**4.3 Results of base scenario S1**

Starting with a look on the economics of the base scenario depicted in **Figure 5**, the total system costs (52,562 USD) slightly exceed total revenues (52,560 USD) by 2 USD—the profitability break-even point is almost reached. In this scenario, the maximum field capacity of 15 ha is utilized, covering the entire domestic food demand (70 tons) and selling the remaining 193 tons to external market participants. Maize grain is sold to the domestic community at the market price of 200 USD per ton and accounts for one quarter of total revenues. On the cost site, the biggest contributor is labor costs related to agriculture, which accounts for 37% of the total costs. The second biggest contributor is investment costs, 30% of total


**Table 1.** *Modeled scenarios.*

*Economic Development of Rural Communities in Sub-Saharan Africa through Decentralized… DOI: http://dx.doi.org/10.5772/intechopen.90424*

#### **Figure 5.**

15 ha. Mismatches in food supply and demand can be balanced by selling or purchasing maize grain on external markets for 200 USD per ton. Additionally, maize stover and chicken manure is fermented into biogas. The capacity of the biogas digestion process is limited to 367.5 kg/day due to the amount of manure available from approx. 3000 chickens in a nearby town. The solar and rainfall time series are obtained by data from geographical information systems (GIS) or online data bases. The technical and economic parameters for all technologies depicted in **Figure 2** are listed in the Appendix. Lastly, the weighted average cost of capital is assumed to

The proposed scenario development, summarized in **Table 1**, evaluates the economic feasibility of a EWFS for sustainable project operation and as an attractive investment for its stakeholders. The base scenario (S1) analyzes these factors for a complete EWFS, as designed in **Figure 2**, with a cost of capital at the average market rate of 15%, the integration of all power generation technologies (diesel generators, solar photovoltaics, and biogas generators), and the coupling of the three sectors: energy, water, and food. Secondly, the system's sensitivity to changes in the cost of capital is tested through a parameter variation for discrete values between WACC 0% and WACC 30% (S2). The WACC variation serves as an appropriate starting point to evaluate the economic attractiveness of a decentralized EWFS in SSA. Indeed, there are highly investment-intensive installations related to an EWFS, and the WACC is therefore of great relevance. The third analysis tests the changes of power-generating technologies in the system design. It compares the fully fledged EWFS, in which electricity is generated from diesel, solar, and biogas,

with a system without biogas and a system based exclusively on diesel.

The techno-economic results for all scenarios are listed in the Appendix.

Starting with a look on the economics of the base scenario depicted in **Figure 5**, the total system costs (52,562 USD) slightly exceed total revenues (52,560 USD) by 2 USD—the profitability break-even point is almost reached. In this scenario, the maximum field capacity of 15 ha is utilized, covering the entire domestic food demand (70 tons) and selling the remaining 193 tons to external market participants. Maize grain is sold to the domestic community at the market price of 200 USD per ton and accounts for one quarter of total revenues. On the cost site, the biggest contributor is labor costs related to agriculture, which accounts for 37% of the total costs. The second biggest contributor is investment costs, 30% of total

**Scenario title WACC (%) Technologies Sectors** S1: Base scenario 15 DG + PV + BG E + W + F S2: WACC variation 0–30 DG + PV + BG E + W + F S3: Technology variation 0, 15, 30 DG,DG + PV E + W + F

be at the market rate of 15% according to the study [17].

*4.1.1 Scenario development*

*Regional Development in Africa*

**4.2 Optimization results**

**Table 1.** *Modeled scenarios.*

**106**

**4.3 Results of base scenario S1**

*Costs and revenues for EWFS with WACC = 15%.*

**Figure 6.**

costs—consisting of depreciation expenses (9%) and cost of capital (21%). Diesel expenses (fuel costs) account for 12% of total costs.

Provided that the domestic community purchases its food from the system and water is provided free of charge, the 2 USD loss must be allocated to the total domestic electricity consumption of 42.5 MWh/year equaling an electricity fee of 0.01 USD/kWh. The total annual costs for energy, water, and food equal 45.52 USD per capita.

