基于遗传算法的钢筋混凝土吸热塔优化研究

Research on optimization of reinforced concrete solar tower based on genetic algorithm

太阳能是目前开发潜力最大但已开发比例最低的可再生能源,开发与利用太阳能已成为世界各国的经济发展战略。塔式光热电站是太阳能发电站的一种,吸热塔是发电站的核心建筑物之一。由于国内外没有专门对吸热塔塔架的设计规范和标准,且可供参考的设计经验较少,因此吸热塔的设计方法和经济性能亟待研究和改善。综合考虑各因素对塔架成本的影响,以钢筋混凝土吸热塔的结构参数为优化变量,以相关规范和行业标准的设计要求为约束条件,以总成本为目标函数,建立了基于遗传算法的优化设计Python模块,对某高度为230m、额定发电功率为100MW的塔式光热电站钢筋混凝土吸热塔塔架进行优化设计。通过优化前后成本、承载力等计算结果的对比,验证了该优化方法能满足设计要求而且能有效降低成本,提高结构设计的经济性。

At present,solar energy is one renewable energy with the most development potential but the lowest exploitation proportion.The development and utilization of solar energy has become the economic development strategy around the world.The tower-type concentrated solar thermal power plant,in which the tower is one core building of the power plant,is one kind of solar power plants.So far there are no design codes and standards of solar towers at home and abroad,and structural engineers have little-to-no relevant design experiences for reference.Therefore,the improvement of design method and the optimization of economic performance for solar tower remains an urgent issue.In this paper,considering the influence of various factors on the total cost of the solar tower,the Python optimization module is developed based on genetic algorithm,in which structural parameters are taken as optimization variables and the design requirements of relevant codes and standards are taken as the constraints.The total cost of the solar tower is taken as the objective function of the optimization module.A 230 m concrete tower for 100 MW concentrating solar power plant is taken as an example to carry out the structural optimization.By comparing the total costs and bearing capacities before and after optimization,it can be found that the optimal design method can not only meet the design requirements,but also reduce the total cost and improve the economy.