Demand starter data kit: Selected socio-economic and technical energy system demand modelling data for all 47 counties in Kenya

IF 1 Q3 MULTIDISCIPLINARY SCIENCES

Data in Brief Pub Date : 2025-04-17 DOI:10.1016/j.dib.2025.111556

Neve Fields , Ariane Millot , Martin Mutembei , Anne Nganga , Pietro Lubello , Leonhard Hofbauer , Mark Howells , Ed Brown

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引用次数: 0

Abstract

The need for data-driven models to inform energy planning and policy making is increasingly important as Kenya looks to transform its energy system to be clean, efficient, diverse and secure. Modelling softwares can be used by policy makers to assess the impacts of different scenarios on energy systems to support planning and decision making. Demand forms an integral foundation of energy planning and insights into possible projections can aid in policy creation, yet access to data is often a barrier to utilising energy demand modelling to support such decision making. Despite the official launch of the energy governance devolution process within Kenya, through the Kenya Energy Act (2019), progress towards county energy planning and developing modelling data and tools to reflect this remains limited and inaccessible. Therefore, this article provides data that can be used to create a simple whole energy system demand model for the individual counties in Kenya, acting as a starting point for teaching, capacity building efforts, and for further data collection, model development and scenario analysis to produce county resolution demand projections. The data was collected from websites, annual reports, and databases of international and national organisations alongside existing modelling databases and academic articles and can be easily updated based on the latest available local data and information. As a demonstration, these data were used to calibrate a demand model for Kilifi County using the Model for the Analysis of Energy Demand (MAED) for a baseline scenario from 2019 to 2070. The assumptions used and results gained are illustrated in the appendix of the article as a demonstration of what can be achieved through application of this dataset.

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需求启动数据包：肯尼亚所有47个县的选定的社会经济和技术能源系统需求建模数据

随着肯尼亚希望将其能源系统转变为清洁、高效、多样化和安全的能源系统，为能源规划和政策制定提供信息的数据驱动模型的需求变得越来越重要。决策者可以使用建模软件来评估不同情景对能源系统的影响，以支持规划和决策。需求是能源规划不可或缺的基础，对可能预测的洞察可以帮助制定政策，但获取数据往往是利用能源需求建模来支持此类决策的障碍。尽管通过《肯尼亚能源法》（2019年）在肯尼亚正式启动了能源治理权力下放进程，但在县能源规划和开发反映这一情况的建模数据和工具方面取得的进展仍然有限且难以获得。因此，本文提供的数据可用于为肯尼亚各个县创建一个简单的整个能源系统需求模型，作为教学、能力建设工作的起点，并作为进一步的数据收集、模型开发和情景分析的起点，以产生县解决需求预测。这些数据是从国际和国家组织的网站、年度报告和数据库以及现有的建模数据库和学术文章中收集的，可以根据最新的本地数据和信息轻松更新。作为示范，这些数据被用于校准基利菲县的需求模型，该模型使用能源需求分析模型（MAED），用于2019年至2070年的基线情景。本文的附录中说明了使用的假设和获得的结果，以演示通过应用该数据集可以实现什么。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

Data in Brief MULTIDISCIPLINARY SCIENCES-

CiteScore

3.10

自引率

0.00%

发文量

996

审稿时长

70 days

期刊介绍： Data in Brief provides a way for researchers to easily share and reuse each other''s datasets by publishing data articles that: -Thoroughly describe your data, facilitating reproducibility. -Make your data, which is often buried in supplementary material, easier to find. -Increase traffic towards associated research articles and data, leading to more citations. -Open up doors for new collaborations. Because you never know what data will be useful to someone else, Data in Brief welcomes submissions that describe data from all research areas.