Intelligent energy management platform for whole life cycle carbon accounting, monitoring and control

Abstract

This invention discloses a smart energy management platform for full lifecycle carbon accounting, monitoring, and control, relating to the fields of port energy management and dual-carbon control technology. This invention constructs a digital twin of the port energy system through 3D modeling, data mapping, dynamic linkage, and functional empowerment. It integrates BIM+GIS technology to achieve high-precision replication of energy scenarios, establishing a real-time data mapping relationship between physical entities and digital models, and simultaneously presenting equipment operating status, energy flow, and carbon emission data. This design transforms port energy and carbon emission data from abstract reports into intuitive 3D scenes, supporting rapid location of anomaly alarms and remote control. It solves the problems of low decision-making efficiency and delayed anomaly handling in 2D display modes, providing managers with a comprehensive and three-dimensional operational view. It addresses the shortcomings of fragmented energy and carbon data and the lack of precise basis for control strategies, ensuring the achievement of carbon emission reduction targets.

Description

Technical Field

[0001] This invention relates to the field of port energy management and dual carbon control technology, specifically a smart energy management platform for full life-cycle carbon accounting, monitoring, and control. Background Technology

[0002] With the continued advancement of the "dual carbon" goals, the green and low-carbon transformation of ports, as important logistics hubs and energy consumption nodes, has become a core trend in the industry's development. Currently, as ports gradually complete the construction of basic IoT platforms, data collection from key energy-consuming equipment such as port gantry cranes, quay cranes, yard cranes, and metering instruments has been achieved. However, significant technical deficiencies still exist in existing technologies and applications: Energy and carbon management are disconnected, failing to form a closed loop throughout the entire life cycle. Most existing port energy systems only collect and display energy consumption data, lacking full-process management that includes source carbon accounting, process carbon monitoring, terminal carbon control, and effect feedback optimization. Carbon emission accounting is disconnected from energy operation and management, making it impossible to achieve refined and dynamic carbon emission control through digital means.

[0003] The existing system lacks the ability to coordinate the power generation, grid, load, and storage. It has not achieved overall coordination and optimization of new energy sources such as port wind power and photovoltaics, energy storage, power grid, and flexible loads. It is unable to cope with the intermittency of new energy power generation and the uncertainty of load, and the local consumption capacity of renewable energy is insufficient.

[0004] The level of control is not refined enough and lacks adaptability to port scenarios. Most existing energy management systems are general-purpose designs and have not been customized for the port's multiple energy categories, multiple equipment types, and complex operation processes. As a result, they cannot achieve refined management and the control strategies are poorly adapted to port production operations.

[0005] Therefore, developing a smart energy management platform that is adapted to port scenarios, realizes a closed loop of carbon accounting, monitoring and control throughout the entire life cycle, and has the ability to coordinate and optimize energy sources, grids, loads and storage has become an urgent need for the green and low-carbon transformation of ports. Summary of the Invention

[0006] The purpose of this invention is to overcome the shortcomings of existing technologies and provide a smart energy management platform for full life-cycle carbon accounting, monitoring, and control. It can construct a digital twin of the port energy system through 3D modeling, data mapping, dynamic linkage, and functional empowerment. It integrates BIM+GIS technology to achieve high-precision replication of energy scenarios, establishes a real-time data mapping relationship between physical entities and digital models, and synchronously presents equipment operating status, energy flow, and carbon emission data. This design transforms port energy and carbon emission data from abstract reports into intuitive 3D scenes, supports rapid location of abnormal alarms and remote control, and solves the problems of low decision-making efficiency and delayed abnormal handling in the 2D display mode, providing managers with a comprehensive and three-dimensional operational view.

[0007] To solve the above-mentioned technical problems, this invention provides the following technical solution: a smart energy management platform for full life-cycle carbon accounting, monitoring, and control. This platform includes a communication connection layer, an application layer, a data service layer, a support platform layer, a network layer, a protocol layer, and a perception layer, wherein: The perception layer is used to collect real-time operating data and energy consumption data of energy-consuming equipment, new energy power generation equipment, energy storage equipment, flexible load equipment and metering instruments in the port. The protocol layer is used to adapt to the communication protocols of various devices in the perception layer, and to realize the standardized parsing and transmission of multi-source heterogeneous data. The network layer is used to provide wired and wireless bidirectional data transmission channels for each layer of the platform, ensuring the real-time performance and security of data transmission. The support platform layer is used to provide basic operational support for the platform in terms of containerization and microservices, as well as basic service capabilities such as device management, data security, and protocol adaptation. The data service layer is used to clean, store, model, analyze and mine the received raw data to build a unified energy and carbon data master data system for the port. The application layer includes a full life-cycle carbon asset management module, a source-grid-load-storage panoramic monitoring module, a source-grid-load-storage collaborative optimization module, a refined energy efficiency service module, a smart operation and control module, a digital twin module, a situational awareness and intelligent alarm module, and an intelligent reporting module, achieving full-process functional coverage from carbon accounting and carbon monitoring to carbon control. The presentation layer is used to provide a visual interactive interface for users at different levels, enabling human-computer interaction and data visualization of platform functions.

[0008] Furthermore, the full life cycle carbon asset management module includes a carbon emission factor management unit, a full life cycle carbon accounting unit, a real-time carbon monitoring unit, a carbon emission analysis and benchmarking unit, a carbon control strategy generation unit, and a carbon trading support unit. The carbon emission factor management unit is used to store and maintain various energy carbon emission calculation coefficients according to industry standards, and supports dynamic updates and custom configurations of the coefficients. The full life cycle carbon accounting unit is used to calculate the port's direct and indirect carbon emissions from the source based on port energy consumption data and production operation data, covering the entire process of energy production, transmission, use and recycling, and generating a full-scenario carbon footprint ledger for the port. The real-time carbon monitoring unit is used to monitor the carbon emission intensity and total carbon emission of each area, equipment and production link of the port in real time based on the accounting results and real-time collected data, so as to realize the minute-level update of carbon emission data. The carbon emission analysis and benchmarking unit is used to conduct multi-dimensional analysis of carbon emission composition and carbon emission trends, enabling vertical benchmarking of various units within the port and horizontal benchmarking with industry standards, and identifying key carbon emission control areas. The carbon management strategy generation unit is used to generate phased and regional carbon emission reduction management strategies based on carbon monitoring and analysis results, combined with port carbon emission quotas and dual carbon targets. The carbon trading support unit is used to manage the port's carbon quotas and carbon emission reductions in a ledger, provide carbon trading decision-making suggestions based on carbon market conditions, and implement refined management of carbon assets.

