Model predictive control of largue scale solar trough plants

Abstract

One of the current technological challenges is to make solar energy economical and competitive. Advanced control techniques may contribute in this direction by maximizing the electricity generated by using optimal control strategies. A number of research works have been developed concerning control and optimization of solar plants. Most of these works have been developed for the experimental solar trough plant of ACUREX at the Plataforma solar de Almería (PSA) (10 parallel loops of collectors). Generally, small plants such as the ACUREX field can be modelled as an equivalent loop for developing control strategies. Commercial solar trough plants are very extensive, covering vast areas. As an example, Solana Generating Station which has 808 parallel loops of four collectors connected in series (3,232 collectors) covering 780 hectares. The optimization of large scale solar trough plants poses important challenges which require new advanced control techniques to address them: 1. The optical efficiency of different groups of loops may be substantially different in large scale solar plants. The most efficient loops will probably have to be defocused to avoid excessive temperatures. Paradoxically, the most efficient loops will have the higher energy losses because of defocusing. To avoid this energy loss, the valves of the most efficient loops would have to be opened to increase the HTF flow. However, any movement of the valve in one of the loops will influence the flow of the rest of the loops. Loop valves are only used in current plants for steady state flow balancing. 2. Scattered clouds may only affect the locations where the sensors are placed, while the rest of the plant may be under the effect of intense DNI, or vice versa. Sudden changes in DNI produced by scattered clouds induce oscillations so severe that the solar field may have to be defocused or shutdown. This fact produces, in general, not only energy losses but plant deterioration. A spatially distributed DNI nowcasting can be used to improve plant operation and optimize the production. This chapter presents some new concepts and ideas that the authors believe will be the future steps in the development and progress of solar thermal energy. Preliminary results for advanced control of solar plants are presented, using more effective defocusing mechanisms and dynamic thermal balance of loops that have already shown to produce significant gains,.