李学军, 杨昌海, 王茗洋, 孙亚璐, 袁铁江. 基于系统动力学的新能源外送规模预测[J]. 高电压技术, 2025, 51(5): 2149-2159. DOI: 10.13336/j.1003-6520.hve.20240171
引用本文: 李学军, 杨昌海, 王茗洋, 孙亚璐, 袁铁江. 基于系统动力学的新能源外送规模预测[J]. 高电压技术, 2025, 51(5): 2149-2159. DOI: 10.13336/j.1003-6520.hve.20240171
LI Xuejun, YANG Changhai, WANG Mingyang, SUN Yalu, YUAN Tiejiang. New Energy Delivery Scale Prediction Based on System Dynamics[J]. High Voltage Engineering, 2025, 51(5): 2149-2159. DOI: 10.13336/j.1003-6520.hve.20240171
Citation: LI Xuejun, YANG Changhai, WANG Mingyang, SUN Yalu, YUAN Tiejiang. New Energy Delivery Scale Prediction Based on System Dynamics[J]. High Voltage Engineering, 2025, 51(5): 2149-2159. DOI: 10.13336/j.1003-6520.hve.20240171

基于系统动力学的新能源外送规模预测

New Energy Delivery Scale Prediction Based on System Dynamics

  • 摘要: 随着新型电力系统建设进程的推进,西北地区本地消纳能力不足问题凸显,综合考虑本地电力和氢能需求,构建了新能源外送消纳预测系统动力学模型。首先,从新能源发展潜力、各产业用电特性以及各领域用氢特性入手,将新能源外送预测系统划分为新能源、电力负荷和氢能负荷3个子系统,分别构建了涉及风电和光伏的新能源发展潜力预测模型,包括工业、电力、热力、交通4个领域的氢能负荷预测模型和涵盖第一产业、第二产业、第三产业、城乡生活用电的电力负荷预测模型;其次,理清3个子系统及与新能源外送规模之间的交互关系和反馈机制,形成了新能源外送预测系统动力学模型;最后,以甘肃地区为例,针对人力、投资、交通和氢储4种发展模式,开展影响新能源外送规模的情景分析。结果表明,人力导向型和投资导向型模式下2030年新能源外送规模提高83.9%和91.5%,交通需求和氢储需求驱动下2030年新能源外送规模降幅6.8%和12.2%。

     

    Abstract: With the advancement of the construction process of new power systems, the problem of insufficient local consumption capacity in the northwest region has become prominent. After considering the requirements of local power and hydrogen energy needs, a new energy external transmission and consumption prediction system dynamics model was constructed. First, starting from the development potential of new energy, the characteristics of electricity consumption in various industries, and the characteristics of hydrogen consumption in various fields, we divided the new energy outsourcing prediction system into three subsystems, namely, new energy, electric power load and hydrogen energy load, and constructed wind power and photovoltaic, respectively. New energy development potential prediction models include hydrogen energy load prediction models in the four fields of industry, electricity, heat, and transportation, and electric power load prediction models covering primary industry, secondary industry, tertiary industry, and urban and rural domestic electricity consumption. Secondly, the three subsystems and their interactive relationships and feedback mechanisms with the scale of new energy delivery were clarified, and a new energy delivery prediction system dynamics model was formed. Finally, taking the Gansu region as an example, we analyzed manpower, investment, transportation and hydrogen storage. Four development models are used to conduct scenario analysis that affects the scale of new energy delivery. The results show that, under the human-oriented and investment-oriented models, the scale of new energy delivery in 2030 will increase by 83.9% and 91.5%; moreover, driven by transportation demands and hydrogen storage demands, the scale of new energy delivery in 2030 will decrease by 6.8% and 12.2%.

     

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