Optimization of the possible pathways for gradual energy system decarbonization
Optimization of the possible pathways for gradual energy system decarbonization
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DOI：
10.1016/j.renene.2022.05.005
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发表时间：
2022-05-19
期刊：
影响因子：
8.7
通讯作者：
Duic, Neven
中科院分区：
文献类型：
--
作者：
Herc, Luka;Pfeifer, Antun;Duic, Neven
欧盟和巴黎气候雅阁的其他签署国同意将全球变暖限制在比工业化前水平高2摄氏度的范围内。以前发表的研究已经研究了满足碳中和最终目标所需的最佳能源系统结构。这项研究的重点是解决脱碳的中间步骤。这些步骤被量化为可再生能源的百分比份额。优化的目标是达到可再生能源和排放的预定水平，最小化可再生能源的削减，最小化系统成本，并限制能源部门中生物质等自然资源的使用。在优化过程中考虑的技术是发电能力，需求响应技术和能源储存。这种方法的结果反映了所考虑的技术的使用，并显示为可再生能源份额和二氧化碳排放水平的函数，这也代表了从2020年到2050年的脱碳时间轴。该方法是使用能源规划软件EnergyCast和高度修改的基于Python的优化软件EPLANopt进行的。研究结果表明，有必要继续实施可变发电容量以及需求响应技术，主要是车辆到电网。(c)2022作者由爱思唯尔有限公司出版。这是一篇开放获取的文章，使用CC BY许可证（http：//creativecommons.org/licenses/by/4.0/）。
The European Union and other signatories to the Paris Climate Accord have agreed to limit global warming to 2 degrees Celsius above pre-industrial levels. Previously published studies have examined the optimal energy system structure required to satisfy carbon neutrality end goals. This research focuses on addressing the intermediate steps towards decarbonization. The steps are quantified as the percentage share of renewable energy sources. The objective of the optimization is to reach a predetermined level of renewable energy and emissions, minimize curtailment of renewable energy sources, minimize system cost, and limit the use of natural resources such as biomass in the energy sector. Considered technologies in the optimization process are energy-generating capacities, demand response technologies, and energy storage. The results of such a method reflect the use of considered technologies and are displayed as a function of renewable energy share and carbon dioxide emissions level, which also represent the decarbonization timeline from 2020 to 2050. The method is carried out with the use of energy planning software EnergyPLAN and highly modified Python-based optimization software EPLANopt. The results presented in the research display the necessity for continuous implementation of variable generating capacities as well as demand response technologies, mainly vehicle to grid.(c) 2022 The Authors. Published by Elsevier Ltd. This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).