Intelligent Production and Operation Platform

Station Control System: The "Intelligent Execution Terminal" for Production Sites

Focused on equipment monitoring and automatic control of gas stations (gate stations, pressure regulating stations, storage and distribution stations, etc.), it replaces traditional manual operations to achieve "unmanned operation and minimal personnel inspection" at stations. Its core functions include:

1. Remote Equipment Monitoring

It collects real-time operating data (pressure, temperature, flow rate, valve opening, equipment status) of core station equipment (compressors, pressure regulators, valves, measuring instruments, security equipment). This data is intuitively displayed via a visual interface (simulated dashboards, equipment status indicator lights), and the system automatically highlights abnormal equipment statuses (e.g., overpressure, equipment offline) in red to issue early warnings.

2. Automatic Process Control

Based on preset logic or scheduling instructions, it enables automatic adjustment of production processes. For example:

• When pipeline pressure drops below the threshold, it automatically starts the backup compressor;
• When the inlet flow fluctuation exceeds 10%, it automatically adjusts the pressure regulator opening to stabilize the output pressure.It supports dual-mode switching between "remote manual control and automatic linkage control" to meet manual intervention needs in special scenarios.

3. Fault Self-Healing and Alarm

• For minor equipment faults (e.g., valve jamming, sensor drift), the system automatically triggers "self-healing commands" (e.g., switching to backup valves, calibrating sensors) and sends early warning information to operation and maintenance personnel.
• For unrepairable faults (e.g., compressor shutdown), it immediately cuts off the circuit associated with the faulty equipment to prevent fault spread and generates a maintenance work order.

4. Station Security Linkage

It integrates station video surveillance, gas detection, and fire-fighting equipment. When gas leakage (excessive concentration) or unauthorized personnel intrusion is detected, it automatically triggers audible and visual alarms, activates ventilation equipment or fire-fighting systems, and synchronizes the information to the production scheduling system—forming a "security-production" linked disposal mechanism.

Production Scheduling System: The "Intelligent Decision-Making Hub" for Overall Production

Focused on the overall coordination and optimized scheduling of gas production, it realizes dynamic matching of "gas source-load-equipment" based on real-time data and algorithm models. Its core functions include:

1. Multi-Factor Load Forecasting

Integrating historical gas consumption data (daily/weekly/monthly patterns), meteorological data (temperature, precipitation), and socioeconomic data (industrial production plans, holidays), it uses an "LSTM+XGBoost" hybrid algorithm to forecast the pipeline gas load for the next 24 hours/7 days. With a prediction accuracy of ≥92%, it provides a basis for gas source procurement and production planning.

2. Gas Source Allocation and Load Balancing

Based on gas supply capacity (e.g., long-distance pipeline gas supply volume, LNG storage tank capacity) and regional gas load, it automatically generates a "multi-station gas source allocation plan." For example:

• When a gas consumption peak arrives in a certain area, it dispatches nearby storage and distribution stations to supplement gas supply;
• When gas sources are insufficient, it prioritizes residential gas supply, dynamically adjusts the gas load for industrial users, and prevents sudden drops in pipeline pressure.

3. Panoramic Production Monitoring

It integrates production data (gas supply volume, equipment status, energy consumption) from all stations and pipeline transmission data (main line pressure, flow rate) to generate a "panoramic production dashboard." It supports data drilling by region, station, and equipment (e.g., clicking "a gate station" to view its daily gas supply volume and compressor operation duration), enabling real-time mastery of the overall production status.

4. Cross-Station Collaborative Scheduling

When a single station malfunctions or experiences load fluctuations, it automatically coordinates nearby stations to compensate. For example, if pressure regulating station A shuts down due to a fault, it dispatches adjacent stations B and C to increase output pressure to cover station A’s gas supply area, ensuring stable pipeline pressure. Scheduling instructions are sent to the station control system in real time via encrypted channels, with a response time of ≤30 seconds.

5. Production Emergency Collaboration

In the event of emergencies such as gas source interruption or large-scale station failures, it automatically generates an "emergency scheduling plan," including "gas source switching paths (e.g., switching from long-distance pipelines to LNG emergency gas sources), station load adjustment range, and early warning scope for affected users." It synchronizes the plan to the safety emergency command platform, links maintenance personnel and emergency resources, and shortens production interruption time.

1. Edge Computing Empowers Real-Time Control to Address the "Remote Control Delay" Pain Point

Edge computing gateways are deployed at stations to enable "local processing of equipment data + on-site issuance of control commands," avoiding control delays caused by reliance on the cloud. Edge nodes collect equipment status data at a frequency of 1 time per second, with a control command response time of ≤50ms—far lower than the 500ms delay of traditional cloud-based control. This ensures the real-time performance of critical operations such as pressure adjustment and fault shutdown, meeting the "millisecond-level response" safety requirement for gas production.

2. Multi-Factor Fusion Forecasting Algorithm Improves Load Prediction Accuracy

Breaking through the traditional forecasting model that "only relies on historical data," this algorithm integrates more than 10 dimensions of influencing factors (e.g., meteorology, industrial production, holidays). It screens key variables through feature engineering (e.g., for every 1℃ drop in temperature, residential gas load increases by 3%) and adopts "sliding window training" to dynamically update model parameters. As a result, the short-term (24-hour) load prediction accuracy is increased to over 92%, and the long-term (7-day) prediction accuracy is ≥88%, reducing "waste caused by excess gas sources" or "gas supply shortages caused by insufficient gas sources."

3. Distributed Collaborative Scheduling Algorithm Optimizes Multi-Station Resource Allocation

Based on the goal of "optimal global load allocation," a distributed optimization algorithm (ADMM, Alternating Direction Method of Multipliers) is adopted. Under the constraints of meeting the equipment capacity of each station and pipeline pressure requirements, the algorithm automatically calculates the optimal gas source allocation plan, achieving a multi-station load balance rate of ≥95%. For example, when 5 gate stations in a city cluster supply gas collaboratively, the algorithm can control the load deviation of each station within ±5%, preventing overload operation of individual stations, extending equipment service life, and reducing overall production energy consumption.

4. Fault Self-Healing and Cross-System Linkage Reduce Production Interruptions

Through "equipment fault knowledge base + real-time data matching," automatic self-healing of more than 20 types of common minor faults (e.g., valve jamming, sensor drift) is realized, with a self-healing success rate of ≥80%. The average fault handling time is reduced from the traditional manual 30 minutes to less than 5 minutes. Meanwhile, linkage with the equipment management system and maintenance & emergency repair system is supported: when a fault cannot be self-healed, a maintenance work order is automatically generated and pushed to operation and maintenance personnel, and equipment fault records are updated simultaneously, forming a full closed loop of "fault discovery - disposal - filing."

5. Global Environment Compatibility Design to Adapt to Domestic and International Deployment Needs

It supports mainstream global operating systems such as Linux (Ubuntu, Red Hat) and Windows Server, and is compatible with general databases including MySQL, PostgreSQL, and Oracle—no reliance on specific localized tools is required. At the same time, it complies with global data compliance standards such as the EU GDPR, US CCPA, and Southeast Asia PDPA. Data transmission adopts TLS 1.3 encryption, meeting the "multi-regional deployment and localized compliance" needs of transnational gas enterprises.