Optimization Design Model of Heliostat Field Based on Simulated Annealing Algorithm

This paper presents an optimization model for the design of a heliostat field in a solar thermal power tower plant. The model aims to maximize the annual average power output per unit heliostat area under constraints including optical efficiency, tower height, and heliostat spacing. An accurate optical efficiency calculation model is established considering factors like cosine loss, shadowing loss, atmospheric transmittance, and receiver interception efficiency. Monte Carlo ray tracing simulates the light propagation to compute the efficiency. The initial heliostat layout follows the Campo circular staggered pattern. The optimization uses a simulated annealing algorithm to search the optimal heliostat size, height and positions by iteratively perturbing the decision variables. Three cases are studied: 1) fixed heliostat parameters, 2) variable size and height, and 3) variable parameters in each ring. Results show the model effectively improves the optical efficiency and power output. The application of stochastic optimization algorithms enhances the heliostat field design. Future work will focus on incorporating economic factors and ground terrain into a multi-objective optimization framework.