In the technological framework of advanced engineering solutions for power cycle evaluation, which CADE has been developing since 2012, CADE submitted the project “CADEi-0014-InCycle” to the 2018 call of the JCCM’s program Innova-Adelante .
The project consists of developing a new power cycle analysis methodology (InCycle) for concentrated solar plants. This innovative methodology integrates all key aspects of steam generation technology: process analysis, mechanical analysis, water quality, equipment reliability and maintenance.
Current problems of concentrated solar plants are usually related to the use of equipment that has been in operation for more than 10 years, conditioned by previous repairs, loss of efficiency and deviations between the initial designed conditions and the real operating conditions.
In addition, concentrated solar plants are mechanically conditioned by the actual operation of its power cycles, which involves daily startup/shutdown cycling operations and fosters main equipment fouling and corrosion. For these reasons, a new approach is necessary to attack the operation and maintenance activities of concentrated solar plants.
‘InCycle’ methodology allows to systematically and specifically address the condition of concentrated solar plants and its key factors, in order to improve their efficiency, increase their service life, and reduce regular failures and shutdowns for maintenance.
Main aspects of InCyle Methodology
- Key points identification at the plant to acquire information: critical node.
- Data evaluation in critical nodes to check its veracity and reliability.
- Plant data collection in critical nodes.
- Equipment characterization: based on actual plant data.
- Generation of equivalent models (thermal, hydraulic and mechanical).
- Integrated optimization of the cycle: improving its performance and reducing mechanical damages and maintenance operations. Increase in efficiency and life cycle.
- Optimization of the monitoring system and the sampling of the water-steam system. Reliability to make decisions.
- Equipment inspection and sample gathering. Dynamic models of corrosion and fouling.
- Prediction of performance and needs of preventive maintenance.
- Plant improvements.
Project challenges and purpose
- To improve the cycle performance, with a consequent increase in its efficiency.
- To reduce power generation costs.
- To increase the equipment service life.
- To reduce the number of stops for maintenance. Predictive Maintenance.
- To improve the current monitoring system: reliable data collection for decision making.
This project has been founded by the Spanish Castilla-La Mancha Community Council’s program Innova-Adelante, and co-funded by the European Development Fund.