Development and implementation of KPIs to optimize the asset management of wind and photovoltaic plants

The exponential growth of renewable energy plants increases the need for solutions to optimize asset management and, in this context, Key Performance Indicators (KPIs) play a significant role. This thesis focuses on the development and implementation of KPIs specifically designed for Wind and Photovoltaic plants. The study begins with an overview of the software Energy Studio Pro (ESP), which allows the creation, implementation and management of KPIs. Subsequently, the Operational and Maintenance (O&M) contracts for Wind and Photovoltaic plants are analysed to identify the indicators required to enhance asset management. In this work two types of indicators are developed for both Wind and PV plants: the first one related to the availability of the plants according to the O&M contract and the second one related to the performance of the plants themselves. These KPIs created and implemented on Energy Studio Pro, illustrate the behaviour and the performance of the renewable energy plants. Additionally, real-world scenarios of Wind and Photovoltaic plants are discussed, highlighting the fundamental role of KPIs in asset management. Furthermore, the thesis explores how artificial intelligence (AI) might be integrated with renewable energy plants, explaining how AI might empower asset management.