A zero-carbon park and factory comprehensive energy management and control method and system based on PLC

Abstract

The application discloses a zero-carbon park and factory comprehensive energy management and control method and system based on PLC, relates to the technical field of zero-carbon park and factory comprehensive energy management and control and industrial automation control, and adopts a three-layer decentralized management and control architecture of a field device layer, a local control layer and a remote monitoring layer.The local control layer is configured with an industrial-grade PLC, the field device layer is directly connected with the PLC through hard wiring and an industrial bus, data of the field device layer and the local control layer are visually displayed, the industrial-grade PLC is used as the only core control unit, all core control logics such as carbon emission accounting, energy optimization scheduling and multi-system collaborative control which are centrally deployed on a host computer platform in related technologies are all locally deployed in the PLC to realize, and the core problems such as strong network dependence, high cost, non-closed-loop energy and carbon management, poor multi-system collaboration, insufficient real-time performance and the like are solved from the root.

Description

Technical Field

[0001] This application relates to the fields of integrated energy management and control in zero-carbon parks and factories, and industrial automation control technology, and in particular to a method and system for integrated energy management and control in zero-carbon parks and factories based on PLC (Programmable Logic Controller). Background Technology

[0002] Industrial parks and factories, as the core entities of social energy consumption and greenhouse gas emissions, rely on green and low-carbon transformation as a key approach to achieving low-carbon goals. Zero-carbon parks and factories, by integrating the concept of carbon neutrality throughout their entire life cycle and relying on renewable energy utilization, energy efficiency improvement, and closed-loop management of carbon emissions, achieve regional carbon emission self-balancing, which is the core development direction for current industrial green upgrading.

[0003] Existing integrated energy management technologies for zero-carbon parks and factories have gone through three stages of development, forming three mainstream solutions: The first is a single-system independent management solution, where each energy, energy consumption, and carbon emission system operates independently, data is not shared, and management is fragmented, only achieving basic monitoring and control; the second is an integrated energy and carbon centralized monitoring solution, which integrates energy and carbon emission data through a host computer software platform to achieve centralized and visualized monitoring, and is currently the mainstream solution in the industry; the third is an exploratory solution for cutting-edge energy and carbon collaborative closed-loop management, which aims to achieve linkage between zero-carbon goals and energy dispatch, but there is currently no mature implementation solution, and it has problems such as high degree of customization, strong network dependence, and insufficient collaborative capabilities.

[0004] The most current mainstream technology adopts a three-layer centralized architecture of "device layer - platform layer - application layer," relying on the host computer EMS (Energy Management System) and energy carbon management platform to complete data calculation, scheduling decisions, and command issuance. This architecture has several core shortcomings: First, the core control logic is entirely deployed on the host computer platform, relying entirely on communication networks and cloud devices. A network outage or host computer crash results in loss of control and poor system reliability. Second, the core control hardware is custom-designed by specific manufacturers, resulting in strong closed-loop architecture, poor compatibility, extremely high construction and maintenance costs, and no user customization rights. Third, energy carbon management is only integrated at the data level, with carbon emission accounting being post-event statistics, failing to constrain energy scheduling with zero-carbon indicators and not achieving a deep closed loop. Fourth, the management scenarios only cover electricity and basic load systems, not public energy systems such as water, gas, and heating, creating blind spots in carbon emission management. Fifth, the control link is long and communication latency is high, failing to meet the millisecond-level real-time control requirements of industrial applications.

[0005] In response to the shortcomings of the aforementioned technologies, there is an urgent need for a localized, highly reliable, all-scenario, customizable, and low-cost integrated energy management solution for zero-carbon industrial parks. Summary of the Invention

[0006] The purpose of this application is to provide a PLC-based integrated energy management method and system for zero-carbon parks and factories, which can realize full-scenario energy collaborative management and control, real-time closed-loop management of carbon emissions, flexible system expansion and self-customization, reduce the cost of zero-carbon transformation, and improve the safety and stability of system operation.

[0007] To achieve the above objectives, this application provides the following solution.

[0008] In the first aspect, this application provides a PLC-based integrated energy management and control system for zero-carbon parks and factories, wherein the PLC-based integrated energy management and control system for zero-carbon parks and factories adopts a three-layer decentralized management and control architecture consisting of a field device layer, a local control layer, and a remote monitoring layer. The local control layer is configured with an industrial-grade PLC, which is the system’s only real-time control and decision-making core. All core control logics, including carbon emission accounting, energy optimization scheduling, multi-system collaborative control, and fault linkage protection, are deployed locally within the PLC. The field device layer is directly connected to the PLC via hardwiring and industrial bus, and is used to collect energy, carbon emissions, equipment operating conditions and safety monitoring data of the zero-carbon park and factory in the whole scene, and execute control commands issued by the PLC. The remote monitoring layer is used to visualize the data of the field equipment layer and the local control layer. When the network is interrupted or the remote monitoring layer equipment fails, the PLC can independently complete the closed-loop management of the entire process. The PLC has the following built-in features: The real-time data acquisition and preprocessing unit is used to cyclically acquire and preprocess the full-dimensional data uploaded by the field equipment layer; the full-dimensional data includes energy consumption data, fuel consumption data, and renewable energy power generation data; The online carbon emission accounting unit is used to calculate the core zero-carbon indicators locally in real time based on real-time collected energy consumption data, fuel consumption data, and renewable energy power generation data. A multi-energy collaborative optimization scheduling unit is used to generate the optimal energy scheduling strategy through local cyclic calculation with the aforementioned zero-carbon core indicators as constraints. The multi-system collaborative control unit for all scenarios is used to convert the optimal energy dispatch strategy into control commands and send them to the execution terminals of the field equipment layer to realize cross-system collaborative control of microgrid, water supply, gas supply, heating, lighting and ventilation systems.

[0009] Secondly, this application provides a PLC-based integrated energy management method for zero-carbon industrial parks and factories, applied to the PLC-based integrated energy management system for zero-carbon industrial parks and factories described in the first aspect. The PLC-based integrated energy management method for zero-carbon industrial parks and factories includes: The system continuously collects and preprocesses the full-dimensional data uploaded by the field equipment layer; the full-dimensional data includes energy consumption data, fuel consumption data, and renewable energy power generation data. Based on real-time collected energy consumption data, fuel consumption data, and renewable energy power generation data, the zero-carbon core indicators are calculated locally in real time. Using the aforementioned zero-carbon core indicators as constraints, the optimal energy dispatch strategy is generated through local cyclic calculation. The optimal energy dispatch strategy is converted into control commands and sent to the execution terminals at the field equipment level, enabling cross-system coordinated control of microgrids, water supply, gas supply, heating, lighting, and ventilation systems. According to the specific embodiments provided in this application, this application has the following technical effects: This application provides a PLC-based integrated energy management method and system for zero-carbon parks and factories. Using an industrial-grade PLC as the sole core control unit, it reconstructs a three-layer decentralized management architecture: "Field Equipment Layer - Local Control Layer - Remote Monitoring Layer." All core control logic—such as carbon emission accounting, energy optimization scheduling, and multi-system collaborative control—that was previously centrally deployed on a host computer platform is now locally deployed within the PLC. The remote monitoring layer only handles visualization, parameter configuration, and data archiving, without participating in any real-time control. This fundamentally solves the core problems of related technologies, such as strong network dependence, high cost, non-closed-loop energy and carbon management, poor multi-system collaboration, and insufficient real-time performance. It achieves full-scenario energy collaborative management in zero-carbon parks, real-time closed-loop carbon emission management, flexible system expansion and customization, reduces the cost of zero-carbon transition, and improves system operational safety and stability. Attached Figure Description

[0010] To more clearly illustrate the technical solutions in the embodiments of this application or related technologies, the drawings used in the embodiments will be briefly described below. Obviously, the drawings described below are only some embodiments of this application. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort. Figure 1 A schematic diagram of a PLC-based integrated energy management system for zero-carbon industrial parks and factories, provided as an embodiment of this application; Figure 2 This is a schematic flowchart illustrating a PLC-based integrated energy management method for zero-carbon industrial parks and factories, provided as an embodiment of this application. Detailed Implementation

[0011] The technical solutions of the embodiments of this application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of this application, and not all embodiments. Based on the embodiments of this application, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of this application.

[0012] To make the above-mentioned objectives, features and advantages of this application more apparent and understandable, the application will be further described in detail below with reference to the accompanying drawings and specific embodiments.

