White Paper Autonomous Power Plant​

ABSTRACT

In the power generation business today, power producers are operating in uncertain times, as traditional operating models are upended by new sources of energy, particularly from wind & solar power and due to their cyclic and unpredictable nature of power generation. The situation is aggravated because of the energy crisis in Europe, as volatile fuel prices will eventually encourage expanded renewable power and the need for more efficient thermal power generation. The electricity markets are demanding a different behaviour from power plants, requiring more flexibility to compete with or back up intermittent renewables.

These new scenarios are simply not addressable with only manual interventions, or with conventional control tools. They show a lack of speed, accuracy, and stability when driving the plant under the dynamic requirements of the System Operator. What the market needs today is an Autonomous Power Plant!

Autonomous power plants link technology, data, and advanced visualizations with operations to ensure they deliver the desired process outputs, and learn from each action taken, historical data, and derived insights. On the one hand, sensing and optimization of the processes are boosted by tools such as AI, IoT, Digital Twin, and Machine Learning. On the other hand, Self-tuning Control Systems are continually, and in real-time, driving processes to optimal setpoints in a desired, fast, precise, and stable way with no human intervention. These elements are jointly increasing the autonomous skills of the plant.

Electricity demand is steadily growing on a global basis. We need more electricity but generated in a different way. However, renewable generation may still suffer from long permitting times, subsidies in constant reduction, and difficulties to find good locations not already in used. This may delay part of the required investment in renewable sources giving an extra opportunity for thermal power plants which are adapted to the new context.