– Company: Enel Green Power
– Industry: hydroelectric power plants management
– Challenge: exploitation of big data analysis to optimize the hydroelectric power plants asset management, with efficiency improvement and O&M costs reduction
Background: 6 EGP hydro plants (5 in Italy, 1 in Spain)
The condition monitoring and monitoring data application in EGP hydro plants was mainly restricted to protection systems shutting down the plants when single monitoring signals exceeded predefined thresholds. Owner was facing a di¬fficult economic decision between overhaul and replacement: the ﬂeet of hydro power mechanical and electrical equipment was reaching its life expectancy. O&M practices such as regular inspections for cavitation damages on turbine blades, stator and rotor windings, bearings and excitation systems, are based on established guidelines and are generally carried out under a scheduled work program.
This situation needed the development of an optimized asset management strategy to improve security and maximize units availability: implementing remote operations at older facilities, installing a real-time asset monitoring system, adding on-site maintaining components to reduce break time and solutions to minimize O&M costs. i-EM had to work to reach efficiency improvement, reduction of production loss, failure anticipations and safety and sustainability increase.
Actions in detail: predictive maintenance savings, EGP data exploitation, maintenance developing data identification, potential value verification on what EGP found out in big data by defining KPI parameters of interest that can both drive action planning and de ne the actions to solve (e.g. Decision Support System).
Digitization implements sophisticated risk-based decision-making tools to optimize near-term O&M asset management plants to maintain, overhaul or replace the most critical fleets components. i-EM has developed, customized and trained advanced algorithms capable of performing deep and multivariate analysis on plants data, in order to allow EGP to take appropriate decisions and apply strategies to extract the achievable value by exploiting the information contained in data themselves.
Through the Big Data Hydro power architecture, data from operating plants are used to optimize their management and quickly identify potential malfunctions through the use of data analysis. Innovation goal is the value creation on RGC Hydroelectric ﬂeet by asset management optimization, generation efficiency improvement, O&M costs reduction and all based on plant data analysis. The potential value of available data in hydro power plants ﬂeet can be evaluated though indexes that are revenues, unbalances and cash costs, safety and sustainability. New interfaces were built to allow access to plant monitoring also from a tablet or any mobile device to facilitate the work of plant O&M operators.
BIG DATA ANALYSIS
– Dataset quality assessment to enhance data management chain robustness
– Innovative monitoring daily system running on 6 hydro power test plants
– Visualization system for the plants test raw data, effi¬ciencies and analytics results
– Notification service
– Existing assets modernization
– Advanced and digital condition monitoring
– Savings in O&M resource
– Hydro power and other renewable sources synergy improving