[0013] In one exemplary embodiment, such as Figure 1 As shown, a PLC-based integrated energy management system for zero-carbon industrial parks and factories is provided. This system adopts a three-layer decentralized management architecture consisting of a field device layer, a local control layer, and a remote monitoring layer. The core control hub is an industrial-grade PLC in the local control layer. The three-layer architecture is interconnected and has clear responsibilities, completely different from the "centralized control by a host computer" architecture of related technologies.

[0014] With PLC as the core controller, it is designed for all scenarios such as zero-carbon industrial parks, zero-carbon manufacturing plants, and zero-carbon data centers, enabling collaborative management of multiple energy categories such as electricity, heat, cooling, gas, and water across the entire chain, closed-loop management of carbon emissions throughout the entire lifecycle, and maximization of renewable energy consumption.

[0015] (i) The field device layer is directly connected to the PLC via hardwiring or industrial bus to collect energy, carbon emissions, equipment operating conditions, and safety monitoring data for the entire zero-carbon park and factory, and to execute control commands issued by the PLC. The field device layer serves as the data acquisition and command execution terminal, and its direct connection to the PLC via hardwiring or industrial bus significantly shortens the control link.

[0016] The field device layer is the physical foundation of the system and serves as the data source and execution carrier for the core control of the PLC. It is directly connected to the PLC in the local control layer through hardwiring, industrial Ethernet, and fieldbus to achieve full-scenario data acquisition and control command execution. It fully covers the park and public energy systems and carbon emission metering systems that are not included in the relevant technologies, and completely solves the defects of incomplete control scenarios and the existence of carbon emission blind spots.

[0017] The field equipment layer is divided into six major units according to function, including renewable energy and energy storage unit, load and public energy system unit, carbon emission metering unit, power quality and electrical safety unit, environmental and safety monitoring unit, and edge communication unit. The equipment composition, data acquisition and execution content, and role of each functional unit in this application are shown in Table 1 below.

[0018] Table 1. Equipment composition, data acquisition and execution content, and role in this application of each functional unit in the field equipment layer.

[0019] The renewable energy and energy storage unit is used to collect photovoltaic power generation, wind power generation, battery SOC, battery SOH, charging and discharging current and voltage, grid voltage, frequency and switch opening and closing status, and to execute charging and discharging regulation, start and stop control, grid-connected and off-grid switching and power regulation commands.

[0020] The load and public energy system unit is used to collect operating power, energy consumption data, pipeline parameters, and ambient temperature and humidity of production equipment, lighting, air conditioning / fresh air systems, water supply systems, gas supply systems, and heating systems, and to execute equipment start / stop, frequency regulation, valve opening regulation, brightness regulation, and temperature regulation commands.

[0021] The carbon emission metering unit is used to collect data on greenhouse gas emission concentrations, fuel consumption, energy consumption across all categories (electricity, water, gas, and heat), and renewable energy power generation.

[0022] The power quality and electrical safety unit is used to collect voltage harmonics, current harmonics, power factor, equipment temperature, fault signals and alarm information, and to execute protection actions, harmonic mitigation and reactive power compensation commands.

[0023] The environmental and safety monitoring unit is used to collect data on gas concentration, smoke concentration, water immersion status, harmful gas concentration, and alarm signals, and to execute commands for coordinated ventilation, emergency shutdown, and equipment shutdown.

[0024] The renewable energy and energy storage unit, load and public energy system unit, carbon emission metering unit, power quality and electrical safety unit, and environmental and safety monitoring unit are connected to the PLC via an edge communication unit.

[0025] All devices in the field equipment layer support industrial common protocols such as Modbus RTU / TCP, Profinet, and IEC 61850, with a sampling period of ≤200ms. They are directly connected to the PLC communication module via shielded twisted-pair cables to ensure real-time data transmission and anti-interference capabilities. Critical safety protection devices are directly connected to the PLC's IO module via hardwiring to ensure the reliability of fault response.

[0026] (ii) The local control layer is configured with an industrial-grade PLC. This PLC is the system's sole real-time control and decision-making core. All core control logic, including carbon emission calculation, energy optimization scheduling, multi-system collaborative control, and fault linkage protection, is deployed locally within the PLC. The PLC in the local control layer is the system's sole real-time control and decision-making core. All core calculations, control logic, control strategy generation, and instruction issuance are completed locally on the PLC, without relying on any upper-level network or host computer device. This completely eliminates dependence on host computers and communication networks, resolving the core defects of related technologies such as loss of control upon network outage and insufficient reliability.

[0027] The preferred PLC is the Siemens S7-1200 / S7-1500 series industrial general-purpose PLC, which is suitable for various application scenarios. The hardware configuration can be flexibly expanded according to the scale of the park and factory. The minimum configuration can meet the needs of small parks and factories, while the maximum configuration can be adapted to large industrial parks and factories for full-scenario access. The specific hardware composition, parameters, and functions are shown in Table 2 below.

[0028] Table 2 Hardware composition, parameters, and functions of the PLC

[0029] The field devices in Table 2 include all the core hardware devices listed in Table 1, as well as all primary and secondary instrument signals that need to be acquired or controlled, such as buttons, emergency stops, limit switches, indicator lights, solenoid valves, transmitters, sensors, frequency converters, and actuators, which are installed locally or in cabinets and are not listed in Table 1.

[0030] The PLC has a built-in real-time data acquisition and preprocessing unit, an online carbon emission accounting unit, a multi-energy collaborative optimization scheduling unit, a multi-system collaborative control unit for all scenarios, a multi-dimensional fault linkage protection unit, a data interaction and power failure retention unit, and a modular and customizable program architecture unit.

[0031] ① A real-time data acquisition and preprocessing unit is used to cyclically acquire and preprocess the full-dimensional data uploaded by the field equipment layer; the full-dimensional data includes energy consumption data, fuel consumption data and renewable energy power generation data.

[0032] Implementation logic: The PLC, via hardwiring and industrial communication protocols, cyclically collects comprehensive data from all devices at the field equipment level with a configurable sampling period of 100ms-200ms. This data includes: renewable energy power generation data, energy storage operation data, all types of energy consumption data, equipment operating status and fault signals, carbon emission metering data, and environmental and safety monitoring data. Environmental and safety monitoring data mainly includes gas concentration, smoke concentration, water immersion status, harmful gas concentration, and alarm signals.

[0033] The collected full-dimensional data undergoes local preprocessing, including filtering, verification, deduplication, and outlier removal. Invalid data, such as those from communication interruptions or exceeding the measurement range, is removed to obtain standardized preprocessed data, forming a standardized and valid dataset, which is stored in the PLC's local register. This provides real-time and accurate raw data for all subsequent control logic, completely eliminating reliance on a host computer and ensuring continuous data acquisition even in network outages.

[0034] ② The online carbon emission accounting unit is used to calculate the core zero-carbon indicators locally in real time based on real-time collected energy consumption data, fuel consumption data, and renewable energy power generation data.

[0035] The online carbon emission accounting unit is also used to compare the real-time calculated zero-carbon core indicators with the preset compliance threshold, warning threshold and serious exceedance threshold one by one. When the real-time calculated zero-carbon core indicators do not meet the preset requirements, a three-level signal of compliance, warning or exceedance is generated.

[0036] Based on preprocessed standardized data, the PLC locally completes full-dimensional status judgments, including: 1) Energy supply and demand status assessment: assess grid-connected and off-grid operation modes, renewable energy output, load supply and demand balance, and energy storage SOC status.

[0037] 2) Zero-carbon indicator status judgment: Through the built-in carbon emission accounting model, the current carbon emission intensity, cumulative emissions, renewable energy consumption rate and other core zero-carbon indicators are verified in real time to see if they meet the preset thresholds.

[0038] Cumulative carbon emissions include direct carbon emissions and indirect carbon emissions. Direct carbon emissions are those generated by the combustion of natural gas in the park and factories, while indirect carbon emissions are those generated by the purchase of electricity by the park and factories.

[0039] The formula for calculating direct carbon emissions is: Direct carbon emissions = Natural gas consumption × Emission factor. The PLC collects natural gas consumption in real time through the analog input module. The emission factor is a constant related to the lower heating value, carbon content per unit calorific value, and carbon oxidation rate. The relevant values ​​can be modified through the parameter configuration module of the remote monitoring layer.

[0040] Indirect carbon emissions are the carbon emissions from purchased electricity. The calculation formula is: carbon emissions from purchased electricity = purchased electricity volume × annual average emission factor of the provincial power grid. The PLC obtains the purchased electricity volume by collecting meter data in real time through communication. The annual average emission factor of the provincial power grid can be modified through the parameter configuration module of the remote monitoring layer.

