Techno-economic Analysis of a Suitable Business Model for a Rooftop Solar PV Project

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TECHNO-ECONOMIC ANALYSIS OF A SUITABLE BUSINESS MODEL FOR A ROOFTOP SOLAR PV PROJECT

(CASE STUDY OF ACCRA, GHANA)

ABSTRACT

The study conducted in this thesis examined the technical and economic potentials of rooftop solar photovoltaic (RSPV) as a viable and easily implementable power generation alternative for solving the power unavailability and unreliability in Accra (and Ghana in general). The technical potential analysis revealed a per capita solar rooftop area of 11.48 m2 and total suitable rooftop area of 22.5 km2 for the metropolitan city of Accra. This resulted in solar power and energy potentials of 2.56 GW AC output and 5,026 GWh respectively, representing about 80% of installed capacity and 43% of electricity supplied in Ghana in 2015.

The economic analysis on a 2% potential capacity cover showed a levelized cost of electricity (LCOE) for RSPV at 19.15 US¢/kWh (as against a FiT of 20.00 US¢/kWh), and modest profitability when economies of scale is considered culminating in an NPV of 4.08 US$ million at an IRR of 22% over a 25-year lifespan of the project. The profitability becomes incremental when higher uptakes of 10% and 50% are considered with NPVs of 45.88 US$ million and 356.94 US$ million, and IRRs of 25% and 28% respectively. The payback period is 4.2 years for a 2% uptake. The report also proves a higher investment return of about 90% when lending rates from China (5%) are applied in the LCOE derivation instead of the high lending rates applied from Ghana (20%).

ACKNOWLEDGEMENTS

My first vote of thanks goes to the Almighty God for the strength, wisdom and guidance He sustained in me throughout the duration of my study leading to this piece. Special acknowledgements also go to my supervisors, Bart van Campen and Dr Mehdi Shahbazpour for the constructive roles they played, and the patience they showed in shaping the course of this project. Finally, but surely not the least, to my young family and wife―Zlatan, Zuria, Zyana, and Mildred Zickson for enduring my absence for an entire year whilst I pushed to achieve this dream.

Table of Contents

ABSTRACT

ACKNOWLEDGEMENTS

LIST OF TABLES

LIST OF FIGURES

CHAPTER 1

1.1 INTRODUCTION

1.1.1 Background

1.1.2 Scope of Project

1.2 LITERATURE REVIEW

1.2.1 Renewable Energy Technologies

1.2.2 Solar Energy

1.2.3 PV Technology

1.2.4 Applications of PV technology

1.2.5 Policy Instruments on Renewable Technologies

1.2.6 Estimation of Rooftop Solar PV (RSPV) Potential

1.2.7 Business Models & Funding Mechanisms on RSPV

CHAPTER 2

2.1 ENERGY OUTLOOK FOR GHANA

2.1.1 Structure of the Electricity Sector

2.1.2 Renewable Power Resource & Potential

2.1.3 Policy Instruments on Renewable Power in Ghana

2.1.4 Penetration of Solar Power in Retail Market

CHAPTER 3

3.1 SOLAR TECHNICAL POTENTIAL ASSESSMENT FOR ACCRA

3.1.1 Suitable Rooftop Area Estimation

3.1.2 Solar Power Potential Assessment

CHAPTER 4

4.1 ECONOMIC ANALYSIS OF RSPV DEPLOYMENT

4.1.1 Business Model Selection

4.1.2 Estimated Cost of Project

4.1.3 Total Installed Project Cost (TIPC)

4.1.4 Levelised Cost of Electricity (LCOE)

4.1.5 Sensitivity Analysis

4.1.6 Profitability Analysis

CHAPTER 5

5.1 SUMMARY & CONCLUSION

5.1.1 Summary

5.1.2 Conclusions and Recommendations

REFERENCES

CHAPTER 1

1.1 INTRODUCTION

1.1.1 Background

The aim of this project is to conduct technical and economic analyses on the pre-feasibility of the deployment of a sustainable business model for a rooftop solar PV (RSPV) project for an urban city in sub-Saharan Africa. The case study for the project is Accra, the capital city of Ghana. Accra was chosen for the following reasons;

  1. Accra is a densely populated major city in one of the highest solar resource potential regions of the world with an average solar radiation of 5.1 kWh/m2-day (Energy Commission, 2014).
  2. Ghana has a recent history of serious power interruptions due to power generation/consumption deficit, hence, an assessment of the impact of the project on power availability in Accra will be critically vital.
  3. The author is from Ghana and intends to develop a business in the area.

