A New Aggregation Methodology for the HPP Health Index

Hydroelectric Power Plant (HPP) supports European Union Electric Power System flexibility with various services (regulation capability, fast frequency control, fast start/stop, fast generating to pumping modes transition, high ramping rate, inertia emulation, and fault ride-through capacity, among others). New technology solutions, such as variable speed, are being studied to provide further flexibility in the framework of the XFLEX project. However, these additional capabilities impose new challenges on HPP's Operations and Maintenance (O&M). This work aims to increase the HPP's availability under this new paradigm. Proper health indexes (HI) should reflect the machine degradation, which is a critical component in health monitoring, fault diagnosis, and remaining useful life prediction. We explore indicators related specifically to Hydraulic Machines, namely the mechanical efficiency and the discharge of run-of-river Kaplan turbines, to develop a model to calculate the HPP global health index as a measurement of the impact in the HPP condition of each selected operating point for the energy production. This work proposes using Data Envelopment Analysis (DEA) to analyse the weights when aggregating the indicators into a global health indicator. Analyzing the global HI improves the equipment's performance, leading to operating points with better power production.

Keywords: Health index, Hydroelectric power plant, Asset management, Data envelopment analysis.

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