Context: Addressing Energy Poverty with Precision ⚡🌍📊
Nearly 1.2 billion people globally lack access to modern electricity, with the majority concentrated in sub-Saharan Africa, South Asia, and East Asia. In regions where centralized grid extension is often impractical, decentralized solar photovoltaic (PV) minigrids present a compelling alternative. However, many electrification efforts historically overlook long-term operation and maintenance (O&M) costs, resulting in underperforming or unsustainable systems. A recent study in Scientific Reports provides a geo-referenced, 1 km² resolution mapping of affordability for PV-based electricity in 71 countries, revealing where solar investments can be both economically and socially viable. 🔗📌💡
🔗 Read the original study here via RAEL at UC Berkeley
Geo-Referenced Affordability Analysis: A Breakthrough for Modellers 🧭📉🛠️
From a financial modelling standpoint, this study is significant. It goes beyond national averages, delivering disaggregated data that reflects the true landscape of affordability. Financial modellers can now identify with greater accuracy the least-cost electrification options by comparing the levelized cost of electricity (LCOE) for PV systems versus diesel minigrids. 📊📍🔍
For example, under adverse policy scenarios (SSP3), the study shows that even at low diesel prices, PV remains the most affordable option for 177 million people. The analysis also identifies ‘no-regret’ zones—regions where solar remains at least $0.20/kWh cheaper than diesel regardless of price volatility. These are ripe areas for impact investment and concessional financing. 🌞🛡️💰
Affordability Matters: Going Beyond CAPEX 💸🧮🕒
Too often, project evaluation focuses on capital expenditures (CAPEX), sidelining O&M costs which are crucial for long-term sustainability. This study splits cost into CAPEX (assumed to be donor or government-funded) and O&M (borne by end users), allowing us to layer financial models with realistic repayment structures. ⚙️📈🏛️
The data show that PV systems have O&M costs that are often ten times lower than those of diesel generators. For modellers, this affects assumptions on tariff levels, internal rate of return (IRR), and project bankability. Countries like Malawi, Uganda, and Madagascar emerge as low-hanging fruit—areas with high solar affordability and sufficient purchasing power to support long-term use. 🌍💡📉
Implications for Financial Modelling 🧾📊🔧
This granular dataset allows financial analysts to:
- Integrate subnational affordability data into project feasibility studies.
- Structure blended finance instruments targeting ‘no-regret’ PV zones.
- Adjust IRR and NPV calculations based on realistic O&M burden on end users.
- Use poverty gap indices to refine demand projections.
Policy and Investment Outlook 🏛️📉🌞
The takeaway is clear: affordability is not uniform. While national averages may suggest viability, only subnational analysis can unveil true demand potential. Investors and policymakers should target areas identified in this study as ‘no-regret’ and ‘low-hanging fruit’ zones for early deployment. 📌💹🚀
For financiers, de-risking mechanisms such as results-based financing and currency hedging will be essential in regions with marginal affordability. For governments, recalibrating fuel subsidies could enhance PV competitiveness and create fiscal space for electrification programs. 🛡️⚖️🏦
Conclusion: A Call to Action for Financial Modellers and Investors 📣🧠💼
This study sets a new benchmark in data-driven electrification planning. By combining geo-spatial data with financial modelling, stakeholders can now pinpoint where their capital will have the most sustainable impact. As diesel volatility and climate constraints intensify, PV minigrids—when aligned with affordability data—represent not just a clean solution, but a financially sound one. 📍🌿🔬
The path to universal electrification is complex, but with tools like this, it’s never been clearer where to begin. 🛤️💡🌍
🔍 Interested in financial modelling for solar? Start with the Finteam template: https://www.eloquens.com/tool/gyxxIMgg/finance/solar-project-financial-modeling/uk-solar-pv-excel-model 📊☀️📥
Finteam 