An energy management system and method for a natural gas purification plant

Abstract

The present application relates to the technical field of energy management and control, in particular to an energy management and control system and method for a natural gas purification plant, the energy management and control system can realize online monitoring and out-of-limit alarm of production operation data, energy consumption statistical data and energy performance parameters; can use the established energy efficiency evaluation chart to evaluate the energy efficiency of the four main units of desulfurization, dewatering, sulfur recovery and tail gas treatment; can optimize the energy efficiency of the energy-using object in the low-efficiency area based on the energy efficiency evaluation analysis result; can perform multi-dimensional performance assessment combined with the energy efficiency optimization effect; to realize the precise management and control of energy consumption of the natural gas purification plant, thereby improving the energy utilization efficiency and the comprehensive energy efficiency level, and ultimately achieving the purpose of cost reduction and cost control and quality improvement and efficiency increase.

Description

Technical Field

[0001] This invention relates to the field of energy management technology, and specifically to an energy management system and method for a natural gas purification plant. Background Technology

[0002] Energy management and control is a comprehensive energy management model that has developed in recent years. It targets energy production, transmission, distribution, and consumption processes, using automation and information technology. Through energy metering and online monitoring, and employing benchmarking analysis and system optimization methods, it dynamically monitors and effectively manages energy utilization, promoting optimal energy use and maximizing economic benefits, thereby improving the scientific management level of an enterprise's energy sector. Gas field production systems generally consist of gas production systems, gathering and transmission systems, purification and treatment systems, and gas field water reinjection systems. Among these, the purification and treatment system accounts for the highest energy consumption, approximately 35% of the total energy consumption, and is characterized by long process flows, numerous process stages, complex inter-process relationships, and a wide variety of hardware equipment. Therefore, there is an urgent need to establish an energy management and control system and methods that meet the production characteristics of natural gas purification plants, in order to achieve unified scheduling and centralized management of energy resources, improve energy utilization efficiency, enhance overall energy efficiency, and achieve the goals of cost reduction, cost control, and quality and efficiency improvement.

[0003] In conclusion, it is particularly important to design a system or method for energy management suitable for natural gas purification plants. Summary of the Invention

[0004] The purpose of this invention is to provide an energy management system and method for natural gas purification plants. This management system meets the production characteristics of natural gas purification plants, realizes unified scheduling and centralized management of energy resources, improves energy utilization efficiency, enhances overall energy efficiency, and achieves the goals of cost reduction, cost control, and quality and efficiency improvement.

[0005] To achieve the above objectives, the present invention provides the following technical solution:

[0006] An energy management and control system for a natural gas purification plant, the system comprising an energy consumption monitoring module, an early warning and alarm module, a benchmarking analysis module, an energy efficiency optimization module, and a performance evaluation module:

[0007] Energy consumption monitoring module: Real-time acquisition of energy consumption data and energy performance parameters of energy-consuming units. Energy consumption data includes: production operation data and energy consumption statistics.

[0008] Early warning and alarm module: Receives energy consumption data, determines whether the energy consumption data exceeds the threshold, and sends an alarm message if the threshold is exceeded;

[0009] Benchmarking Analysis Module: Receives energy consumption data and performs zoned evaluation of energy-consuming units based on energy consumption statistics and online energy efficiency evaluation charts. Zoned evaluation is as follows: draw standard lines and average lines based on the average energy consumption of energy-consuming units and energy consumption standards. Divide the online energy efficiency evaluation charts into high-efficiency zones, potential zones, and low-efficiency zones using the standard lines and average lines. Zones above the average line are low-efficiency zones, zones between the standard line and the average line are potential zones, and zones below the standard line are high-efficiency zones.

[0010] Energy efficiency optimization module: Receives energy efficiency evaluations and constructs energy efficiency optimization schemes for energy-consuming units;

[0011] Performance evaluation module: Receives energy consumption data and energy performance parameters from energy-consuming units and conducts performance evaluations of the energy-consuming units.

[0012] Furthermore, energy consumption data is obtained through the following systems: power data acquisition system, natural gas data acquisition system, fresh water data acquisition system, and production data acquisition and control system; the production data acquisition and control system acquires real-time production data from the desulfurization unit, dehydration unit, sulfur recovery unit, and tail gas treatment unit, including: liquid level, temperature, pressure, and flow rate;

[0013] Furthermore, the production data acquisition and control system regulates the parameters of the desulfurization unit, dehydration unit, sulfur recovery unit, and exhaust gas treatment unit.

[0014] Furthermore, the thresholds in the early warning and alarm module include production operation data thresholds and energy consumption statistics thresholds. The production operation data thresholds are set based on historical data or the current production plan; the energy consumption statistics thresholds are set based on historical data or the current production plan.

[0015] Furthermore, the energy efficiency optimization module applies benchmarking, theoretical calculation, and neural network methods to generate optimization schemes for production parameters and equipment operating parameters, and automatically tracks the optimization process and analyzes the optimization effect in real time.

[0016] Furthermore, the performance evaluation of energy-consuming units involves customizing performance evaluation indicators for each unit and piece of equipment, conducting horizontal benchmarking and vertical comparison. Horizontal benchmarking is used to compare the total energy consumption, energy performance parameters, and completion status of performance requirements among each unit and piece of equipment; vertical comparison is used to evaluate the progress of each unit and piece of equipment at the same stage. Energy performance parameters include comprehensive energy consumption indicators, unit energy consumption indicators, energy consumption indicators of energy-consuming units, and energy-consuming equipment indicators.

[0017] An energy management method for a natural gas purification plant includes the following steps:

[0018] Collect energy consumption data and energy performance parameters from energy-consuming units. The energy consumption data includes: production operation data and energy consumption statistics.

[0019] Determine whether the energy consumption data of the energy-consuming unit exceeds the threshold. If it exceeds the threshold, issue an over-limit alarm.