[0009] Furthermore, the source-grid-load-storage panoramic monitoring module includes a source-side monitoring unit, a grid-side monitoring unit, a load-side monitoring unit, a storage-side monitoring unit, and a full-category energy monitoring unit; The source-side monitoring unit is used to collect and monitor in real time the operating status, power generation, power generation, grid-connected power, and consumption of new energy power generation equipment such as wind power and photovoltaic power in the port. The grid-side monitoring unit is used to monitor the operating parameters, power quality, and power flow distribution of the port power distribution network, intelligent power distribution equipment, and shore power system in real time. The load-side monitoring unit is used to monitor the energy consumption data and operating status of the production equipment of port gantry cranes, quay cranes, and yard cranes, as well as the non-production equipment such as high-mast lights, charging piles, battery swapping stations, and sewage treatment equipment in real time, and to distinguish between adjustable loads and non-adjustable loads. The energy storage-side monitoring unit is used to monitor the operating data of the PCS and BMS equipment, charging and discharging status, remaining power SOC, battery health SOH, and charging and discharging amount of the energy storage system in real time. The comprehensive energy monitoring unit is used to statistically monitor the total consumption, consumption trends, and regional distribution of all types of energy in the port, including electricity, water, oil, gas, and steam, and to perform centralized display of multi-energy data.

[0010] Furthermore, the source-grid-load-storage coordinated optimization module includes a new energy power prediction unit, a load prediction unit, an adjustable capacity analysis unit, a multi-objective coordinated optimization decision-making unit, and a strategy decomposition and verification unit. The new energy power prediction unit has built-in linear regression, time series, exponential smoothing, Kalman filtering, artificial neural network, and deep neural network algorithm models. Combined with historical power generation data and real-time meteorological data, it performs short-term and ultra-short-term predictions of wind power and photovoltaic power generation. The load forecasting unit is used to combine historical port load data, production operation plans, meteorological data, and holiday information to achieve short-term forecasting of port electricity load. The adjustable capacity analysis unit has a built-in weighted moving average model, which is used to statistically analyze the historical operating curves of the port's adjustable load, calculate the load operating baseline, and calculate the adjustable capacity, adjustable time period, and adjustable capability of each adjustable device by combining the rated power, maximum operating power, and ramping capability of the equipment. The multi-objective collaborative optimization decision-making unit takes optimal operating revenue, peak load migration, maximum absorption of new energy, and minimum carbon emissions as multiple optimization objectives. It incorporates a mixed integer linear programming algorithm to construct a collaborative optimization model with multiple time scales, including day-ahead, intraday, and real-time, and outputs the optimal operating scheme for the port energy system. The strategy decomposition and verification unit is used to decompose the optimized operation plan into specific control instructions for each adjustable device, and to verify the instructions in combination with device operation constraints and response reputation to ensure the executability of the control instructions.

[0011] Furthermore, the refined energy efficiency service module includes an energy composition statistical analysis unit, an energy balance analysis unit, a full-chain energy consumption analysis unit, an energy efficiency indicator management unit, a multi-dimensional energy intensity benchmarking unit, and an energy consumption assessment and incentive unit. The energy composition statistical analysis unit is used to perform multi-dimensional statistical analysis of port energy consumption according to energy type, user, and usage nature, and to perform analysis of the proportion of production load to non-production load and the proportion of new energy power generation to purchased energy. The energy balance analysis unit is used to perform a full-process balance analysis of the input, output, and loss of various energy sources such as electricity, water, gas, and oil in the port, and to locate the points of energy leakage and abnormal loss. The full-chain energy consumption analysis unit is used to combine port production and operation data to perform multi-level energy consumption statistical analysis from single equipment, single process, single ship, single shift to the entire port area, and to complete the unit consumption calculation for single ton throughput and single container handling volume. The energy efficiency indicator management unit is used to construct a hierarchical energy efficiency assessment indicator system for ports, and to perform custom configuration, real-time calculation and dynamic tracking of indicators. The energy consumption intensity multidimensional benchmarking unit is used to perform energy consumption intensity benchmarking of the same object at different time periods and different objects at the same time period through time ratio analysis and analogy analysis. The energy consumption assessment and incentive unit is used to conduct energy consumption assessments of various branches, work teams, and equipment of the port based on energy efficiency indicators and benchmarking results, and supports custom configuration of the assessment and incentive mechanism and public disclosure of results.

[0012] Furthermore, the intelligent operation and control module includes a flexible load resource management unit, a demand response and aggregation management unit, a strategy push and execution unit, and a response revenue settlement unit; The flexible load resource management unit is used to uniformly manage the ledger information, operating parameters, and adjustable attributes of the port's adjustable flexible load, and to perform ledger-based and visual display of adjustable resources. The demand response and aggregation management unit is used to receive grid demand response invitations, aggregate flexible load resources such as port energy storage, charging piles, battery swapping stations, and adjustable lighting, and complete the aggregation calculation and application of demand response capacity. The strategy push and execution unit is used to send the optimized control strategy to the corresponding device or subsystem through a standardized protocol, and to execute the remote control of the device and the execution of the strategy. The response revenue settlement unit is used to calculate the response capacity completion rate, response time efficiency and reputation of each participating device based on the demand response execution results, and to complete the calculation and allocation of demand response revenue.

[0013] Furthermore, the digital twin module is used to perform three-dimensional modeling of core energy scenarios such as port roll-on / roll-off terminals, photovoltaic power stations, wind farms, battery swapping stations, shore power facilities, and energy storage power stations, and to construct a digital twin of the port energy system. The digital twin is linked with the physical entity in real time to perform three-dimensional visualization mapping of port energy flow, equipment operating status, energy consumption data, and carbon emission data, and supports scene roaming, anomaly alarm location, simulation, and remote control.

[0014] Furthermore, the situational awareness and intelligent alarm module includes an energy consumption sensing and early warning unit, a carbon emission sensing and early warning unit, and an equipment operation abnormality alarm unit; The energy consumption sensing and early warning unit is used to provide early warning of abnormal fluctuations in port energy consumption based on energy consumption trend prediction and preset thresholds, and to display a comparison between energy consumption prediction and actual values, as well as an anomaly list. The carbon emission sensing and early warning unit is used to provide early warning of the risk of carbon emission exceeding the quota based on carbon emission prediction data and annual quota, and to track the progress of carbon emission quota completion. The equipment operation abnormality alarm unit is used to provide real-time alarms for equipment operating parameters exceeding limits and fault status, display alarms in a hierarchical manner according to alarm level, and support the full lifecycle recording and closed-loop processing of alarm events.

