Tropical zone zero-carbon building integrated energy-saving energy production and consumption design and regulation and control system

Abstract

The invention discloses a tropical zone zero-carbon building integrated energy-saving energy production and consumption design and regulation and control system. Comprising a parameterization modeling module used for establishing parameterization models of a building energy-saving subsystem, a capacity subsystem and an energy consumption subsystem; the simulation module is used for simulating energy consumption and carbon emission performance of the building under different parameter combinations; the optimization module is used for executing multi-objective optimization calculation based on the simulation result so as to determine optimal building design parameters and operation parameters meeting a preset carbon emission objective; the control module is used for carrying out coordination control on the energy-saving subsystem, the energy production subsystem and the energy consumption subsystem according to the optimal parameters output by the optimization module; and the monitoring feedback module is used for monitoring real-time energy consumption, capacity and environment data of the building and feeding back the data to the simulation module and the optimization module so as to iteratively update the model and the optimization strategy. The method has the remarkable advantages of energy conservation and emission reduction.

Description

Technical Field

[0001] The present application relates to the field of green building and intelligent control technology, and in particular to a zero-carbon building integrated energy-saving production capacity and energy use design and control system in tropical areas. Background Art

[0002] During design and operation, comprehensive consideration should be given to reducing energy consumption (energy conservation), generating energy from renewable energy (energy production), and using energy efficiently and rationally (energy use). Buildings in tropical regions, due to their hot and humid climate, experience heavy air conditioning and cooling loads, long lighting hours, and high energy demands. Furthermore, these regions are also rich in solar resources, offering advantages for installing photovoltaic power generation. Therefore, promoting zero-carbon buildings in tropical regions requires a holistic solution that integrates energy-saving design strategies, renewable energy production systems, and energy management strategies. Current technologies often operate independently of building energy-saving design and renewable energy system design. During the design phase, attention is focused on passive energy conservation measures such as building orientation, building envelope, and shading, while renewable energy systems are added later. In terms of building operation and management, systems such as air conditioning and lighting employ independent control strategies, lacking overall coordination. This disconnected design and control approach makes it difficult to ensure that buildings achieve zero-carbon goals. For example, simply improving building envelope insulation or increasing photovoltaic capacity, without combining it with appropriate energy use control, can lead to supply-demand imbalances or reduced comfort levels. There is a lack of an integrated system that comprehensively optimizes multiple energy-saving and energy-production measures during the design phase and dynamically regulates and corrects these subsystems during operation. Summary of the Invention

[0003] The purpose of this invention is to provide an integrated energy-saving, energy-efficient, and energy-use design and control system for zero-carbon buildings in tropical regions. This system overcomes the existing lack of coordination across building energy-saving design, energy-efficient system configuration, and energy-use control. This system optimizes and integrates multiple low-carbon measures during the building design phase, and coordinates and controls various energy systems during the building operation phase, providing real-time feedback and adjustments to ensure that the building achieves and maintains zero-carbon operation.

[0004] To achieve the above objectives, the present invention provides the following technical solutions: a tropical zero-carbon building integrated energy-saving production capacity and energy use design and control system, including a parametric modeling module, a simulation module, an optimization module, a control module and a monitoring feedback module. The parametric modeling module is used to establish parametric models of the building's energy-saving subsystem, energy-production subsystem, and energy-consuming subsystem, integrating the design and operating parameters of each subsystem into a unified data framework; A simulation module, connected to the parametric modeling module, for simulating the energy consumption and carbon emission performance of the building under different parameter combinations; an optimization module, connected to the simulation module, for performing multi-objective optimization calculations based on the simulation results to determine optimal building design parameters and operating parameters that meet preset carbon emission targets; a control module, configured to coordinate and control the energy-saving subsystem, the energy-generating subsystem, and the energy-consuming subsystem according to the optimal parameters output by the optimization module; The monitoring and feedback module is used to monitor the real-time energy consumption, production capacity and environmental data of the building, and feed the data back to the simulation module and optimization module to iteratively update the model and optimization strategy, thereby forming a closed-loop optimization and control of the building's carbon emissions.

[0005] More preferably, the parametric modeling module includes: an energy-saving parameter group for representing passive energy-saving measures of a building, a production capacity parameter group for representing a renewable energy production system, and an energy consumption parameter group for representing energy-consuming equipment and control strategies.

