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<正>本文围绕储能专业人才培养,提出了建立完整的《储能科学与工程》课程知识体系、加强专业技能与全面应用分析能力的培养等建议,探索了该课程的建设路径,为储能专业人才的高质量培养提供参考。储能技术是能源技术领域的重要创新方向之一,其贯穿于新能源开发与利用的全部环节,是能源转换与缓冲、调峰与提效、传输与调度、管理与运用的核心技术。由于新能源的波动性、间歇性等特点,储能在构建以新能源为主体的新型电力系统过程中发挥着重要作用。在“双碳”目标实现过程中,“新能源+储能”的开发利用成为主要途径之一。面对储能专业人才的巨大缺口, 相似文献
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The recycle fluidization roasting in alumina production was studied and a temperature forecast model was established based on wavelet neural network that had a momentum item and an adjustable learning rate. By analyzing the roasting process, coal gas flux, aluminium hydroxide feeding and oxygen content were ascertained as the main parameters for the forecast model. The order and delay time of each parameter in the model were deduced by F test method. With 400 groups of sample data (sampled with the period of 1.5 min) for its training, a wavelet neural network model was acquired that had a structure of {7^-21^-1}, i.e., seven nodes in the input layer, twenty-one nodes in the hidden layer and one node in the output layer. Testing on the prediction accuracy of the model shows that as the absolute error ±5.0 ℃ is adopted, the single-step prediction accuracy can achieve 90% and within 6 steps the multi-step forecast result of model for temperature is receivable. 相似文献
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针对氧化铝悬浮焙烧能耗信息表征和模型应用的实际需求,建立一种最小二乘支持向量机(LS-SVM)能耗估计模型。基于该类模型结合遗传算法(GA)提出一种模型参数优化和工业应用策略。采用灰关联分析确定模型的主输入为主炉温度、烟气含氧量、原料含水量;采用K折交叉验证优化样本数据;采用比较模型预测误差确定核函数为径向基函数(RBF)核。建立输入为能耗参数,输出为模型标志的支持向量机工况模型选择器。能耗估计模型的自学习与动态优化通过样本的更新和聚类实现,模型的选择和投运通过模型选择器依据工况状态实施切换。实验结果表明,建立的焙烧能耗估计模型和模型应用策略,能提高模型的泛化能力、增强模型的工况适应性,是一种有效的焙烧能耗参数估计和分析方法。 相似文献