The project therefore attempts to answer two very pertinent questions:

  1. What is the total technical rooftop solar potential for the metropolitan city of Accra?
  2. What is the economic feasibility of the deployment of a suitable business model for RSPV in Accra?

1.1.2 Scope of Project

Pursuant to the objectives of this project, a thorough investigation will be conducted in Accra to ascertain answers to relevant issues needed for the success of the project. The roadmap to be followed is rolled out in chapters. The first part of chapter one covers the introduction to the project with insights into the aims and objectives, plus the scope expected to be covered. The second part covers the literature review and delves into relevant topics such as; solar energy (PV & CSP), policy instruments on renewable energy, methods of estimating RSPV potential as a pre-feasibility run for RSPV projects and policy analysis, and available RSPV business models on the international landscape including their challenges and risks. Chapter two of the project focuses on the study area (Accra, and Ghana in general where imperative) and discusses; the structure of the electricity sector in Ghana, renewable power resource and potential, policy instruments on renewable power in Ghana, and the penetration of solar power in the national retail system.

In chapter three, solar technical potential is conducted for Accra by estimating the suitable RSPV area, and the equivalent solar power/energy potential. This is to identify the amount of power generation opportunity available, and inform subsequent decisions on the economic analysis and business model selection. In chapter four, a suitable business model is selected. Then, estimates of the unit cost of solar power for project deployment in Accra is calculated using the levelized cost of electricity (LCOE) approach at various uptake levels (2%, 10% & 50% power potential) of RSPV. Sensitivity analyses are run on important LCOE parameters such as discount rate, and operation and maintenance (O&M) costs to test the robustness of the LCOE tool. Finally, profitability analysis is conducted using net present value (NPV), internal rate of return (IRR) and payback criteria to judge the investment worthiness of the project.  Chapter five involves the summary and discussion of results, and the conclusion and recommendations based on findings made through the thesis.

CHAPTER 3

3.1 SOLAR TECHNICAL POTENTIAL ASSESSMENT FOR ACCRA

Solar potential assessment can be carried out in several ways depending on the scope and limitations of a project. For this thesis, a method that is simplistic, yet draws out all the required parameters for solar potential estimation is utilized. The methodology of assessment is split in two steps;

  1. Suitable rooftop area estimation
  2. Solar power potential assessment

3.1.1 Suitable Rooftop Area Estimation

Data for the accurate estimation of suitable RSPV area (like GIS-based data) for most cities in Africa are either not available or not in the public domain. Hence, estimation of suitable RSPV area is best achieved using easily accessible data like population, land use and housing stock, and exploring their relationships with roof area. These methods (just like all other CVM methods) even though less accurate than GIS-based methods provide reasonable basis for economic analysis for RSPV deployment.

The suitable RSPV area estimation method used in this report is a population type CVM model and is broken down into two parts: First, use is made of an empirical relationship linking the population density of cities and the useful roof area per capita available for solar PV installation generated by OECD/IEA. The formula permits the calculation of the suitable rooftop area per capita of RSPV installation for a city (with population exceeding 100,000) once the population density is known (OECD/IEA, 2016). The OECD/IEA derived the formula by after collating data on existing individual assessments for solar rooftop potentials from a pool of 1,600 cities around the world which have a population exceeding 100,000. After plotting the dataset in a double-logarithmic form, a linear relationship was identified as in Figure 12 below.

Figure 11:: Available solar rooftop area per capita in cities as a function of population density (OECD/IEA, 2016)

The statistics enabled the derivation of an empirical formula between population density and the suitable roof area available for RSPV which has proved a tool worthy of application for markets with no/little available data on the subject. The resulting empirical formula derived is:

It = investment expenditures in the year t;

Mt = operations and maintenance expenditures in the year t;

Ft = fuel expenditures in the year t;

Et = electricity generation in the year t;

r = discount rate; and

n = economic life of the system.