[0006] More preferably, the energy-saving parameter group includes at least the design parameters of building orientation, shape coefficient, thermal performance of the envelope structure, window-to-wall ratio, and shading coefficient; the production capacity parameter group includes at least the design parameters of photovoltaic module layout and capacity, and energy storage device capacity; the energy consumption parameter group includes at least the operating parameters of air-conditioning temperature setting value, ventilation rate, lighting power density, and equipment operation schedule.

[0007] Preferably, the optimization module is configured with a multi-objective evolutionary algorithm for simultaneously optimizing at least two objective functions; the objective functions include indicators related to carbon emissions and energy utilization, and balance the objectives based on pre-set weights or a Pareto optimal solution selection mechanism; the optimization module aims to minimize annual total carbon emissions during the design phase, and to minimize the immediate carbon emission rate or balance energy supply and demand during the operation phase.

[0008] Preferably, the simulation module uses dynamic building energy consumption simulation software or a verified machine learning prediction model to perform performance simulation on the parameter scheme provided by the parametric modeling module; during the operation phase, the simulation module uses real-time monitoring data as a digital twin model to correct the simulation to improve the accuracy of optimization decisions.

[0009] Preferably, the control module includes: an air conditioning control unit, a lighting control unit, an equipment power control unit, and a photovoltaic and energy storage control unit; each control unit respectively receives the corresponding subsystem optimization parameters output by the optimization module, and automatically adjusts the operating settings of the relevant equipment, so that the various subsystems of the building work together according to the optimization plan.

[0010] Preferably, the monitoring and feedback module is equipped with energy consumption monitoring instruments and environmental sensors for collecting indoor and outdoor temperature, humidity, illumination, equipment power, photovoltaic power generation, and power purchase from the grid; when actual carbon emissions deviate from the target threshold, the monitoring and feedback module triggers the optimization module to re-optimize the calculation and send the updated optimal control parameters to the control module to continuously correct the building operation strategy and maintain low-carbon operation.

[0011] Preferably, the control module includes at least one industrial controller that supports BACnet / IP and Modbus-TCP protocols and is used to perform command interaction with subsystems such as air conditioning, lighting, energy storage and electric meters.

[0012] Preferably, the control module is integrated with a remote upgrade interface and a local configuration port, which support the sending of control parameters and the transmission of operating status via Ethernet and Wi-Fi.

[0013] Preferably, the system has a fault switching logic. When the local controller goes offline, crashes, or the data link is interrupted for more than a preset time limit, the system automatically calls the cloud control model to take over the generation and execution of instructions.

[0014] In summary, the system of the present invention achieves the following functions through the synergy of the above modules: During the design phase, the system can obtain the optimal design solution covering energy conservation, production capacity, and energy use measures through parametric modeling, simulation, and optimization, theoretically achieving zero carbon emissions for the building; during the operation phase, the system takes over building energy management, regulating the operation of each subsystem through optimized control strategies, and continuously correcting it with the help of feedback mechanisms to ensure that actual operating results are consistent with design goals. This integrated system, which integrates design and operation, maximizes the synergistic benefits of each subsystem, avoids the inefficiencies and deviations caused by independent design and control, and has significant advantages in energy conservation and emission reduction.

[0015] Compared with the existing technology, the beneficial effects of the present invention are: 1. Design optimization integration: the passive energy-saving design, active energy production system configuration and terminal energy use strategy of the building are incorporated into a unified parametric model and optimization framework, so that the energy consumption and carbon emissions of each scheme can be comprehensively weighed in the design stage to achieve one-time optimization, avoiding the problem of inconsistent schemes that may occur in traditional item-by-item design; 2. Multi-objective optimization decision-making: the system has a built-in intelligent optimization algorithm, which can simultaneously consider multiple goals such as energy consumption, carbon emissions, economic costs, and comfort. By assigning weights or multi-dimensional Pareto optimization, a design and control scheme that takes into account all aspects of performance is obtained, thereby improving the comprehensiveness and scientificity of the scheme; 3. Operation and control coordination: in the operation stage, the control module unifies Coordinate the operation of subsystems such as air conditioning, lighting, equipment, and photovoltaics, and use optimal control parameters to reduce unnecessary energy waste, overcome the low operating efficiency that may be caused by each system acting independently, and achieve coordinated and efficient operation of the entire building system; 4. Intelligent feedback iteration: Introducing a monitoring feedback mechanism, the system can automatically correct the model and optimization strategy according to actual data, gradually learn changes in the environment and usage patterns, and achieve adaptive regulation and optimization. Even in the case of abnormal climate or changes in usage patterns, it can still ensure the building's near-zero-carbon operating performance; 5. Strong applicability: This system is aimed at buildings in tropical areas, but its method is also of reference value for general green building design and operation, and can be promoted and applied to different types of buildings to reduce carbon emissions. In summary, the system of the present invention significantly improves the energy efficiency and carbon emission reduction effects of tropical zero-carbon buildings from design to operation, and has high application value. BRIEF DESCRIPTION OF THE DRAWINGS

