With ambitious targets to drastically increase economic activity over the next decade, Kenya’s future is undoubtedly energy-intensive. Current power capacity expansion plans will see Kenya considerably ramp up fossil fuel generation, significantly increasing emissions. Therefore, Kenya is at a crucial stage of its national development, with critical decisions to make regarding its future power expansion and production. OSeMOSYS modelling software (clicSAND version v1.1) is employed to produce a series of possible clean energy transition pathways to increase renewable power production under rapidly intensifying demand. This study integrates existing national priorities and policies into six modelled scenarios to provide insights into their generation, total production, and costs, which can assist future policymaking and capacity-building efforts. The high-level insights gained in this research were employed to suggest key recommendations for Kenya’s power sector. Most notably, policy alignment, increased wind power production, energy-efficiency penetration, finance and investment securement, the development of storage technologies, power transmission, and distribution improvements should be prioritised.

Sierra Leone is an electricity-poor country with one of the lowest electricity consumption per capita rates across sub-Saharan Africa. Yet, with ambitious targets to transform and stimulate its economy in the coming decades, energy demand forecasting becomes an integral component of successful energy planning. Through applying the MAED-D (version 2.0.0) demand software, this research study aims to generate Sierra Leone’s electricity demand forecasts from 2023 to 2050. Three novel scenarios (baseline-, high-, and low-demand) are developed based on socio-economic and technical parameters. The baseline scenario considers the current electricity sector as business-as-usual; the high-demand scenario examines an ambitious development future with increased economic diversification and mechanisation, and the low-demand scenario examines more reserved future development. The modelled scenario results project an increase in electricity demand ranging from 7.32 PJ and 12.23 PJ to 5.53 PJ for the baseline-, high-, and low-demand scenarios, respectively, by 2050. This paper provides a base set of best-available data needed to produce an electricity demand model for Sierra Leone which can be used as a capacity-building tool for in-country energy planning alongside further integration into data modelling pipelines.

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.

Energy systems modelling plays a pivotal role in understanding and optimizing complex energy systems. By integrating various factors such as energy demand, supply, infrastructure, and environmental considerations, energy systems modelling provides valuable insights for policymakers, industry stakeholders, and researchers. This can be key to informing stakeholder and policy decisions and facilitate the mobilisation of capital and market development to support the development of the energy sector. This article presents the data, assumptions, and related calculations used for the development of a national scale power system model for Sierra Leone. The focus of the model was a techno-economic analysis of specific hydropower expansion plans. Where possible, this data has been collected from publicly available sources such as scientific literature, feasibility studies, international databases, data from existing modelling efforts in Sierra Leone, and local stakeholders. The collection of the data, development of the model, and creation of scenarios was done in collaboration with the Ministry of Energy in Sierra Leone and verified by a broad range of stakeholders. The following paper outlines the key data presented in the full database which can be accessed through the URL found in the Specifications Table. The URL also contains the Reference Energy System (RES) used in this study.