Design of heliostat fields using a multi-objective evolutionary algorithm

The paper discusses the interest of the multi-objective optimization approaches for the design of complex energy systems and the basics of the original evolutionary algorithm used. The specific problems linked to the design of the concentrators of solar tower power plants are then introduced to illustrate the objective of the work presented. The first analysis deals with the optimization of the x-y positioning of each of the 500 rectangular reflectors of an existing predesigned field. In spite of the large number of variables (1000) the algorithm successfully calculated an optimum positioning of each concentrators and the main induced variations are shown. The second part of the paper describes a new program, which was made and coupled with the same algorithm to optimize the whole design in a two-objective approach (specific energy cost versus investment cost). The main hypothesis made, to keep the number of variables within a reasonable domain, was to distribute identical reflectors along a set of concentric ellipses around the tower. The interest of the method is illustrated for one given period with the Pareto curve showing all the optimum solutions (lowest specific energy cost at any given investment). The investment cost includes the cost of the heliostats themselves, the cost of land, the cost of the tower, etc. Variables include the x-y positioning, the height of the support and the dimensions of each rectangular reflectors as well as the height of the tower and the number of reflectors. These decision variables being given for each solution, the extracted energy is calculated by a program of CIEMAT [Sanchez, Romero, 2003]. Details of the design parameters are illustrated for selected optima along the Pareto curve References M. Sanchez, M. Romero Optimisation of heliostat field layout in central receiver systems based on yearly normalized energy surfaces. ISES, 2003, Goteborg