[0016] The present invention is further described with reference to the accompanying drawings. However, the embodiments in the accompanying drawings do not constitute any limitation to the present invention. A person skilled in the art can obtain other drawings based on the following drawings without creative effort.

[0017] Figure 1 This is a functional module diagram of a tropical zero-carbon building integrated energy-saving production capacity and energy use design and control system according to the present invention; Figure 2 This is a schematic diagram of the integration of energy-saving, production capacity, and energy-consuming subsystems based on Hall 3D. DETAILED DESCRIPTION

[0018] The following will clearly and completely describe the technical solutions in the embodiments of the present invention in conjunction with the accompanying drawings. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without making creative efforts are within the scope of protection of the present invention.

[0019] See also Figure 1The present invention provides a tropical zero-carbon building integrated energy-saving production capacity and energy use design and regulation system, including a parametric modeling module, a simulation module, an optimization module, a control module and a monitoring feedback module.

[0020] Parametric Modeling Module: Used to establish parametric models for the building's energy-saving, energy-production, and energy-use subsystems. This module digitally models key parameters for building design and operation, including but not limited to: energy-saving subsystem parameters (such as building shape coefficient, orientation, building envelope heat transfer coefficient, window-to-wall area ratio, and shading coefficient); energy-production subsystem parameters (such as photovoltaic module installation area ratio, photovoltaic conversion efficiency, and energy storage device capacity); and energy-use subsystem parameters (such as air conditioning system control parameters, ventilation rate, lighting power density, and electrical equipment power and usage patterns). Through a parameter integration framework, these parameters are linked in a unified data model to describe the building's global energy system. The parametric modeling module supports the distinction between design-phase parameters (fixed parameters) and operational-phase parameters (adjustable parameters), providing a foundational model for subsequent simulation and optimization.

[0021] Simulation module: connected to the parametric modeling module, used to simulate the energy performance and carbon emissions of the building under different parameter combinations. The simulation module uses a building energy consumption simulation engine or a verified machine learning prediction model to calculate the various energy indicators of the building within an annual cycle for given parameter inputs, such as the energy consumption of air conditioning, lighting, and equipment and the resulting carbon emissions, as well as renewable energy power generation and carbon emission reductions. The simulation module can batch process the grouped parameter schemes provided by the parametric modeling module and output the corresponding performance indicators to provide data support for the evaluation and optimization of the design scheme. During the operation stage, the simulation module can also serve as a digital twin model, receiving real-time updated operating parameters and environmental conditions, predicting the energy performance of the building in the short term, and assisting real-time decision-making.

[0022] Optimization module: Connected to the simulation module, it is used to perform multi-objective optimization calculations to determine the optimal system design and control parameter combination that meets zero-carbon operation requirements. The optimization module has a built-in multi-objective optimization algorithm that can optimize according to the different needs of the design and operation stages: the design stage takes the minimization of the building's net carbon emissions throughout the year as the main goal, while taking into account constraints such as indoor thermal comfort, and searches for the optimal design parameter combination (such as envelope structure configuration, equipment selection, photovoltaic scale, etc.); the operation stage takes the real-time energy consumption and production capacity balance and the minimization of carbon emissions as the goals, and optimizes adjustable parameters (such as air conditioning temperature setting, start-up and shutdown timing of cold and heat storage equipment, etc.). The optimization module preferably uses a global intelligent optimization algorithm (such as genetic algorithm, particle swarm algorithm, etc.) and can combine it with a machine learning prediction model to accelerate evaluation.