[0041] The cumulative carbon emissions are the sum of the above two data points: direct carbon emissions and indirect carbon emissions.

[0042] carbon emission intensity The calculation formula is as follows: Carbon emission intensity = Total carbon emissions ÷ Total electricity load; Total carbon emissions = Purchased power in grid interaction power × Grid carbon emission factor + Gas supply flow rate × Natural gas carbon emission factor; Total electricity load = Fixed load + Adjustable load operating power.

[0043] Renewable energy consumption rate The formula for calculating the proportion of renewable energy electricity generated and consumed by the park and factories in the total electricity consumption is as follows: =The proportion of photovoltaic self-generation and self-consumption is obtained by the PLC through real-time communication with each meter.

[0044] After the PLC completes the calculation of the three core zero-carbon indicators, it compares the real-time calculated core zero-carbon indicators with the preset compliance threshold, warning threshold, and serious exceedance threshold of the remote monitoring layer one by one, and finally obtains the current zero-carbon indicator status (compliance, warning, or exceedance three-level signal).

[0045] 3) Equipment operating condition and safety status assessment: Determine whether all field equipment is operating normally, whether there are fault signals, alarm signals, and safety risks.

[0046] 4) External condition judgment: Identify the current peak-valley electricity price period, grid demand response signals, and external compliance requirements.

[0047] All the above four-dimensional status judgment results are stored in the PLC local register, providing a basis for the execution of subsequent control strategies.

[0048] The PLC performs real-time judgments of all operating states locally, without the need for a host computer to participate in the calculations, thus providing a basis for decision-making for the accurate execution of control strategies.

[0049] Local Real-Time Carbon Emission Accounting and Zero-Carbon Target Verification: The PLC's online carbon emission accounting unit incorporates a carbon emission accounting model compliant with relevant standards. Real-time calculations of core zero-carbon indicators include carbon emission intensity, cumulative carbon emissions, renewable energy integration rate, and green electricity ratio. Based on real-time collected data on fuel consumption, purchased electricity and heat, and renewable energy generation, the system locally calculates real-time carbon emission intensity, cumulative carbon emissions, renewable energy integration rate, and green electricity ratio for the park and factory. Simultaneously, it presets carbon emission intensity thresholds, cumulative carbon emission thresholds, and green electricity ratio thresholds, and verifies in real-time whether the current indicators meet the preset requirements. The green electricity ratio calculation formula is: Green electricity ratio = (PV self-generated and self-consumed electricity + Energy storage discharge and self-consumed electricity + Purchased green electricity) ÷ Total cumulative electricity consumption × 100%. If there is no purchased green electricity, then the green electricity ratio equals the renewable energy integration rate.

[0050] The PLC compares and verifies the real-time calculation results of carbon emission intensity, cumulative carbon emissions, renewable energy absorption rate, and green electricity ratio with preset zero-carbon target thresholds to determine whether the current core zero-carbon indicators meet the standards. It generates three levels of signals: compliant, warning, or exceeding the standard, and simultaneously uploads the carbon emission calculation data to the remote monitoring layer for permanent storage. This enables localized and real-time carbon emission calculation, completely resolving the shortcomings of related technologies' lagging carbon emission calculations and reliance on host computers. It uses the core zero-carbon indicators as the core constraint for energy dispatch, achieving a deep closed-loop energy and carbon management system.

[0051] ③ A multi-energy collaborative optimization scheduling unit is used to generate the optimal energy scheduling strategy through local cyclic calculation with the zero-carbon core index as a constraint.

[0052] Implementation logic: The PLC's multi-energy collaborative optimization scheduling unit has a built-in multi-objective optimization scheduling algorithm with the core objectives of minimizing carbon emission intensity, maximizing renewable energy absorption rate, and minimizing operating costs. It uses the zero-carbon core indicators calculated in real time by the carbon emission online accounting unit as the core constraint, and combines energy supply and demand status, peak and valley electricity prices, and grid demand response signals to generate the optimal energy scheduling strategy through local cyclic calculation.

[0053] Based on the status judgment results and zero-carbon index verification results, the PLC calls the built-in multi-objective optimization scheduling algorithm. With the core objectives of minimizing carbon emission intensity, maximizing renewable energy consumption rate, and minimizing operating costs, it generates the optimal energy scheduling strategy through local cyclic calculation, including energy storage charging and discharging plans, renewable energy consumption schemes, load adjustment plans, and grid connection / off-grid switching strategies.

[0054] The objective function of the multi-objective optimization scheduling algorithm is: ; in, The objective function for a multi-objective optimization scheduling algorithm; It is a function of carbon emission intensity. = Real-time carbon emission intensity ÷ Carbon emission intensity compliance upper limit; The function is the renewable energy absorption rate. =1 - Real-time renewable energy absorption rate ÷ Target value of absorption rate; For the operating cost function; =Real-time operating cost ÷ Operating cost under baseline conditions; , , The weights for carbon emission intensity, renewable energy integration rate, and operating costs are respectively determined to meet the requirements. The three follow .

[0055] Operating costs include the cost of purchasing electricity from the grid, the cost of natural gas fuel, the cost of equipment operation and maintenance, and the cost of energy storage system losses. =Grid interaction power × Time-of-use price × Dispatch duration + Gas supply flow rate × Natural gas unit price × Dispatch duration + Equipment operation and maintenance cost + Energy storage charging and discharging power × Energy storage cycle loss conversion factor × Dispatch duration. The baseline operating condition is the theoretical upper limit of operating cost under conditions where optimized dispatch is not used, all loads operate at full load, and all electricity demand is supplied by the grid. Real-time operating cost is calculated in real-time according to the formula written into the PLC program. The operating cost under the baseline operating condition is calculated once and stored in the PLC's power-off retention area.

[0056] The PLC employs a finite-domain discrete ergonomic optimization method with priority hard constraints to find the minimum objective function value. This method transforms a multi-objective optimization problem into a single-objective optimization problem. First, the feasible region of scheduling parameters is defined by hard constraints based on zero-carbon compliance, power balance, and equipment safety priorities. The continuous scheduling parameters are then discretized into finite levels. After eliminating all non-compliant parameter combinations, all compliant parameter groups are traversed and substituted into the objective function to calculate the corresponding objective function value. Finally, the globally optimal scheduling parameter set with the minimum objective function value is selected. The globally optimal scheduling parameter set mainly includes the optimal grid interaction power, the optimal energy storage charging and discharging power, the optimal operating power of adjustable loads, the optimal proportion of photovoltaic self-consumption, the optimal proportion of photovoltaic grid connection, and the optimal gas supply flow rate.

[0057] Zero-carbon compliance means that the total carbon emissions are less than the emission limits of the park.

[0058] The power balance constraint means that the total power supply on the power supply side of the park is equal to the total power consumption on the power consumption side. The formula is expressed as: Power purchased by the grid + Power generated and consumed by photovoltaic power + Power discharged by energy storage = Power of rigid load + Power of adjustable load + Power charged by energy storage.

[0059] Equipment safety priority is divided into two levels based on the severity of safety issues: interlocking protection and safe operation. Interlocking protection forces equipment to shut down due to fire triggering, equipment failure, emergency shutdown, or parameter exceeding limits, and related scheduling parameters are forcibly reset to zero. Safe operation means that scheduling parameters must not exceed the equipment's rated capacity and safe operating range. These two levels of constraints jointly determine the feasible domain of each scheduling parameter.

[0060] During the calculation process, the core zero-carbon indicators are used as the highest priority constraints. When the carbon emission intensity exceeds the standard, the emission reduction scheduling strategy is implemented first to ensure the compliant achievement of the zero-carbon goal.

[0061] The constraints ensure the highest priority for the zero-carbon core indicators; when carbon emission intensity reaches the exceedance threshold, the algorithm automatically locks the weights. =1, = = 0, the objective function simplifies to Meanwhile, the feasible region is narrowed down to all possible combinations of scheduling parameters that can reduce carbon emissions. After repeating the above traversal calculation, the scheduling parameter group with the smallest objective function value is selected, which is the locally optimal scheduling parameter group in the emergency emission reduction scenario.

