AI in Telecom Power Engineering: Intelligent Energy & Power Operations
5 DAYS
INSTRUCTOR LED WORKSHOP
“OUR COURSES CAN BE SPECIALLY TAILORED TO ADDRESS YOUR REQUIREMENT – TELECONTRAN”
Telecom power engineering is evolving from static backup-power design and alarm-based maintenance toward data-driven, predictive and increasingly automated energy operations. Modern mobile networks, 5G densification, tower sharing, unstable grids, rising electricity costs and hybrid energy systems require power engineers to manage -48 VDC plants, batteries, generators, solar, utility supply and environmental systems as an integrated energy platform. Artificial Intelligence (AI), machine learning and advanced analytics can turn telemetry from these assets into forecasts, anomaly detection, maintenance priorities and optimized operating decisions.
This workshop focuses on AI applications for telecom power engineers rather than RAN optimization. It connects established power-engineering practice with commercially available telecom energy platforms and controllers. Product examples are used to demonstrate real capabilities such as remote monitoring, battery health management, risk prediction, intelligent energy scheduling, load visibility and energy OPEX optimization.
After successful completion of this workshop participants will be able to
- Explain where AI/ML adds value in telecom power operations and where conventional control logic remains appropriate.
- Map the complete telecom site power chain from grid/genset/renewables through rectifiers, -48 VDC distribution, batteries and critical loads.
- Identify the telemetry, alarms and maintenance data required for useful AI models and trustworthy engineering decisions.
- Apply anomaly detection and predictive-maintenance concepts to rectifiers, batteries, generators, power quality and environmental systems.
- Use forecasting concepts for site load, battery autonomy, fuel demand, solar production and energy consumption.
- Evaluate AI-assisted grid, solar, battery and generator scheduling for hybrid telecom sites without compromising service availability.
- Understand fleet-level energy optimization, remote O&M and site prioritization across hundreds or thousands of telecom sites.
- Assess commercially available solutions and build a realistic phased AI adoption roadmap for telecom power operations.
COURSE CURRICULUM
This program is designed for directors, managers, engineers, technicians, telecom power engineers, energy and infrastructure engineers, BTS/site power specialists, NOC and field O&M engineers, tower-company technical teams, DC power and battery specialists, generator and renewable-energy engineers, energy managers, infrastructure planners, technical managers and other personnel responsible for the availability, efficiency, maintenance or modernization of telecom power infrastructure.
Module 1: AI for Telecom Power – What It Really Means
- AI vs automation vs rules-based control
- Predictive, prescriptive and generative AI
- Where AI fits in telecom power operations
- Human-in-the-loop decision making
- Safety, reliability and operational boundaries
Module 2: Telecom Power Architecture and Data Sources
- Grid / utility supply and ATS
- DG and fuel system
- Rectifier and -48 VDC power plant
- VRLA and lithium-ion battery systems
- Solar / hybrid energy systems
- Cooling and environmental loads
- Controllers, sensors, meters and NMS telemetry
Module 3: Data Foundation for AI-Ready Power Operations
- Voltage, current, temperature and energy data
- Battery SOC / SOH and discharge history
- Generator runtime, fuel and start records
- Alarm/event and maintenance history
- Data quality, missing data and bad sensors
- Time synchronization and asset identity
Module 4: From Alarm Monitoring to Intelligent Operations
- Threshold alarms vs anomaly detection
- Correlating multiple symptoms
- Site baselines and peer comparison
- False alarms and alarm storms
- Remote diagnosis and site-visit reduction
Module 5: AI for Battery Health and Backup Assurance
- VRLA ageing and failure indicators
- Lithium-ion BMS telemetry
- SOC, SOH and remaining-useful-life concepts
- Backup-time prediction
- Abnormal string/cell detection
- Thermal risk and charging behaviour
Module 6: Rectifier and DC Plant Analytics
- Rectifier efficiency and load sharing
- Module degradation and abnormal behaviour
- Capacity headroom and N+1 risk
- DC distribution and branch-load visibility
- Predicting overload and capacity shortfall
Module 7: Generator and Fuel Analytics
- Start-failure patterns
- Runtime and maintenance prediction
- Fuel-consumption baselines
- Fuel-loss / theft anomaly indicators
- Generator loading and inefficient operation
- DG maintenance prioritization