Assumptions

The calculations were done with a couple of assumptions. The year 1 project data assumed that all the cost and delay due to project development due diligence was started and completed within that year together with all accompanying cost. The project lifetime was taken as 25 years which is quite standard for utility scale PV projects. Except for the panels, which is considered to last the entire duration of the project, the BOS (excluding the ancillary equipments) is replaced after 10 years in line with supplier warranty deadlines to secure the continuous production of the plant. Hence, the cost of BOS which is calculated as 30% of TIPC is reapplied in the 11th year of the project lifetime. Fuel expenditure was taken as zero for the project duration.

The cost of O&M was taken as 10% of TIPC and includes roof rental fee payments as per business model (IRENA, 2016). The quantity of electricity produced is assumed to decline during the lifetime of the project according to the panel manufacturer’s power warranty of performance. Subsequently, the expected power output is taken as 90% of the total output for the first 10 years of production, and 81% for the subsequent 15 years. An “economies of scale” (EOS) criterion is assumed and variated at 10%, 15% and 20% of TIPC for the Base Case, 10% and 50% uptake levels of the project respectively. This is typically lower than the percentages for real projects― as Farrel (2016) reports of economies of scale up to 35% for RSPV utility scale projects of about 185 MW―but chosen to keep within a safe investment net. The discount rate applied was selected as equal to the average current bank lending rate (real rate) in Ghana, which is 20% (Ghana Trade, 2017). The calculation was done in excel format and the results shown in Table 14 below.

Table 14: The LCOE for the different uptakes of Solar PV for Accra

Uptake Cost NPV

US$ million

Generation NPV, kWh LCOE, US$/kWh Current FiT, US$/kWh Unit Cost of Investment, US$/kWh
Base Case (2%)  101.99 532,638,683 0.1915 0.20 1,992
10%  481.66 2,663,193,413 0.1809 0.20 1,882
50%  2266.59 13,315,967,063 0.1702 0.20 1,771
Base Case without Economies of Scale  109.23 532,638,683 0.2051 0.20 2,133
Base Case without Batteries & without Economies of Scale  85.54 532,638,683 0.1606 0.20 1,671

The LCOE derived for the Base Case without economies of scale, 20.51 US ¢/kWh, is lower than the LCOE derived in the Energy Commission audit of 2016, 22.41 US ¢/kWh with a margin of 8.5%.

Figure 12: Project LCOE Calculations

4.1.5 Sensitivity Analysis

Due to the simplistic approach adopted in the derivation of the LCOE, sensitivity variation of key indicators is necessary to ascertain the robustness of the LCOE against such variations which will help inform the need for deeper interrogation of the issues at stake. Two areas chosen for the sensitivity analysis were: discount rate and the O&M. Given the capital-intensive nature of most renewable power projects and the fact that fuel costs are often low/zero, the weighted average cost of capital (WACC), also referred to as the discount rate, used to evaluate the project has a critical impact on the LCOE. Ghana has very high WACC compared to some countries in Europe and Asia. This translates into high discount rates for projects, assuming capital is sourced from within the country. The analysis will consider a discount rate variation of ±25% because it falls within practicality in Ghana as financial institutions are showing a broad-band of lending rates between 18-25% (inflation-corrected).

Additionally, an analysis will be done assuming an international project capital finance from a more “lending rate friendly” economy. The country considered here will be China, mostly because of the high proliferation of Chinese businesses in Ghana: in fact, the largest utility scale ground mounted solar PV plant in Ghana and the West African Region (20MW) is owned by the Chinese technology firm Beijing Xiaocheng Company (BXC).  The lending rate applied for the international finance case scenario is 5% (Trading Economics, 2017)[7]. The essential annual cost in the project is the cost of O&M. It is crucial to identify the effect of over- or under-estimating the O&M on the LCOE. Therefore, it is variated at ±20%.

