With photovoltaic (PV) systems proliferating in the last few years due to the high prices of fossil fuels and pollution issues, among others, it is extremely important to monitor the efficiency of these plants and optimize the energy production process. This will also result in improvements related to the maintenance and security of the installation. In order to do so, the main parameters in the plant must be continuously monitored so that the appropriate actions can be carried out. This monitoring should not only be carried out at a global level, but also at panel-level, so that a better understanding of what is actually happening in the PV plant can be obtained. This paper presents a system based on a wireless sensor network (WSN) that includes all the components required for such monitoring as well as a power supply obtaining the energy required by the sensors from the photovoltaic panels. The system proposed succeeds in identifying all the nodes in the network and provides real-time monitoring while tracking efficiency, features, failures and weaknesses from a single cell up to the whole infrastructure. Thus, the decision-making process is simplified, which contributes to reducing failures, wastes and, consequently, costs.

Parabolic trough solar power plants use a thermal fluid to transfer thermal energy from solar radiation to a water-steam Rankine cycle in order to drive a turbine that, coupled to an electrical generator, produces electricity. These plants have a heat transfer fluid (HTF) system with the necessary elements to transform solar radiation into heat and to transfer that thermal energy to the water-steam exchangers. In order to get the best possible performance in the Rankine cycle and, hence, in the thermal plant, it is necessary that the thermal fluid reach its maximum temperature when leaving the solar field (SF). Also, it is mandatory that the thermal fluid does not exceed the maximum operating temperature of the HTF, above which it degrades. It must be noted that the optimal temperature of the thermal fluid is difficult to obtain, since solar radiation can change abruptly from one moment to another. The aim of this document is to provide a model of an HTF system that can be used to optimize the control of the temperature of the fluid without interfering with the normal operation of the plant. The results obtained with this model will be contrasted with those obtained in a real plant.

Many thermal solar power plants use thermal oil as heat transfer fluid, and molten salts as thermal energy storage. Oil absorbs energy from sun light, and transfers it to a water-steam cycle across heat exchangers, to be converted into electric energy by means of a turbogenerator, or to be stored in a thermal energy storage system so that it can be later transferred to the water-steam cycle. The complexity of these thermal solar plants is rather high, as they combine traditional engineering used in power stations (water-steam cycle) or petrochemical (oil piping), with the new solar (parabolic trough collector) and heat storage (molten salts) technologies. With the engineering of these plants being relatively new, regulation of the thermal energy storage system is currently achieved in manual or semiautomatic ways, controlling its variables with proportional-integral-derivative (PID) regulators. This makes the overall performance of these plants non optimal. This work focuses on energy storage systems based on molten salt, and defines a complete model of the process. By defining such a model, the ground for future research into optimal control methods will be established. The accuracy of the model will be determined by comparing the results it provides and those measured in the molten-salt heat storage system of an actual power plant.

Capacitive deionization (CDI) is becoming a suitable alternative for desalination. The low cost of the material required for it and the lower energy consumption can be two critical factors for the development of this technology. CDI technology does not require a high-pressure system or specific membranes to operate. The energy storage capability of CDI cells allows most of the stored energy to be recovered and used in other CDI cells. The aim of the power stage in charge of the energy recovery is to transfer the stored energy from one cell to another with the maximum possible efficiency to continue with the desalination process. With this goal this paper shows a new control strategy, in which the evolution of the current follows the efficiency of the converter. This new control improves the efficiency behavior of the converter as well as the energy recovery. The CDI modules have been electrically modeled and their electrical parameters have been defined according to the geometrical characteristics of the module. This allows the optimum geometrical parameters to be specified in order to optimize the energy storing process. A mathematical algorithm developed allows an easy simulation of the converter behavior with large input and output capacitors.