Work

Co-creating Taita-Taveta County energy demand projections for integrated national energy planning in Kenya through a mixed methods modelling approach

Year: 2026

Type: article

Abstract: Energy devolution in Kenya has progressed unevenly, with many counties yet to complete their County Energy Plans (CEPs), posing challenges for integration into the forthcoming Integrated National Energy Plan (INEP). A key gap lies in translating qualitative, needs-based insights from county planning documents into quantitative inputs for energy demand modelling. This study applies a mixed-methods approach to address this gap. Building on existing Model for the Analysis of Energy Demand (MAED)-based datasets and multi-scale modelling frameworks, we develop a structured process to translate qualitative planning narratives into quantitative scenario assumptions. Using Taita Taveta County (TTC) as a case study, we construct four demand scenarios (baseline, ambitious, reserved, and a county priorities scenario). The latter is co-developed through interviews, a workshop, and analysis of CEP and County Integrated Development Plan (CIDP) documents with 26 county and national stakeholders. The county priorities scenario is operationalised by systematically mapping qualitative insights, such as electrification ambitions, cooking transitions, and sectoral development priorities, onto model parameters, including electrification rates, fuel shares, sectoral composition, and technical coefficients. The resulting scenarios illustrate how aligning modelling assumptions with county planning narratives produces different demand trajectories and sectoral structures compared to nationally aligned socio-economic scenarios. The findings highlight both the value and challenges of incorporating locally grounded qualitative insights into energy demand modelling, particularly regarding transparency, uncertainty, and inclusivity. This study provides an applied demonstration of how county-level planning documents can be translated into structured inputs for energy demand modelling, supporting alignment between devolved planning processes and national modelling efforts in Kenya. Results should be interpreted as exploratory rather than predictive.

Source: Energy Research & Social Science

DOI: 10.1016/j.erss.2026.105067