Sensitivity Results

Overall, the ±25% discount rate variation (WACC at 25%) resulted in a ±11% variation in LCOE which is quite significant. Most importantly, the Base Case scenario losses profitability at +25% discount rate variation whilst the 10% uptake level barely breaks even at the end of project life under the same scenario. The -25% scenario (WACC at 15%) further enriches the project, creating huge investment comfort for potential investors. However, this financial improvement does not match the 5% China WACC case. Strikingly, the lower discount rate from China translates to an LCOE reduction of 33%.

Table 15: LCOE Sensitivity Analysis of ±25% Discount Rate variation

UPTAKE -25% LCOE +25% 5% CHINA RATE
Base Case 0.1705 0.1915 0.2116 0.1285
10% 0.1610 0.1809 0.1999 0.1214
50% 0.1516 0.1702 0.1881 0.1143

Figure 13: A comparison of LCOE values at ±25% sensitivity variation of Discount Rate, and the 5% Chinese lending rate estimate

The LCOE values for the ±20% O&M variation show an overall swing of ±7.2%. This is modest and shows higher robustness than the discount rate case. Only the +20% variation of the Base Case losses profitability under this scenario as shown in Figure 15 below.

Table 16: LCOE Sensitivity Analysis of ±20% O&M Variation

UPTAKE -20% LCOE +20%
Base Case 0.1776 0.1915 0.2053
10% 0.1678 0.1809 0.1939
50% 0.1579 0.1702 0.1825

Figure 14: A comparison of LCOE values at ±20% sensitivity variation of O&M

The LCOE swing is 11.1% with the O&M variation when applied to the China lending rate. Although a much wider swing compared to the Ghana lending rate cases, the highest LCOE which is 14.28 US ¢/kWh is still below the current FiT to threaten any investment security as shown in Figure 16 below.

Figure 15:: A comparison of LCOE values at ±20% sensitivity variation of O&M on China Discount Rate

4.1.6 Profitability Analysis

In the analysis of project profitability, simple investment criteria such as NPV, Internal Rate of Return (IRR) and Payback were used. For the sake of simplicity, it was assumed that any investment cost was fully tax deductible in the same year it was expensed. A 25% corporate income tax was applied as per the situation in Ghana. Interestingly, the IRR and the Payback were the same for equivalent cases using both the Ghana and China WACC. The NPVs however, were different with the China cases showing 85%-95% more profit than the Ghana cases. All uptake levels generate profits over the lifetime of the project except the scenario of the Base Case not considering economies of scale, which is unprofitable with regards to the current FiT and has an IRR of 19%; below the 20% discount rate applied. All cases reveal payback periods less than 5 years with the Base Case without economies of scale and batteries project paying back fastest at 2.9 years as shown in Table 17.

Table 17: Profitability Analysis of Project

Uptake NPV Generation, kWh Unit Profit, US¢/kWh NPV, US$ million IRR Payback, years
Based on Ghana WACC  
Base Case (2%) 532,638,683 0.00851 4.08 22% 4.2
10% 2,663,193,413 0.01914 45.88 25% 3.7
50% 13,315,967,063 0.02978 356.94 28% 3.3
Base Case w/o EOS 532,638,683 -0.0051 -2.43 19% 4.7
Base Case w/o EOS & Batteries 532,638,683 0.0394 18.88 34% 2.9
Based on China WACC  
Base Case (2%) 1,471,153,616 0.0715 82.79 22% 4.2
10% 7,355,768,082 0.0786 455.28 25% 3.7
50% 36,778,840,412 0.0857 2,483.34 28% 3.3

Since the selected business model permits direct sales to end users, and taking Tables 6 and 7 into consideration, higher profits could be accrued should the project secure more PPAs with end users for direct reduced retail, especially with non-residential customers.