[0020] The energy efficiency of energy-consuming units is evaluated using online energy efficiency evaluation charts and energy consumption data. The online energy efficiency evaluation charts are established based on the average energy consumption of the energy-consuming units and energy consumption standards.

[0021] Based on the energy efficiency evaluation results and energy consumption data, an energy efficiency optimization model is established for the energy-consuming unit, and an energy efficiency optimization scheme is generated.

[0022] Implement energy efficiency optimization schemes for energy-consuming units, record the energy efficiency optimization results, and conduct performance evaluations based on the energy efficiency optimization results.

[0023] Furthermore, the energy-consuming unit includes the main unit, the public works system unit, and the auxiliary production equipment unit. The main unit is the main energy-consuming unit, which mainly includes the desulfurization unit, the dehydration unit, the sulfur recovery unit, and the tail gas treatment unit.

[0024] Furthermore, the production and operation data include natural gas processing volume, product gas volume, sulfur production, liquid level, temperature, pressure, and flow rate; energy consumption statistics include electricity consumption, gas consumption, and water consumption; and energy performance parameters include comprehensive energy consumption indicators, unit consumption indicators, main unit energy consumption indicators, and energy-consuming equipment indicators.

[0025] Furthermore, the energy efficiency evaluation of energy-consuming units includes the following steps:

[0026] Based on the average energy consumption of energy-consuming units and energy consumption standards, standard lines and average lines are drawn. The online energy efficiency evaluation chart is divided into high-efficiency zone, potential zone, and low-efficiency zone using the standard lines and average lines. Zones above the average line are low-efficiency zones, zones between the standard line and the average line are potential zones, and zones below the standard line are high-efficiency zones. Energy-consuming units are evaluated by zone based on energy consumption statistics.

[0027] Furthermore, benchmarking, theoretical calculation, or neural network methods are used to generate optimization schemes for production parameters and equipment operating parameters.

[0028] This invention also provides an energy management system for a natural gas purification plant.

[0029] The energy management system for natural gas purification plants includes an energy consumption monitoring module, an early warning and alarm module, a benchmarking analysis module, an energy efficiency optimization module, and a performance evaluation module. The specific functions of each module are as follows:

[0030] Online monitoring module: performs online monitoring of production operation data, energy consumption statistics, and energy performance parameters;

[0031] Over-limit alarm module: Provides over-limit alarms for online monitoring of production operation data, energy consumption statistics, and energy performance parameters;

[0032] Energy efficiency evaluation module: Evaluates the energy efficiency of the four main units: desulfurization, dehydration, sulfur recovery, and exhaust gas treatment;

[0033] Energy efficiency optimization module: Based on the energy efficiency evaluation results, an energy efficiency optimization plan is generated;

[0034] Performance evaluation module: Conduct multi-dimensional performance evaluation based on the effects of energy efficiency optimization.

[0035] The energy management system for the natural gas purification plant also includes an electricity data acquisition system, a natural gas data acquisition system, a fresh water data acquisition system, a production data acquisition and control system, a data processing and transfer system, a production system database, an energy management system database, and a data center.

[0036] The power data acquisition system collects electricity consumption data from metering points and transmits the relevant power metering network topology and daily power data to the data center. The online monitoring module collects data by unit and by device according to the power consumption topology, calculates the actual power consumption of each main unit and type of equipment, and stores the actual power consumption data in the energy management system database.

[0037] The natural gas data acquisition system collects gas consumption data from metering points and transmits the relevant natural gas metering network topology and daily natural gas data to the data center. The online monitoring module collects data by unit and by equipment according to the gas consumption topology, calculates the actual gas consumption of each main unit and type of equipment, and stores the actual gas consumption data in the energy management system database.

[0038] The fresh water data acquisition system collects water usage data from metering points and transmits the relevant fresh water metering network topology and daily fresh water data to the data center. The online monitoring module collects data by unit and by equipment according to the water usage topology, calculates the actual water usage of each main unit and type of equipment, and stores the actual water usage data in the energy management system database.

[0039] The production data acquisition and control system collects real-time production data from the desulfurization unit, dehydration unit, sulfur recovery unit, and tail gas treatment unit, including but not limited to liquid level, temperature, pressure, and flow rate, and remotely controls the production operation parameters of the desulfurization unit, dehydration unit, sulfur recovery unit, and tail gas treatment unit.

[0040] When calculating the actual power consumption of each main unit and type of equipment, the power consumption of each main unit is generated by summarizing the power consumption data of each unit's branch lines, and the power consumption of each type of equipment is generated by summarizing the power consumption data of each power consumption point. Specifically, the power consumption data of the desulfurization unit is collected from the electricity meters of equipment such as the lean amine liquid circulation pump, the regeneration tower top reflux pump, the lean liquid air cooler, and the acid gas air cooler; the power consumption data of the dehydration unit is collected from the electricity meters of equipment such as the TEG circulation pump; the power consumption data of the sulfur recovery unit is collected from the electricity meters of equipment such as the recovery fan and the liquid sulfur degassing fan; and the power consumption data of the tail gas treatment unit is collected from the electricity meters of equipment such as the online furnace fan, the tail gas incinerator fan, the tail gas fan, the quench water air cooler, the lean liquid air cooler, the acid gas air cooler, the quench water pump, the rich liquid pump, the lean liquid pump, and the regeneration tower top reflux pump.

[0041] When calculating the actual gas consumption of each main unit and type of equipment, the gas consumption of each main unit is generated by summarizing the gas consumption data of each unit's sub-pipeline, and the gas consumption of each type of equipment is generated by summarizing the gas consumption data of each gas consumption point. Specifically, the gas consumption data of the dehydration unit is collected from gas meter data collected by gas-consuming equipment such as the TEG regeneration tower reboiler and the TEG lean liquor distillation column; the gas consumption data of the sulfur recovery unit is collected from gas meter data collected by gas-consuming equipment such as the primary reheat furnace, the secondary reheat furnace, and the tertiary reheat furnace; and the gas consumption data of the tail gas treatment unit is collected from gas meter data collected by gas meter data collected by gas-consuming equipment such as the online combustion furnace and the tail gas incinerator.

