0076] The phase carbon emission calculation submodule is based on the thermal inertia characteristic parameters of components and the carbon standard factor, which collect the heat capacity, heat conduction time and unit carbon emission of components. It divides the environmental response cycle of each component in the construction, construction and operation phases. After matching the thermal inertia and carbon factor data within the cycle, it calculates the carbon emission of each component within a specified time and sums them up to obtain the total phase carbon emission.

[0077] Based on the component's thermal inertia parameters and carbon standard factor, the component's heat capacity parameters are first extracted. Thermal conduction response time and unit carbon emission factor This involves constructing a thermal response mapping system. By analyzing the material properties and operational data of building components (such as concrete walls), the system acquires their daily heat exchange fluctuations. The construction, operation, and maintenance phases are then divided into different time periods with corresponding response cycles. For example, the operation phase can be set to four cycles per day, each cycle lasting six hours, based on changes in summer solar radiation intensity. These cycles are then labeled as follows: , , , In each cycle, the ratio of the component's heat capacity participating in heat exchange is collected. This is combined with the basic carbon factor for calculation. Specifically, if a component is a reinforced concrete wall, the mass... Specific heat per unit Unit carbon emission factor Then its total heat capacity is If the activation heat capacity percentage per cycle The effective heat capacity during the cycle is Further assuming that this thermal energy is equivalent to carbon energy consumption, then the carbon emissions for this cycle are: The daily carbon emissions for the four cycles are as follows: , , , The daily carbon emissions of this component are Extending to a 180-day operational phase, the total is This process can be extended to sub-processes such as construction (e.g., the formwork fixing stage) and construction (e.g., the spraying stage), forming a stage carbon emission distribution map one by one.

[0078] The factor value adjustment submodule detects the usage frequency and functional status of components in each stage based on the difference between the carbon emission values ​​and carbon factor values ​​of components in the construction stage and the operation stage in the total carbon emission of each stage. It uses the thermal inertia response cycle of the components as a reference to perform coefficient supplementation processing on the adjusted carbon emission factor values ​​and obtain the stage factor adjustment coefficient group.

[0079] Based on the differences in carbon emission values ​​and carbon factor values ​​between components in the construction and operation phases of the total carbon emissions, it is necessary to first obtain the actual usage frequency of the components in each phase. For example, the usage frequency of an office building's exterior wall component is 10 hours per day in the operation phase and 3 hours per day in the construction phase. Combining the functional status of the components, such as using materials with high thermal inertia (e.g., thick concrete) for highly sealed exterior walls, their thermal stability is significant within the response cycle. Furthermore, the thermal inertia parameters within the cycle are used as a benchmark to form a factor adjustment reference set with the carbon emission values. A component-factor mapping table is constructed for each cycle. Then, for cycles with large factor differences, adjustment coefficients are set, and the expression for the adjustment coefficients is defined as follows: ,in:

[0080] : Represents a component In the cycle The factor offset adjustment value below; :cycle The actual observed carbon emission factor is given in units of ; Reference benchmark factors for the same period, with consistent units; :cycle Lower thermal inertial response time (unit: hours); :member In all The sum of thermal response times over each cycle; :cycle Functional runtime (in hours); :member Total functional duration across all cycles. Assume the operational phase of a component is divided into 3 cycles, with the observed factors being... , , The unified reference value is The corresponding periodic thermal response time is Functional time is Calculate the sum of the parameters to obtain: Substitute into the calculation: , , These three adjustment values ​​constitute the carbon factor correction sequence for the component during each cycle of the operation phase, and serve as important input data for subsequent calculations of the component's total carbon factor.

[0081] The emission list construction submodule calls the correction value of each component in the stage factor adjustment coefficient group and combines it with the initial carbon factor value. It then redistributes the carbon emission factor according to the stage in which the component is located, and combines the number of components in each stage with the corresponding carbon emission value to collect and output the adjusted data by stage, thus establishing a staged carbon emission list.