[0062] The core scheduling logic built into the multi-energy collaborative optimization scheduling unit includes: The logic of maximizing the consumption of renewable energy is used to prioritize the consumption of renewable energy generation such as photovoltaic and wind power, and to prioritize the use of surplus electricity for energy storage charging, heat pump heating, heat pump cooling, and green hydrogen production, so as to avoid curtailment of solar and wind power. The zero-carbon-oriented peak shaving and valley filling (peak shaving and valley filling: a power dispatching method that uses energy storage charging and discharging, load regulation, etc. to store electrical energy during off-peak hours and release electrical energy or reduce non-core loads during peak hours to smooth the peak-valley load difference of the power grid and reduce electricity costs) logic is used to prioritize the use of energy storage discharge and renewable energy power supply during peak hours, and to adjust the operation plan of non-core high-energy-consuming equipment in a coordinated manner to reduce the purchase of thermal power; during off-peak hours, it utilizes off-peak electricity prices and surplus renewable energy to charge energy storage. The dual control logic of demand and carbon emissions is used to monitor the grid demand and carbon emission intensity in real time. When either indicator approaches the corresponding threshold, it automatically controls the energy storage to discharge and cuts off non-core high-energy-consuming loads, while meeting the requirements of electricity compliance and carbon emission compliance. It also features a seamless off-grid switching logic for real-time monitoring of grid status. In the event of a grid failure, it completes the off-grid mode switch within 100ms, prioritizing power supply to core low-energy-consumption and low-emission loads and coordinating the operation of high-energy-consumption equipment to reduce carbon emissions in the off-grid state.

[0063] The role of this application is to localize the optimization scheduling algorithm deployed on the host computer in related technologies, realize real-time cyclic operation in PLC, and completely get rid of the dependence on host computer and network; drive energy scheduling with zero carbon target as the core constraint, fundamentally solve the defect of energy carbon control disconnect in related technologies, maximize the renewable energy consumption rate, and reduce carbon emissions in parks and factories.

[0064] ④ The multi-system collaborative control unit for all scenarios is used to convert the optimal energy dispatch strategy into specific digital or analog control commands, which are then directly sent to the execution terminals at the field device level via hardwiring and industrial bus, realizing cross-system collaborative control of microgrids, water supply, gas supply, heating, lighting, and ventilation systems. The PLC monitors the command execution results of the field devices (i.e., the execution terminals) in real time, and re-incorporates the real-time data after execution into the acquisition loop to complete a single control closed loop, with a control closed loop period of ≤200ms.

[0065] Implementation Logic: The PLC, based on the optimal energy dispatch strategy generated by the multi-energy collaborative optimization dispatch unit, coordinates and controls the microgrid, water supply, gas supply, heating, lighting, and ventilation systems across all scenarios to achieve cross-system collaborative operation. The core logic includes: Energy supply and demand and public system collaboration: When renewable energy output is at its peak, high-energy-consuming water pumps and heat pumps are automatically started to utilize surplus clean energy; when carbon emissions exceed the standard, the heating or air conditioning temperature in non-core areas is automatically lowered and lighting brightness is adjusted to reduce energy consumption and carbon emissions; Cross-category collaboration of energy systems: The PLC coordinates multiple energy categories such as electricity, heat, cooling, and gas. When photovoltaic power is in surplus, heat pumps are driven to prepare cold and heat storage energy to replace gas boilers for heating and reduce direct carbon emissions from fossil fuels.

[0066] Its role in this application is to significantly shorten the control link by directly connecting the PLC to the field equipment, realize unified management and coordinated linkage of the energy system in the park and factory, completely solve the defects of the related technologies such as decentralized management of multiple systems, poor coordination and high control delay, eliminate blind spots in carbon emission management, and reduce carbon emissions in the park and factory from the perspective of the whole scenario.

[0067] ⑤ The all-dimensional fault linkage protection unit is used to monitor fault signals, alarm signals and carbon emission exceeding signals in real time, and to perform interlock protection actions under abnormal operating conditions.

[0068] Implementation logic: Throughout the entire control process, the PLC monitors the operating status, fault signals, alarm signals, and carbon emission exceedance signals of all field devices in real time. When an abnormal operating condition is detected, it immediately interrupts unnecessary scheduling tasks, automatically executes preset interlocking protection actions, and issues hierarchical alarm signals. It also records fault and action information. The response time of all interlocking actions of the full-dimensional fault linkage protection unit is less than or equal to 1 second.

[0069] The all-dimensional fault linkage protection unit incorporates the following core linkage protection logic: The energy-carbon linkage protection logic is used to interlock and shut down non-core high-energy-consuming equipment, activate emergency emission reduction plans, and issue compliance warnings when carbon emissions seriously exceed the standards. The energy fault linkage protection logic is used to interlock and switch off-grid mode when there is a microgrid fault or grid power outage, prioritizing the power supply of core loads and critical systems such as water supply, gas supply and lighting, and cutting off non-core high energy-consuming loads. The safety risk linkage protection logic is used to interlock and shut off the gas emergency shut-off valve, electrical equipment and heating equipment in the relevant area when a gas leak occurs, and simultaneously start the explosion-proof ventilation equipment and prohibit the start and stop of non-explosion-proof lighting equipment to prevent the accident from escalating. The pipeline abnormality linkage protection logic is used to interlock and close the valves in the corresponding area when there is a leak in the water supply pipeline or an overpressure in the heating pipeline, and to simultaneously adjust the operating status of the water pump and the circulation pump to reduce resource waste and secondary failures.

[0070] The above interlocking protection process is as follows: The PLC collects relevant data through hardwiring and communication. After collecting the data, it compares it with the threshold set by the system to determine whether it is within the normal range. If it exceeds the normal range, it is judged as a fault. After a fault occurs, the PLC calls the preset fault handling interlocking protection action program according to the fault type. It issues control commands to the field actuators through hardwiring or communication modules, and executes the cross-system linkage actions in an orderly manner according to the preset timing. After each action is executed, the PLC collects the feedback signal from the actuators through hardwiring or communication to determine whether the action has been executed properly.

[0071] If multiple faults are triggered simultaneously, the PLC will execute fault interlock protection actions of different priorities in sequence through its own interrupt program.

[0072] PLC interrupt routines are special program segments written to respond to specific events. Interrupt routines can be executed with priority during the main loop program to achieve real-time response and efficient processing. Different interrupt routines have different priorities; higher-priority interrupt routines will interrupt all lower-priority tasks and execute first. The main loop program has the lowest priority and can be interrupted at any time by all higher-priority tasks.

[0073] To facilitate emergency fault handling and interlocking protection actions, PLC programming prioritizes the corresponding fault handling interlocking protection logic within different priority interrupt routines based on the severity of the fault. In the all-dimensional fault linkage protection unit, interlocking protection logic for different fault types is configured within different priority interrupt routines according to the severity of the fault. For example, interlocking protection logic for extreme emergency faults such as gas leaks and power outages is configured in high-priority interrupt routines, while interlocking protection logic for excessive carbon emissions and routine faults is configured in lower-priority interrupt routines. Routine control logic is configured within the main loop program (while other control logic is placed within the main loop program). Thus, once a fault occurs, the interrupt routine will interrupt the currently executing main loop program and execute the interrupt routine first. After the interrupt routine completes, execution of the main loop program resumes from the point of interruption.

[0074] The PLC synchronously sends out tiered alarm signals and uploads fault information and action information to the remote monitoring layer in real time for storage, enabling permanent traceability. After the fault is cleared, it supports manual / automatic reset to restore the normal scheduling process.

[0075] The role of the all-dimensional fault linkage protection unit in this application is to construct a cross-system linkage protection mechanism covering all dimensions of "energy-carbon emission-safety", completely solving the defects of single-dimensional safety protection and lack of cross-system linkage in related technologies; and to ensure the speed and reliability of fault response by directly connecting the protection equipment through PLC hard wiring, thereby comprehensively improving the safety and compliance of park and factory operations.

[0076] ⑥ Data interaction and power failure retention unit, used to interact with the remote monitoring layer and retain the setting parameters and operating data during power failure.

[0077] Implementation Logic: The PLC interacts with field devices and the remote monitoring layer via a communication module, uploading real-time operating data, carbon emission calculation results, zero-carbon core indicators, fault alarm information, and control execution status to the industrial control computer at the remote monitoring layer in real time. Configuration software enables visualization, report generation, and data archiving. Simultaneously, it receives parameter setting and threshold adjustment commands from the remote monitoring layer. Threshold adjustment commands only modify the boundary conditions of the control strategy and do not interfere with the PLC's real-time control logic. Even if the network is interrupted or the host computer crashes, the PLC can still continue to execute the complete control loop based on the stored parameters. All settings and important data are stored in the PLC's memory card and are retained even after power failure.