[0023] In one specific implementation, the optimization module utilizes a multi-objective particle swarm optimization (MOPSO) algorithm framework based on the XGBoost prediction model to comprehensively optimize multiple building carbon emission indicators, obtaining a series of Pareto-optimal solutions. The optimal solution is then selected using a decision-making algorithm. The optimization module can set multiple objective functions based on the optimization goals, such as minimizing annual total carbon emissions, minimizing operating energy costs, maximizing renewable energy utilization, and so on, and can assign different weights to each objective to meet project priorities. The optimization solution process can be performed offline, centralized, during the design phase, or triggered periodically or in real time during operation.

[0024] The control module coordinates and controls the building's energy-saving, energy-production, and energy-use subsystems based on the optimal parameter solution output by the optimization module. The control module includes several control units corresponding to each subsystem: the air conditioning control unit, the lighting control unit, the equipment power control unit, and the photovoltaic and energy storage control units. Integrated with the building's building automation system (BAS) or energy management system (BEMS), the control module automatically applies the control setpoints specified in the optimal solution to adjust equipment operation. For example, the control module sends the optimal solution's air conditioning temperature settings and humidity control strategy to the air conditioning control unit for execution; sends the lighting daylight sensor dimming settings to the lighting control unit; sends the equipment start and stop schedule to the power equipment management unit; and sends the photovoltaic power output or energy storage charge and discharge strategy to the energy-production system control unit. Through this coordinated control, the building's various energy subsystems operate in coordination according to the optimized parameters, achieving the lowest overall energy consumption and carbon emissions. In actual operation, the control module also prioritizes each control unit based on instructions provided by the feedback module, for example, prioritizing non-critical loads when carbon emissions approach a threshold.

[0025] The Monitoring and Feedback Module monitors the building's operating status and provides feedback to refine models and optimize decisions. This module deploys various sensors and metering devices to collect real-time operational data, including indoor and outdoor environmental parameters (temperature, humidity, and illuminance), electricity consumption of air conditioning and lighting equipment, photovoltaic power generation, grid purchases, and indoor comfort indicators. The Monitoring and Feedback Module provides this data to the Simulation Module for calibrating model parameters to improve prediction and simulation accuracy. It also transmits key information to the Optimization Module, triggering iterative optimization. Specifically, when actual carbon emissions deviate from targets or environmental boundary conditions change significantly (e.g., extreme heat waves or changes in grid carbon intensity), the Optimization Module adjusts the model accordingly (e.g., updating constraints or redefining optimization objectives) and recalculates the optimal control solution. The Monitoring and Feedback Module also reassesses certain design parameters in the parametric modeling module based on daily and seasonal data accumulation, providing a basis for subsequent building renovations or strategy adjustments. This closed-loop monitoring-feedback-reoptimization mechanism ensures continuous improvement in energy performance throughout the building's lifecycle, ensuring a robust zero-carbon status.

[0026] In this embodiment, the design parameters of the tropical zero-carbon building energy-saving subsystem are shown in Table 1 below: Table 1 Summary of design parameters and typical research of energy-saving subsystems of tropical zero-carbon buildings The design parameters of the tropical zero-carbon building energy generation subsystem are shown in Table 2: Table 2 Summary of design parameters and typical research of energy generation subsystems of tropical zero-carbon buildings The operating parameters of the energy subsystem of tropical zero-carbon buildings are shown in Table 3: Table 3 Summary of operating parameters and typical research of energy subsystems in tropical zero-carbon buildings Depend on Figure 2Analysis shows that the energy-saving system dimension (S1~S12), the production capacity system dimension (P1~P15) and the energy consumption system dimension (U1~U8) interact in three dimensions in the form of an integrated system. That is, the three-dimensional parameters are first integrated, and then the redundant parameters are eliminated to form a three-dimensional integrated system and its design scheme. For example, in Scheme 1, the three-dimensional integrated system parameterization design of the energy-saving system dimension (S1-S5), the power generation system dimension (P1-P5), and the energy consumption system dimension (U1-U4) is: Scheme 1 = {S ∩P∩U} = {(S1, S2, S3,S4, S5) ∩ (P1, P2, P3, P4, P5) ∩ (U1, U2, U3, U4} = {(S1=P1), S2, S3, S4, S5,P2, P3, P4, P5, U1, U2, U3, U4}, where S1 and P1 are both building directions. By analogy, under the three-dimensional interaction conditions of energy-saving, power generation, and energy consumption, countless integrated system design schemes can be formed.