[0082] The process involves combining the adjusted value of each component in the stage factor adjustment coefficient group with the initial carbon factor value. First, components are categorized according to their construction, operation, or maintenance phase. For example, the foundation structure of a building might be in the construction phase, the exterior wall structure in the maintenance phase, and the air conditioning system in the operation phase. Then, the initial carbon emission factor value and adjustment coefficient are extracted from the component list to construct the adjusted total carbon emission factor value. This is used for subsequent calculations of total carbon emissions, and its formula is as follows: ,in: :member The adjusted carbon emission factor at each stage of its life cycle, in units of ; The basic carbon factor of this component (uncorrected value); :member In the Correction coefficients in each cycle; : Number of stages / cycles. If we take... The sum of the adjustment values ​​is: ,but: To calculate the total carbon emissions of this component, use the following formula: ,in: :member Total carbon emissions, in units of ; Component mass, in units of In this example, it is ; : Corrected carbon emission factor, taking Substitute into the calculation: The total carbon emissions are used to classify and summarize the total emissions at each stage. Combined with the component number and material type, the output is summarized in stages. Detailed output can be provided at the component level according to the component dimension. Finally, a complete sub-item data structure containing carbon factors and carbon emissions at each stage is established.

[0083] Please see Figure 2 and Figure 6 The carbon emission monitoring module includes:

[0084] The emission path construction submodule is based on the carbon emissions of components and the information of the stage in the phased carbon emission list. The phased carbon emission values ​​are input into the LEAP model, and the corresponding time nodes are arranged and integrated. After normalizing the total carbon emission values ​​of multiple stages according to the building area, the slope of change and fluctuation density in the time series are extracted to generate the carbon emission intensity change path.

[0085] Based on the component carbon emissions and their respective phase information in the phased carbon emission list, the carbon emission values ​​of each component at different phases (such as construction, operation, etc.) are first extracted. Then, the carbon emission data for each phase are input into the LEAP model. The LEAP model arranges and integrates the carbon emission information for each phase according to the timeline of the building project. To better analyze the relationship between carbon emissions at each phase and building area, the carbon emission values ​​for each phase are normalized according to the total building area, with units of [unit missing]. This facilitates comparison and analysis between different stages. The normalization calculation formula is as follows: ,in: Indicates the first Carbon emission intensity per unit area at each stage, in units of ; Indicates the first Total carbon emissions for the phase, in units ; The total floor area of ​​the building, in units of For example, suppose the total area of ​​a building is... The carbon emissions at a certain stage were Then the carbon emission intensity per unit area during this stage is: Next, the normalized carbon emission intensity sequences for each stage are arranged according to time nodes to generate a continuous path of carbon emission intensity change. To analyze the trend of carbon emission changes, the slope and fluctuation density between each time node are further extracted. The slope reflects the rate of change of carbon emission intensity over time; the slope is calculated using the central difference method. ,in: For time points The slope of carbon emission intensity at the location; and They are time points respectively and The carbon emission intensity at a given location. For example, if the carbon emission intensity sequence for a certain period is... (unit: Then at the midpoint of time The slope at is: Furthermore, fluctuation density reflects the frequency of fluctuations in carbon emission intensity over time. A threshold condition is set; if the absolute value of the slope exceeds a set threshold (e.g., ...), a judgment condition is established. If the change slope sequence for a given period is [value missing], then that period is considered a highly volatile segment with significant changes in carbon emissions. For example, if the change slope sequence for a given period is [value missing], then [value missing]. If so, it can be determined that the fluctuation density is high during that period.

[0086] The phase sequence prediction submodule calls the change trend and phase boundary information in the carbon emission intensity change path. Based on the life cycle segmentation setting in the LEAP model, it performs time series filling and trend extrapolation for multiple phases such as construction, delivery and operation, continuously calculates the change nodes and superimposes the phase effect factors to obtain the life cycle carbon emission sequence.