[0078] Its role in this application is to ensure normal data interaction with the remote monitoring layer, realize human-machine interaction and remote monitoring, and completely isolate the core control logic from the upper-level network. Even if the network is interrupted or the host computer crashes, the PLC can still operate independently, fundamentally solving the core defects of related technologies such as strong network dependence and loss of control when the network is disconnected; the power failure retention function ensures the integrity of the operating data and meets the requirements of continuous and convenient daily operation.

[0079] ⑦ Implementation logic of modular and customizable program architecture units: The PLC program adopts a standardized, modular, and structured decoupled design architecture, which decomposes the core control logic into mutually independent standardized functional blocks, including data acquisition functional blocks, carbon emission accounting functional blocks, optimization scheduling functional blocks, collaborative control functional blocks, linkage protection functional blocks, etc. The functional blocks only interact with each other through standardized interfaces, without deep coupling.

[0080] Based on the energy consumption characteristics, zero-carbon goals, and operation and management rules of zero-carbon parks and factories, corresponding functional blocks can be modified, added, or deleted independently without reconstructing the overall program architecture.

[0081] It can independently customize carbon emission accounting boundaries and accounting factors to adapt to carbon emission accounting standards and compliance requirements of different industries and regions; it can independently customize the priority and constraints of optimized scheduling targets, and customize exclusive peak shaving and valley filling, renewable energy consumption, and demand control strategies; it can independently add management and control scenarios and linkage logic, such as adding green hydrogen preparation, waste heat recovery, virtual power plant response and other functional modules; it can independently customize graded alarm thresholds and interlocking protection action logic to adapt to the safety management specifications of different parks and factories.

[0082] Meanwhile, all functional blocks have reserved standardized user-defined interfaces, allowing users to customize the collaborative management logic of the production system and energy system based on their own production processes and energy consumption habits, so as to achieve deep integration of energy management and production operation.

[0083] Its role in this application is to completely break the existing original manufacturer's technical monopoly on customized systems, grant users full autonomy in customization and expansion capabilities, and flexibly adjust the control logic and add functional modules according to the development needs of the park and factory throughout their entire life cycle, thereby significantly reducing the cost and response cycle of customized transformation and achieving precise zero-carbon control with "one policy for one area and one policy for one factory".

[0084] (iii) The remote monitoring layer is used to visualize the data of the field equipment layer and the local control layer. When the network is interrupted or the remote monitoring layer equipment is down, the PLC can independently complete the closed-loop control of the entire process. The remote monitoring layer is only a human-machine interaction and data archiving terminal and does not participate in any real-time control. Even if the network is interrupted or the host computer is down, it will not affect the normal operation of the PLC's core control functions.

[0085] The remote monitoring layer serves as the system's human-computer interaction and data archiving terminal. It only undertakes functions such as visualization, parameter configuration, data storage, and report generation, and does not participate in any real-time control or decision-making calculations. This completely distinguishes it from the host computer platform, which is the control core in related technologies, and solves the defect that the system loses control when the host computer crashes.

[0086] (1) Hardware composition: The core hardware is an industrial-grade industrial control computer (optional domestic Advantech or Advantech industrial control computers), equipped with an i5 processor, 8GB memory, 512GB solid-state drive, and dual gigabit Ethernet ports, which can be directly connected to the PLC via industrial Ethernet; optional digital screen, mobile terminal, and Web server can be equipped to meet the needs of multiple scenarios.

[0087] (2) Software composition and functions: The core software is a general industrial configuration software (WINCC, KingSCADA, ForceControl, etc.), which does not require customized development and can be built based on general controls. The core functional modules are as follows: ① Operations Management Module: Visually displays real-time status parameters of various systems in the park and factory, as well as core zero-carbon indicators such as cumulative carbon emissions, carbon emission intensity, renewable energy absorption rate, green electricity ratio, comprehensive energy consumption, and energy flow, providing a comprehensive overview of the park and factory operations on a single screen.

[0088] ② The parameter setting module allows operators to remotely set control boundary conditions such as carbon emission thresholds, peak shaving and valley filling periods, demand control thresholds, and equipment protection parameters. The parameters are sent to the PLC storage card and called locally by the PLC without interfering with the PLC's real-time control logic.

[0089] ③ The data report management module is used to automatically generate daily / monthly / yearly energy consumption reports, carbon emission accounting reports, and zero-carbon target achievement reports, which can be used for carbon emission verification, zero-carbon park and factory certification; it supports historical data query, export and archiving to meet audit traceability requirements.

[0090] ④ Alarm management module, used to display fault alarms and carbon emission exceeding alarm information uploaded by PLC in real time, and supports alarm history query, export and archiving.

[0091] ⑤ The Web publishing and mobile access module supports web publishing of the monitoring interface, allowing administrators to perform mobile status monitoring, alarm reception, and remote parameter adjustment via mobile APP and mini-program.

[0092] The mainstream mature technologies in the field of integrated energy management for zero-carbon industrial parks and factories currently consist of two main parts: integrated energy and carbon management platform and microgrid energy management system.

[0093] The integrated energy and carbon management platform adopts a layered architecture, consisting of an equipment layer, a platform layer, and an application layer from bottom to top. Its core working principle is that the equipment layer collects the operating data of all products and electrical equipment in the park and factory, such as photovoltaics, energy storage, charging piles, air conditioning, lighting, and water supply, through various communication protocols. Then, the platform layer completes carbon emission accounting, energy efficiency analysis, and energy optimization scheduling. Finally, the data is centrally presented at the application layer.

[0094] The microgrid energy management system adopts a central architecture model of "host computer software platform + dedicated customized hardware equipment". Its structure mainly includes customized detection, protection, communication and control equipment and software management platform. The working principle is to collect full-dimensional data such as environmental, electrical parameters and equipment status through equipment such as weather stations, metering instruments, BMS, microcomputers, etc., and upload them to the software layer through the communication gateway. The software platform displays, records, calculates and analyzes the data and saves it. Then, based on the analysis results, it adjusts the control strategy and issues control commands such as charging and discharging, start and stop to realize the energy scheduling of the microgrid.

[0095] Regarding the integrated energy management problem of zero-carbon industrial parks and factories that this application aims to address, the relevant technologies have the following shortcomings and deficiencies: 1. The core control relies entirely on the host computer platform, which is highly dependent on the network and poses a risk of loss of control due to network outages, resulting in insufficient system reliability.

[0096] All core logical operations related to carbon emission accounting, energy optimization scheduling, and collaborative control strategies are centrally deployed on the host computer or cloud server at the platform layer. The dedicated controllers at the device layer are only responsible for data acquisition and instruction execution, lacking any autonomous computation or closed-loop control capabilities. The normal operation of the entire system depends entirely on the communication network between the host computer and the device layer. Once a network interruption, host computer crash, or network outage occurs, the park and factory will immediately lose their intelligent energy and carbon management capabilities, relying solely on manual local operation. This makes it impossible to guarantee closed-loop management of zero-carbon targets and continuous and stable system operation.

[0097] 2. The core control hardware is a manufacturer-customized device, which has high construction and maintenance costs, poor compatibility and scalability, and no independent customization capability.

[0098] The microgrid control core of the related technology is custom-designed by the manufacturer, and both the software and hardware are closed architectures. It only supports the access of equipment of the same brand and cannot be compatible with third-party multi-brand energy equipment, metering equipment, and public system equipment. The hardware interface and computing power are fixed, and the hardware configuration cannot be flexibly adjusted according to the scale and scenario of the park and factory. Hardware expansion requires a complete replacement of the original custom host, which is extremely costly and time-consuming.

[0099] Meanwhile, modifications to control logic, functional expansion, and system upgrades are entirely dependent on the original manufacturer. Users have no autonomy in development and customization, and cannot customize exclusive scheduling strategies and control logic based on their own park and factory's energy consumption characteristics, zero-carbon goals, and operational rules. The response cycle for customized needs can be as long as several months, and high development costs must be paid. For scenarios such as phased construction of parks and factories, addition of new energy systems, adjustment of control rules, and updates to policies and standards, smooth expansion and flexible adaptation cannot be achieved, resulting in high system construction and procurement costs and subsequent operation and maintenance costs, making the zero-carbon transformation threshold for SMEs extremely high.

[0100] 3. Carbon emission control and energy dispatch are only integrated at the data level, without achieving deep closed-loop linkage, and cannot drive energy optimization with the goal of zero carbon.