[0042] When calculating the actual water consumption of each main unit and type of equipment, the online monitoring module generates the water consumption data of each main unit from the water consumption data of its respective pipeline, and the water consumption data of each type of equipment from the water consumption data of its respective water point. Specifically, the water consumption data of the desulfurization unit is collected from the water meter data of the lean liquor aftercooler, acid gas aftercooler, and other water-using equipment; the water consumption data of the dehydration unit is collected from the water meter data of the TEG lean liquor cooler; the water consumption data of the sulfur recovery unit is collected from the water meter data of the waste heat boiler heat exchanger, primary sulfur condenser cooler, secondary sulfur condenser cooler, tertiary sulfur condenser cooler, and other water-using equipment; and the water consumption data of the tail gas treatment unit is collected from the water meter data of the waste heat boiler, quench water aftercooler, lean liquor aftercooler, incinerator waste heat boiler, and other water-using equipment.

[0043] This online monitoring module monitors production operation data, energy consumption statistics, and energy performance parameters in real time. The production operation data includes natural gas processing volume, product gas volume, sulfur production, liquid level, temperature, pressure, and flow rate. The energy consumption statistics include electricity consumption, gas consumption, and water consumption. The energy performance parameters include comprehensive energy consumption indicators, unit energy consumption indicators, main unit energy consumption indicators, and energy-consuming equipment indicators.

[0044] The online monitoring module transmits real-time production operation data, energy consumption statistics, and energy performance parameters to the limit-over alarm module for judgment. The limit-over alarm module establishes limit values ​​for production operation data, energy consumption statistics, and energy performance parameters; exceeding these limits automatically sends an alarm message. The limit values ​​for production operation data can be set according to relevant established standards, calculated based on historical data regression analysis of the monitored object's recent actual operation and objective influencing factors, or manually set according to the production plan. Similarly, the limit values ​​for energy consumption statistics and energy performance parameters can be set according to relevant established standards, calculated based on historical data regression analysis of the monitored object's recent energy consumption and objective influencing factors, or manually set according to future production plans. When the system sends an alarm signal indicating an increase in electricity, gas, or water consumption in key units such as desulfurization, dehydration, sulfur recovery, and tail gas treatment, an energy efficiency evaluation analysis of that unit is required.

[0045] The online monitoring module calculates and generates energy performance parameters, which are then transmitted to the energy efficiency evaluation module for energy efficiency assessment and analysis. This module establishes an evaluation map covering four main units: desulfurization, dehydration, sulfur recovery, and tail gas treatment. It automatically categorizes energy-consuming equipment into high-efficiency, potential, and low-efficiency zones, prioritizing energy-consuming equipment in the low-efficiency zones of each unit for remediation. Specifically, the desulfurization unit primarily evaluates electricity consumption per unit of natural gas processed; the dehydration unit primarily evaluates fuel gas consumption per unit of product gas; the sulfur recovery unit primarily evaluates electricity consumption per unit of product sulfur; and the tail gas treatment unit primarily evaluates the comprehensive energy consumption per unit of acid gas processed.

[0046] The energy efficiency evaluation module transmits data on energy-consuming objects in the selected inefficient areas to the energy efficiency optimization module for energy efficiency optimization and adjustment. This optimization module, targeting substandard energy-consuming objects, comprehensively applies three methods—benchmarking, theoretical calculation, and neural network methods—to generate optimized production parameters and equipment operating parameters. These optimized plans are then reviewed and approved by production management personnel before implementation. The production data acquisition and control module allows for remote adjustment of production and operating parameters. The benchmarking method primarily compares the differences in production parameters between substandard units and benchmark units, and the differences in operating parameters between substandard equipment and benchmark equipment. The theoretical calculation method calculates the theoretically optimal production and operating parameters for the unit / equipment. The neural network method trains an energy efficiency optimization model using big data analysis and utilizes historical data to calculate the optimal production and operating parameters for the unit / equipment.

[0047] The online monitoring module will calculate and generate energy consumption statistics and energy performance parameters, and transmit them to the performance evaluation module for evaluation. Based on the total energy consumption data and energy intensity data statistics of each main unit, it will determine whether the performance indicators of each main unit have reached the set performance targets; based on the specific parameters and operating efficiency of each piece of equipment, it will compare whether the performance indicators of each piece of equipment meet the set performance requirements.

[0048] The data processing and transfer system preprocesses the data collected from the power data acquisition system, natural gas data acquisition system, fresh water data acquisition system, and production data acquisition and control system, and then transfers the data to the production system database, energy management system database, and data center, respectively.

[0049] The production system database stores and provides corresponding real-time production data and service interfaces.

[0050] The energy management system's database stores data resources such as energy consumption plans, actual electricity consumption, actual gas consumption, actual water consumption, assessment indicators, evaluation standards, energy consumption evaluation models, and energy efficiency optimization effect tracking.

[0051] This data center serves as a platform for the centralized storage, management, and service of data resources from natural gas purification plants. It includes data resources such as models of the natural gas purification plant, its main units, equipment, and production dynamics, providing energy management and control systems with data resources and services such as production data, equipment data, and geographic coordinate data.