[0015] Furthermore, the intelligent reporting module provides custom report templates and parameter binding tools, enabling port users to generate energy consumption reports, carbon emission reports, energy efficiency assessment reports, and production statistics reports according to their actual needs, and to automatically generate, query, export, and print these reports.

[0016] Furthermore, the full lifecycle control logic of the platform is as follows: S100: Collects all raw data on energy consumption, equipment operation, and production operations across the entire port scenario through the perception layer. After being parsed by the protocol layer and transmitted through the network layer, the data is stored in the data service layer through the support platform layer. The S200 and data service layers clean, deduplicate, and standardize the raw data to build a unified energy and carbon data model, which is then output to the panoramic monitoring module and the full life cycle carbon asset management module, respectively. The S300 and full life cycle carbon asset management module are based on standardized data. They complete the full-scenario and full-process carbon emission accounting through carbon emission factors, generate a carbon footprint ledger, and realize the dynamic updating and visualization of carbon emission data through the real-time carbon monitoring unit. S400, based on carbon monitoring results and historical data, completes multi-dimensional analysis and benchmarking of carbon emissions, identifies high-carbon emission links and potential points for energy conservation and carbon reduction, and generates carbon management strategies in combination with the port's dual carbon targets. S500 inputs carbon management strategies into the source-grid-load-storage collaborative optimization module, and combines the results of new energy forecasting, load forecasting and adjustable capacity analysis to generate a multi-objective optimized operation scheme that takes into account carbon emission reduction, economic efficiency and new energy consumption. S600 decomposes the optimization plan into specific equipment control commands through the intelligent operation and management module, and sends them to the physical equipment for execution. The S700 collects equipment operation data, energy consumption data, and carbon emission data in real time after the strategy is executed through the perception layer, and feeds them back to the carbon monitoring and energy efficiency analysis module to complete the quantitative evaluation of the control effect. At the same time, it optimizes the carbon accounting model and control strategy based on the execution effect to form a full life cycle control system.

[0017] Compared with existing technologies, this smart energy management platform for full life-cycle carbon accounting, monitoring, and control has the following advantages: I. This invention constructs a closed-loop carbon management system covering the entire life cycle, including source accounting, process monitoring, terminal control, and effect feedback. It solves the problem of disconnect between energy and carbon management in traditional energy systems and realizes full-process digital management of carbon emissions from accounting, monitoring, analysis, control to optimization, making port carbon emissions calculable, visible, manageable, and controllable.

[0018] Second, this invention creates a horizontal, grid-based, refined management system for energy and carbon, encompassing both horizontal (cold, hot, electricity, and water) and vertical (source, grid, load, and storage). This system achieves full coverage of energy and carbon data across all types of energy, all equipment scenarios, and all production processes in the port. Furthermore, through the deep integration of production data and energy consumption data, it enables refined analysis of unit consumption for single equipment, single process, and single ship operations, accurately uncovering potential for energy conservation and carbon reduction.

[0019] Third, this invention achieves overall coordinated optimization of port new energy, energy storage, power grid, and flexible load through multi-timescale source-grid-load-storage coordinated optimization technology, combined with new energy power prediction, load prediction and multi-objective optimization algorithms. This effectively improves the efficiency of local consumption of renewable energy and reduces port energy costs and total carbon emissions.

[0020] Fourth, this invention realizes a full-scene three-dimensional visualization mapping of the port energy system through digital twin technology. Combined with situational awareness and intelligent alarm technology, it allows managers to intuitively grasp the overall picture of port energy operation and carbon emissions, greatly improving the efficiency of anomaly handling and the scientific nature of decision-making.

[0021] V. This invention is based on a microservice architecture design, which has high scalability, high openness and high reliability. It can adapt to the business needs of different port areas and different scales, and can be seamlessly connected with the port's existing IoT platform, production system and ERP system to avoid duplication of construction. At the same time, the functional modules can be flexibly expanded as the port's business develops.

[0022] Other advantages, objectives and features of the invention will be set forth in part in the description which follows, and in part will be apparent to those skilled in the art from the following examination or study, or may be learned from the practice of the invention. Attached Figure Description

[0023] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the accompanying drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are merely some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without any creative effort.

[0024] Figure 1 This is a flowchart illustrating the operation of life-cycle carbon management in this embodiment of the invention. Figure 2 A block diagram of the components of a smart energy management platform that integrates carbon accounting, monitoring, and control throughout the entire lifecycle; Figure 3 A flowchart illustrating the working principle of a smart energy management platform that integrates carbon accounting, monitoring, and control throughout the entire lifecycle. Detailed Implementation

[0025] To better understand the above technical solutions, a detailed description of the solutions will be provided below in conjunction with the accompanying drawings and specific embodiments. Obviously, the described embodiments are merely some, not all, of the embodiments of the present invention. All other embodiments obtained by those skilled in the art based on the embodiments of the present invention without creative effort are within the scope of protection of the present invention.

[0026] The terminology used in the embodiments of this invention is for the purpose of describing particular embodiments only and is not intended to limit the invention. The singular forms “a,” “the,” and “the” as used in the embodiments of this invention and the appended claims are also intended to include the plural forms, and “multiple” generally includes at least two unless the context clearly indicates otherwise.

[0027] To address the shortcomings of existing port energy management platforms, such as disconnects in energy and carbon management, insufficient coordination between energy sources, grids, loads, and storage, inadequate precision in control, and lack of adaptability to port scenarios, this invention provides a smart energy management platform encompassing full lifecycle carbon accounting, monitoring, and control. This embodiment aims to achieve full-process digital management of port carbon emissions—from source accounting and process monitoring to terminal control and feedback—by constructing a complete technical system encompassing data acquisition, standardized processing, in-depth analysis, collaborative optimization, and closed-loop control. Simultaneously, through multi-objective collaborative optimization and digital twin technology, it enhances the port's renewable energy absorption capacity and the level of refined energy efficiency control.

