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Electrification of transport and residential heating sectors in support of renewable penetration: Scenarios for the Italian energy system

机译:运输和住宅加热部门的电气化支持可再生渗透:意大利能源系统的情景

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The integration of significant shares of renewable energies poses remarkable issues related to the intermittent nature of these sources. Nonetheless, solutions in support of renewables integration exist and become particularly effective if conceived under a smart energy system perspective, to exploit potential synergies among different energy sectors. With this respect, shifting programmable consumption from fossil fuels to electricity represents one measure to exploit otherwise-curtailed renewable generation. In this study, the impact of electrification of both private transport and space heating is assessed for the Italian energy system with the help of EnergyPLAN software and quantified in terms of critical environmental and techno-economic indicators, evaluating to what extent increasing the electricity demand supports the development of renewables. Results confirm that both transport and heating electrification can lead to significant reductions in CO2 emissions, around 25-30% if pursued independently. However, smart charge allows managing transport electricity demand more flexibly than heating demand, which makes the former more effective than the latter in fostering an increased renewable penetration, unless additional technologies are deployed to enhance flexibility in the heating sector. A techno-economic optimisation identifies possible optimal scenarios capable to reduce emissions by up to 47% with an increase in annualised costs of 34%. (C) 2020 Elsevier Ltd. All rights reserved.
机译:可再生能源大量股份的整合构成了与这些来源间歇性质相关的显着问题。尽管如此,如果在智能能量系统的角度下构思,则存在支持可再生能源集成的解决方案,并在智能能源系统的角度下进行特别有效,以利用不同能源部门之间的潜在协同作用。为此,将化石燃料的可编程消耗转移到电力代表一个措施,以剥削另行缩减可再生的一代。在这项研究中,私人运输和空间加热电气化的影响是在能量平板软件的帮助下对意大利能源系统进行评估,并根据批判的环境和技术经济指标进行量化,评估在多大程度上增加了电力需求支持可再生能源的发展。结果证实,如果独立追求,运输和加热电气化均可导致二氧化碳排放量大减少约25-30%。然而,智能费用允许比加热需求更灵活地管理运输电力需求,这使得前者比培养可再生渗透率增加的后者更有效,除非部署了额外的技术,以提高加热部门的灵活性。技术经济优化识别可能的最佳情景,可将排放量减少47%,随着年化成本的增加34%。 (c)2020 elestvier有限公司保留所有权利。

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