[0087] This method utilizes the trend and stage boundary information of carbon emission intensity change paths, using known stage start and end points from the original path sequence as the index base and life cycle stages from the LEAP model as stage reference templates. It then fills in time gaps or discontinuities between known stages on the time axis using linear interpolation. For example, if data for years 25 to 30 of the operational period is missing, the carbon intensity of year 24 is used. 31st year Using the start and end points as the starting and ending points, we can calculate the results sequentially. , , , , , Simultaneously, a slope trend line is extended at the change points at the stage transition boundary, and the stage effect factor of each stage is superimposed to correct the fitting trend. The stage effect factor is used to adjust the increase or decrease in carbon emissions caused by the characteristics of each stage, and its calculation formula is as follows: ,in: :member In the stage The stage effect factor (dimensionless). :member In the stage The actual average carbon emissions, in units of ; :member In the stage Industry reference carbon emission values, in units of ; Component functional utilization factor, indicating the component's performance in a given stage. Frequency of use (percentage) in the data; Component time occupancy factor: indicates the component's time occupancy during the stage. The ratio of usage time to standard time. (Based on components) During the operation phase For example, let: actual average carbon emissions. Industry reference carbon emission values Functional usage coefficient Time occupancy factor Substitute into the formula: Therefore, the effect factor of this component during the operation phase is: This will be used as a gain coefficient when filling in the carbon emission sequence, and will be superimposed on the corresponding interpolation points. The corrected point value is Ultimately, a complete life-cycle carbon emission sequence with stage characteristics and taking into account the influence of structural thermal inertia is generated.

[0088] The peak contribution analysis submodule extracts the total carbon emission value of components and component number during the peak period based on the peak node of carbon emission in each stage of the life cycle carbon emission sequence, calculates the proportion of carbon emission of components, classifies components, summarizes the emission contribution of components in the peak interval, and outputs the carbon emission change trend monitoring results.

[0089] Based on the peak carbon emission nodes of each stage in the life cycle carbon emission sequence, a sliding window extraction method is used to identify the largest local segment of carbon emission. The judgment condition is that the median of any five consecutive time nodes is greater than any two points on either side and exceeds the sliding average by more than 10%. This is considered a peak node and included in the analysis sequence. Subsequently, the total carbon emission data of components within this peak interval and their component numbers are extracted. By using the component number, the category and stage to which the component belongs are traced back. The proportion of total carbon emission of components by stage and category is calculated. For example, if the total carbon emission of the peak interval is... The structural components are emitted as Enclosure components are Equipment components are Then their contribution ratios are respectively structural components Enclosure components Equipment components After classification, the data are summarized according to component category to obtain the quantitative proportion of each component in the peak carbon emission range. This result serves as the input for component carbon emission distribution trend analysis, forming a carbon peak contribution dataset for back-inferring high-intensity nodes in the carbon monitoring model.

[0090] Please see Figure 2 and Figure 7 It also includes an energy consumption parameter optimization module. Based on the monitoring results of carbon emission change trends, the energy consumption parameter optimization module uses the particle swarm optimization algorithm to iteratively adjust the parameters of carbon emission factors, outputs a carbon factor optimization list, updates the carbon emission parameters, and obtains the energy consumption parameter optimization results.

[0091] The energy consumption parameter optimization module includes:

[0092] The factor variable initialization submodule extracts the initial value and change range of carbon emission factors for the corresponding stage of the component based on the carbon emission intensity change path, peak interval and component category contribution in the carbon emission change trend monitoring results. It then divides the change range into intervals, sets the initial position of the optimization particles and assigns stage labels to generate a carbon emission factor variable group.

[0093] Based on the carbon emission intensity change paths, peak intervals, and component category contributions from carbon emission trend monitoring results, this study first extracts the initial carbon emission factor values ​​for each component at different lifecycle stages (e.g., construction, operation) from the carbon emission intensity change paths. Combining the lifecycle and stage characteristics of the components, the carbon emission factor and its change amplitude at each stage are divided into intervals. Based on the characteristics of these change amplitudes, suitable initial particle positions for each stage are determined, and each particle is assigned a stage label. This label identifies the stage category of the carbon emission factor to which each particle belongs. For example, the initial carbon emission factor values ​​for a project's building at different stages (construction, operation) are as follows: , , After calculation, the magnitude of factor change in each stage was obtained as follows: Based on these variation ranges, starting positions were set for each particle initialization, and their respective stage labels (such as construction stage, building stage, and operation stage) were marked. Subsequently, these initialized particle positions and labels were combined to form a set of carbon emission factor variables for use in subsequent iterative calculations of emission factors.