CHAPTER 5

5.1 SUMMARY & CONCLUSION

5.1.1 Summary

Ghana has recently endured intense load shedding exercise to suppress electricity demand to match supply. The reason for this exercise is not because peak demand tends to exceed installed capacity, but because dependable and available capacities keep shrinking due to drought and inconsistent supply of natural gas to power baseload plants. According to the Energy Commission (2016) of Ghana, in 2015[8], the total electricity made available for gross transmission was only 11,692 GWh compared to 13,071 GWh in 2014 and 12,927 GWh in 2013―i.e. 1,379 GWh (12%) less than in 2014 and 1,235 GWh (11%) less than in 2013. The net grid electricity transmitted was about 21-26% less than the projected requirement for the year needed for low economic growth forecast (even with VALCO[9] operating at one pot-line instead of three). Consequently, the economy suffered a 4% drop in growth compared to 2014. Peak load on the transmission grid (excluding export) in 2015 was 1,933 MW, about 2% less than in 2014. By the end of the same year, Ghana had an installed electricity capacity of 3,174 MW, of which 2,756 MW was dependable but only 2,058.6 MW (65%) was available for power generation. Hydropower contributed 50.86% to the generation mix whilst thermal contributed 49.10%, with solar contributing a meagre 0.04%.

Government identified this suppressed demand situation as the main cause of the economic downturn plaguing the country since 2012, and implemented a 200MW National Rooftop Solar Programme in 2016 aimed at reducing peak load. As part of the programme, capital subsidy in the form of free solar PV panels up to a maximum of 500Wp is granted to residents who show prove of acquisition of the BOS necessary to complete the system. The programme, however laudable, has not caught the full attention of the public due to varied concerns, one of which is the issue with operation and maintenance (O&M).

This thesis sought to estimate the techno-economic solar potential of Accra, the capital city of Ghana to judge the feasibility of the large-scale deployment of a rooftop solar PV (RSPV) project. To achieve this aim, the solar technical potential was calculated by first using an empirical formula to estimate the total rooftop area suitable for solar PV installation for the Accra Metropolitan Accra (AMA), which is 22.5km2 (11.48m2/cap). This area was then used to calculate the total solar power and energy potentials, 2.56GW AC output and 5,026GWh respectively.

These figures laid the foundation for economic analysis. An economic potential of RSPV was done using 2% technical potential power cover as a Base Case, with 10% and 50% cases also done for comparison utilizing the LCOE approach. The LCOE calculated for the Base Case was 19.15 US¢/kWh, employing a discount rate equal to the average real lending rate in Ghana (20%). Variants of the Base Case calculations were done to compare with scenarios where the system sizing did not include economies of scale and/or batteries. The analyses reveal LCOE values of 20.51 and 16.06 US¢/kWh for Base Case without economies of scale and Base Case without economies of scale and batteries respectively. The 10% and 50% cases led to LCOE values of 18.09 and 17.02 US¢/kWh respectively, matching expectations of LCOE reductions due to economies of scale. A complete re-calculation was done with discount rate equal to the average lending rate from China (5%) aimed at identifying the difference in project profitability when capital investment is sourced from within Ghana and from the international community. The LCOE for the Base Case of this scenario was 12.85 US¢/kWh, 33% lower than the scenario using Ghana’s lending rate.

The analysis also resulted in a unit investment cost of 1,992 US$/kWh for the Base Case, reducing to 1,882 US$/kWh and 1,771 US$/kWh for the 10% and 50% cases respectively. The scenarios without EOS and without EOS and batteries were 2,133 and 1671 US$/kWh respectively. A sensitivity analysis was conducted to judge the robustness of the LCOE to variations in discount rate and O&M. For a ±25% variation in the discount rate, the LCOE values responded by a swing of ± 11%. On the other hand, the LCOE values variated at ±7.2% in response to a ±20% sensitivity variation of the O&M. For the profitability analysis, the projects reveal NPVs of 4.08 US$, 45.88 US$ and 356.94 US$ for the Base Case, 10% and 50% scenarios respectively. The IRRs were 22%, 25% and 28% in the same order, with payback periods of 4.2, 3.7 and 3.3 years respectively.

