Digital Savings in the Pipeline Industry
From January through September 2026, Transneft-Privolga JSC, a subsidiary of Transneft PJSC, saved 346.3 metric tons of fuel equivalent, corresponding to 2.8 million kilowatt-hours of electricity. The savings resulted from a range of technical improvements, including digital monitoring systems for heating infrastructure.
Transneft-Privolga is continuously working to improve the energy efficiency of its production and administrative buildings and modernize its infrastructure. Alongside its regular preparations for the heating season, which include scheduled maintenance of heating networks, the company has made substantial investments in equipping individual heating substations with monitoring devices and automatic temperature control systems (ATCS).
An ATCS is a set of technical devices that adjusts the temperature of the heating medium to match outdoor weather conditions and a building's heating needs, without human intervention. The system consists of sensors, controllers and actuators. On average, its use can reduce thermal energy consumption by 15% to 30%. It is particularly effective during the shoulder seasons, when it prevents buildings from overheating. These digital technologies help the company cut operating costs while reducing emissions.
Transneft-Privolga has also brought its vehicle fleet under smart monitoring. Its vehicles and specialized equipment are fitted with GLONASS satellite navigation systems that track routes and monitor fuel consumption, generating additional savings.
Taken together, these upgrades deliver cumulative benefits. Smart automation and monitoring have become practical tools for reducing operating costs.
Digital Twins and Russian-Made Process Control Systems
Transneft's subsidiaries are not the only companies working to reduce energy costs. At the federal level, Russia has approved its Energy Strategy through 2050. The document calls for the widespread adoption of artificial intelligence, digital monitoring and platform-based technologies across the fuel and energy sector.
Energy efficiency is about more than saving on heating. Digital twins of oil pumping stations can combine models of power supply systems with models of the oil pumping process. This makes it possible not only to forecast potential emergencies but also to identify optimal equipment operating modes, reducing fuel and energy consumption.
The industry is continuing to modernize its facilities by switching to Russian-developed automated process control systems (APCS). Upgrading control systems at oil pumping stations makes it possible to introduce remote dispatching and monitoring of energy infrastructure.
Cumulative Savings From the Kama Region to the Upper Volga
A long-running energy conservation program is delivering substantial results across Transneft's subsidiaries. In 2022, Transneft-Prikamye reported saving 10.9 million kWh of electricity and 47 million rubles (about $570,000) through optimized pumping operations and heating system upgrades. In 2023, Transneft-Sever saved 2.2 million kWh and 181 metric tons of fuel equivalent. Transneft-Verkhnyaya Volga reported savings of 5.8 million kWh and 45 million rubles (about $550,000) in 2024.
The trend is clear: Transneft's subsidiaries are continually expanding their expertise and developing their capabilities in automation and energy management.
Where Energy Savings Meet Digital Transformation
Energy conservation across the fuel and energy sector is a complex technological challenge that requires action on several fronts at once. Network repairs go hand in hand with automatic controls and satellite-based monitoring. The economic benefits come from combining engineering improvements with digital technologies.
Further implementation of the energy strategy across the fuel and energy sector will also create new opportunities for the IT industry. Demand is expected to grow for industrial software, digital twin development, automated process control systems, energy optimization tools and telemetry systems. Over time, managing the sector's complex infrastructure will increasingly rely not only on automation but also on artificial intelligence algorithms.