[0052] This invention also provides a method for energy management in natural gas purification plants;

[0053] Energy management methods for natural gas purification plants:

[0054] Step S1: Determine the scope of energy consumption evaluation and establish a unit-based and equipment-based energy consumption evaluation system;

[0055] Step S2 involves online monitoring of production operation data, energy consumption statistics, and energy performance parameters;

[0056] Step S3: Set limit values ​​and issue alarms for exceeding limits on online monitored production operation data, energy consumption statistics data, and energy performance parameters;

[0057] Step S4: Establish an online energy efficiency evaluation chart for the desulfurization unit, dehydration unit, sulfur recovery unit, and tail gas treatment unit, and evaluate the energy efficiency of the four main units: desulfurization, dehydration, sulfur recovery, and tail gas treatment.

[0058] Step S5: Establish an energy efficiency optimization model and generate an energy efficiency optimization scheme;

[0059] Step S6: Conduct multi-dimensional performance evaluation based on the energy efficiency optimization results.

[0060] In step S1, the overall energy consumption control scope includes all energy types and all energy-consuming units. Energy types include electricity, natural gas, fresh water, and other energy sources. All energy-consuming units include main units, utility system units, and auxiliary production units. The main units are the primary energy consumers and require detailed energy consumption control. The focus is on evaluating the energy performance parameters of the desulfurization unit, dehydration unit, sulfur recovery unit, and tail gas treatment unit. The main energy performance parameters are determined as follows:

[0061] Total energy consumption = Total electricity consumption × Energy conversion factor + Total gas consumption × Energy conversion factor;

[0062] Unit product natural gas comprehensive energy consumption = (total electricity consumption × energy conversion factor + total gas consumption × energy conversion factor) / product natural gas volume;

[0063] Energy consumption per unit of natural gas processed = (Total electricity consumption × energy conversion factor + Total gas consumption × energy conversion factor) / Natural gas processed;

[0064] Fresh water consumption per unit of natural gas = Total fresh water consumption / Natural gas consumption per unit of product;

[0065] Power consumption of main unit = power consumption of desulfurization unit + power consumption of dehydration unit + power consumption of sulfur recovery unit + power consumption of tail gas treatment unit;

[0066] Main unit gas consumption = Dehydration unit gas consumption + Sulfur recovery unit gas consumption + Tail gas treatment unit gas consumption;

[0067] Water consumption of main unit = water consumption of desulfurization unit + water consumption of dehydration unit + water consumption of sulfur recovery unit + water consumption of tail gas treatment unit;

[0068] Power consumption per unit of sulfur desulfurization unit = Power consumption of desulfurization unit / Sulfur output;

[0069] Fuel gas consumption per unit of product gas dehydration unit = Gas consumption of dehydration unit / Product natural gas quantity;

[0070] Unit product sulfur: Sulfur recovery unit power consumption = Sulfur recovery unit power consumption / Sulfur production;

[0071] Comprehensive energy consumption per unit of acid gas treatment volume = (Power consumption of tail gas treatment unit × Energy conversion factor + Gas consumption of tail gas treatment unit × Energy conversion factor) / Acid gas treatment volume;

[0072] In step S4, standard lines and average lines are drawn based on energy efficiency identification standards and actual average energy efficiency levels. The energy efficiency distribution map of the evaluated objects is divided into high-efficiency zones, potential zones, and low-efficiency zones. Online evaluation is conducted on the energy consumption levels of key equipment objects in the four main units: desulfurization, dehydration, sulfur recovery, and tail gas treatment. Specifically, the desulfurization unit mainly evaluates the electricity consumption per unit of natural gas processed; the dehydration unit mainly evaluates the fuel gas consumption per unit of product gas; the sulfur recovery unit mainly evaluates the electricity consumption per unit of product sulfur; and the tail gas treatment unit mainly evaluates the comprehensive energy consumption per unit of acid gas processed.

[0073] In step S5, an energy efficiency optimization model is established, production parameter optimization and operation parameter optimization schemes are pushed, the optimization process is automatically tracked, and the optimization effect is automatically analyzed; energy efficiency optimization schemes are pushed, and the optimization effect is automatically tracked; a comprehensive optimization scheme is formed using three methods: benchmarking, theoretical calculation, and neural network method, and substandard and potential units and equipment are optimized, and the optimization effect is tracked. Attached Figure Description

[0074] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0075] Figure 1 This is a schematic diagram of the architecture of the energy management system for a natural gas purification plant according to a specific embodiment of the present invention. In the figure:

[0076] 1. Power Data Acquisition System; 2. Natural Gas Data Acquisition System; 3. Fresh Water Data Acquisition System; 4. Production Data Acquisition and Control System, 41. Production Data Acquisition Module; 42. Desulfurization Unit Remote Control Module; 43. Dehydration Unit Remote Control Module; 44. Sulfur Recovery Unit Remote Control Module; 45. Tail Gas Treatment Unit Remote Control Module; 5. Data Processing and Storage System; 6. Data Center; 7. Production System Database; 8. Energy Management System Database; 9. Online Monitoring Module; 10. Exceeding Limit Alarm Module; 11. Energy Efficiency Evaluation Module; 12. Energy Efficiency Optimization Module; 13. Performance Appraisal Module;

[0077] Figure 2 This is a schematic diagram of the energy efficiency evaluation of a desulfurization unit in a specific embodiment of the present invention;

[0078] Figure 3 This is a schematic diagram of the energy efficiency evaluation of the dehydration unit in a specific embodiment of the present invention;

[0079] Figure 4 This is a flowchart illustrating the energy management method for natural gas purification plants in a specific embodiment of the present invention. Detailed Implementation

[0080] To make the objectives, technical solutions, and advantages of the embodiments of the present invention clearer, the technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0081] Example 1:

[0082] See the schematic diagram of the energy management system for natural gas purification plants. Figure 1 ;

