Ang Edge Intelligence Nagpapakita ng Pwersa sa Digital na Transformasyon ng AIS CTs: Kompatibleng sa Tradisyonal at Smart Grids para sa Bagong Sistemang Pwersa

I. Konteksto sa Proyekto
Tungod sa pagtaas sa mga pangangailhan sa New Power System para sa pag-monitor sa dinamiko, katugmaan sa mga equipment, ug data intelligence, ang tradisyonal nga Air Insulated Switchgear (AIS) Current Transformers (CTs) nangin kritikal nga magbutang og digital transformation aron makamit ang mosunod nga mga breakthrough:

Konflikto sa Katugmaan: Kinahanglan suportahan ang parehas ang tradisyonal nga analog substations ug digital substations.
Bottleneck sa Akurasyon: Ang insufisyanse nga PMU (Phasor Measurement Unit) synchronization accuracy naglimita sa pagsusi sa dynamic process analysis.
Data Deluge: Ang transmision sa raw sampled values nakakupi sa mas 90% sa channel bandwidth.

II. Core Technical Solution

1. Dual-Mode Output Interface Architecture

Output Mode	Technical Parameters	Application Scenario
Traditional Analog	5A/1A, Accuracy Class 0.2S	Protection devices, mechanical meter access
Digital Output	IEC 61850-9-2 LE Sampled Values (SV), 4000 Hz	Merging Unit (MU), PMU centralized analysis

Innovation: Naggamit og magnetically isolated dual-winding design, naayaw sa digital/analog signal interference, nakamit ang full-scale error < ±0.1%.

2. Microsecond (μs) Level Time Synchronization System

3. Edge Computing Intelligent Terminal
* Hardware Configuration:
* Dual-core ARM Cortex-M7 processor @ 480MHz
* 128KB SRAM + 4MB Flash storage
* Local Analysis Functions:
* Harmonic Distortion Ratio (THD) calculation (±0.2% accuracy when THD ≤ 1.5%)
* Three-phase imbalance analysis (Response time < 20ms)
* Load waveform feature extraction (Compression ratio 7:1)
* Data Transmission Optimization: Only uploads feature data, reducing bandwidth usage by 70%.

III. Transformation Implementation Pathway

Three-Phase Implementation Plan for Digital Transformation

Phase	Activity	Timeline, Effort (Quarter-Person)
Device Layer Refit	Traditional CT Replacement	2025 Q1, 6qp
	Optical Fiber Network Deployment	2025 Q2, 4qp
System Layer Upgrade	MU Data Access	2025 Q3, 3qp
	Edge Computing Configuration	2025 Q4, 2qp
Advanced Applications	PMU Dynamic Monitoring	2026 Q1, 4qp
	AI Load Forecasting	2026 Q2, 6qp

(qp = Quarter-Person effort unit)

IV. Technical and Economic Benefits

Indicator	Before Refit	After Refit	Improvement
Data Acquisition Dimensions	6 parameters	27+ features	350% Increase
PMU Synchronization Accuracy	10 μs	0.8 μs	12.5x Improvement
Data Transmission Volume	12 Mbps/unit	3.6 Mbps/unit	70% Reduction
Fault Diagnosis Response Time	300 ms	45 ms	85% Improvement