Clustering strategies are becoming increasingly relevant to boost the scalability of
distributed control methods by focusing the cooperation efforts on highly coupled agents …

Due to the growing interest in 4th and 5th generation district heating systems, characterized
by lower working fluid temperatures compared to the past, poligenerative solar-assisted …

This paper presents a clustering-based model predictive controller for optimizing the heat
transfer fluid (HTF) flow rates circulating through every loop in solar parabolic trough plants …

In solar parabolic-trough plants, the use of Model Predictive Control (MPC) increases the
output thermal power. However, MPC has the disadvantage of a high computational …

The present work focuses on the development of a detailed dynamic model of an existing
parabolic trough solar power plant (PTSPP) in Spain. This work is the first attempt to analyse …

This article focuses on maximizing the thermal energy collected by parabolic-trough solar
collector fields to increase the production of the plant. To this end, we propose a market …

Parabolic-trough solar collector fields are large-scale systems, so the application of
centralized optimization-based control methods to these systems is often not suitable for real …

Fault detection is crucial for ensuring optimal operation and maintenance of solar plants.
This paper proposes a methodology for fault detection and isolation using artificial neural …

Abstract Concentrated Solar Power plants (CSP) have the energy storage capability to
generate electricity when sunlight is scarce. However, due to the highly non-linear dynamics …

This article considers a robotic sensor network that measures the loss of irradiance in a
thermosolar power plant due to moving clouds. To this end, a receding-horizon predictive …