[0083] The power data acquisition system 1 collects electricity meter data from each power supply line and electricity point. After preprocessing by the data processing and transfer system, the data is transmitted to the data center 5. The data is then collected by unit and equipment according to the power topology. The actual electricity consumption of each main unit and type of equipment is calculated. The electricity consumption of each main unit is generated by summarizing the electricity consumption data of each unit's sub-line, and the electricity consumption of each type of equipment is generated by summarizing the electricity consumption data of each electricity point. The power consumption data for the desulfurization unit includes meter readings from equipment such as the lean amine circulating pump, the regeneration tower top reflux pump, the lean liquid air cooler, and the acid gas air cooler. The power consumption data for the dehydration unit includes meter readings from equipment such as the TEG circulating pump. The power consumption data for the sulfur recovery unit includes meter readings from equipment such as the recovery fan and the liquid sulfur degassing fan. The power consumption data for the tail gas treatment unit includes meter readings from equipment such as the online furnace fan, tail gas incinerator fan, tail gas fan, quench water air cooler, lean liquid air cooler, acid gas air cooler, quench water pump, rich liquid pump, lean liquid pump, and regeneration tower top reflux pump. The production data acquisition module 41 collects production data such as liquid level, temperature, pressure, and flow rate from the desulfurization unit, dehydration unit, sulfur recovery unit, and tail gas treatment unit, and transmits this data to the data center 5. Based on electricity consumption and production data, the online monitoring module 9 automatically generates the operating status of energy consumption indicators for each unit and equipment, including daily electricity consumption data and comprehensive unit consumption of main units such as desulfurization, dehydration, sulfur recovery, and tail gas treatment; daily electricity consumption data and operating efficiency of energy-consuming equipment such as pumps and fans; daily production data such as natural gas processing volume, product natural gas volume, and sulfur production of the purification plant; and comparison data with indicators such as planned daily electricity consumption.

[0084] The online monitoring module 9 calculates and generates daily power consumption data and indicators for each unit and equipment, which are then transmitted to the over-limit alarm module 10 for judgment. The over-limit alarm module 10 establishes limit values ​​for production operation data, energy consumption statistics, and energy performance parameters. If these limits are exceeded, an alarm is automatically pushed. The over-limit alarm model includes power fluctuations for each unit and each equipment, mainly comparing the data with yesterday's production and power consumption. When the system pushes an alarm signal indicating an increase in power consumption in the desulfurization unit, an energy efficiency evaluation analysis of the desulfurization unit is required.

[0085] The energy consumption per unit calculated by the online monitoring module 9 is transmitted to the energy efficiency evaluation module 11 for energy efficiency evaluation and analysis. The energy efficiency evaluation module 11 is designed with an energy efficiency evaluation chart. Based on standards and document requirements, an evaluation chart covering four main units—desulfurization, dehydration, sulfur recovery, and tail gas treatment—is established. Energy-consuming equipment is automatically zoned for evaluation, sequentially identifying high-efficiency, potential, and low-efficiency zones. Specifically, the desulfurization unit primarily evaluates the electricity consumption per unit of natural gas processed; the dehydration unit primarily evaluates the fuel gas consumption per unit of product gas; the sulfur recovery unit primarily evaluates the electricity consumption per unit of product sulfur; and the tail gas treatment unit primarily evaluates the comprehensive energy consumption per unit of acid gas processed. Energy-consuming objects in the low-efficiency zones of each main unit are prioritized for remediation. The desulfurization unit identifies and optimizes amine circulation pumps that do not meet the electricity consumption per unit of natural gas processed.

[0086] A specific application of the two-line, three-zone energy efficiency evaluation chart, taking the evaluation of the power consumption index per unit natural gas processing capacity of the desulfurization unit's amine liquid circulation pump as an example, such as... Figure 2 As shown in the power consumption evaluation chart for a unit natural gas processing capacity of amine liquid circulation pumps, the indicator line is the numerical line of the specific energy-saving assessment target issued annually, and the average line is the average numerical line of power consumption per unit natural gas processing capacity of amine liquid circulation pumps. The indicator line and the average line divide the power consumption evaluation chart for a unit natural gas processing capacity into three areas: inefficient area, potential area, and high-efficiency area. Amine liquid circulation pumps in the inefficient area are the key targets for treatment. Priority will be given to implementing energy efficiency optimization and adjustment for amine liquid circulation pumps in this area to promote the transformation of inefficiency into potential, potential into high efficiency, and high efficiency into further efficiency improvement.

[0087] The energy efficiency evaluation module 11 filters out the energy-consuming objects in the inefficient area and transmits the data to the energy efficiency optimization module for energy efficiency optimization and adjustment. In the energy efficiency optimization module 12, for the substandard amine liquid circulation pump, a comprehensive application of benchmarking, theoretical calculation, and neural network methods is used. The benchmarking method mainly compares the differences in operating parameters between the substandard amine liquid circulation pump and the benchmark amine liquid circulation pump. The theoretical calculation method calculates the theoretically optimal operating parameter values ​​for the amine liquid circulation pump. The neural network method trains the energy efficiency optimization model through big data analysis and uses historical data to calculate the optimal operating parameter values ​​for the amine liquid circulation pump. The above three methods are used to generate an operating parameter optimization plan, which is then reviewed and approved by production control personnel before implementation. The desulfurization unit remote control module 42 is used to directly adjust the operating parameters of the amine liquid circulation pump remotely. After all optimization plans are implemented, the optimization process is automatically tracked and the optimization effect is automatically analyzed.

[0088] The online monitoring module 9 calculates and generates daily electricity consumption data and energy consumption indicators for each unit and equipment, and transmits them to the performance evaluation module 13 for evaluation. Based on the statistical results of the total energy consumption data and energy intensity data of each main unit, the module analyzes and compares the year-on-year progress of electricity consumption indicators for each unit and each equipment.

[0089] It enables closed-loop management of energy consumption control, including online monitoring of power consumption, alarms for exceeding limits, energy efficiency evaluation, energy efficiency optimization, and effect tracking.

