Optimization Strategies for Heliostat Field Design Based on Enhanced Genetic Algorithm

As a novel clean energy technology with low carbon emissions, Concentrated Solar Power (CSP) with a power tower is of paramount importance to China’s sustainable development strategy. This paper addresses the optimization of heliostat fields in tower solar thermal power generation, a novel low-carbon and environment-friendly clean energy technology pivotal to China’s sustainable development strategy. The technical challenge of maximizing power generation efficiency through optimal heliostat field design is tackled by constructing a calculation model for the optical efficiency of heliostats. Through the application of stereographic projection geometry, the research delineates the intricate spatial interplay between the heliostat plane, the receiver tower and the sun, enabling refined model development. Utilizing an adaptive genetic algorithm enhanced by an elitist strategy, this paper successfully identifies the optimal adjustment strategies for various decision variables to maximize optical efficiency. This study culminates in achieving an annual average optical efficiency of 0.5784. This finding not only contributes to the efficiency optimization of solar thermal power generation but also offers a methodological advancement in the design and analysis of heliostat fields.