[0028] This embodiment is mainly applicable to smart energy and dual-carbon management of coastal and inland river container terminals, roll-on / roll-off terminals, and bulk cargo terminals. It can achieve full coverage of energy and carbon data for all types of energy, all types of equipment, and all production processes in the port, solving the core bottlenecks of energy and carbon disconnect, insufficient coordination, and extensive management in traditional port energy management systems.

[0029] In this embodiment, as Figure 2 As shown, this smart energy management platform for full lifecycle carbon accounting, monitoring, and control includes a communication connectivity layer, an application layer, a data service layer, a support platform layer, a network layer, a protocol layer, and a perception layer, among which: The aforementioned sensing layer is used to collect real-time operating data and energy consumption data of energy-consuming equipment, new energy power generation equipment, energy storage equipment, flexible load equipment and metering instruments in the entire port scenario; The aforementioned protocol layer is used to adapt to the communication protocols of various devices in the sensing layer, enabling standardized parsing and transmission of multi-source heterogeneous data; The network layer is used to provide wired and wireless bidirectional data transmission channels for each layer of the platform, ensuring the real-time performance and security of data transmission. The aforementioned support platform layer is used to provide basic operational support for the platform in terms of containerization and microservices, as well as basic service capabilities for device management, data security, and protocol adaptation. The data service layer is used to clean, store, model, analyze and mine the received raw data to build a unified energy and carbon data master data system for the port. The application layer includes a full life-cycle carbon asset management module, a source-grid-load-storage panoramic monitoring module, a source-grid-load-storage collaborative optimization module, a refined energy efficiency service module, a smart operation and control module, a digital twin module, a situational awareness and intelligent alarm module, and an intelligent reporting module, achieving full-process functional coverage from carbon accounting and carbon monitoring to carbon control. The aforementioned presentation layer is used to provide a visual interactive interface for users at different levels, enabling human-computer interaction and data visualization of platform functions.

[0030] In practical implementation, the perception layer is deployed across the entire port environment. Through various intelligent sensors, smart meters, RTUs (Remote Terminal Units), and PLCs (Programmable Logic Controllers), it collects operational and energy consumption data from energy-consuming equipment such as port gantry cranes, quay cranes, yard cranes, high-mast lights, charging piles, battery swapping stations, and sewage treatment equipment, as well as from new energy power generation equipment such as wind power and photovoltaics, and energy storage systems (including PCS and BMS). The protocol layer has a built-in multi-protocol parsing engine to achieve unified access and data standardization for multi-source heterogeneous devices. The network layer integrates multiple communication methods such as 5G and industrial Ethernet to build a highly reliable, low-latency bidirectional data transmission channel, ensuring the real-time performance and security of data acquisition and command issuance. The support platform layer provides basic service capabilities such as microservice registration and discovery, configuration management, device shadowing, and data security encryption.

[0031] The data service layer is responsible for cleaning, interpolating, repairing, and normalizing the raw data, and constructing a unified energy and carbon data master data system for the port. Specifically, for the time-series data reported by the sensing layer, a sliding window mean filtering method is used to remove noise points, and cubic spline interpolation is used to complete missing data. The data service layer incorporates the distributed time-series database InfluxDB and the relational database PostgreSQL, storing high-frequency operational data and basic information such as equipment ledgers and carbon emission factors, respectively. Simultaneously, this layer uses a data modeling engine to construct a unified data model including equipment models, energy models, carbon emission models, and production models, achieving deep integration of production operation data and energy consumption data.

[0032] The application layer includes a full life-cycle carbon asset management module, a source-grid-load-storage panoramic monitoring module, a source-grid-load-storage collaborative optimization module, a refined energy efficiency service module, a smart operation and control module, a digital twin module, a situational awareness and intelligent alarm module, and an intelligent reporting module. The following describes each module in detail with specific implementation methods.

[0033] The full life cycle carbon asset management module consists of a carbon emission factor management unit, a full life cycle carbon accounting unit, a real-time carbon monitoring unit, a carbon emission analysis and benchmarking unit, a carbon control strategy generation unit, and a carbon trading support unit.

[0034] The carbon emission factor management unit has built-in carbon emission coefficients for various energy sources published by industry standards, such as electricity carbon emission factors and diesel carbon emission factors, and supports administrators to dynamically update and customize configurations based on the average emission level of the regional power grid or the requirements of the International Maritime Organization.

[0035] The life-cycle carbon accounting unit is based on port energy consumption data and production operation data, and uses the IPCC emission factor method for accounting. The calculation formula is as follows: ,in, Indicates total carbon emissions. For the first Energy-related activity data (such as electricity consumption, fuel consumption), To calculate the carbon emission factors of corresponding energy sources, the system covers the entire process of energy production, transmission, operation, and recycling, generating a comprehensive carbon footprint ledger for ports.

[0036] Based on the accounting results and real-time collected data, the real-time carbon monitoring unit uses a sliding time window algorithm to dynamically update the carbon emission intensity and total carbon emissions of each area, equipment and production process in the port on a minute-by-minute basis.

[0037] The carbon emission analysis and benchmarking unit utilizes multi-dimensional online analysis and processing technology to analyze the composition of carbon emissions from multiple dimensions such as time, space, and equipment type. It also performs horizontal and vertical benchmarking with historical port data and industry benchmarks to output a list of key high-carbon emission control areas and critical equipment.

[0038] Based on the above analysis results, the carbon management strategy generation unit combines port carbon emission quotas and dual carbon targets, and uses linear programming to generate phased and regional carbon reduction strategies.

[0039] The carbon trading support unit manages port carbon quotas and certified emission reductions through digital ledgers. It combines real-time carbon market data with time series forecasting models to provide carbon trading decision-making suggestions, thereby achieving refined management of carbon assets.

[0040] The panoramic monitoring module for energy generation, grid, load, and storage includes a source-side monitoring unit, a grid-side monitoring unit, a load-side monitoring unit, a storage-side monitoring unit, and a full-category energy monitoring unit. The source-side monitoring unit connects to photovoltaic inverters and wind turbine controllers to collect data in real time, such as power generation, electricity generation, grid-connected electricity, and self-consumption, to monitor the operating status and health of new energy equipment.

[0041] The grid-side monitoring unit deploys smart meters and power quality analyzers in port power distribution rooms, transformer substations, and shore power access points to monitor parameters such as voltage, current, frequency, harmonic distortion rate, and power factor in real time, and analyzes the load distribution and line loss of the distribution network based on power flow calculations.

