Smarte Nuaimhe agus Réiteach Meaitseála Effeicínta do Tharbhainithe Trasnais

17yrs 700++ staff 108000m²+m² US$150,000,000+ China

1. Cúlra agus Dúshláin
Tá dúshláin suntasacha ann do roinnt transformaithe tosaithe i gcúigiúil comhthacaíochtais reatha. Ar an taobh amháin, tá an t-equipment aontaithe ag éirí níos sine agus ag déanamh laghdú ar fheidhmíocht teicniúil, ionsaíocht, agus slándacht. Ar an taobh eile, is éifeachtaí neamhiontaofa agus coireachtaí rialta na seiceálacha de láimh, agus ní féidir leis feabhsúcháin chun dul i gcoinne. Tá costais ard, cruinniú deacair, agus dúshláin ina chaidreamh le lorg fóige ag cur isteach ar an obair. Tá sé seo tar éis a bheith mar bhonnóg atá ag codú eficiúlacht, slándacht, agus staidéar an chórais. Mar sin, tá sé riachtanach an t-equipment a nuashonrú agus modhanna coireachta inteiligentí a dhiúltú go mionsonrach.

2. Réiteach: Stratéis Dual-Driven don Nuashonrú Equipment agus Coireachta Inteileach
Úsáideann an moladh seo stratéis a chomhbhaint "Nuashonrú Hardware" agus "Empowerment Software" chun aird a thabhairt ar fheidhmíocht, ionsaíocht, agus eficiúlacht na coireachta transformaithe tosaí trí úsáid nua-teicnící.

2.1 Nuashonrú Core Equipment

Cuir chun cinn On-Load Tap Changers (OLTC): Athraigh transformaithe tap-shocraithe nó gan inteleacht go huathoibríoch. Déanann OLTC athrú uaireanta ar raátai voltaga le linn oibriú, ag freagairt do chodarsnuithe an chórais. Seo a dhéanann ardú suntasach ar staidseacht agus cáilíocht an voltaga, agus is fearr é ná transformaithe traidisiúnta chun aird a thabhairt ar athruithe carraige agus cuardaíocht fuinnimh athnuachana, agus laghdú ar riscaí damáiste ábhar nó codú carraige mar gheall ar ghéarchéim voltaga.
Úsáid Gas-Insulated Switchgear (GIS): Toghadh GIS i gcomparáid le Air-Insulated Switchgear (AIS) sna tionscadail nua nó athchóiriú. Integreann GIS scuabaireachtaí circe, disconectors, grounding switches, transformaithe, agus surge arresters i gcomhbháid meitil sealda le gaís insulating. Forbairtí príomha chomh maith:

Solas Spás: Gníomhaíonn sé ar 10%-30% de theasais AIS, ag óptamáil úsáid talún an substation - iontaofa do chentra cathracha, limistéir talún conspóide, nó fo-thalamh.
Forbartha Comhshaoil: Coscann an tógáil sealda ar dust, meascán, bréagán salainn, agus polúdú, ag laghdú ar riscaí deacrachtaí externa agus ag díol le haontaibhí an-chrua.
Árd Ionsaíocht & Slándacht: Laghdú suntasach ar riscaí arcing agus spriocáin; is ísealí tuairisciú failte ná AIS. Laghdú ar oibre coireachta, ag forbartha slándacht an phobail agus an t-equipment.
Íseal Ghuth & EMI: Coscann an t-sealda meitil ar ghuth oibriúcháin agus ar electromagnetic interference, ag laghdú ar tionchar comhshaoil.

2.2 Córas Monatóireachta Stádas Inteileach

Dissolved Gas Analysis (DGA) Online Monitoring: Tá sé mar bhunscuaine. Analysers i réalaíocht suite sa chiorcal oil ag monatóireacht ar choinsias agus treoí gasa dissolt (H₂, CH₄, C₂H₆, C₂H₄, C₂H₂, CO, CO₂).

Léargas: Cineál, coinsias, agus ráta gnéithe gasa mar "fingerprints" a léiríonn deacrachtaí latent (mar shampla, decompost thermal, partial/arcing discharge, oil overheating). Úsáideann an córas modhanna analais (mar shampla, Duval Triangle, Rogers Ratios) chun sláinte a meas, ag cuir carthanachtaí deacrachta luath, cruinn (mar shampla, windings overheating, core grounding faults, insulation degradation), ag bogadh ó dhearcadh réactaí chun coireachta aimhréadach chun a stopadh deacrachtaí caillte.

2.3 AI-Driven Smart Maintenance Management

Unified Data Platform: Integreann sonraí ilphoinnt (DGA, partial discharge, core current, oil temperature/level, bushing losses), taifid equipment, stair coireachta, agus sonraí oibriú (load, voltaga, teocht comhshaoil) chun a chruthú digital twin transformaithe.
Big Data Analytics: Úsáideann data mining chun ceangaltas idir sonraí monatóireachta agus stáid equipment, ag bunú modhanna base-line agus aitheantas éagsúlacht (go háirithe i paraméad DGA).
AI-Powered Diagnosis & Decision-Making:

Fault Diagnosis & Localization: ML algorithms (e.g., DNNs, SVM, Random Forest) learn from historical faults and expert knowledge. Combined with real-time data, models intelligently identify fault types (e.g., thermal vs. electrical faults) and locate origins (e.g., windings, core, tap changers), aiding rapid troubleshooting.
Health Assessment & Lifespan Prediction: AI synthesizes multi-dimensional data to quantify health scores (e.g., Health Index) and predict remaining useful life, guiding replacement decisions.
Risk Alerts & Maintenance Optimization: Systems auto-evaluate risk levels and issue alerts. Optimization algorithms recommend tailored maintenance strategies (e.g., outage planning, task prioritization) based on risk, criticality, and resources. Confirmed faults trigger automated repair protocols.
Expert Knowledge Base: Built-in knowledge graphs and expert systems structure domain expertise and standards, supporting explainable AI decisions and boosting credibility.

3. Beartas Súilgthe

Forbairt Inteileach: Combines smart hardware (OLTC auto-regulation), sensors, and AI to enable "self-perception, self-diagnosis, self-decision, self-optimization."
Forbairt Ionsaíocht: Higher inherent reliability of GIS/OLTC; AI monitoring reduces unplanned outages by preempting failures.
Forbairt Slándacht: GIS design and smart monitoring lower explosion/fire risks; early fault intervention prevents accidents.
Forbairt Costais Coireachta: Reduces manual inspection frequency; condition-based maintenance avoids over-/under-maintenance and optimizes resources/spares; preventive measures cut repair expenses.
Forbairt Eficiúlacht Achaim: GIS saves land; smart maintenance boosts equipment/personnel utilization.
Forbairt Saol: Proactive health management slows insulation aging and performance decline, prolonging service life.

4. Moltaí Impleachta

Phased Rollout: Prioritize aging equipment, critical substations, and urban load centers.
Standardization First: Develop uniform specs for equipment selection, sensor installation, data protocols, platform interfaces, and AI modeling.
Data Integration: Break silos by consolidating monitoring and management data onto a unified platform.
Workforce Transformation: Train staff in smart monitoring, data analytics, and AI diagnostics to shift toward data-driven, human-AI collaboration.
Continuous Improvement: Iteratively refine AI models and strategies using operational feedback.