[0027] To ensure the completeness and representativeness of the parameterized design of the integrated system in this study, all parameters are integrated to form a basic scheme of a universally representative energy-saving, production and energy-consumption integrated system. As a result, the parameterized design of the three-dimensional integrated system of energy-saving system dimension (S1~S12), production system dimension (P1~P15) and energy-consumption system dimension (U1~U8) is as follows: Basic scheme = {S ∩ P ∩ U} = {(S1, S2,……, S12) ∩ (P1, P2, ……, P15) ∩ (U1, U2, ……,U8} = {(S1=P1), S2, S3,……, S7, (S8=P8), (S9=P9), (S10=P10), (S11=P11), S12,P2, P3,……, P7, P12, P13,……, P15, U1, U2, ……, U8}, where S1 and P1 are both building orientations, S8 and P8 are both east-facing window-to-wall ratios, S9 and P9 are both west-facing window-to-wall ratios, S10 and P10 are both south-facing window-to-wall ratios, and S11 and P11 are both north-facing window-to-wall ratios. Therefore, the design parameters for the integrated energy-saving, production, and energy-consumption system are formed, as shown in Table 4.

[0028] Table 4 Statistics of integrated system design parameters The standard format of triangular distribution is T(a, b, c), where a, b, and c are the minimum, peak, and maximum values, respectively; the standard format of uniform distribution is U(a, b), where a and b are the lower and upper limits.

[0029] Example 1: Integrated Optimization during the Design Phase. An office building in a tropical region was planned to be constructed as a zero-carbon building. The system of the present invention was used to optimize its energy conservation, production capacity, and energy usage during the design phase. First, an integrated parametric model of the building was established using a parametric modeling module. The building's north-south orientation (I1), shape coefficient, and window-to-wall ratio for each orientation (I8I11) were incorporated into the energy-saving parameter set. Passive energy-saving indicators such as the heat transfer coefficients of the exterior walls, roof, and floor slabs (I16, I17, I18) and the exterior window shading coefficient (I19) were also incorporated into the model. Regarding production capacity parameters, the roof and portions of the facade were assumed to be capable of photovoltaic installations, and the photovoltaic coverage ratio (I12I15) and photovoltaic panel efficiency were used as production capacity parameters. Regarding energy usage parameters, the air conditioning system type (all-air system), design cooling capacity, lighting power density (I25), and annual personnel and equipment load schedule were set. The parametric model distinguished between fixed design parameters and adjustable operational parameters. For example, I1I22 are parameters that cannot be changed after design, while I23I30 are operational parameters that can be adjusted in the future. Next, the simulation module simulated the performance of the preliminary design. Using EnergyPlus simulation software and inputting typical local meteorological data, the module calculated the building's annual total cooling load, lighting power consumption, and equipment power consumption under the current parameter settings, as well as the annual power generation assuming a certain area of ​​photovoltaic installation. Preliminary results showed that the proposed design, without photovoltaic installation, did not meet the zero-carbon target for annual carbon emissions. The optimization module then conducted a multi-objective optimization of the design: minimizing net carbon emissions and building lifecycle costs, while also constraining the number of indoor discomfort hours to a certain value. The optimization module employed a genetic algorithm to search for key design parameters, such as adjusting the orientation angle, increasing insulation thickness, replacing the air conditioning system with a more efficient one, and increasing photovoltaic coverage. After hundreds of generations of evolution, a series of Pareto-optimal design combinations were obtained. The optimization results showed that shifting the building's orientation by 30 degrees from the original plan to reduce western exposure, reducing the exterior wall heat transfer coefficient by 20%, installing as many photovoltaic panels as possible on the roof and south-facing exterior walls (increasing coverage to 90%), and selecting high-efficiency chillers could reduce the building's annual net carbon emissions to near zero. The optimization module compared the weighted comprehensive scores and selected the plan with the lowest net carbon emissions as the recommended solution. The design team adjusted the building design accordingly, adopting the optimized parameters. In the final design, the office building's exterior envelope is more efficient, the air conditioning system capacity is adapted, and the photovoltaic capacity is increased. This reduced the estimated annual net carbon emissions during the design phase to just one-ninth of the original plan, achieving a near-zero carbon level. This example demonstrates that the system can integrate multiple low-carbon measures during the building design phase, identify an optimized design solution, and significantly reduce carbon emissions during subsequent operation.