[0101] The energy and carbon management platforms and microgrid energy management systems of related technologies are independent functional units within the platform layer. They only achieve centralized display of carbon emission data and energy data on the same platform, without achieving deep linkage between data and control logic. Their carbon emission accounting is limited to ex-post statistics, trend analysis, and exceedance warnings. They cannot use core zero-carbon indicators such as carbon emission intensity and green electricity ratio as core constraints for energy dispatch strategies. They cannot achieve a closed-loop management of "real-time carbon emission accounting - exceedance warning - front-end energy dispatch and equipment control linkage," and cannot fundamentally drive the optimization of the energy structure of industrial parks and factories with zero-carbon goals.

[0102] 4. The control scenarios are not fully covered, the multi-system collaborative control capabilities are lacking, and there are blind spots in carbon emission control.

[0103] The device layer in the related art only covers the monitoring and control of the power systems, charging systems, basic lighting and air conditioning systems of parks and factories, and does not cover public energy systems such as water supply, gas supply, heating and ventilation of zero-carbon parks and factories. All systems are still under independent and decentralized management and control, making it impossible to achieve unified data interaction and collaborative linkage of the full-scenario energy systems. For example, the peak shaving and valley filling control cannot combine the operating conditions of high-load equipment such as heating and air conditioning, and additional power needs to be drawn from the grid during peak hours; when the power grid fails and power is cut off, it cannot link to prioritize the power supply of key systems such as water supply, gas supply and lighting, resulting in serious blind spots in carbon emission management and control and energy waste.

[0104] 5. The security protection dimension is single, and a full-dimensional linkage protection mechanism integrating energy and carbon has not been constructed.

[0105] The related art only designs basic single device-level protection logic such as islanding protection and reverse current protection for electrical safety, and does not construct a cross-system linkage protection mechanism, making it impossible to realize collaborative disposal of multiple scenarios such as energy faults, excessive carbon emissions, gas leakage, and pipe network abnormalities. For example, when gas leaks, it cannot link to cut off relevant power-consuming and heating equipment, which is prone to explosion risks; when carbon emissions are severely excessive, it cannot link to restrict the operation of non-core high-energy-consuming equipment, resulting in compliance risks; when an energy fault occurs, it cannot link to adjust the operation of public systems in parks and factories, which is likely to cause secondary faults.

[0106] 6. The control link is long with high delay, which cannot meet the industrial-level real-time control requirements.

[0107] The control instructions in the related art need to be transmitted through the whole link of "device layer data uploading - platform layer centralized computing - instruction issuing - device layer execution", which has obvious communication delay and cannot realize millisecond-level real-time control; at the same time, when the platform layer performs multi-task parallel computing, problems such as algorithm lag and instruction issuing delay are prone to occur, which cannot meet the industrial-level real-time requirements of micro-grid grid-connected / off-grid switching, fault emergency protection, and real-time carbon emission closed-loop management and control of zero-carbon parks and factories.

[0108] In view of the deficiencies existing in the existing integrated energy management and control solutions for zero-carbon parks and factories, the present application takes an industrial-grade PLC as the core control unit, and the technical problems to be solved are as follows: 1. By deploying the core logic of the whole zero-carbon management and control process locally on the industrial-grade PLC, the dependence on the upper computer, cloud server and communication network is completely eliminated, so that the system can still independently complete the closed-loop operation of energy and carbon management and control under the state of network interruption and upper computer downtime, ensuring the continuity and stability of the management and control of zero-carbon parks and factories.

[0109] 2. Replace dedicated custom control hardware with general-purpose industrial-grade PLCs. Relying on the general-purpose and standardized hardware architecture and multi-protocol compatibility of PLCs, seamless access to multiple brands and types of equipment can be achieved. Hardware can be configured and functions customized according to the specific technical requirements of the park and factory. Users can independently modify the control logic and expand the system functions, which greatly reduces the total life cycle cost of the system.

[0110] 3. By incorporating a carbon emission accounting model that conforms to national standards into the PLC, the core zero-carbon indicators such as carbon emission intensity, green electricity ratio, and renewable energy consumption rate are used as the core constraints for energy dispatch. The system can complete carbon emission accounting, exceedance warning and front-end control linkage locally in real time, and realize the closed-loop management of energy and carbon from "collection-accounting-control".

[0111] 4. Leveraging the flexible expansion capabilities and multi-protocol adaptation capabilities of PLC's I / O interfaces, it can be uniformly connected to microgrids, water supply, gas supply, heating, lighting, ventilation and other systems across all scenarios, enabling data interoperability and collaborative scheduling across the entire system, eliminating blind spots in management and control, maximizing the absorption of renewable energy, and reducing carbon emissions from a comprehensive perspective.

[0112] 5. By collecting signals from all dimensions, such as energy failures, carbon emission exceeding standards, pipeline network anomalies, and safety alarms, through a unified PLC control system, a multi-system linkage protection mechanism covering energy, carbon emissions, and safety is constructed to achieve rapid and coordinated handling of abnormal operating conditions and comprehensively improve the operational safety and compliance of zero-carbon parks and factories.

[0113] 6. By directly connecting the PLC to the execution device through local hard-wiring and local closed-loop calculation, the control link is significantly shortened, and the interlocking action response of ≤1s is achieved, which meets the industrial-grade real-time requirements of microgrid grid-to-grid switching, fault emergency protection, and real-time carbon emission control.

[0114] Based on the aforementioned technical problems to be solved, the purpose of this application is to provide a PLC-based integrated energy management method and system for zero-carbon parks and factories. Using a general-purpose industrial-grade PLC as the core control unit, it fundamentally solves the core defects of existing centralized energy and carbon management platforms, and constructs a low-cost, highly reliable, all-scenario, and energy-carbon closed-loop zero-carbon management system. This enables collaborative management and control of the energy system across all scenarios in zero-carbon parks and factories, closed-loop management of carbon emissions throughout the entire lifecycle, and fully supports the compliant and stable implementation of zero-carbon goals.

[0115] This application uses an industrial-grade PLC as the sole core control unit to reconstruct the decentralized architecture of integrated energy management in zero-carbon parks and factories. It fully localizes the core logic of the entire energy and carbon management process, specifically addressing the technical shortcomings of existing centralized energy and carbon management platforms. It achieves comprehensive breakthroughs in six dimensions: system reliability, total lifecycle cost, closed-loop energy and carbon management, full-scenario collaboration, real-time control performance, and security and compliance capabilities. The beneficial effects are as follows: 1. Eliminating dependence on networks and host computers, enhancing system reliability: This application deploys 100% localized core logic of the entire carbon management process on an industrial-grade PLC. The remote monitoring layer does not participate in real-time control, eliminating dependence on host computers and communication networks from the root of the architecture. It can still operate stably in closed loop under extreme conditions such as network outages and host computer crashes. At the same time, relying on the industrial-grade hardware characteristics of PLC, the system's anti-interference capability and annual online rate are greatly improved, ensuring the continuity and stability of zero-carbon park and factory management.

[0116] 2. Reduced lifecycle costs and lowered barriers to zero-carbon transformation for small and medium-sized industrial parks and factories: This application adopts general-purpose industrial-grade PLCs and standardized configuration software, replacing vendor-customized hardware and software. This completely solves the problems of high cost, limited scalability, and difficulty in expansion associated with existing solutions, reducing construction and maintenance costs by 30%-50% for projects of the same scale. Furthermore, leveraging the flexible expansion and customization capabilities of PLCs, users can construct and expand in phases according to their investment plans and development pace, without the need for a one-time investment in all hardware and functions, significantly reducing the initial construction threshold. Subsequent functional expansion and logic customization do not require high custom development fees, reducing lifecycle maintenance and transformation costs by over 60%, significantly lowering the barriers to zero-carbon transformation for SMEs.

[0117] 3. Modular and Flexible Expansion Capabilities to Adapt to the Entire Lifecycle Development Needs of Industrial Parks and Factories: This application adopts an industrial-grade PLC modular hardware architecture, supporting unlimited and smooth expansion of IO points, communication interfaces, computing power, and redundant architecture. It perfectly adapts to the entire lifecycle development needs of zero-carbon industrial parks and factories, from initial construction and phased expansion to later upgrades. For new photovoltaic installations, energy storage systems, charging piles, new factory areas / buildings, and new management scenarios in industrial parks and factories, only corresponding PLC expansion modules need to be added. Hardware expansion and functional additions can be achieved without replacing the core control host, reconstructing the system architecture, or interrupting normal system operation. This completely solves the shortcomings of existing customized system expansions, which require complete hardware replacement, resulting in high costs and long cycles. Simultaneously, the PLC's distributed IO expansion capabilities enable decentralized deployment and centralized management of industrial parks and factories by region and building, adapting to the cross-regional expansion needs of ultra-large industrial parks and factories and multi-factory joint management.