[0094] The emission factor iteration submodule calls the carbon emission factor parameter values ​​and variation ranges of each stage component in the carbon emission factor variable group, compares the difference between the carbon emission factor value corresponding to the current position of each particle and the target carbon emission value in the life cycle carbon emission sequence, adjusts the particle position proportionally according to the difference and records the optimal position, and obtains the carbon factor optimization list.

[0095] The carbon emission factor parameter values ​​and variation ranges of each stage component in the carbon emission factor variable group are called. The difference between the carbon emission factor value corresponding to the current position of each particle in each round and the target carbon emission value in the life cycle carbon emission sequence is compared. By calculating the magnitude of the difference between the current position of each particle and the target carbon emission value, the position of the particle is adjusted proportionally according to this difference, and the optimal position in each round is recorded. For this purpose, the position change formula of each particle adopts the following form: ,in: The new position of the particle (i.e., the new carbon emission factor value); The position of the particle (i.e., the current carbon emission factor value); The adjustment step size of a particle represents the shift of the particle's current position towards the optimal position;

[0096] Target carbon emission factor value (e.g., target life cycle emission value); The carbon emission factor at the particle's current position. Assume the initial carbon emission factor of a particle is... The target carbon emission value is Then, the new position of the particle can be calculated using the formula above: ,in, Substituting, we get: In each iteration, the position of the particle is gradually adjusted, and the carbon emission factor of the particle is recorded and updated according to the optimal position after adjustment, eventually forming a list containing the optimized carbon emission factor values ​​of all components.

[0097] The energy consumption parameter update submodule compares the adjusted carbon emission factor parameters of components in the carbon factor optimization list with the original carbon emission factor parameters, and replaces the optimized carbon emission factor parameters with the parameter table according to the category and stage of the components, thus establishing the energy consumption parameter optimization results.

[0098] Based on the comparison between the adjusted carbon emission factor parameters of components in the carbon factor optimization list and the original carbon emission factor parameters, adjustments are made according to the optimized carbon emission factors. The optimized carbon emission factor parameters replace the original factor parameters and are written into the parameter table according to the component's category and stage order. Based on stage-specific adjustments, the carbon emission factor parameters of each component are replaced according to its optimized carbon emission factor values ​​at different stages. For example, if the initial carbon emission factor of a component is... After iterative optimization of the emission factors, the optimized factors are obtained as follows: Then the parameters of the component will be updated and replaced with the new ones. The values ​​are then used to generate an optimized energy consumption parameter table, facilitating subsequent carbon emission calculations and energy consumption monitoring. This process continuously optimizes the carbon emission factors of different components at each stage of their life cycle, ensuring that the overall carbon emission level of the building project better meets target requirements.

[0099] The above are merely preferred embodiments of the present invention and are not intended to limit the present invention in any other way. Any person skilled in the art may make changes or modifications to the above-disclosed technical content to create equivalent embodiments that can be applied to other fields. However, any simple modifications, equivalent changes, and modifications made to the above embodiments based on the technical essence of the present invention without departing from the scope of the present invention shall still fall within the protection scope of the present invention.

