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EMS Energy Management System

Invisible energy waste is the most terrifying. Shi-He Intelligent EMS visualizes energy data and uses AI algorithms for precise prediction, achieving automated optimal dispatch.

Core Function Modules

Comprehensive Energy Management Toolbox

Full-Field Visual Monitoring

Integrates solar, storage, and load into a single dashboard. Supports real-time mobile push notifications for instant anomaly awareness.

AI Demand Prediction & Shedding

System automatically learns usage patterns to predict overrun risks. Automatically dispatches storage discharge or sheds non-critical loads before overrun occurs to avoid high penalties.

Automated Report Generation

One-click export of daily/monthly/annual energy reports. Can generate energy consumption analysis reports in ISO 50001 format, significantly reducing management workload.

AI Energy Command Center

Real-time Monitoring War Room

Dashboard Placeholder

Unified monitoring for energy, demand and alarms

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Main Load

1.82 MW

Real-time total consumption

Prediction Window

15 min

AI risk warning before demand spike

Report Sync

ISO 50001

Daily, monthly, annual exports

Safety First

Energy Storage Fire Safety System

Comprehensive Multi-Level Protection

PACK Level Protection

Built-in sensors and aerosol fire suppression in every battery pack to stop thermal runaway at the source.

Perfluorohexanone Technology

Using FK-5-1-12 clean agent, non-conductive and residue-free, protecting valuable electronic equipment.

AI Smart Linkage

Deeply integrated with EMS to automatically cut power and activate suppression upon anomaly detection.

Why Choose EMS?

AI-Empowered Core Algorithms

Non-traditional rule-based control. We use deep learning models to dynamically adjust optimal charge/discharge strategies based on weather, past usage data, and price fluctuations, achieving 95% prediction accuracy.

High Scalability Architecture

Supports Modbus, DNP3, and other industrial protocols. Seamlessly expandable for single-factory microgrids or multinational Virtual Power Plant (VPP) integration.

Bank-Grade Security

ISO 27001 compliant. End-to-end encryption (E2EE) and physical network isolation ensure your valuable energy data never leaks.

Architecture Placeholder

System architecture from field devices to cloud analytics

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PV / BESS / meters

Edge gateway & protocol integration

AI forecasting & dispatch engine

Cloud dashboard & ESG reporting

FAQ

EMS Energy Management FAQ

Common questions regarding smart energy management systems and power-saving solutions

How much initial investment does an EMS system require?

It depends on facility scale and number of monitoring points. We offer a cloud-based EMS solution where SMEs can subscribe monthly, significantly reducing upfront costs.

Can EMS integrate with existing equipment?

Yes. Our EMS supports Modbus, DNP3, and other mainstream industrial protocols, enabling integration with most existing meters, chillers, and HVAC controllers without full replacement.

After implementing ShiHe's EMS, how long does it take to recover the investment cost?

Depending on the energy-saving efficiency of different industries, most enterprises can recover costs within 1.5 to 3 years. ShiHe's EMS uses AI demand forecasting to effectively reduce "penalty fees for exceeding contract capacity." This optimization alone usually reduces the basic electricity bill by 15-20%. Combined with AI automated control of AC and lighting, measured average energy savings reach over 25%, showing particularly significant effects for energy-intensive industries like metal processing and chemical engineering.

How does ShiHe's EMS ensure my corporate data security?

We use a "Hybrid Cloud" architecture where sensitive production data remains on the enterprise's internal network (Edge Computing), and only encrypted energy statistics are uploaded to the cloud. The system is certified under ISO 27001 Information Security Management and features bank-grade AES-256 encrypted transmission to ensure energy data and production logic are not leaked, providing hierarchical permission management to prevent internal operational errors.

If my factory equipment is very old, can the EMS still integrate them?

Certainly. ShiHe excels at "Heterogeneous Equipment Integration," supporting various industrial communication protocols like Modbus, BACnet, and OPC UA. For old machines without communication interfaces, we can capture data by installing "add-on power sensors" and "IoT Gateways," achieving true site-wide data transparency without needing to replace expensive existing equipment.

How exactly does "AI Demand Forecasting" in the EMS system work?

The system uses machine learning algorithms to predict the electricity consumption peak for the next 15 minutes based on historical data from the past three years, current weather information, and production schedules. When the predicted value nears 95% of the contract capacity, the system automatically triggers a "load shedding strategy" (such as fine-tuning AC frequency) to avoid penalties. This is more precise than traditional human monitoring and helps enterprises maximize power utilization.

Do the reports generated by the system comply with ISO 50001 energy management standards?

Yes, this is a core advantage of ShiHe's EMS. The system automatically generates Energy Baseline and Energy Performance Indicator (EnPI) reports required for ISO 50001, ISO 14064, and other certifications. It supports one-click export to PDF or Excel, significantly reducing the manual recording burden for energy managers and providing visual dashboards for ESG decision-making.

If the network disconnects, can the EMS system still operate normally?

Yes. ShiHe's intelligent edge gateways feature "offline storage and logic control" functions. Even if the network is temporarily interrupted, on-site automated energy-saving logic (such as demand control) will continue to execute, and data will be temporarily stored in the hardware. Once the network is restored, the system automatically performs breakpoint transmission to ensure the integrity and continuity of the energy database.