Discussion of Results

The technical analysis estimate of 22.5km2 of suitable RSPV area for Accra is a modest and promising rooftop area for solar deployment. The 2.56 GW capacity solar potential of Accra is equivalent to 80% of 2015 installed capacity of Ghana. For the year 2016, the total electricity requirement of Ghana was projected to be between 16,798-16,900 GWh with VALCO operating at one pot-line so as to achieve a marginal economic growth of 4.0-4.5% over the previous year; and 18,185-18,737 GWh with VALCO operating at most two pot-lines to achieve a growth above 4.5%. The corresponding total peak demand (excluding suppressed demand) and total transmission system peak for 2016 was projected to be between 2,500-2,736 MW. These projections only lay credence to the need for large scale deployment of distributed power generation especially in congested and high demand locations of Ghana such as Accra. An addition of more than 5,000 GWh from a distributed power project (such as discussed here) would greatly ameliorate the power deficit, release suppressed demand, boost economic activity, and reduce social discontent due to unavailable and unreliable power.

The economic analysis points to an LCOE derived for the Base Case as 19.15 US¢/kWh which leads to a marginal NPV of 4.08 US$ for investment into the RSPV potential for Accra. However, if such a project is pursued by Government, the socio-economic benefits becomes wide and enormous beyond just the direct financial gain expected from a pure private investment perspective. Furthermore, economies of scale plays favourably into profitability and ensures higher returns at higher uptake levels of the project as seen from Table 17. Better still, Government can engage the partnership of a private investor to drive benefits of the project higher in terms of key state-controlled cost exemptions, reductions in administrative cost and bottlenecks for permitting and licensing, ease of negotiating grid connection agreements and PPAs, etc.

The economic analysis also revealed an important aspect of local vs international financing of renewable energy projects (REPs) in Ghana. Due to the high upfront cost of REPs and the relatively low annual operational cost, REPs are more affected by high discount rates compared to fossil fuel power plants. Therefore, investments from a high WACC economy like Ghana gravely reduces the financial viability of such projects. This was clearly recognized in the calculation with the WACC estimate from China which resulted in a 33% LCOE reduction in all three cases. The IRR range for the various projects (22%-28%), particularly in the cases with the Ghana WACC, does not offer much comfort to a local investor who might request for interest rates closer to the nominal rates (30%-38%) in order to hedge against high credit risk. This same situation does not affect the China WACC cases because the IRRs are way above any nominal rates offered in China.

Additionally, the NPVs of the China investment cases are on average 90% higher than those using investments from Ghana. This will be a source of worry and a strong deterrent to local investment in REPs in Ghana. The effect of discount rate variation was also evident from the sensitivity analysis where the Base Case and 10% case lost project profitability at a 25% increase in the discount rates. Relatively, the project exhibited more resilience against O&M variation compared to the discount rate with only the Base Case becoming unprofitable at 20% O&M increase.

The Base Case LCOE without EOS 20.51 US¢/kWh, compares well with the Energy Commission report of 22.41 US¢/kWh and expectedly lower (8.5%) considering that the release from the Commission was over a year ago. The Base Case LCOE without EOS and batteries 16.06 US¢/kWh, is even more closer to the 16.30 US¢/kWh reported by the Commission with an error margin of 1.5%. The unit investment cost for the Base Case, 1,992 US$/kW falls competitively in the range reported by IRENA (2016) for on-grid commissioned and planned utility-scale solar PV projects in Africa―1,200 to 4,900 US$/kW, for the period 2014-2018. IRENA further reports that project announcements in 2016 which are targeting commissioning dates in 2018 are targeting a competitive unit investment cost range of 1,200 to 1,900 US$/kW. These real project scenarios conform with the results derived in this thesis.

Limitations

In completing the thesis, several limitations were identified. Prime amongst them is the unavailable (or inaccessible) literature in the context of the study area (Accra) needed for comparisons to test the robustness of the work carried out. For example, no literature existed or could be accessed on the solar technical potential study of Accra in terms of estimated suitable rooftop area for PV installation or the estimated total solar power potential. Therefore, data obtained from this study although seems appropriate for pre-feasibility on the subject, requires further litmus test if real project development case scenarios are to be considered. Likewise, the LCOE for solar PV systems reported by the Energy Commission in 2016 has no details of assumptions and procedure applied in its derivation, which leaves little room for direct methodology appraisal.