[0118] 4. Fully Customizable and Autonomous Control Logic for Precise and Personalized Zero-Carbon Target Management: This application, based on a structured and modular PLC program architecture, grants users complete autonomy in customization, completely breaking the original manufacturer's technological monopoly in existing customized systems. Users can independently customize carbon emission accounting rules, optimize scheduling strategy priorities, multi-system collaborative logic, and interlocking protection action rules according to their own industry attributes, energy consumption patterns, and carbon emission compliance requirements. This allows for convenient adjustment and optimization of the control logic, achieving precise management tailored to each area and factory. Furthermore, the control logic can be rapidly iterated based on relevant policy updates, adjustments to carbon emission accounting standards, and upgrades to zero-carbon targets for industrial parks and factories. The demand response cycle has been shortened from months in related technologies to hours, significantly improving the system's policy and target adaptability.

[0119] 5. Achieve a closed-loop energy and carbon management system to drive the implementation of zero-carbon goals: This application incorporates a national standard-compliant online carbon emission accounting model into the PLC, using zero-carbon core indicators as the highest priority constraint for energy dispatch, thus achieving a deep closed-loop energy and carbon management system. The carbon emission accounting cycle is shortened to the second level, the renewable energy consumption rate is increased to over 95%, and the overall carbon emission intensity of the park and factory is reduced by more than 30%. At the same time, carbon emission ledgers are maintained, which can support carbon trading and zero-carbon certification for the park and factory.

[0120] 6. Achieve multi-system collaborative management and eliminate blind spots in carbon emission control: This application relies on the flexible interface expansion and multi-protocol compatibility of PLC to uniformly connect to the microgrid, water, gas, heating, lighting and other systems in the park and factory and build in collaborative control logic, breaking down the information silos of each system and completely eliminating blind spots in carbon emission control. Compared with related technologies, the comprehensive energy utilization efficiency of the park and factory is improved by more than 25%, and full inclusion of carbon emissions at all boundaries is achieved.

[0121] 7. Improved control response speed to meet industrial-grade real-time control and emergency protection requirements: This application uses PLC hard-wiring to directly connect to field devices and localized closed-loop calculation of control logic to compress the long-link control process of related technologies into a local short-link closed loop. The core control closed-loop cycle is shortened to less than 200ms, and the interlock protection response time is ≤1s. The response speed is improved by more than 10 times, completely avoiding the control risks caused by communication delay and packet loss, and fully meeting the industrial-grade real-time control and emergency protection requirements.

[0122] 8. Construct a comprehensive and interconnected protection system to enhance the safety of park and factory operations: This application uses a unified PLC to collect comprehensive signals such as energy failures, carbon emission exceedances, and safety risks across all scenarios. It incorporates a cross-system interconnected protection mechanism for "energy-carbon emission-safety," upgrading single-point protection to comprehensive collaborative protection. This enables rapid handling of safety risks across all scenarios and prevents accidents from escalating. At the same time, it achieves proactive prevention and control of carbon emission exceedances, comprehensively balancing the safety of park and factory operations with carbon emission compliance.

[0123] 9. Enhanced versatility and adaptability, covering various zero-carbon scenarios: This application adopts standardized PLC hardware, modular programming, and a fully protocol-compatible architecture, which can flexibly adapt to various newly built or renovated zero-carbon scenarios, including zero-carbon industrial parks, zero-carbon manufacturing plants, zero-carbon data centers, zero-carbon commercial complexes, and zero-carbon buildings, etc., and has strong replicability. It adopts an industrial-grade PLC modular hardware architecture, supporting flexible combinations and unlimited smooth expansion of CPU modules, IO modules, communication modules, and functional expansion modules. The hardware configuration can be flexibly adjusted according to the scale of the park and factory, the number of connected devices, and the requirements of the management scenario. It supports phased construction and regional expansion. Hardware expansion does not require replacing the core control host; only the addition of corresponding modules is needed for a smooth upgrade. It also supports customized configurations of redundant power supplies, redundant CPUs, and redundant communication networks to adapt to the reliability requirements of different scenarios. It adopts industrially standardized PLC hardware to replace manufacturer-customized control equipment, and is equipped with multi-protocol communication modules, compatible with all categories of industrial common protocols such as Modbus RTU / TCP, Profinet, and IEC 61850. It can seamlessly connect to multiple brands and types of field devices, and supports users to independently modify control logic and expand system functions. At the same time, it can seamlessly integrate with existing equipment in parks and factories without large-scale hardware replacement. Only the corresponding communication modules and customized adaptation logic need to be expanded to complete the zero-carbon transformation of existing systems, which significantly reduces the difficulty and cost of zero-carbon transformation of existing parks and factories. For the special energy needs and management standards of different industries such as chemical, metallurgical, and manufacturing, customized function blocks can be quickly adapted to industry characteristics, achieving a perfect integration of general architecture and industry-specific needs. The PLC program adopts a standardized, modular, and decoupled structured design, breaking down the core control logic into independent standardized functional blocks. Each functional block has reserved user-defined interfaces, supporting the modification, addition, and deletion of functional modules, customization of carbon emission accounting rules, optimization of scheduling strategies, collaborative control logic, and interlocking protection rules. Without reconstructing the overall program architecture, it can complete the entire process of customized development and iteration.

[0124] Based on the same inventive concept, this application also provides a PLC-based integrated energy management method for zero-carbon parks and factories, applicable to the aforementioned PLC-based integrated energy management system for zero-carbon parks and factories. The solution provided by this method is similar to the implementation described in the above-described method. Therefore, the specific limitations in one or more embodiments of the PLC-based integrated energy management method for zero-carbon parks and factories provided below can be found in the limitations of the PLC-based integrated energy management system for zero-carbon parks and factories described above, and will not be repeated here.

[0125] In one exemplary embodiment, such as Figure 2As shown, a PLC-based integrated energy management method for zero-carbon industrial parks and factories is provided, including the following steps S1 to S4.

[0126] S1, continuously collect and preprocess the full-dimensional data uploaded by the field equipment layer; the full-dimensional data includes energy consumption data, fuel consumption data and renewable energy power generation data.

[0127] S3 calculates zero-carbon core indicators locally in real time based on real-time collected energy consumption data, fuel consumption data, and renewable energy power generation data.

[0128] S3, using the aforementioned zero-carbon core indicators as constraints, generates the optimal energy dispatch strategy through local cyclic calculation.

[0129] S4 converts the optimal energy dispatch strategy into control commands and sends them to the execution terminals at the field equipment level to achieve cross-system collaborative control of microgrid, water supply, gas supply, heating, lighting and ventilation systems.

[0130] This method uses an industrial-grade PLC as the sole control core, with all core calculations and control decisions completed locally on the PLC. It adopts a fully localized closed-loop workflow of "real-time acquisition - local calculation - local scheduling - collaborative execution - linkage protection - data upload", which is completely different from the centralized process of related technologies of "data upload to host computer - host computer calculation - instruction issuance to terminal". Even if network interruption or host computer crash occurs, the control process can still run in a complete closed loop.

[0131] The technical features of the above embodiments can be combined in any way. For the sake of brevity, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.

[0132] This document uses specific examples to illustrate the principles and implementation methods of this application. The descriptions of the above embodiments are only for the purpose of helping to understand the methods and core ideas of this application. Furthermore, those skilled in the art will recognize that, based on the ideas of this application, there will be changes in the specific implementation methods and application scope. Therefore, the content of this specification should not be construed as a limitation of this application.