[0030] The system of this invention began to function during the operational phase. The building was equipped with a comprehensive monitoring and feedback module: smart meters were installed at air conditioning units, lighting distribution circuits, socket circuits, and photovoltaic inverters, recording power consumption by each item in real time. Indoor and outdoor environmental sensors collected temperature, humidity, and illumination data. The building automation system (BAS) aggregated this data and transmitted it to the monitoring and feedback module. During the initial months of operation, the control module operated equipment according to the optimized control parameters determined during the design phase: the air conditioning temperature was set to 26°C in summer, the fresh air system adjusted appropriately based on CO2 concentration and temperature requirements, and the lighting system used sensors to enable occupancy and daylight dimming. All photovoltaic power generation was self-sufficient, with excess power stored in batteries for backup. The monitoring and feedback module calculated the building's actual carbon emissions daily and compared them with design predictions. In the initial weeks, actual data closely matched the simulation predictions. However, during the extremely hot mid-to-late August, monitoring revealed that air conditioning power consumption significantly exceeded predictions, causing net carbon emissions for that month to exceed the zero-carbon threshold by 20%. After a deviation occurs, the system automatically initiates an optimization iteration. The optimization module incorporates the latest week's meteorological conditions (continued high temperatures leading to increased cooling loads) and actual building responses (such as thermal storage in the building envelope) into the model. The optimization objective is reset to "bring net carbon emissions back to zero while ensuring thermal comfort." The optimization targets include air conditioning temperature settings, nighttime pre-cooling strategies, and lighting brightness standards as decision variables. Using a fast genetic algorithm, the system proposes an improved solution: raising the air conditioning temperature to 26.5°C during office hours and leveraging pre-cooling during nighttime periods with lower electricity prices. Lighting illumination standards are also slightly lowered to reduce heat dissipation loads. If necessary, backup diesel generators can be switched to biodiesel (fuel) to mitigate peak grid electricity purchases. After evaluation and approval by management, the control module implemented this solution: the air conditioning temperature was gradually increased by 0.5°C, the dimming system reduced lighting output by 10%, and air conditioning pre-cooling was started one hour earlier at night to ensure that indoor temperatures remained within the upper comfort limit during peak daytime heat waves. After implementing the new control strategy, energy consumption in the second half of August decreased significantly, photovoltaic power generation and electricity consumption were balanced again, and net carbon emissions returned to below the zero-carbon line. Since then, the system has regularly (monthly) checked the carbon emission compliance status, and triggered similar optimization adjustments in the event of deviation. For example, at the change of seasons, the optimization module will recalculate more energy-efficient control parameters in response to the new situation of shorter lighting hours and reduced air conditioning load, such as further extending the air conditioning nighttime downtime. Throughout the operation period, through the continuous closed loop of monitoring-optimization-control, the system of the present invention has ensured that the building always operates within the target and achieved a cumulative near-zero-carbon operating performance for several years. This embodiment demonstrates the ability of the system to continuously optimize the control strategy through feedback iteration during the operation phase, effectively responding to environmental and load changes and ensuring the realization of the zero-carbon building goal.

[0031] The above are only specific embodiments of the present invention, but the scope of protection of the present invention is not limited thereto. Any changes or substitutions that can be easily conceived by those skilled in the art within the technical scope disclosed in the present invention should be covered by the scope of protection of the present invention. Matters not described in detail in this specification belong to the prior art known to those skilled in the art.