Module 8: Exercise – Power Failure Root-Cause Analysis
- Interpret multi-source site telemetry
- Separate symptom from root cause
- Rank sites by operational risk
- Recommend remote action vs field visit
Module 9: Load and Energy Forecasting for Telecom Sites
- Traffic growth translated into power demand
- 5G expansion and power-capacity impact
- Short-term and seasonal load forecasting
- Peak-demand prediction
- Capacity planning with uncertainty
- Forecast error and engineering margins
Module 10: AI for Hybrid Energy Optimization
- Grid, battery, solar and DG operating modes
- Solar-production forecasting
- Battery charge/discharge scheduling
- Peak staggering / peak shaving concepts
- Reducing DG runtime and fuel cost
- Tariff-aware operating strategies
Module 11: Renewable Energy and Energy Storage
- PV performance monitoring
- Battery energy storage in telecom
- Weather-informed energy planning
- Renewable utilization vs backup reserve
- Hybrid-site resilience constraints
Module 12: Commercial Solution Case – iIntelligent Site Management System
- AI-based peak staggering
- Grid-solar-battery intelligent scheduling
- Remote battery testing and SOH management
- Remote DG management and fault diagnosis
- Risk forecast and proactive management
Module 13: Fleet-Level Power Operations and Remote O&M
- Single-site vs fleet analytics
- Site clustering and benchmarking
- Critical-site prioritization
- Remote diagnosis and dispatch optimization
- SLA, availability and energy KPIs
Module 14: Commercial Solution Case – Intelligent DC Power System
- -48 VDC telecom power applications
- Battery and AC service monitoring
- Site monitoring and configuration management
- Remote access using Ethernet / SNMP / Modbus
- Individual load / branch current visibility
Module 15: Commercial Solution Case – Site Energy Orchestration
- AI/ML-assisted site energy management
- Coordinating large fleets of sites
- Energy-cost visibility and control
- Policy-based energy operation
- Virtual-power-plant concept where market rules permit
Module 16: Predictive Maintenance Workflow
- Asset health score concepts
- Failure probability vs consequence
- Risk-based maintenance priority
- Work-order and field-team integration
- Measuring avoided failures and truck rolls
Module 17: AI Governance, Cybersecurity and Safety
- OT / power-system cybersecurity
- Secure remote access
- Data ownership and vendor access
- Model drift and incorrect recommendations
- Fail-safe control and manual override
- Audit trail and change management
Module 18: Business Case and KPI Framework
- Energy OPEX per site
- DG fuel and runtime reduction
- Battery replacement optimization
- Truck-roll and MTTR reduction
- Availability and backup assurance
- CAPEX vs OPEX and lifecycle value
Module 19: AI Adoption Roadmap for Telecom Power Teams
- Assess current telemetry and monitoring maturity
- Select high-value use cases
- Pilot-site selection
- Baseline KPIs before AI deployment
- Integration with NOC / EMS / field O&M
- Scale from pilot to network-wide operation
Module 20: Capstone – Intelligent Telecom Power Operations
- Analyze a mixed portfolio of grid, DG and hybrid sites
- Identify data gaps and instrumentation needs
- Select AI use cases by value and risk
- Define alarms, predictions and operator actions
- Choose relevant market-available solution capabilities
- Build a phased implementation roadmap
Module 21: Solution Evaluation Checklist
- Operational problem solved
- Required sensors and data
- Integration protocols and APIs
- Battery / rectifier / DG compatibility
- Cybersecurity and access control
- Local support and lifecycle considerations
- KPI and ROI verification
TRAINING/WORKSHOP | DURATION | TRAINING DATE | LOCATION |
AI in Telecom Power Engineering: Intelligent Energy & Power Operations | 5 Days | 16 - 20 November 2026 | Singapore |
OUR HAPPY CLIENTS
WHAT OUR CLIENTS SAY ABOUT TELECONTRAN !!
The workshop enhanced my knowledge about solar power calculations, power consumption, earthing, different ways of power outage, lightning foundation, surge protection etc.
Covering overall power plant system used in Telecommunication as well the planning and processing of the power system, I must say the course was very much useful in learning about Telecom Power System
The material was very much inclusive and comprehensive along with detail discussion on Solar/Wind power system, Generator operations and maintenance, UPS etc.
This course has given me more insight on 5G network as a whole, from introduction to Smart Cities. The presentation was well outlined and learning objectives were successfully completed.
This course covered most of the basis of Data Centre infrastructure, specially deigning and maintaining the data centre.
