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Introduction

Asset Performance Management for Power Generation

Background

Market demands and regulatory surcharges that are designed to reduce the environmental impact of power generation have compelled Enel’s Global Power Generation business line (Enel GPG) to seek greater operational efficiencies. As it drowned in data, Enel GPG realized that turning that flow of information into operational decisions required a new approach to asset management.

“It takes more than software to transform our complex business. We also needed expertise, process optimization and implementation insights," says Claudio Macchia, Enel GPG Head of Hydro, Geothermal and Thermal Monitoring and Maintenance Scheduling.

Challenge

Competitive market forces created urgent need for cost reduction

The only way to stay competitive was to become more efficient. In Spain and Italy, strict pricing regulations aimed at reducing carbon emissions put further pressure on thermal generators to reduce costs as they accelerate their path to renewable energy.

As a mature business, Enel GPG had difficulty optimizing costs. The team had already designed and implemented asset maintenance best practices to keep equipment in optimal operating condition. However, these initiatives could only take the company so far. Indeed, by adopting an industrial Artificial Intelligence (AI) software with Machine Learning (ML) capabilities, Enel GPG can take the next revolutionary leap and anticipate equipment failure with much greater accuracy.

Solution

Predictive strategies anticipate failure to better align maintenance actions and improve uptime

Enel GPG envisioned a complete digitalization of routine processes. GE Digital's Asset Performance Management (APM) offered the expertise and technology needed to bring this vision to reality.

Transforming Enel GPG’s approach to asset management took a great deal of careful planning. Enel GPG, with the support of the GE team, executed initial tag mapping and model development.  Enel GPG then worked on fine tuning its blueprint and improving model quality.

Results

Forty-five catches avoided downtime and reduced costs

Today, the Enel GPG team can identify anomalies before they become alarms, leveraging real time data and advanced analytics to optimize operations.  In the last 27 months, 45 catches have resulted in about 750 GWh of avoided downtime and estimated cost avoidance of Euro 3M (USD 3.6M).

What’s next

Building on the success of the APM deployment, Enel GPG plans to roll out APM Strategy on Termini Imerese and La Casella power generating assets in Italy. APM Strategy’s risk-based approach will complement the health & reliability analytics already in place on the two sites.

By balancing risk, production goals, and resource investment, APM Strategy will allow Enel GPG to focus costs on the most critical assets—reducing maintenance and inventory costs, increasing availability and reliability, and moving away from reactive maintenance practices to a proactive approach.