驾驭复杂性:将政治现实纳入撒哈拉以南非洲有效政策的能源系统建模中

Meron Tesfamichael, Janina Fuchs
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引用次数: 0

摘要

社会和经济系统必须迅速实现低碳转型,这就更加依赖系统建模为决策提供信息。能源模型在确定可行途径和指导干预措施方面发挥着关键作用,从而影响政策议程和公共讨论。然而,在撒哈拉以南非洲地区,能源规划和政策对基于模型的分析的利用仍然有限,这主要是由于现有模型存在缺陷。研究表明,这些模型中的许多都不适合捕捉非洲国家普遍存在的具体挑战。尽管提供了有价值的见解,但大多数模型缺乏对与政治和治理动态相关的不确定性的表述。这些研究结果突出表明,迫切需要提高国内机构的建模能力。虽然技术专长至关重要,但本文认为,鉴于能源政策决策本身的政治性质,建模者必须认识到问题建模和寻求解决方案所处的政治环境。我们认为,旨在影响政策的能源建模人员必须努力理解能源规划与政策制定交汇处的潜在政治经济。在此基础上,我们阐述了建模团队可以采取的实际步骤,以进行政治经济分析并掌握影响能源决策的因素。通过坚持这些步骤,我们认为建模团队可以提高通过建模工作提出的政策方案的相关性、现实性和适用性。
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Navigating complexity: integrating political realities into energy system modelling for effective policy in Sub-Saharan Africa
The imperative for rapid low-carbon transformations in social and economic systems has heightened reliance on systems modelling to inform decisions. Energy models are pivotal in shaping viable pathways and guiding interventions, thereby influencing policy agendas and public discourse. However, in sub-Saharan Africa, the utilization of model-based analysis for energy planning and policy remains limited, largely due to deficiencies in existing models. Research indicates that many of these models are ill-equipped to capture the context-specific challenges prevalent in African countries. Despite offering valuable insights, most models lack representation of uncertainties associated with political and governance dynamics. These findings underscore the urgent need to enhance domestic institutions’ modelling capabilities. While technical expertise is crucial, this paper contends that, given the inherently political nature of energy policy decisions, modelers must be cognizant of the political landscape in which problems are modelled and solutions are sought. We assert that energy modellers aiming to influence policies must endeavour to comprehend the underlying political economy at the intersection of energy planning and policymaking. Expanding on this premise, we delineate practical steps that modelling teams can adopt to conduct political economy analysis and grasp the factors influencing energy policymaking. By adhering to these steps, we posit that modelling teams could enhance the relevance, realism, and applicability of policy options proposed through modelling efforts.
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