Claims

1. A BIM-based building carbon emission monitoring system, characterized in that: The system includes: The model building module is used to acquire component composition data, including material type, size and quantity information. Based on the IFC standard, it parses BIM data as component quantity parameters and calculates preliminary carbon emission factors, which are then integrated into a carbon standard factor set and transferred to the thermal inertia analysis module. The thermal inertia analysis module is used to call the component engineering quantity parameters and the carbon standard factor set, combine them with the statistical environmental temperature change sequence, perform correction calculations on the material heat capacity coefficient and thermal conduction delay time, and output the component thermal inertia characteristic parameters to the carbon list generation module. The carbon list generation module is used to calculate the carbon emissions for each stage by referring to the thermal inertia characteristic parameters of the component and the carbon standard factor set, and to adjust the carbon emission factors for the construction and operation stages by referring to the carbon emissions, and to generate a phased carbon emission list and transmit it to the carbon emission monitoring module. The carbon emission monitoring module is used to input the phased carbon emission list into the LEAP model, construct the carbon emission intensity change path, obtain the carbon emission prediction sequence for each stage of the life cycle, analyze the peak time of carbon emissions, component type and component contribution rate, and output the carbon emission change trend monitoring results. The thermal inertia analysis module includes: The component data linkage submodule calls the component engineering quantity parameters and the component number, material name and total component engineering quantity value in the carbon standard factor set. It performs matching processing based on the component number, filters out component items with complete material and size information, and performs data linkage processing with the matching results and the statistical environmental temperature change sequence to generate the component thermal response input set. The thermal parameter correction submodule, based on the component thermal response input set, calls the initial value of the material's thermal capacity coefficient and the initial time of thermal conduction delay, combines the hourly temperature gradient in the ambient temperature change sequence, compares the deviation difference between the measured temperature difference and the theoretical temperature difference of the component's thermal response, and adjusts the original thermal capacity coefficient and thermal conduction delay time according to the deviation difference to obtain the thermal parameter correction coefficient pair. The inertial parameter output submodule calculates the thermal flux response amplitude, temperature transfer time interval, and reaction rate range of each component in parallel based on the thermal parameter correction coefficients for the heat capacity and thermal conductivity correction coefficients of each component, combined with the component material type and size structure parameters, to obtain the component thermal inertial characteristic parameters. The carbon list generation module includes: The phase carbon emission calculation submodule is based on the thermal inertia characteristic parameters of the components and the heat capacity, heat conduction time and unit carbon emission of the components in the carbon standard factor. It divides the environmental response cycle of each component in the construction, operation and operation phases. After matching the thermal inertia and carbon factor data within the cycle, it calculates the carbon emission of each component within a specified time and sums them up to obtain the total phase carbon emission. The factor value adjustment submodule detects the usage frequency and functional status of components in each stage based on the difference between the carbon emission values ​​and carbon factor values ​​of components in the construction stage and the operation stage in the total carbon emission of the stage. It uses the thermal inertia response cycle of the component as a reference to perform coefficient supplementation processing on the adjusted carbon emission factor value to obtain the stage factor adjustment coefficient group. The emission list construction submodule calls the correction value of each component in the stage factor adjustment coefficient group and the initial carbon factor value to combine them numerically. It then redistributes the carbon emission factor according to the stage division of the component and combines the number of components in each stage with the corresponding carbon emission value to collect and output the adjusted data by stage, thus establishing a staged carbon emission list. The adjusted carbon emission factor value is supplemented with a coefficient using the following formula: ； Calculation components In the cycle Factor offset adjustment value ; in, It is a cycle Actual carbon emission factors were observed. It is a reference benchmark factor for the same period. It is a cycle Thermal inertial response time It is a component In all The sum of thermal response times over each cycle It is a cycle Function runtime It is a component Total duration of functionality across all cycles.

2. The BIM-based building carbon emission monitoring system according to claim 1, characterized in that: The component engineering quantity parameters include component quality indicators, size combination form, and engineering quantity structural hierarchy. The component thermal inertia characteristic parameters specifically include heat capacity adjustment coefficient, thermal conductivity delay factor, and temperature change response coefficient. The phased carbon emission list includes the initial construction period carbon emission list, the operation and maintenance period carbon emission list, and carbon emission factor adjustment records. The carbon emission change trend monitoring results specifically include carbon intensity evolution curve, carbon peak time prediction value, and component contribution ranking list.