[0090] Example 2:

[0091] Natural gas data acquisition system 2 collects gas meter data from each gas supply line and gas consumption point. After preprocessing by the data processing and transfer system, the data is transmitted to data center 5. Data is then aggregated by unit and equipment according to the gas consumption topology, calculating the actual gas consumption of each main unit and type of equipment. The gas consumption of each main unit is generated by summarizing the gas consumption data of its respective pipeline, and the gas consumption of each type of equipment is generated by summarizing the electricity consumption data of each gas consumption point. Specifically, the gas consumption data for the dehydration unit is collected from gas meter data collected from gas-consuming equipment such as the TEG regeneration tower reboiler and TEG lean liquor distillation column; the gas consumption data for the sulfur recovery unit is collected from gas meter data collected from gas-consuming equipment such as the primary reheat furnace, secondary reheat furnace, and tertiary reheat furnace; and the gas consumption data for the tail gas treatment unit is collected from gas meter data collected from gas-consuming equipment such as the online combustion furnace and tail gas incinerator. Production data acquisition module 41 collects production data such as liquid level, temperature, pressure, and flow rate from the desulfurization unit, dehydration unit, sulfur recovery unit, and tail gas treatment unit, and transmits this data to data center 5. Based on gas consumption and production data, the online monitoring module 9 automatically generates the operating status of energy consumption indicators for each unit and equipment, including daily gas consumption data and comprehensive unit consumption of main units such as desulfurization, dehydration, sulfur recovery, and tail gas treatment; daily gas consumption data and operating efficiency of energy-consuming equipment such as reboilers, reheat furnaces, combustion furnaces, and incinerators; daily production data such as natural gas processing volume, product natural gas volume, and sulfur production of the purification plant; and comparison data with indicators such as planned daily gas consumption.

[0092] The online monitoring module 9 calculates and generates daily gas consumption data and indicators for each unit and equipment, which are then transmitted to the over-limit alarm module 10 for judgment. The over-limit alarm module 10 establishes limit values ​​for production operation data, energy consumption statistics, and energy performance parameters. If the limit value is exceeded, an alarm message is automatically pushed. The over-limit alarm model includes gas volume fluctuations for each unit and equipment, and mainly compares with the production and gas consumption of the previous day. When the system pushes an alarm signal for increased gas volume in the dehydration unit, an energy efficiency evaluation analysis of the dehydration unit is required.

[0093] The energy consumption per unit, calculated by the online monitoring module 9, is transmitted to the energy efficiency evaluation module 11 for energy efficiency evaluation and analysis. The energy efficiency evaluation module 11 features an energy efficiency evaluation chart. Based on standards and document requirements, it establishes an evaluation chart covering four main units: desulfurization, dehydration, sulfur recovery, and tail gas treatment. It automatically categorizes energy-consuming equipment into high-efficiency, potential, and low-efficiency zones. Specifically, the desulfurization unit primarily evaluates the electricity consumption per unit of natural gas processed; the dehydration unit primarily evaluates the fuel gas consumption per unit of product gas; the sulfur recovery unit primarily evaluates the electricity consumption per unit of sulfur; and the tail gas treatment unit primarily evaluates the comprehensive energy consumption per unit of acid gas processed. Energy-consuming devices in the low-efficiency zones of each main unit are prioritized for treatment. The dehydration unit identifies reboilers with substandard fuel gas consumption per unit of product gas for optimization and adjustment.

[0094] A specific application of the two-line, three-zone energy efficiency evaluation chart, taking the evaluation of fuel gas consumption per unit of product gas in a dehydration unit as an example, is as follows: Figure 3 As shown in the evaluation chart of unit product gas and fuel gas consumption of reboilers, the indicator line is the numerical line of the specific energy-saving assessment target issued in the year, and the average line is the average numerical line of unit product gas and fuel gas consumption of reboilers. The indicator line and the average line divide the evaluation chart of unit product gas and fuel gas consumption into three areas: inefficient area, potential area, and high-efficiency area. Reboilers in the inefficient area are the key targets for treatment. Priority is given to implementing energy efficiency optimization and adjustment for reboilers in this area to promote the transformation of inefficiency into potential, potential into high efficiency, and high efficiency into further efficiency improvement.

[0095] The energy efficiency evaluation module 11 filters out the energy-consuming objects in the inefficient area and transmits the data to the energy efficiency optimization module for energy efficiency optimization and adjustment. In the energy efficiency optimization module 12, for the substandard reboilers, a comprehensive application of benchmarking, theoretical calculation, and neural network methods is used. The benchmarking method mainly compares the differences in operating parameters between the substandard reboiler and the benchmark reboiler. The theoretical calculation method calculates the theoretically optimal operating parameter values ​​for the reboiler's energy consumption. The neural network method trains the energy efficiency optimization model through big data analysis and uses historical data to calculate the optimal operating parameter values ​​for the reboiler's energy consumption. The above three methods are used to generate an operating parameter optimization plan, which is then reviewed and approved by production control personnel before implementation. The dehydration unit remote control module 43 directly adjusts the reboiler's operating parameters remotely. After all optimization plans are implemented, the optimization process is automatically tracked and the optimization effect is automatically analyzed.

[0096] The online monitoring module 9 calculates and generates daily gas consumption data and energy consumption indicators for each unit and equipment, and transmits them to the performance evaluation module 13 for evaluation. Based on the statistical results of the total energy consumption data and energy intensity data of each main unit, the module analyzes and compares the year-on-year progress of gas consumption indicators for each unit and each equipment.

[0097] It enables closed-loop management of energy consumption control, including online monitoring of natural gas consumption, alarms for exceeding limits, energy efficiency evaluation, energy efficiency optimization, and effect tracking.

