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作 者:李红霞 张祥成 李芳 张海宁 李楠 马雪 LI Hongxia;ZHANG Xiangcheng;LI Fang;ZHANG Haining;LI Nan;MA Xue(Green Energy Development Research Institute,State Grid Qinghai Electric Power Company,Xining 810008,China)
机构地区:[1]国网青海省电力公司清洁能源发展研究院,青海西宁810008
出 处:《中国电力》2021年第7期1-10,26,共11页Electric Power
基 金:国家自然科学基金资助项目(我国减少清洁能源发电弃能的机制设计及其模拟模型研究,71573084)。
摘 要:2018年青海省获批建设国家清洁能源示范省并于同年提出《青海省建设国家清洁能源示范省工作方案(2018-2020年)》,以绿色、高效和安全为总目标,推进能源生产和消费革命,为中国能源清洁转型与现代能源体系建设贡献力量。在清洁能源示范省建设背景下,开展青海能源需求预测及清洁化发展对策研究。首先,分析青海省清洁能源发展现状以及面临的挑战;然后,通过双变异差分进化算法优化BP神经网络预测模型,建立DMDE-BPNN混合预测模型;分析青海省典型水平年能源需求预测结果,探讨青海省能源清洁化发展对策。In 2018,Qinghai Province was approved to build the National Clean Energy Demonstration Province and proposed the"Qinghai Province National Clean Energy Demonstration Province Work Plan(2018-2020)"in the same year.The work plan takes the greennesss,high efficiency and safety as the overall goal,and promotes the revolution in energy production and consumption,so as to make a contribution to the clean transition of China’s energy and the construction of a modern energy system.Under this background,a study is made on the Qinghai energy demand forecasting and clean development strategy under the background of clean energy demonstration province construction.Firstly,the paper analyzes the current status and challenges of clean energy development in Qinghai Province.Then,a DMDE-BPNN hybrid prediction model is established by optimizing the BP neural network prediction model with the double mutation differential evolution algorithm.By taking Qinghai Province as an example,the annual energy demand in typical years is forecasted,and some measures are proposed for the development of clean energy in Qinghai Province.
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