[0042] The load-side monitoring unit distinguishes between production equipment and non-production equipment. For equipment such as gantry cranes and quay cranes, vibration sensors and electrical parameter acquisition modules are added to monitor their energy consumption data and operating conditions. For adjustable loads such as charging piles and high-mast lights, their adjustable attributes are additionally marked.

[0043] The energy storage monitoring unit acquires data such as battery pack voltage, temperature, SOC (state of charge), SOH (state of health), and charge / discharge power in real time through the energy storage system BMS (battery management system) interface, and evaluates the battery life degradation based on the equivalent cycle count algorithm.

[0044] The full-category energy monitoring unit integrates data from metering instruments for electricity, water, oil, gas, and steam. By constructing an energy network topology map, it enables centralized display of multi-energy data and analysis of consumption trends.

[0045] The source-grid-load-storage coordinated optimization module includes a renewable energy power prediction unit, a load prediction unit, an adjustable capacity analysis unit, a multi-objective coordinated optimization decision-making unit, and a strategy decomposition and verification unit. The renewable energy power prediction unit incorporates various prediction algorithms, including linear regression, time series analysis, exponential smoothing, Kalman filtering, artificial neural networks, and deep neural networks.

[0046] The load forecasting unit also uses the aforementioned LSTM model, combining historical port load data, production operation plans, meteorological data, and holiday information to achieve short-term forecasting of the port's total electricity load. The adjustable capacity analysis unit incorporates a weighted moving average method to statistically analyze the historical operating curves of adjustable loads (such as charging piles, battery swapping stations, and adjustable lighting) and calculate the load operating baseline. In this embodiment, taking charging piles as an example, the adjustable capacity calculation formula is as follows: ,in, The adjustable capacity at time t The rated maximum power of the equipment, For minimum operating power, For baseline load, This represents the climbing ability coefficient.

[0047] The multi-objective collaborative optimization decision unit takes optimal operational benefits, peak load migration, maximum renewable energy utilization, and minimum carbon emissions as multiple optimization objectives. A multi-timescale collaborative optimization model is constructed, encompassing day-ahead, intraday, and real-time time scales. The objective function can be expressed as: ,in, It is the sum of revenue from renewable energy generation and revenue from demand response. For carbon emission costs (based on carbon trading prices), For electricity purchase costs, The weighting coefficients are used for the constraints, which include power balance constraints, energy storage SOC constraints, and equipment ramp-up constraints. The model is solved using a mixed-integer linear programming algorithm, and outputs the optimal operation schemes for each time period of the next day, such as the energy storage charging and discharging plan, adjustable load adjustment instructions, and grid power purchase plan.

[0048] The strategy decomposition and verification unit decomposes the optimization scheme into specific control commands for each adjustable device, such as the charging and discharging power setting value of the energy storage PCS, the start and stop time and power limit of the charging pile, and combines the real-time operating status and response reputation of the device to verify the executability of the commands to ensure that the issued control commands are safe and reliable.

[0049] The refined energy efficiency service module includes an energy composition statistical analysis unit, an energy balance analysis unit, a full-chain energy consumption analysis unit, an energy efficiency indicator management unit, a multi-dimensional benchmarking unit for energy intensity, and an energy consumption assessment and incentive unit.

[0050] The energy composition statistical analysis unit uses data cube technology to conduct multi-dimensional statistics based on energy type, user, and usage nature, and calculates key indicators such as the proportion of new energy power generation and the proportion of production load.

[0051] The energy balance analysis unit constructs an energy balance model for the port's energy network, including electricity, water, and gas. Based on the comparative analysis of input, output, and loss, it uses a differential evolution algorithm to locate abnormal loss points.

[0052] The full-chain energy consumption analysis unit connects with the port's TOS and ERP systems to obtain production data such as single-ship handling volume and single-container throughput, constructing a multi-layered energy efficiency indicator system from single equipment and single process to the entire port area. The formula for calculating energy consumption per unit throughput is: .in, Energy consumption per unit throughput This represents the total energy consumption within the statistical period. This refers to the throughput during the same period.

[0053] The energy efficiency indicator management unit allows users to customize and configure energy efficiency assessment indicators at each level, and enables real-time calculation and dynamic tracking of the indicators.

[0054] The multidimensional benchmarking unit for energy intensity benchmarks against industry standards through year-on-year (different time periods for the same object) and month-on-month (different objects in the same time period) analysis.

[0055] Based on the benchmarking results mentioned above, the energy consumption assessment and incentive unit automatically generates energy consumption assessment scores for each branch, work group, and key equipment, and supports the configuration and result disclosure of incentive mechanisms such as points rewards and performance assessments.

[0056] The intelligent operation and control module includes a flexible load resource management unit, a demand response and aggregation management unit, a strategy push and execution unit, and a response revenue settlement unit.

[0057] The flexible load resource management unit establishes a flexible load resource database to manage adjustable resources such as port charging piles, battery swapping stations, adjustable lighting, air conditioning systems, and energy storage systems in a ledger-based manner, recording parameters such as their rated power, adjustment rate, and daily operating characteristic curves.

[0058] The demand response and aggregation management unit connects to the provincial power demand response management platform, receives demand response invitations (response period, response quantity, response type), calculates the port's declareable response capacity based on the adjustable capacity analysis results using an aggregation algorithm, and automatically completes the declaration.

[0059] The strategy push and execution unit sends optimized control commands to field devices or subsystems through standardized protocols, tracks the command execution status in real time, and supports switching between remote manual intervention and automatic execution.

[0060] After the demand response is completed, the response revenue settlement unit calculates the response capacity completion rate and response time efficiency of each participating device based on the comparison between the actual response curve and the baseline load, and calculates the response revenue and allocates it to each participating entity in accordance with the electricity market settlement rules.

[0061] The digital twin module and situational awareness module utilize BIM+GIS technology to create high-precision 3D models of core energy scenarios such as port roll-on / roll-off terminals, photovoltaic power stations, wind farms, battery swapping stations, shore power facilities, and energy storage power stations. This constructs a digital twin that interacts with the physical world in real time. This digital twin establishes a real-time data mapping with the data service layer through communication protocols, visually mapping equipment operating status, energy flow, energy consumption data, and carbon emission data in 3D using colors, arrows, and heat maps. This allows managers to navigate the scene and query equipment information using a mouse or VR device. When the perception layer detects abnormal data, the corresponding device in the digital twin scene automatically highlights and flashes, and an alarm details card pops up, supporting one-click access to the video monitoring screen for rapid location and remote handling of abnormal alarms.

