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作 者:刘昌 朱小林[1] 满奕[1,2] 何正磊 LIU Chang;ZHU Xiaolin;MAN Yi;HE Zhenglei(State Key Lab of Pulp and Paper Engineering,South China University of Technology,Guangzhou,Guangdong Province,510640;Guangdong Artificial Intelligence and Digital Economy Lab(Guangzhou),Guangzhou,Guangdong Province,510335)
机构地区:[1]华南理工大学制浆造纸工程国家重点实验室,广东广州510640 [2]人工智能与数字经济广东省实验室(广州),广东广州510335
出 处:《中国造纸》2023年第12期158-168,共11页China Pulp & Paper
基 金:人工智能与数字经济广东省实验室(广州)青年学者项目(PLZ2021KF0019)。
摘 要:本课题提出了一种多种能源协同互补的调度方法,以提高风电与光伏发电消纳水平,促进造纸园区节能降碳。本方法在造纸园区全年用能负荷的基础上,利用机器学习技术建立了代表全年用能负荷情况的特征日获取模型;基于综合经济成本和与环境成本,建立了风-光-热-电-储协同的多能调度模型。在多个典型场景下,对模型运行结果进行验证发现,本方法可在保证用能需求的前提下,有效提升造纸园区功能系统的低碳化水平。A dispatching method of multi-energy synergies and complementarity was put forward in this paper,to improve the consumption level of wind power and photovoltaic,and promote the energy saving and carbon reduction of papermaking park.Firstly,based on the annu-al energy consumption of papermaking park,a characteristic daily acquisition model representing the annual energy consumption was estab-lished by machine learning technology.Secondly,for a combination of economic and environmental cost,a multi-energy scheduling model of wind,light,heat,electricity,and storage was established.Through the verification of model operation results in several typical scenes,it was found that the proposed complementary dispatching model method could effectively improve the low carbonization level of functional sys-tem in papermaking park under the premise of ensuring the energy demand.
分 类 号:TS7[轻工技术与工程—制浆造纸工程]
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