集成多能系统的建模:驱动因素、需求和机会

P. Mancarella, G. Andersson, J. Lopes, K. Bell
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引用次数: 78

摘要

越来越多的人认识到,现有电力使用的脱碳只是“故事的一部分”,需要更密切地关注供热、制冷和运输领域的能源需求,以及满足最终用途需求的所有能源载体和基础设施。在这方面,诸如“多能源系统”(MES)之类的概念已经提出,并且正在获得越来越大的动力,其目的是确定如何将传统上在独立孤岛中运行、规划和监管的多个能源系统整合起来,以提高其整体技术、经济和环境绩效。本文解决了MES建模的需求,该建模能够评估不同部门之间的相互作用以及它们所关注的能源向量,从而揭示能源系统集成带来的好处和潜在的不可预见或不希望看到的缺点。讨论了MES建模的驱动因素和不同模型用户的需求,以及这种建模的一些实用性,包括在空间和时间维度方面做出的选择,这些模型可能用于量化的内容,以及如何用数学方法构建它们。提供了现有MES模型和工具及其功能的示例,以及作者在自己的研究中使用这些模型的研究示例,以说明所讨论的一般概念。最后,总结了挑战、机遇和建议,以便建模人员参与开发处理MES复杂性所需的一系列新的分析能力。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Modelling of integrated multi-energy systems: Drivers, requirements, and opportunities
There is growing recognition that decarbonisation of existing uses of electricity is only `part of the story' and that closer attention needs to be given to demand for energy in heating or cooling and in transport, and to all the energy vectors and infrastructures that supply the end-use demand. In this respect, concepts such as `multi-energy systems' (MES) have been put forward and are gaining increasing momentum, with the aim of identifying how multiple energy systems that have been traditionally operated, planned and regulated in independent silos can be integrated to improve their collective technical, economic, and environmental performance. This paper addresses the need for modelling of MES which is capable of assessing interactions between different sectors and the energy vectors they are concerned with, so as to bring out the benefits and potential unforeseen or undesired drawbacks arising from energy systems integration. Drivers for MES modelling and the needs of different users of models are discussed, along with some of the practicalities of such modelling, including the choices to be made in respect of spatial and temporal dimensions, what these models might be used to quantify, and how they may be framed mathematically. Examples of existing MES models and tools and their capabilities, as well as of studies in which such models have been used in the authors' own research, are provided to illustrate the general concepts discussed. Finally, challenges, opportunities and recommendations are summarised for the engagement of modellers in developing a new range of analytical capabilities that are needed to deal with the complexity of MES.
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