[0098] When the system sends an alarm signal indicating an increase in energy consumption in the sulfur recovery unit and the exhaust gas treatment unit, the relevant energy-consuming equipment can be evaluated and optimized in accordance with Examples 1 and 2. Technical personnel can remotely adjust the operating parameters of the energy-consuming equipment through the remote control module 44 of the sulfur recovery unit and the remote control module 45 of the exhaust gas treatment unit in conjunction with the optimization plan, thereby improving the energy efficiency level of the sulfur recovery unit and the exhaust gas treatment unit.

[0099] Example 3:

[0100] like Figure 4 As shown, this embodiment of the invention provides an energy management method for a natural gas purification plant, comprising:

[0101] Step S1: Determine the scope of energy consumption evaluation and establish a unit-based and equipment-based energy consumption evaluation system. The overall energy consumption control scope includes all energy types and all energy-consuming units. Energy types include electricity, natural gas, fresh water, and other energy types. All energy-consuming units include main units, utility system units, and auxiliary production unit units. The main units are the primary energy consumers and require detailed energy consumption control. The evaluation will focus on the energy performance parameters of the desulfurization unit, dehydration unit, sulfur recovery unit, and tail gas treatment unit. The main energy performance parameters are determined as follows:

[0102] Total energy consumption = Total electricity consumption × Energy conversion factor + Total gas consumption × Energy conversion factor

[0103] Unit product natural gas comprehensive energy consumption = (total electricity consumption × energy conversion factor + total gas consumption × energy conversion factor) / product natural gas volume

[0104] Energy consumption per unit of natural gas processed = (Total electricity consumption × energy conversion factor + Total gas consumption × energy conversion factor) / Natural gas processed

[0105] Fresh water consumption per unit of natural gas = Total fresh water consumption / Natural gas consumption per unit of product

[0106] Power consumption of main unit = power consumption of desulfurization unit + power consumption of dehydration unit + power consumption of sulfur recovery unit + power consumption of exhaust gas treatment unit

[0107] Main unit gas consumption = Dehydration unit gas consumption + Sulfur recovery unit gas consumption + Tail gas treatment unit gas consumption

[0108] Water consumption of main unit = Water consumption of desulfurization unit + Water consumption of dehydration unit + Water consumption of sulfur recovery unit + Water consumption of tail gas treatment unit

[0109] Unit power consumption of sulfur desulfurization unit = Power consumption of desulfurization unit / Sulfur output

[0110] Fuel gas consumption per unit of product gas dehydration unit = Gas consumption of dehydration unit / Product natural gas quantity

[0111] Unit product sulfur: Sulfur recovery unit power consumption = Sulfur recovery unit power consumption / Sulfur production

[0112] Comprehensive energy consumption per unit of acid gas treatment capacity = (Electricity consumption of tail gas treatment unit × Energy conversion factor + Gas consumption of tail gas treatment unit × Energy conversion factor) / Acid gas treatment capacity

[0113] Step S2: Apply online monitoring functions to monitor production operation data, energy consumption statistics and energy performance parameters in real time.

[0114] Step S3: Apply the limit alarm function, set the limit value, and issue limit alarms for online monitoring of production operation data, energy consumption statistics data and energy performance parameters, so as to realize real-time alarm from macro totals to specific indicators.

[0115] Step S4: Establish online energy efficiency evaluation charts for the desulfurization unit, dehydration unit, sulfur recovery unit, and tail gas treatment unit; conduct energy efficiency evaluation analysis; and identify inefficient energy-consuming objects. Based on energy efficiency assessment standards and actual average energy efficiency levels, draw standard lines and average lines. Divide the energy consumption efficiency distribution map of the evaluated objects into high-efficiency zones, potential zones, and inefficient zones. Conduct online evaluations of the energy consumption levels of key equipment in the four main units: desulfurization, dehydration, sulfur recovery, and tail gas treatment. Specifically, the desulfurization unit mainly evaluates the electricity consumption per unit of natural gas processed; the dehydration unit mainly evaluates the fuel gas consumption per unit of product gas; the sulfur recovery unit mainly evaluates the electricity consumption per unit of sulfur per unit of product; and the tail gas treatment unit mainly evaluates the comprehensive energy consumption per unit of acid gas processed. Energy-consuming objects in the inefficient zones of each main unit are prioritized for remediation.

[0116] Step S5: Establish an energy efficiency optimization model, automatically push production parameter optimization and operating parameter optimization schemes, automatically track the optimization process, and automatically analyze the optimization effect. The model pushes energy efficiency optimization schemes and automatically tracks the optimization effect. It utilizes three methods—benchmarking, theoretical calculation, and neural network methods—to form a comprehensive optimization scheme, optimizing substandard and potential units and equipment, automatically tracking the optimization effect, and achieving "online optimization."

[0117] Benchmarking method: Select high-efficiency units and equipment, identify the main influencing factors by comparing sensitive parameters, and determine the optimization methods and paths.

[0118] Theoretical calculation method: Based on the principles and design of natural gas purification and treatment, a mathematical model is built using theoretical formulas. Information technology is used to automate the four processes of parameter input, iterative calculation, result screening, and comparative output. Practical experience parameters are also incorporated to ensure the accuracy of the calculation results.

[0119] Neural Network Method: A high-fit model is established using the BP neural network algorithm. For energy-consuming objects in inefficient areas, a well-trained BP neural network model is used to predict the optimal energy efficiency operation of units and equipment, and to select the best alternative technical solutions.

[0120] For substandard amine circulation pumps, an energy efficiency optimization model is established using benchmarking, theoretical calculation, and neural network methods. Based on the optimization results from theoretical calculation and neural network methods, the system automatically generates optimized operating parameter schemes. After technical personnel review and implement the schemes, the system automatically tracks the optimization process and analyzes the optimization effects.