[0062] The situational awareness and intelligent alarm module includes an energy consumption sensing and early warning unit, a carbon emission sensing and early warning unit, and an equipment operation abnormality alarm unit.

[0063] Based on load forecast results and preset thresholds, the energy consumption sensing and early warning unit uses a differential detection algorithm to provide early warnings of abnormal energy consumption fluctuations, and displays a comparison between the predicted curve and the actual curve, as well as an anomaly list, on a large screen.

[0064] The carbon emission sensing and early warning unit dynamically tracks the progress of quota completion based on the annual quota and real-time cumulative carbon emissions. When it predicts that the quota may be exceeded in the remaining period, it triggers a tiered early warning.

[0065] The equipment operation abnormality alarm unit provides real-time alarms for equipment operating parameters exceeding limits and fault status. It is divided into three levels according to severity: emergency, important, and general. It also records the entire life cycle process of alarm occurrence, confirmation, handling, and closure, forming a closed-loop processing record.

[0066] The presentation layer is based on a dual-terminal architecture of web and mobile. The web terminal provides port management personnel with a panoramic dashboard, a 3D digital twin interface, and full-process control functions, while the mobile terminal provides on-site personnel with mobile inspection, alarm reception, and data query functions. In this embodiment, the presentation layer adopts the RBAC permission model to configure corresponding interfaces and operation permissions for users at different levels, meeting the usage needs of all roles in the port.

[0067] like Figure 3 As shown, the platform's full lifecycle control logic achieves closed-loop management through the following steps: S100: The perception layer collects all raw data on energy consumption, equipment operation, and production operations across the entire port scenario. After being parsed by the protocol layer and transmitted by the network layer, the data is stored in the data service layer through the support platform layer.

[0068] S200: The data service layer cleans, deduplicates, and standardizes the raw data to build a unified energy and carbon data model, which is then output to the panoramic monitoring module and the full life cycle carbon asset management module.

[0069] S300: The full life cycle carbon asset management module is based on standardized data. It completes carbon emission accounting for all scenarios and processes through carbon emission factors, generates a carbon footprint ledger, and realizes dynamic updates and visualization of carbon emission data through the real-time carbon monitoring unit.

[0070] S400: Based on carbon monitoring results and historical data, complete multi-dimensional analysis and benchmarking of carbon emissions, identify high-carbon emission links and potential points for energy conservation and carbon reduction, and generate carbon management strategies in combination with the port's dual carbon targets.

[0071] S500: Input carbon management strategies into the source-grid-load-storage collaborative optimization module, and combine the results of new energy forecasting, load forecasting, and adjustable capacity analysis to generate day-ahead, intraday, and real-time multi-timescale optimized operation schemes that take into account carbon emission reduction, economic efficiency, and new energy consumption through multi-objective optimization algorithms.

[0072] S600: The intelligent operation and management module decomposes the optimization plan into specific equipment control commands and sends them to the physical equipment for execution.

[0073] S700: The sensing layer collects equipment operation data, energy consumption data, and carbon emission data in real time after the strategy is executed, and feeds them back to the carbon monitoring and energy efficiency analysis module. By comparing the difference between the actual effect and the expected target, the module completes the quantitative evaluation of the control effect, and optimizes the carbon accounting model parameters and control strategy thresholds based on the evaluation results, forming a continuously iterative full life cycle control system.

[0074] like Figure 1 As shown, this embodiment also provides the working principle of the smart energy management platform for full life cycle carbon accounting-monitoring-control in carrying out full life cycle carbon management, which is used to explain in detail the specific workflow of this system. The specific steps of this workflow are as follows: (1) Data acquisition and access Deploy perception layer equipment to connect to energy-consuming equipment, new energy equipment, energy storage equipment, flexible loads, etc. in the port's full range of scenarios.

[0075] Collect real-time operational data and energy consumption data.

[0076] By adapting to multiple communication protocols at the protocol layer, standardized parsing of multi-source heterogeneous data can be achieved.

[0077] (2) Data transmission and storage Data is transmitted to the platform in real time through the network layer.

[0078] The support platform layer provides a containerized, microservice-based infrastructure environment to ensure data transmission security and device management.

[0079] The data service layer cleans, deduplicates, and standardizes the raw data to build a unified energy and carbon data master data system.

[0080] (3) Carbon accounting and modeling Call the carbon emission factor library to match the carbon emission coefficients corresponding to various types of energy consumption.

[0081] A full-process accounting system is implemented for both direct and indirect emissions from ports.

[0082] Establish a carbon footprint ledger covering all aspects of energy production, transmission, use, and recycling.

[0083] (4) Carbon monitoring and dynamic updates Real-time monitoring of carbon emission intensity and total amount in various regions, equipment and processes, achieving minute-level data updates.

[0084] Dynamically track carbon emission trends to create a dynamic profile of carbon emissions.

[0085] (5) Carbon analysis and benchmarking A multi-dimensional analysis of the composition and trends of carbon emissions. Conduct internal and external benchmarking.

[0086] Identify high-carbon emission links and potential energy-saving and carbon-reducing areas.

[0087] (6) Generation of carbon management strategies Combine the port's dual carbon targets with carbon emission quotas to formulate phased and regional carbon reduction strategies.

[0088] Generate actionable control recommendations.

[0089] (7) Collaborative optimization and scheduling Input the carbon management strategy into the source-grid-load-storage collaborative optimization module.

[0090] By combining new energy power generation forecasting, load forecasting, and adjustability analysis, a multi-objective optimized operation plan is generated.

[0091] The optimization scheme is broken down into specific equipment control commands.

[0092] (8) Instruction execution and feedback The intelligent operation and control module sends instructions to the corresponding devices or subsystems for execution.

[0093] Real-time collection of equipment operation data, energy consumption data, and carbon emission data after execution.

[0094] Feedback is sent to the carbon monitoring and energy efficiency analysis module to assess the effectiveness of the control measures.

[0095] (9) Effect evaluation and model optimization Quantify the changes in carbon emissions before and after control measures to assess the effectiveness of carbon reduction.

[0096] Optimize the carbon accounting model and management strategy based on the implementation results to form a closed-loop control system.

[0097] In summary, this embodiment, through the deep integration of IoT, big data, artificial intelligence, and digital twin technologies, constructs a closed-loop carbon management system covering the entire lifecycle, from source accounting and process monitoring to terminal control and effect feedback. This effectively solves the problems of disconnected energy and carbon management, insufficient coordination capabilities, and low precision in traditional port energy systems, providing a complete digital solution for the green and low-carbon transformation of ports.

