- The paper introduces a robust multidisciplinary framework that integrates spatial analysis, renewable energy modeling, and water sustainability to assess local green hydrogen costs.
- The methodology employs open-source tools and coupled models to generate detailed cost metrics, including wind LCOE (14–31 c€/kWh), PV LCOE (~2.9–3.1 c€/kWh), and hydrogen LCOH (1.3–2.4 €/kgH2) for diverse regions.
- The approach also evaluates socio-economic impacts using composite indicators aligned with key SDGs, providing actionable insights for region-specific green hydrogen strategies.
This paper presents a comprehensive, multidisciplinary approach to evaluate the local cost-potentials of green hydrogen production across Sub-Saharan Africa. It addresses the critical need for detailed and consistent information spanning technical, environmental, economic, and social dimensions to support the development of green hydrogen strategies in the region. The methodology integrates several coupled models and data sources, aiming to serve as a robust decision-support tool.
The core of the approach involves several key stages:
- Land Eligibility Assessment (LEA): The paper begins by identifying areas suitable for placing renewable energy technologies, specifically open-field photovoltaic (PV) parks and onshore wind turbines. This is achieved through a detailed spatial analysis using the open-source geospatial toolkits GeoKit and GLAES. Crucially, the assessment incorporates a wide range of exclusion criteria (33 in total), including topography, land use, environmental constraints, and, importantly, local preferences gathered through workshops with regional stakeholders (community members, government bodies, international institutions). The LEA applies buffer distances around sensitive areas (e.g., roads, settlements, forests) to determine eligible land, often resulting in significant exclusion of available land area, as shown in an example for the Oueme region in Benin where only 23.8% of the land was found eligible after applying just three criteria.
- Renewable Energy Potential Assessment: Following the LEA, wind turbines and PV modules are strategically placed within the identified eligible areas. Wind turbines are positioned based on rotor diameter and main wind direction, while PV parks are placed considering minimum distances and utilizing Voronoi polygons to assign eligible area around placement locations. Hourly electricity generation time series for these placements are simulated using meteorological data (ERA5) and the open-source tool RESkit. Additionally, the assessment includes potentials from existing and planned hydropower plants in Africa, converting monthly generation data to hourly series, and enhanced geothermal systems, calculated based on land eligibility, geological temperature, heat flow data, and thermal conversion efficiency.
- Sustainable Water Supply Assessment: Recognizing the significant water demand for electrolysis (up to 9 kg of water per kg of hydrogen), the methodology includes a detailed assessment of water availability, considering two primary sources: sustainable groundwater and seawater desalination.
- Sustainable Groundwater: Annual groundwater recharge is simulated using the Community Land Model (CLM5) and climate model outputs under different climate change scenarios (RCP2.6 and RCP8.5). Sustainable yield is calculated by subtracting environmental flow (minimum ecological water requirement, considered under conservative, medium, and extreme scenarios relative to recharge) and existing sectoral water use from the simulated recharge. Long-term averages (e.g., 2015-2035 for 2020 potential) are used, showing a projected decrease in sustainable groundwater yield by 2050.
- Seawater Desalination: For regions without sufficient sustainable groundwater, seawater desalination and transport are considered. Desalination cost is calculated using established models, including the electricity cost (based on regional average PV levelized cost for 24/7 operation, accounting for storage) and water transport cost, which depends on distance to the coast and elevation, estimated using a validated cost model. The analysis prioritizes groundwater extraction due to its lower cost, resorting to desalination only when sustainable groundwater limits are reached.
- Local Green Hydrogen Potential Assessment: An independent energy system model is created for each administrative region (GID_2 level) using the ETHOS.FINE optimization framework. Each model includes aggregated renewable electricity sources (wind, PV, hydro), lithium-ion batteries for storage, and PEM electrolyzers for hydrogen production. The optimization minimizes the annual cost of the system required to meet an exogenously increasing gaseous hydrogen demand up to the maximum potential of the region. This process determines the optimal capacity and hourly operation of each component, yielding a hydrogen cost-potential curve and the levelized cost of hydrogen (LCOH) for each region.
- Socio-economic Impact Assessment: To complement the techno-economic and environmental analysis, the paper includes a socio-economic dimension. This is based on an approach using composite indicators, guided by the OECD checklist. The assessment focuses on the potential local impacts related to several Sustainable Development Goals (SDGs), including access to energy (SDG 7), decent work and economic growth (SDG 8), poverty reduction (SDG 1), zero hunger (SDG 2), good health and well-being (SDG 3), and climate action (SDG 13). Indicators such as population without access to electricity/clean fuel, direct employment potential per installed capacity, and share of the population below the poverty line are calculated using spatial data at the regional level. These indicators are normalized and aggregated to assess the overall socio-economic local impact.
- Result Dissemination: The findings from the multidisciplinary analysis are made accessible through a web-based Graphical User Interface (GUI) powered by technologies like Docker, React, Mapbox, Node.js, and a PostgreSQL database with PostGIS extensions. This GUI visualizes the results on a map, allowing stakeholders to explore various factors influencing green hydrogen potential across regions.
Case studies demonstrate the approach's capability. The LEA shows how local preferences significantly influence available land. The renewable energy assessment highlights the variability in LCOE for wind (14-31 c€/kWh) and PV (~2.9-3.1 c€/kWh in 2030) even within a single region. The groundwater analysis reveals considerable spatial and temporal variability in sustainable yield under different climate scenarios, with projected decreases over time. The hydrogen modeling for a hypothetical region illustrates how different energy sources are utilized as hydrogen demand increases, showing LCOH ranging from ~1.3 €/kgH2 (pure hydro) to ~2.4 €/kgH2 (including wind and batteries) in 2050. It finds that the cost of water supply (including desalination) is currently negligible in the overall LCOH for the scenarios considered. The socio-economic assessment method shows how different spatial data layers are combined to provide a localized impact indicator.
In summary, the paper provides a novel and robust methodology for assessing green hydrogen potential in Sub-Saharan Africa by integrating technical feasibility, environmental constraints (particularly water availability under climate change), economic optimization, and local socio-economic considerations. The tools and datasets employed are largely open-source and adaptable, offering a practical framework for decision-makers and practitioners to understand local conditions and plan sustainable green hydrogen projects. The paper highlights the need for this integrated, location-specific analysis due to significant regional variations in resources and socio-political contexts.