[0121] Step S6 involves applying performance evaluation functions and conducting multi-dimensional performance evaluations based on energy efficiency optimization results. Through demonstration and guidance, and evaluation policies, the responsibilities of energy conservation and consumption reduction entities at all levels are solidified, ensuring that energy consumption control is "knowable in its targets, comparable in its indicators, and traceable in its benchmarks." A comprehensive evaluation is conducted on indicators such as planned operation of the natural gas purification plant, comprehensive energy consumption, comprehensive energy consumption per unit of natural gas, unit consumption of desulfurization units, unit consumption of dehydration units, unit consumption of sulfur recovery units, and unit consumption of tail gas treatment units. Daily morning meetings are held, weekly key reviews are conducted, monthly summaries are held, and quarterly assessments are implemented.

Claims

1. An energy management system for a natural gas purification plant, characterized in that, The system includes an energy consumption monitoring module, an early warning and alarm module, a benchmarking analysis module, an energy efficiency optimization module, and a performance evaluation module. Energy consumption monitoring module: Real-time acquisition of energy consumption data and energy performance parameters of energy-consuming units. Energy consumption data includes: production operation data and energy consumption statistics. Early warning and alarm module: Receives energy consumption data, determines whether the energy consumption data exceeds the threshold, and sends an alarm message if the threshold is exceeded; Benchmarking Analysis Module: Receives energy consumption data and performs zoned evaluation of energy-consuming units based on energy consumption statistics and online energy efficiency evaluation charts. The zoned evaluation is as follows: draws standard lines and average lines based on the average energy consumption of energy-consuming units and energy consumption standards. The online energy efficiency evaluation charts are divided into high-efficiency zones, potential zones, and low-efficiency zones by using the standard lines and average lines. Zones above the average line are low-efficiency zones, zones between the standard line and the average line are potential zones, and zones below the standard line are high-efficiency zones. Energy efficiency optimization module: Receives energy efficiency evaluations and constructs energy efficiency optimization schemes for energy-consuming units; Performance evaluation module: Receives energy consumption data and energy performance parameters from energy-consuming units and conducts performance evaluations of the energy-consuming units.

2. The energy management system according to claim 1, characterized in that, The energy consumption data is obtained through the following systems: power data acquisition system, natural gas data acquisition system, fresh water data acquisition system, and / or production data acquisition and control system; the production data acquisition and control system acquires real-time data generated by the desulfurization unit, dehydration unit, sulfur recovery unit, and tail gas treatment unit, the real-time data including: liquid level, temperature, pressure, flow rate, and / or, the production data acquisition and control system regulates the production and operation parameters of the desulfurization unit, dehydration unit, sulfur recovery unit, and tail gas treatment unit.

3. The energy management system according to claim 1, characterized in that, The thresholds in the early warning and alarm module include production operation data thresholds and energy consumption statistics thresholds. The production operation data thresholds are set based on historical data or the current production plan; the energy consumption statistics thresholds are set based on historical data or the current production plan.

4. The energy management system according to claim 1, characterized in that, The energy efficiency optimization module uses benchmarking, theoretical calculation, and neural network methods to generate optimization schemes for production parameters and equipment operating parameters, and automatically tracks the optimization process and analyzes the optimization effect in real time.

5. The energy management system according to claim 1, characterized in that, The performance evaluation of energy-consuming units involves customizing performance evaluation indicators for each unit and device, conducting horizontal benchmarking and vertical comparison. Horizontal benchmarking is used to compare the total energy consumption, energy performance parameters, and completion status of performance requirements among each unit and device. Vertical comparison is used to evaluate the progress of each unit and device at the same stage. The energy performance parameters include comprehensive energy consumption indicators, unit energy consumption indicators, energy consumption indicators of energy-consuming units, and energy-consuming equipment indicators.

6. An energy management method for a natural gas purification plant, characterized in that, The method includes the following steps: Collect energy consumption data and energy performance parameters from energy-consuming units. The energy consumption data includes: production operation data and energy consumption statistics. Determine whether the energy consumption data of the energy-consuming unit exceeds the threshold. If it exceeds the threshold, issue an over-limit alarm. The energy efficiency of energy-consuming units is evaluated using an online energy efficiency evaluation chart and energy consumption data. The online energy efficiency evaluation chart is established based on the average energy consumption of the energy-consuming units and energy consumption standards. Based on the energy efficiency evaluation results and energy consumption data, an energy efficiency optimization model is established for the energy-consuming unit, and an energy efficiency optimization scheme is generated. Implement energy efficiency optimization schemes for energy-consuming units, record the energy efficiency optimization results, and conduct performance evaluations based on the energy efficiency optimization results.

7. The control method according to claim 6, characterized in that, The energy-consuming unit includes a main unit, a public works system unit, and an auxiliary production device unit. The main unit is the main energy-consuming unit, which mainly includes a desulfurization unit, a dehydration unit, a sulfur recovery unit, and a tail gas treatment unit.

8. The control method according to claim 6, characterized in that, The production and operation data include natural gas processing volume, product gas volume, sulfur production, liquid level, temperature, pressure, and flow rate. Energy consumption statistics include electricity consumption, gas consumption, and water consumption. Energy performance parameters include comprehensive energy consumption index, unit consumption index, main unit energy consumption index, and energy-consuming equipment index.

9. The control method according to claim 6, characterized in that, The energy efficiency evaluation of the energy-consuming unit includes the following steps: Based on the average energy consumption of energy-consuming units and energy consumption standards, standard lines and average lines are drawn. The online energy efficiency evaluation chart is divided into high-efficiency zone, potential zone, and low-efficiency zone using the standard lines and average lines. Zones above the average line are low-efficiency zones, zones between the standard line and the average line are potential zones, and zones below the standard line are high-efficiency zones. Energy-consuming units are evaluated by zone based on energy consumption statistics.

10. The control method according to claim 6, characterized in that, Use benchmarking, theoretical calculation, or neural network methods to generate optimization schemes for production parameters and equipment operating parameters.

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