Claims

1. A tropical zero-carbon building integrated energy-saving production capacity and energy use design and control system, characterized by: Including parameterized modeling module, simulation module, optimization module, control module and monitoring feedback module, The parametric modeling module is used to establish parametric models of the building's energy-saving subsystem, energy-production subsystem, and energy-consuming subsystem, integrating the design and operating parameters of each subsystem into a unified data framework; A simulation module, connected to the parametric modeling module, for simulating the energy consumption and carbon emission performance of the building under different parameter combinations; an optimization module, connected to the simulation module, for performing multi-objective optimization calculations based on the simulation results to determine optimal building design parameters and operating parameters that meet preset carbon emission targets; a control module, configured to coordinate and control the energy-saving subsystem, the energy-generating subsystem, and the energy-consuming subsystem according to the optimal parameters output by the optimization module; The monitoring and feedback module is used to monitor the real-time energy consumption, production capacity and environmental data of the building, and feed the data back to the simulation module and optimization module to iteratively update the model and optimization strategy, thereby forming a closed-loop optimization and control of the building's carbon emissions.

2. The tropical zero-carbon building integrated energy-saving production capacity and energy use design and control system according to claim 1, characterized in that: The parametric modeling module includes: an energy-saving parameter group for representing passive energy-saving measures of buildings, a production capacity parameter group for representing renewable energy production systems, and an energy consumption parameter group for representing energy-consuming equipment and control strategies.

3. The tropical zero-carbon building integrated energy-saving production capacity and energy use design and control system according to claim 2, characterized in that: The energy-saving parameter group includes at least the design parameters of building orientation, shape coefficient, thermal performance of the envelope structure, window-to-wall ratio, and shading coefficient; the production capacity parameter group includes at least the design parameters of photovoltaic module layout and capacity, and energy storage device capacity; the energy consumption parameter group includes at least the operating parameters of air-conditioning temperature setting value, ventilation rate, lighting power density, and equipment operation schedule.

4. The tropical zero-carbon building integrated energy-saving production capacity and energy use design and control system according to claim 1, characterized in that: The optimization module is configured with a multi-objective evolutionary algorithm for simultaneously optimizing at least two objective functions; the objective functions include indicators related to carbon emissions and energy utilization, and balance the various objectives based on pre-set weights or a Pareto optimal solution selection mechanism; the optimization module aims to minimize annual total carbon emissions during the design phase and to minimize the immediate carbon emission rate or balance energy supply and demand during the operation phase.

5. The tropical zero-carbon building integrated energy-saving production capacity and energy use design and control system according to claim 1, characterized in that: The simulation module uses dynamic building energy consumption simulation software or a verified machine learning prediction model to simulate the performance of the parameter scheme provided by the parametric modeling module; during the operation stage, the simulation module uses real-time monitoring data as a digital twin model to correct the simulation.

6. The tropical zero-carbon building integrated energy-saving production capacity and energy use design and control system according to claim 1, characterized in that: The control module includes: an air conditioning control unit, a lighting control unit, an equipment power control unit, and a photovoltaic and energy storage control unit; each control unit receives the corresponding subsystem optimization parameters output by the optimization module and automatically adjusts the operating settings of the relevant equipment to enable the building subsystems to work together according to the optimization plan.

7. The tropical zero-carbon building integrated energy-saving production capacity and energy use design and control system according to claim 1, characterized in that: The monitoring and feedback module is equipped with energy consumption monitoring instruments and environmental sensors to collect indoor and outdoor temperature, humidity, illumination, equipment power, photovoltaic power generation, and power purchase from the grid. When actual carbon emissions deviate from the target threshold, the monitoring and feedback module triggers the optimization module to re-optimize the calculation and send the updated optimal control parameters to the control module to continuously correct the building operation strategy and maintain low-carbon operation.

8. The tropical zero-carbon building integrated energy-saving production capacity and energy use design and control system according to claim 1, characterized in that: The control module includes at least one industrial controller that supports BACnet / IP and Modbus-TCP protocols and is used to perform command interaction with subsystems such as air conditioning, lighting, energy storage and electricity meters.

9. The tropical region zero-carbon building integrated energy-saving production capacity and energy use design and control system according to claim 1, characterized in that: The control module is integrated with a remote upgrade interface and a local configuration port, which support the sending of control parameters and the transmission of operating status via Ethernet and Wi-Fi.

10. The tropical zero-carbon building integrated energy-saving production capacity and energy use design and control system according to claim 1, characterized in that: The system has fault switching logic. When the local controller goes offline, crashes, or the data link is interrupted for more than a preset time limit, the system automatically calls the cloud control model to take over the generation and execution of instructions.

Images