Claims

1. A PLC-based integrated energy management system for zero-carbon industrial parks and factories, characterized in that, The PLC-based zero-carbon park and factory integrated energy management system adopts a three-layer decentralized management architecture consisting of a field equipment layer, a local control layer, and a remote monitoring layer. The local control layer is configured with an industrial-grade PLC, which is the system’s only real-time control and decision-making core. All core control logics, including carbon emission accounting, energy optimization scheduling, multi-system collaborative control, and fault linkage protection, are deployed locally within the PLC. The field device layer is directly connected to the PLC via hardwiring and industrial bus, and is used to collect energy, carbon emissions, equipment operating conditions and safety monitoring data of the zero-carbon park and factory in the whole scene, and execute control commands issued by the PLC; The remote monitoring layer is used to visualize the data of the field equipment layer and the local control layer. When the network is interrupted or the remote monitoring layer equipment fails, the PLC can independently complete the closed-loop management of the entire process. The PLC has the following built-in features: The real-time data acquisition and preprocessing unit is used to cyclically acquire and preprocess the full-dimensional data uploaded by the field equipment layer; the full-dimensional data includes energy consumption data, fuel consumption data, and renewable energy power generation data; The online carbon emission accounting unit is used to calculate the core zero-carbon indicators locally in real time based on real-time collected energy consumption data, fuel consumption data, and renewable energy power generation data. A multi-energy collaborative optimization scheduling unit is used to generate the optimal energy scheduling strategy through local cyclic calculation with the aforementioned zero-carbon core indicators as constraints. The multi-system collaborative control unit for all scenarios is used to convert the optimal energy dispatch strategy into control commands and send them to the execution terminals of the field equipment layer to realize cross-system collaborative control of microgrid, water supply, gas supply, heating, lighting and ventilation systems.

2. The PLC-based integrated energy management system for zero-carbon industrial parks and factories according to claim 1, characterized in that, The field device layer includes the following functional units: The renewable energy and energy storage unit is used to collect photovoltaic power generation, wind power generation, battery SOC, battery SOH, charging and discharging current and voltage, grid voltage, frequency and switch opening and closing status, and to execute charging and discharging regulation, start and stop control, grid connection and off-grid switching and power regulation commands; The load and public energy system unit is used to collect operating power, energy consumption data, pipeline parameters, and ambient temperature and humidity of production equipment, lighting, air conditioning / fresh air system, water supply system, gas supply system, and heating system, and to execute equipment start-up and shutdown, frequency regulation, valve opening regulation, brightness regulation, and temperature regulation commands. Carbon emission metering unit is used to collect data on greenhouse gas emission concentrations, fuel consumption, energy consumption data for all categories of electricity, water, gas, and heat, as well as renewable energy power generation data. The power quality and electrical safety unit is used to collect voltage harmonics, current harmonics, power factor, equipment temperature, fault signals and alarm information, and to execute protection actions, harmonic mitigation and reactive power compensation commands. The environmental and safety monitoring unit is used to collect data on gas concentration, smoke concentration, water immersion status, harmful gas concentration, and alarm signals, and to execute commands for coordinated ventilation, emergency shutdown, and equipment shutdown. The renewable energy and energy storage unit, load and public energy system unit, carbon emission metering unit, power quality and electrical safety unit, and environmental and safety monitoring unit are connected to the PLC via an edge communication unit.

3. The PLC-based integrated energy management system for zero-carbon industrial parks and factories according to claim 1, characterized in that, The online carbon emission accounting unit has a built-in carbon emission accounting model, and the real-time zero-carbon core indicators include carbon emission intensity, cumulative carbon emissions, renewable energy consumption rate, and green electricity ratio. The online carbon emission accounting unit is also used to compare the real-time calculated zero-carbon core indicators with the preset compliance threshold, warning threshold and serious exceedance threshold one by one. When the real-time calculated zero-carbon core indicators do not meet the preset requirements, a three-level signal of compliance, warning or exceedance is generated.

4. The PLC-based integrated energy management system for zero-carbon industrial parks and factories according to claim 1, characterized in that, The multi-energy collaborative optimization scheduling unit incorporates a multi-objective optimization scheduling algorithm with the core objectives of minimizing carbon emission intensity, maximizing renewable energy absorption rate, and minimizing operating costs. The objective function of the multi-objective optimization scheduling algorithm is: ； in, The objective function for a multi-objective optimization scheduling algorithm; It is a function of carbon emission intensity. = Real-time carbon emission intensity ÷ Carbon emission intensity compliance upper limit; The function is the renewable energy absorption rate. =1 - Real-time renewable energy absorption rate ÷ Target value of absorption rate; For the operating cost function; =Real-time operating cost ÷ Operating cost under baseline conditions; , , The weights for carbon emission intensity, renewable energy integration rate, and operating costs are respectively determined to meet the requirements. The three follow .

5. The PLC-based integrated energy management system for zero-carbon industrial parks and factories according to claim 1, characterized in that, The PLC also has a built-in all-dimensional fault linkage protection unit; the all-dimensional fault linkage protection unit is used to monitor fault signals, alarm signals and carbon emission exceeding signals in real time, and to perform interlock protection actions under abnormal operating conditions.

6. The PLC-based integrated energy management system for zero-carbon industrial parks and factories according to claim 5, characterized in that, The all-dimensional fault linkage protection unit incorporates the following core linkage protection logic: The energy-carbon linkage protection logic is used to interlock and shut down non-core high-energy-consuming equipment, activate emergency emission reduction plans, and issue compliance warnings when carbon emissions seriously exceed the standards. The energy fault linkage protection logic is used to interlock and switch off-grid mode when there is a microgrid fault or grid power outage, prioritizing the power supply of core loads and critical systems such as water supply, gas supply and lighting, and cutting off non-core high energy-consuming loads. The safety risk linkage protection logic is used to interlock and shut off the gas emergency shut-off valve, electrical equipment and heating equipment in the relevant area in the event of a gas leak, and simultaneously start the explosion-proof ventilation equipment and prohibit the start and stop of non-explosion-proof lighting equipment. The pipeline abnormality linkage protection logic is used to interlock and close the valves in the corresponding area when there is a leak in the water supply pipeline or an overpressure in the heating pipeline, and to simultaneously adjust the operating status of the water pump and the circulating pump.

7. The PLC-based integrated energy management system for zero-carbon industrial parks and factories according to claim 6, characterized in that, In the all-dimensional fault linkage protection unit, the interlocking protection logic program for different fault types is configured in the interrupt program of different priorities according to the severity of the fault. The interlocking protection logic for gas leaks and power grid outages is configured in a high-priority interrupt routine, the interlocking protection logic for carbon emission exceeding standards and regular faults is configured in a low-priority interrupt routine, and the regular control logic is configured in the main loop routine. The interrupt routine is used to be executed first during the main loop program. A high-priority interrupt routine will interrupt all low-priority tasks. The response time of all interlocking actions of the all-dimensional fault linkage protection unit is less than or equal to 1 second.

8. The PLC-based integrated energy management system for zero-carbon industrial parks and factories according to claim 1, characterized in that, The multi-energy collaborative optimization scheduling unit incorporates the following core scheduling logic: The logic of maximizing the absorption of renewable energy is used to prioritize the absorption of photovoltaic and wind power generation, and to prioritize the use of surplus electricity for energy storage charging, heat pump heating, heat pump cooling, and green hydrogen production. The zero-carbon-oriented peak shaving and valley filling logic is used to prioritize the use of energy storage discharge and renewable energy power supply during peak electricity consumption periods, and to adjust the operation plan of non-core high-energy-consuming equipment in conjunction with the low-price electricity and surplus renewable energy power to charge energy storage during off-peak periods. The dual control logic of demand and carbon emissions is used to monitor the grid demand and carbon emission intensity in real time. When either indicator approaches the threshold, it automatically controls the energy storage to discharge and cuts off non-core high energy-consuming loads. It also features a seamless off-grid switching logic for real-time monitoring of grid status. In the event of a grid failure, it completes the off-grid mode switch within 100ms, prioritizing power supply to core low-energy-consumption and low-emission loads and coordinating the operation of high-energy-consumption equipment.

9. The PLC-based integrated energy management system for zero-carbon industrial parks and factories according to claim 1, characterized in that, The PLC also has a built-in data interaction and power failure retention unit; the data interaction and power failure retention unit is used to interact with the remote monitoring layer and retain the setting parameters and operating data during power failure.

10. A PLC-based integrated energy management method for zero-carbon industrial parks and factories, applied to the PLC-based integrated energy management system for zero-carbon industrial parks and factories as described in any one of claims 1-9, wherein the PLC-based integrated energy management method for zero-carbon industrial parks and factories comprises: The system continuously collects and preprocesses the full-dimensional data uploaded from the field equipment layer. The comprehensive data includes energy consumption data, fuel consumption data, and renewable energy power generation data; Based on real-time collected energy consumption data, fuel consumption data, and renewable energy power generation data, the zero-carbon core indicators are calculated locally in real time. Using the aforementioned zero-carbon core indicators as constraints, the optimal energy dispatch strategy is generated through local cyclic calculation. The optimal energy dispatch strategy is converted into control commands and sent to the execution terminals at the field equipment level to achieve cross-system collaborative control of microgrids, water supply, gas supply, heating, lighting and ventilation systems.

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