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为找到汽轮机变工况运行时的最优初压,利用改进的磷虾群算法(A-KH)和快速学习网(FLN)建立热耗率预测模型,然后利用A-KH算法的全局搜索能力,在可行的压力区间内对所建模型热耗率最低时对应的主蒸汽压力进行寻优,并将优化后的最优初压曲线与厂家设计压力曲线进行对比.结果表明:优化后的最优初压曲线能有效降低汽轮机组的热耗率,对汽轮机的安全经济运行更具有指导意义.
In order to find the optimum initial pressure of the steam turbine under variable working conditions, the heat consumption prediction model was established by using improved Krine Group Algorithm (A-KH) and Fast Learning Network (FLN), and then the global search ability of A-KH algorithm , The main steam pressure corresponding to the model with the lowest heat rate was found to be optimal in the feasible pressure range and the optimized optimal initial pressure curve was compared with the design pressure curve of the manufacturer.The results showed that the optimized The optimal initial pressure curve can effectively reduce the heat rate of the steam turbine, which is more instructive for the safe and economical operation of the steam turbine.