3. The BIM-based building carbon emission monitoring system according to claim 1, characterized in that: The model building module includes: The component data extraction submodule obtains the material type, size and quantity information from the component composition data, classifies and numbers the material types, constructs a component size structure table based on the size and quantity information, and combines the component size structure table with the classification and numbering results to generate a component code list. The parameter calculation and aggregation submodule, based on the component code list, calls the geometric parameters and physical information of the corresponding components in the IFC standard data structure, parses and obtains the volume, quantity and material density of the components, combines the three parameters to perform data merging processing to form single component engineering quantity parameters, aggregates and calculates the engineering quantity data of all components, and generates a set of total component engineering quantity values. The carbon factor generation submodule selects basic carbon emission factor data matching the component material properties based on the total value set of component engineering quantities, compares the component material density with the standard factor density benchmark, adjusts the carbon factor according to the deviation ratio, maps the adjusted carbon factor to the component engineering quantity parameters and integrates them to generate a carbon standard factor set. The standard factor density benchmark was obtained by consulting the component material classification item in the industry carbon emission database.

4. The BIM-based building carbon emission monitoring system according to claim 1, characterized in that: The carbon emission monitoring module includes: The emission path construction submodule is based on the carbon emission of components and the information of the stage in the phased carbon emission list. It inputs the stage carbon emission value into the LEAP model, arranges and integrates the corresponding time nodes, normalizes the total carbon emission value of multiple stages according to the building area, and extracts the change slope and fluctuation density in the time series to generate the carbon emission intensity change path. The stage sequence prediction submodule calls the change trend and stage boundary information in the carbon emission intensity change path, and based on the life cycle segmentation setting in the LEAP model, performs time series filling and trend extrapolation for multiple stages such as construction, delivery and operation, continuously calculates the change nodes and superimposes the stage effect factors to obtain the life cycle carbon emission sequence. The peak contribution analysis submodule extracts the total carbon emission value of components and component number during the peak period based on the peak node of carbon emission in each stage of the life cycle carbon emission sequence, calculates the proportion of carbon emission of components, classifies components, summarizes the emission contribution of components in the peak interval, and outputs the carbon emission change trend monitoring results.

5. The BIM-based building carbon emission monitoring system according to claim 4, characterized in that: For the stage effect factor, the formula is used: ； Calculation components In the stage Stage effect factor ; in, It is a component In the stage The actual average carbon emissions, It is a component In the stage Industry reference carbon emission values, It is the component's functional utilization factor, indicating the component's performance at a given stage. The activation frequency in It is the component time occupancy factor, indicating the component's time occupancy during the stage. The ratio of usage time to standard time.

6. The BIM-based building carbon emission monitoring system according to claim 1, characterized in that: It also includes an energy consumption parameter optimization module, which uses a particle swarm optimization algorithm to iteratively adjust the parameters of carbon emission factors based on the carbon emission change trend monitoring results, outputs a carbon factor optimization list, updates the carbon emission parameters, and obtains the energy consumption parameter optimization results. The carbon factor optimization list includes a set of correction coefficients, a set of optimization and adaptation parameters, and update and iteration records. The energy consumption parameter optimization results specifically refer to the carbon factor correction table, life cycle energy consumption index, and optimized carbon emission benchmark.

7. The BIM-based building carbon emission monitoring system according to claim 6, characterized in that: The energy consumption parameter optimization module includes: The factor variable initialization submodule extracts the initial value and change range of carbon emission factors for the corresponding stage of the component based on the component carbon emission intensity change path, peak interval and component category contribution in the carbon emission change trend monitoring results, performs interval division processing on the change range, sets the initial position of the optimization particles and assigns stage labels, and generates a carbon emission factor variable group. The emission factor iteration submodule calls the carbon emission factor parameter values ​​and variation ranges of each stage component in the carbon emission factor variable group, compares the difference between the carbon emission factor value corresponding to the current position of each particle and the target carbon emission value in the life cycle carbon emission sequence, adjusts the particle position proportionally according to the difference and records the optimal position, and obtains the carbon factor optimization list. The energy consumption parameter update submodule compares the adjusted carbon emission factor parameters of components in the carbon factor optimization list with the original carbon emission factor parameters, and replaces the optimized carbon emission factor parameters with the parameter table according to the category and stage of the components, thus establishing the energy consumption parameter optimization results.

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