[0098] The above description is merely a preferred embodiment of the present invention and is not intended to limit the present invention in any way. Although the present invention has been disclosed above with reference to preferred embodiments, it is not intended to limit the present invention. Any person skilled in the art can make some modifications or alterations to the above-disclosed technical content to create equivalent embodiments without departing from the scope of the present invention. Any simple modifications, equivalent changes and alterations 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 scope of the present invention.

Claims

1. A smart energy management platform for full life-cycle carbon accounting, monitoring, and control, characterized in that: The platform comprises a presentation layer, application layer, data service layer, support platform layer, network layer, protocol layer, and perception layer for communication connectivity, among which: The perception layer is used to collect real-time operating data and energy consumption data of energy-consuming equipment, new energy power generation equipment, energy storage equipment, flexible load equipment and metering instruments in the port. The protocol layer is used to adapt to the communication protocols of various devices in the perception layer, and to realize the standardized parsing and transmission of multi-source heterogeneous data. The network layer is used to provide wired and wireless bidirectional data transmission channels for each layer of the platform, ensuring the real-time performance and security of data transmission. The support platform layer is used to provide basic operational support for the platform in terms of containerization and microservices, as well as basic service capabilities such as device management, data security, and protocol adaptation. The data service layer is used to clean, store, model, analyze and mine the received raw data to build a unified energy and carbon data master data system for the port. The application layer includes a full life-cycle carbon asset management module, a source-grid-load-storage panoramic monitoring module, a source-grid-load-storage collaborative optimization module, a refined energy efficiency service module, a smart operation and control module, a digital twin module, a situational awareness and intelligent alarm module, and an intelligent reporting module, achieving full-process functional coverage from carbon accounting and carbon monitoring to carbon control. The presentation layer is used to provide a visual interactive interface for users at different levels, enabling human-computer interaction and data visualization of platform functions.

2. The smart energy management platform for full life-cycle carbon accounting, monitoring, and control as described in claim 1, characterized in that, The full life cycle carbon asset management module includes a carbon emission factor management unit, a full life cycle carbon accounting unit, a real-time carbon monitoring unit, a carbon emission analysis and benchmarking unit, a carbon control strategy generation unit, and a carbon trading support unit. The carbon emission factor management unit is used to store and maintain various energy carbon emission calculation coefficients according to industry standards, and supports dynamic updates and custom configurations of the coefficients. The full life cycle carbon accounting unit is used to calculate the port's direct and indirect carbon emissions from the source based on port energy consumption data and production operation data, covering the entire process of energy production, transmission, use and recycling, and generating a full-scenario carbon footprint ledger for the port. The real-time carbon monitoring unit is used to monitor the carbon emission intensity and total carbon emission of each area, equipment and production link of the port in real time based on the accounting results and real-time collected data, so as to realize the minute-level update of carbon emission data. The carbon emission analysis and benchmarking unit is used to conduct multi-dimensional analysis of carbon emission composition and carbon emission trends, enabling vertical benchmarking of various units within the port and horizontal benchmarking with industry standards, and identifying key carbon emission control areas. The carbon management strategy generation unit is used to generate phased and regional carbon emission reduction management strategies based on carbon monitoring and analysis results, combined with port carbon emission quotas and dual carbon targets. The carbon trading support unit is used to manage the port's carbon quotas and carbon emission reductions in a ledger, provide carbon trading decision-making suggestions based on carbon market conditions, and implement refined management of carbon assets.

3. The smart energy management platform for full life-cycle carbon accounting, monitoring, and control as described in claim 1, characterized in that, The source-grid-load-storage panoramic monitoring module includes a source-side monitoring unit, a grid-side monitoring unit, a load-side monitoring unit, a storage-side monitoring unit, and a full-category energy monitoring unit; The source-side monitoring unit is used to collect and monitor in real time the operating status, power generation, power output, grid connection power, and consumption of new energy power generation equipment such as wind power and photovoltaic power in the port. The grid-side monitoring unit is used to monitor the operating parameters, power quality, and power flow distribution of the port power distribution network, intelligent power distribution equipment, and shore power system in real time. The load-side monitoring unit is used to monitor the energy consumption data and operating status of the production equipment of port gantry cranes, quay cranes, and yard cranes, as well as the non-production equipment such as high-mast lights, charging piles, battery swapping stations, and sewage treatment equipment in real time, and to distinguish between adjustable loads and non-adjustable loads. The energy storage-side monitoring unit is used to monitor the operating data of the PCS and BMS equipment, charging and discharging status, remaining power SOC, battery health SOH, and charging and discharging amount of the energy storage system in real time. The comprehensive energy monitoring unit is used to statistically monitor the total consumption, consumption trends, and regional distribution of all types of energy in the port, including electricity, water, oil, gas, and steam, and to perform centralized display of multi-energy data.

4. The smart energy management platform for full life-cycle carbon accounting, monitoring, and control as described in claim 1, characterized in that, The source-grid-load-storage coordinated optimization module includes a new energy power prediction unit, a load prediction unit, an adjustable capacity analysis unit, a multi-objective coordinated optimization decision-making unit, and a strategy decomposition and verification unit. The new energy power prediction unit has built-in linear regression, time series, exponential smoothing, Kalman filtering, artificial neural network, and deep neural network algorithm models. Combined with historical power generation data and real-time meteorological data, it performs short-term and ultra-short-term predictions of wind power and photovoltaic power generation. The load forecasting unit is used to combine historical port load data, production operation plans, meteorological data, and holiday information to achieve short-term forecasting of port electricity load. The adjustable capacity analysis unit has a built-in weighted moving average model, which is used to statistically analyze the historical operating curves of the port's adjustable load, calculate the load operating baseline, and calculate the adjustable capacity, adjustable time period, and adjustable capability of each adjustable device by combining the rated power, maximum operating power, and ramping capability of the equipment. The multi-objective collaborative optimization decision-making unit takes optimal operating revenue, peak load migration, maximum absorption of new energy, and minimum carbon emissions as multiple optimization objectives. It incorporates a mixed integer linear programming algorithm to construct a collaborative optimization model with multiple time scales, including day-ahead, intraday, and real-time, and outputs the optimal operating scheme for the port energy system. The strategy decomposition and verification unit is used to decompose the optimized operation plan into specific control instructions for each adjustable device, and to verify the instructions in combination with device operation constraints and response reputation to ensure the executability of the control instructions.

