Energy and complexity: New ways forward
Energy and complexity: New ways forward
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DOI：
10.1016/j.apenergy.2014.10.057
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发表时间：
2015-01-15
期刊：
影响因子：
11.2
通讯作者：
Foxon, Timothy J.
中科院分区：
文献类型：
--
作者：
Bale, Catherine S. E.;Varga, Liz;Foxon, Timothy J.
本文综述了复杂性科学方法在理解能量系统和系统变化中的应用。转向可持续能源系统的挑战，提供安全，负担得起和低碳的能源服务，需要应用的方法，认识到能源系统的复杂性与社会，技术，经济和环境方面。能源系统由许多参与者组成，通过网络相互作用，导致涌现特性以及适应和学习过程。对这些类型的现象的见解已经在其他背景下通过复杂系统理论进行了研究。然而，这些见解只是最近才开始被应用于理解能源系统和系统transitions.The文章讨论的能源系统的方面（在技术，生态系统，用户，机构，商业模式），适合复杂性科学的应用及其涌现和共同进化的特点。复杂系统建模不同于标准（例如经济）建模，并提供超出传统模型的能力，但这些方法才刚刚开始实现其解决最关键能源挑战的全部潜力。特别是，在理解技术与行为之间的这些挑战方面，有很大的进步潜力。一些目前可用的计算方法进行审查：基于代理和网络建模。这些建模技术的优点和局限性进行了讨论。最后，本文认为，在最近的研究从复杂的系统能源建模的运输，能源行为和物理基础设施系统的新兴主题。虽然复杂性科学在能源领域的从业者并不很好地理解（并且往往难以沟通），但模型可以用于帮助国家和地方等多个层面的决策，并帮助理解和决策。因此，复杂性科学的技术和工具为理解实现低碳能源系统所需的复杂决策过程提供了强有力的手段。最后，我们对未来的研究和应用领域的建议。(C)2014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/3.0/）。
The purpose of this paper is to review the application of complexity science methods in understanding energy systems and system change. The challenge of moving to sustainable energy systems which provide secure, affordable and low-carbon energy services requires the application of methods which recognise the complexity of energy systems in relation to social, technological, economic and environmental aspects. Energy systems consist of many actors, interacting through networks, leading to emergent properties and adaptive and learning processes. Insights on these type of phenomena have been investigated in other contexts by complex systems theory. However, these insights are only recently beginning to be applied to understanding energy systems and systems transitions.The paper discusses the aspects of energy systems (in terms of technologies, ecosystems, users, institutions, business models) that lend themselves to the application of complexity science and its characteristics of emergence and coevolution. Complex-systems modelling differs from standard (e.g. economic) modelling and offers capabilities beyond those of conventional models, yet these methods are only beginning to realize anything like their full potential to address the most critical energy challenges. In particular there is significant potential for progress in understanding those challenges that reside at the interface of technology and behaviour. Some of the computational methods that are currently available are reviewed: agent-based and network modelling. The advantages and limitations of these modelling techniques are discussed.Finally, the paper considers the emerging themes of transport, energy behaviour and physical infrastructure systems in recent research from complex-systems energy modelling. Although complexity science is not well understood by practitioners in the energy domain (and is often difficult to communicate), models can be used to aid decision-making at multiple levels e.g. national and local, and to aid understanding and allow decision making. The techniques and tools of complexity science, therefore, offer a powerful means of understanding the complex decision-making processes that are needed to realise a low-carbon energy system. We conclude with recommendations for future areas of research and application. (C) 2014 The Authors. Published by Elsevier Ltd. This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/3.0/).