Bankability analysis of a 30-Megawatt Sub-Saharan Solar Farm
Better holistic understanding of Investment risks using the VesBox Platform
Making solar energy bankable in Sub-Saharan Africa is a challenging process and needs careful attention to understand all issues that can affect project bankability for solar energy infrastructures (Photo-Voltaic or PV). The standard method of measuring bankability (referred to as the Baseline Approach) identifies a set of risk parameters that usually have a direct impact on the project finance. For example, factors such as project returns, state of distribution and transmission networks; currency fluctuation; type of solar PV technology are all examples of the standard issues or risks identified by energy developers. Although energy developers all have their own set of criteria when assessing a project's bankability, the Baseline approach of measurement is usually adopted by industry.
Although very effective when used in low risk and developed countries, this baseline approach has seen to fail when adopted in higher risk or emerging countries. This is simply because for higher risk economies, it is extremely imperative that one goes beyond the baseline approach. Addressing factors that both directly and indirectly affect project finance is crucial to success fully measuring bankability in emerging countries. This means, identifying key performance metrics (or project risks) that addresses project finance, the environment in which that project will be built, the social structure of the community and country and the ecological factors that can indirectly impact the project. This new approach is referred to as the VesBox Approach.
The VesBox approach of measurement identifies over 30 unique performance indicators that have a direct and indirect impact on the bankability of solar energy projects. This approach was tested out using the VesBox Platform, on a 30-Megawatt sub-Saharan solar farm located in Benue, Nigeria. The goal of this study is for the VesBox Platform to identify and analyse project risks that fall under finance (baseline approach), environmental, social and resource management (also referred to as ecological or ecosystem risk). Results of this study help us understand the true picture of a projects performance, looking beyond the baseline approach of measurement. From the results, users can better identify the quantitative and qualitative factors that can affect their project, understand the impact of such risks on their project and address proper mitigation strategies on how to avoid such risks where necessary.
The current approach for measuring solar energy bankability (i.e. baseline Approach), follow a linear style of measurement by only accounting for the financial system addressed earlier in this research. This linear approach has led to the decline in the long-term growth of solar energy, especially in developing and emerging countries. The new approach (i.e. VesBox Approach) addresses this issue by helping project developers, financiers and decision-makers identify country-specific market uncertainties as well as environmental, social and resource management concerns not addressed on the current approach for assessing solar energy bankability, to better understand the potential impacts on deployments and boost investor confidence to invest, especially in new developing and emerging markets (see fig. 1).
Baseline Approach vs. the VesBox Approach
Fig. 1: Baseline Approach vs. the VesBox Approach
Furthermore, in light of a growing population and the ever-increasing demand for energy, the need to secure along-term and sustainable energy supply is vital to our economic growth. The VesBox Approach can play a significant role in achieving this, as such, the International Energy Agency stated in 2014, that an enhanced approach if implemented, that addresses non-financial uncertainties can potentially improve the overall investment forecast for renewable solar energy by around 83.3% (+20% per year) between 2016-20 compared to the current baseline forecast of around 33.2% (+8.3% per year) within the same time period (IEA, 2014a; REN21, 2016). The increase in solar energy deployment using the VesBox Approach can, therefore, lead to the increase in the long-term growth of solar energy, therefore eliminating the over dependency on conventional energy sources. This White Paper outlines a few measures on how to address bankability for the case study project (30-Megawatt Sub-Saharan Solar Farm) by using the VesBox approach.
Addressing the bankability of the 30 MW Sub-Saharan Solar Farm using the VesBox Approach
A pre-feasibility tool for adopting the VesBox Approach (referred herein as the VesBox Platform), was used to measure the bankability of the above project. Results from its analysis (see fig. 2) presented an overall project risk of “High Risk” with a score of 59.2% (also known as the VesBox Score). The VesBox Score adopts a ‘systems thinking’ framework that incorporates the baseline line approach (financial principles only) and the VesBox approach of measurement (combination of financial, environmental, social and resource management principles). The risk breakdown conducted for this analysis were as follows:
30 MW Sub-Saharan Solar Farm Located in Benue, Nigeria
Benue State Solar Project | VesBox
Debt: Equity Split
Expected delivery date
Project Site information
Name of State/Country
Land Area Acquired
Mono Crystalline Modules
Benue State, Nigeria
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Sustainable land use
1Y 2Y 5Y 10Y
Overall project risk
1Y 2Y 5Y 10Y
Fig 2: Results from the VesBox Platform
The results presented confirm that the VesBox Platform has the potential to play a vital role in enabling decision-makers to effectively measure the project bankability and contribute to the enhanced growth of solar energy investments globally. Though the pre-feasibility tool has a few limitations that could be easily addressed with further development as all software platforms do, verification and validation analysis carried out, demonstrated that it was suitable for its intended use. Applying it to multiple case studies produced results that gave a clear indication that the level of errors and the model’s accuracy are at an acceptable level, to improve decision making.
This case study was prepared by Beacon Oak.