5. The smart energy management platform for full life-cycle carbon accounting, monitoring, and control as described in claim 1, characterized in that, The refined energy efficiency service module includes an energy composition statistical analysis unit, an energy balance analysis unit, a full-chain energy consumption analysis unit, an energy efficiency indicator management unit, a multi-dimensional benchmarking unit for energy consumption intensity, and an energy consumption assessment and incentive unit. The energy composition statistical analysis unit is used to perform multi-dimensional statistical analysis of port energy consumption according to energy type, user, and usage nature, and to perform analysis of the proportion of production load to non-production load and the proportion of new energy power generation to purchased energy. The energy balance analysis unit is used to perform a full-process balance analysis of the input, output, and loss of various energy sources such as electricity, water, gas, and oil in the port, and to locate the points of energy leakage and abnormal loss. The full-chain energy consumption analysis unit is used to combine port production and operation data to perform multi-level energy consumption statistical analysis from single equipment, single process, single ship, single shift to the entire port area, and to complete the unit consumption calculation for single ton throughput and single container handling volume. The energy efficiency indicator management unit is used to construct a hierarchical energy efficiency assessment indicator system for ports, and to perform custom configuration, real-time calculation and dynamic tracking of indicators. The energy consumption intensity multidimensional benchmarking unit is used to perform energy consumption intensity benchmarking of the same object at different time periods and different objects at the same time period through time ratio analysis and analogy analysis. The energy consumption assessment and incentive unit is used to conduct energy consumption assessments of various branches, work teams, and equipment of the port based on energy efficiency indicators and benchmarking results, and supports custom configuration of the assessment and incentive mechanism and public disclosure of results.

6. The intelligent energy management platform for full life-cycle carbon accounting, monitoring, and control as described in claim 1, characterized in that, The intelligent operation and control module includes a flexible load resource management unit, a demand response and aggregation management unit, a strategy push and execution unit, and a response revenue settlement unit. The flexible load resource management unit is used to uniformly manage the ledger information, operating parameters, and adjustable attributes of the port's adjustable flexible load, and to perform ledger-based and visual display of adjustable resources. The demand response and aggregation management unit is used to receive grid demand response invitations, aggregate flexible load resources such as port energy storage, charging piles, battery swapping stations, and adjustable lighting, and complete the aggregation calculation and application of demand response capacity. The strategy push and execution unit is used to send the optimized control strategy to the corresponding device or subsystem through a standardized protocol, and to execute the remote control of the device and the execution of the strategy. The response revenue settlement unit is used to calculate the response capacity completion rate, response time efficiency and reputation of each participating device based on the demand response execution results, and to complete the calculation and allocation of demand response revenue.

7. The intelligent energy management platform for full life-cycle carbon accounting, monitoring, and control as described in claim 1, characterized in that, The digital twin module is used to perform three-dimensional modeling of core energy scenarios such as port roll-on / roll-off terminals, photovoltaic power stations, wind farms, battery swapping stations, shore power facilities, and energy storage power stations, and to construct a digital twin of the port energy system. The digital twin is linked with the physical entity in real time to perform three-dimensional visualization mapping of port energy flow, equipment operating status, energy consumption data, and carbon emission data, and supports scene roaming, anomaly alarm location, simulation, and remote control.

8. The smart energy management platform for full life-cycle carbon accounting, monitoring, and control as described in claim 1, characterized in that, The situational awareness and intelligent alarm module includes an energy consumption sensing and early warning unit, a carbon emission sensing and early warning unit, and an equipment operation abnormality alarm unit. The energy consumption sensing and early warning unit is used to provide early warning of abnormal fluctuations in port energy consumption based on energy consumption trend prediction and preset thresholds, and to display a comparison between energy consumption prediction and actual values, as well as an anomaly list. The carbon emission sensing and early warning unit is used to provide early warning of the risk of carbon emission exceeding the quota based on carbon emission prediction data and annual quota, and to track the progress of carbon emission quota completion. The equipment operation abnormality alarm unit is used to provide real-time alarms for equipment operating parameters exceeding limits and fault status, display alarms in a hierarchical manner according to alarm level, and support the full lifecycle recording and closed-loop processing of alarm events.

9. The intelligent energy management platform for full life-cycle carbon accounting, monitoring, and control as described in claim 1, characterized in that, The intelligent reporting module provides custom report templates and parameter binding tools, enabling port users to generate energy consumption reports, carbon emission reports, energy efficiency assessment reports, and production statistics reports according to their actual needs, and to automatically generate, query, export, and print the reports.

10. The intelligent energy management platform for full life-cycle carbon accounting, monitoring, and control as described in claim 1, characterized in that, The platform's full lifecycle control logic is as follows: S100: Collects all raw data on energy consumption, equipment operation, and production operations across the entire port scenario through the perception layer. After being parsed by the protocol layer and transmitted through the network layer, the data is stored in the data service layer through the support platform layer. The S200 and data service layers clean, deduplicate, and standardize the raw data to build a unified energy and carbon data model, which is then output to the panoramic monitoring module and the full life cycle carbon asset management module, respectively. The S300 and full life cycle carbon asset management module are based on standardized data. They complete the full-scenario and full-process carbon emission accounting through carbon emission factors, generate a carbon footprint ledger, and realize the dynamic updating and visualization of carbon emission data through the real-time carbon monitoring unit. S400, based on carbon monitoring results and historical data, completes multi-dimensional analysis and benchmarking of carbon emissions, identifies high-carbon emission links and potential points for energy conservation and carbon reduction, and generates carbon management strategies in combination with the port's dual carbon targets. S500 inputs carbon management strategies into the source-grid-load-storage collaborative optimization module, and combines the results of new energy forecasting, load forecasting and adjustable capacity analysis to generate a multi-objective optimized operation scheme that takes into account carbon emission reduction, economic efficiency and new energy consumption. S600 decomposes the optimization plan into specific equipment control commands through the intelligent operation and management module, and sends them to the physical equipment for execution. The S700 collects equipment operation data, energy consumption data, and carbon emission data in real time after the strategy is executed through the perception layer, and feeds them back to the carbon monitoring and energy efficiency analysis module to complete the quantitative evaluation of the control effect. At the same time, it optimizes the carbon accounting model and control strategy based on the execution effect to form a full life cycle control system.

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