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Qatar Power

Qatar Power improves the efficiency of its power plants with AVEVA PI System

Qatar Power, an independent power and water producer in the State of Qatar, must simultaneously improve the efficiency and safety of its plants in the face of major challenges: global warming, extreme climate-driven demand fluctuations and sustained population growth. Rising fuel and seawater costs, the lack of available historical data and the gradual erosion of plant efficiency called for a structured response, including heat stress monitoring to prevent health, safety and environmental incidents. Deploying AVEVA PI System, complemented by AVEVA PI Server and AVEVA PI Vision, transformed operational performance. The operator saved $1.3 million on seawater margins, improved energy efficiency by 10% to generate $1.4 million in annual savings, and strengthened worker safety. Qatar Power now has a data infrastructure aligned with the demands of a particularly challenging environment.

Objectives

  • Meeting health and safety goals
  • Meeting the demand for electricity and water
  • Maintain higher factory capacity

Solutions

  • AVEVA PI System
  • AVEVA PI Server
  • AVEVA PI Vision

Results

  • $1.3 million in savings on seawater margins
  • 10% improvement in energy efficiency, saving $1.4 million in one year
  • Improved worker safety

Testimonials

"At Qatar Power, we use this PI system not only for operation but also for maintenance and for the well-being of people who work in extreme conditions."
Parshu Borkar
Senior Commercial and Performance Engineer, Qatar Power

FAQ

How does AVEVA PI System help Qatar Power balance efficiency and safety in an extreme climate?
Qatar Power, an independent power and water producer, faces combined challenges: global warming, extreme fluctuations in demand and population growth. AVEVA PI System, complemented by PI Server and PI Vision, structures the collection and use of operational data. It integrates heat stress monitoring to prevent HSE incidents and improve worker safety. The platform turns operations constrained by extreme conditions into operations governed by real-time data.
What financial gains has AVEVA PI System generated for Qatar Power?
Qatar Power saved $1.3 million on seawater margins and improved its energy efficiency by 10%, generating $1.4 million in annual savings. These gains come from the optimized use of operational data made possible by AVEVA PI System, PI Server and PI Vision. With fuel and seawater costs rising, these cumulative savings significantly strengthen the competitiveness of a power and water operator in an environment with severe climatic constraints.
Why is AVEVA PI Vision essential for visualizing a power plant's performance?
AVEVA PI Vision gives Qatar Power's engineers and operators customizable real-time dashboards on critical indicators: energy efficiency, seawater consumption and equipment heat stress. This contextualized visualization speeds up decision-making, highlights optimization opportunities and democratizes access to data. It is an essential complement to the PI System foundation for turning raw data into actionable information every day.
How does AVEVA improve worker safety in an industrial environment with heat risks?
Heat stress monitoring is one of the use cases Qatar Power has deployed on AVEVA PI System. The platform correlates environmental data (temperature, humidity) with health and productivity indicators for field teams. This data-driven approach makes it possible to anticipate HSE risks, adapt staff rotations and meet regulatory obligations. It is an excellent example of how real-time data management can contribute directly to human safety in a demanding industrial sector.
How can a reliable data history be rebuilt at an older power plant?
Qatar Power initially had few historical data points, which limited analysis. AVEVA PI Server, combined with PI System, made it possible to set up structured, lasting data collection, gradually building a reference history. This foundation underpins continuous improvement: trend analysis, cross-unit benchmarks and detection of slow drift caused by equipment aging. It is an essential long-term investment for preserving industrial efficiency in power generation.