鉄道インフラにおける効率的なエネルギー管理
Railway infrastructure managers are often among the largest consumers of electrical energy in their countries. They also procure energy and re-invoice operators making real-time visibility, reliability, billing accuracy, and consumption optimization critical to efficient operations
Connecting field devices, operational data, and energy intelligence creates a live view of the railway network so energy can be managed where and when it matters.
Smart meters and IoT capture electrical data across the network for real-time monitoring and operational action
Train energy use and braking data support the reuse of regenerative energy or its storage in batteries
Modeling identifies feasible nodes for renewable self-consumption and supports evaluation of energy and ROI scenarios
Traction, overload, oscillation, and train-frequency analysis help improve network performance and energy consumption
NTTデータのサポート体制は？
Connect smart meters, electrical devices, IoT, edge computing, and cloud infrastructure to collect and process energy data across the network
Simulate traction, train frequency, overloads, oscillations, green-time energy, and renewable scenarios before decisions reach the field
We don’t collect data and stop there. We turn it into live information that helps technicians respond to energy alerts and incidents.
Identify feasible renewable-energy nodes for self-consumption and evaluate production, consumption, energy balance, and ROI scenarios
Apply NTT DATA’s Railway Smart Grid methodology and technical approach to structure energy-efficiency management from field devices through business processes
The solution moves customer engagement from individual transactions toward an ongoing digital relationship supported by a broader mobility-services ecosystem
Real-time information across network nodes supports faster, better-grounded operational decisions
Centralized monitoring enables immediate incident management and helps improve network reliability
Energy-saving scenarios and traction optimization target more efficient use of electrical energy across the railway network
Scenario modeling evaluates renewable self-consumption opportunities and their potential ROI before investment decisions
Unlock real-time intelligence to reduce waste, optimize traction, and improve railway performance at scale→
