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Dynamics of long-term electricity demand profile: Insights from the analysis of Swiss energy systems

机译:长期电力需求的动态剖面:瑞士能源系统分析的见解

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Electrification becomes the most cost effective option to decarbonise the energy system by integrating large share of intermittent renewable energy sources. Numerous analytical tools/methods have been developed for analysing long-term electricity supply by incorporating advanced features. In almost all analyses, historical load profile has been assumed for the future electricity demands, i.e., load profile is linearly extrapolated or interpolated with respect to the change in annual electricity demands. This approach undermines the implication of emerging electrification such as e-mobility. New methods have been explored to generate future load curves. A limitation of such methods is that they ignore the interdependency between electricity supply and demands. Energy system approaches have advantages of determining the electricity demands endogenously and often have limited temporal representation to deal with infra-annual variability. This limitation has been widely addressed by introducing higher level of intra-annual time slices. Using a set of exemplary Swiss energy scenarios from the Swiss TIMES energy systems model with an hourly time resolution, this paper aims to showcase 'how can the electricity load profile evolve under different boundary conditions' and 'how can electricity supply influence the choice of end use technology'. The scenario analyses show that for changes in the annual electricity demands of - 3% to + 38% in 2050 relative to 2010 levels, the corresponding changes in winter peak are between - 30% and + 30% whereas summer peak consistently increase by 2%-23%. Summer peak is more pronounced due to growing air-conditioning demands whereas winter peak depends on emerging electrification requirements for heating and mobility.
机译:通过整合大量的间歇可再生能源来脱碳,电气化成为最具成本效益的选择。已经开发了许多分析工具/方法,用于通过纳入先进的功能来分析长期电力供应。在几乎所有分析中,已经假设了未来电力需求的历史载荷曲线,即负载型材是线性推断或在年电力需求的变化方面的线性推断或插值。该方法破坏了新兴电气化的含义,例如电子移动性。已探索新方法以生成未来的负载曲线。对这些方法的限制是它们忽略了电力供需之间的相互依赖性。能源系统方法具有确定内源性需求的优点,并且通常具有有限的时间表示,以应对红外线变异性。通过引入较高水平的年内时间片来广泛解决了这种限制。使用一组示例性瑞士能源方案,具有每小时分辨率的瑞士时报能源系统模型,本文旨在展示“电力负荷概况如何在不同的边界条件下发出,并且电力供应如何影响结束的选择使用技术'。情景分析表明,对于2050年的每年电力需求的变化相对于2010年,冬季峰值的相应变化介于 - 30%和+ 30%,而夏季峰始终如一增加2% -23%。由于不断增长的空调需求,夏季峰更加明显,而冬季峰值取决于采暖和移动性的新兴电气化要求。

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