Additionally, recognition must be given to the fact that the LCOE approach adopted for the economic analysis itself has pros and cons as an effective tool for measuring the investment worthiness of a project. The LCOE is a very useful tool owing to its ability to combine both the fixed and variable costs of a project into a single measure to simplify analysis. However, the LCOE tool does not cover all aspects of investment finance and loses some effect due to its standardized nature. Because it projects over the entire duration of a project, it does not cater for the needs of stage-wise implementation of large scale projects, where dramatic shocks can significantly alter the parameters used in the LCOE determination. It also does not cover taxes, depreciation, government subsidies, grants etc., which could all change project landscape. Overall, it is vital to note that real REP investment decisions are affected by specific technological and location characteristics of a project, which include several other factors not reflected by LCOE values.

Also, in estimating revenue sources for the economic analysis, only the FiT was considered although the chosen business model permits direct retail to customers. This was because it was deemed difficult to properly estimate the percentage of customers who will accept a solar PPA from the project in the absence of any model RSPV project of this kind in Ghana.

5.1.2 Conclusions and Recommendations

Ghana, like most countries in Africa, is endowed with significant renewable resources of all forms. Traditionally, hydropower has been the largest renewable power generation resource in Ghana. However, recent hydropower variability, high equivalent cost of thermal generation and consistent cost reductions for renewable power projects necessitate a comprehensive re-adjustment of energy generating policies in favour of renewable distributed generation. Globally, new capacity additions of solar PV have increased twelve-fold from about 6 GW in 2008 to about 71 GW in 2016 (IRENA, 2017). This global growth has virtually bypassed Africa, despite experiencing solar radiation about 52%―117% higher than in most higher solar PV uptake countries like Germany (IRENA, 2016). This thesis lays down the preliminary techno-economic evidence required by the Government of Ghana to pursue detailed study needed to shape policies and partnerships, which are necessary to tap into the solar potential of Accra―and the entire country. A further study is also strongly encouraged to test the robustness of the analysis and findings made in this study.

It is also recommended that detailed financial analysis be done beyond the LCOE analysis and NPV, IRR and Payback to capture the real financial parameters of large scale project deployment especially in a country with relatively low mix of renewable power generation (excluding hydro). Coupled with this, it is advised that project implementation should start at a low utility-scale level possibly by utilizing the chosen business model to target high-end electricity tariff band customers so as to earn from direct power purchase due to the replacement of their retail tariffs (as in Tables 6 and 7), before expanding scope of project to higher scales.

This is because RSPV breakthrough in an emerging solar market like Ghana is expected to face several large-scale implementation challenges. This might necessitate stage-wise small-scale deployments, which means ‘economies of scale’ could end up been eroded. Consequently, the project will plunge into unprofitability with an LCOE of 20.51 US¢/kWh, unless the business model relies on the higher electricity retail market to sell power directly to high-end users.  Finally, it is recommended that access to international funds for investment should be sought for the viability of a project of this scale, and other similar renewable energy projects in Ghana, in lieu of the prohibitive cost of local finance.


[1] “Free on Board” (FOB), is a term in international commercial law specifying at what point respective obligations, costs, and risk involved in the delivery of goods shift from the seller to the buyer.

[2] Cost, insurance and freight (CIF) is a trade term requiring the seller to arrange for the carriage of goods by sea to a port of destination, and provide the buyer with the documents necessary to obtain the goods from the carrier.

[3] A system’s direct current to alternating current (DC-to-AC) ratio is the ratio of the nameplate capacity of the PV modules to the AC-rated capacity of the inverters. For example, a system with a DC-to-AC ratio of 1.2 would have 8.33 kW of inverters installed for every 10 kW of nameplate PV capacity (NREL, 2016b).

[4] Based on an average power consumption of a four person household in Ghana, 1795 kWh/yr (Essah, 2011) and minimum mean daily sunshine hours of 4.7 .

[5] The system efficiency is calculated as a product of the efficiencies of the inverter (0.95), charge controller (0.95), cables (0.95), and battery (0.8)

[6] Days of autonomy are the continuous number of days the battery is expected to deliver power in the event of solar power unavailability

[7] TradingEconomics.com reports a stagnant lending rate of 4.35% in china over the past few years. 5% was chosen as a fair cap.

[8] 2015 is the latest year data available

[9] Volta Aluminium Company (VALCO) is Ghana’s only state-owned aluminium smelter.

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