All the models mentioned in the previous sections can be used for daily planning of electricity production. As a simple example, a simulation experiment is shown in this section on applying the hierarchical daily production planning structure shown in Fig. 8.2. This application can use real data from the installation or a model of direct solar irradiance shown in Chap. 2, the hot oil storage system model briefly explained in Sect. 18.104.22.168, the distributed parameter model of the solar field explained in Chap. 4, Sect. 4.3.2, the optimizing reference governor explained in Chap. 5, Sect. 22.214.171.124, and the feedback linearization controller developed in Chap. 5, Sect. 5.8.1, to regulate the outlet temperature. In this way, different operation alternatives can be evaluated as a function of the state of the storage tank and the weather and thus it is possible to estimate the net electric power supplied to the network.
Figure 8.3 shows a simulation using real data of the field. Subindex ‘sim’ corresponds with the simulated trends. Depending on qT, the evolution of the thermo – clines of storage tank can be observed, as well as the net power Pr.
Basic concepts involved in the operational planning of solar plant with PTC have been treated in this chapter. Different levels of the hierarchical control problem involved have been defined within time scales of weekly planning, daily planning
Fig. 8.3 Simulation test of a hierarchical control scheme (courtesy of C. M. Cirre, )
and tracking. Many static and dynamic models are required to fulfill the operational planning objectives: solar irradiance, ambient temperature, market, electrical prices, costs, solar field, storage systems and power conversion systems. Both Committed and Non-committed production cases have been studied from an optimization viewpoint and several illustrative simulation results have been provided.
This is the amount of total energy that contains the extraterrestrial solar irradiance, integrated in
The frequency response corresponds to the system constituted by the feedforward studied in Sect. 4.4.1 in series with the plant.
If the feedforward analyzed in Sect. 4.4.1 is placed in series with the plant, the control signal will be the reference temperature to the feedforward controller.
a = 5.67 • 10-8 W/(m2 K4).