Total capital expenditure (CapEx) for long-term assets amount to 98.4 k USD, which is only 30% of the cumulative investment costs over the respective useful life of the assets. The remaining 70% of the cumulative investment costs originates from the WACC and is distributed to investors. Analyzing the annual investment costs on a technology level, as depicted in **Figure 6**, it is observed that the majority of the annual investment costs is invested in electricity-related technologies (53%), while 38% is spent on food-related assets and 10% on water-related assets. Within the costs for energy-related investments, the majority (55%) is invested in solar photovoltaics and only 5% in nonrenewable electricity generation technologies (diesel generator). However, the diesel generator accounts for a drastically greater share of total installed capacity (14%) then of total investment costs (5%) illustrating the low specific investment costs of this technology. In contrast, the relatively lower ratios of installed capacity to investment costs for photovoltaic and biogas systems reflect the high CapEx intensity of renewable energy technologies.

The unit costs of the respective commodities, as shown in **Table 2**, depict that the costs related to producing 1 ton of maize grain (164 USD) are below the sales price of 200 USD. The profit generated from this revenue-cost difference is used to provide water free of charge and subsidize electricity prices to the domestic community. The unit cost of electricity (LCOE) is at 0.22 USD/kWh. Due to the relatively high cost of capital as well as the CapEx-intensive photovoltaic and battery system, LCOE from PV (0.18 USD/kWh) is still above values around

*Investment costs and capacities of power generation technologies.*


scenario, maize grain production is still at 104 tons per year and hence more than sufficient to meet the annual domestic demand of 70 tons. The domestic demand for electricity and water remains constant, but cultivable farm land decreases.

*Economic Development of Rural Communities in Sub-Saharan Africa through Decentralized…*

investment costs and fuel costs are the main drivers of profitability.

*DOI: http://dx.doi.org/10.5772/intechopen.90424*

**Figure 7** provides an overview of the annual revenues and costs of the respective profit maximizing system design. Revenues move proportionally to the food production, remaining constant all through the WACC 20% scenario (52.6 k USD), and decrease by 60% for WACC 30% to 20.9 k USD per year. Agriculture-related labor costs and other operating costs move in line with revenues, accounting for approx. 37 and 21%, respectively. Investment costs and fuel costs increase with higher WACC as they cover investor returns and an increase in consumed diesel; thus,

**Figure 8** shows the EWFS profitability. A fully socially financed system (WACC 0%) generates 14.1 k USD in annual profits, equivalent to a profit margin of 27%. In the case of a WACC 10%, which could represent the support of a financial cooperative, costs would increase by 24%, resulting in an annual net profit of 4.8 k USD, equivalent to a 9% net profit margin. The profit break-even point is reached for a WACC value slightly below the expected market rate of 15%; for WACC 15% a net loss of 1.8 USD is generated. Under the premise of free electricity and water, increasing net losses are generated for WACC values greater than 15%, which implies that the business model is no longer economically sustainable. For the scenario of WACC 30%, costs exceed revenues by the factor of 0.5, resulting in an annual net loss of 10.4 k USD. The profit overview illustrates an almost linear relationship between the cost of capital and the system profitability. An increase in WACC by one percentage point results in a decrease in profits by 880.42 USD.

Regarding the cost analysis, investment costs are the only cost category factored

in the cost of capital, as it is assumed that all other expenses can be financed internally going from period to period. Consequently, it is intuitive that with an

*Costs and revenues for EWFS for WACC variation from 0 to 30%.*

*EWFS profitability for WACC variation from 0 to 30%.*

**Figure 7.**

**Figure 8.**

**109**

#### **Table 2.**

*Unit costs of electricity, water, and food.*


#### **Table 3.**

*Total financial value generated.*

0.13 USD/kWh, which is the benchmark for small-scale PV systems in Germany [34]. Sufficient profits from maize grain production enable an almost complete subsidization of electricity for the local community and burden households with only 0.03 USD for electricity per year to cover the loss of the system.

The financial attractiveness of the project for all major stakeholders is shown in **Table 3**. This analysis does not include a financial valuation of the water and electricity that is provided to the domestic community free of charge, nor does it account for social and environmental value added. Some system expenses can be considered as income to the respective shareholders. Consequently, labor expenses of 19,426 USD are income to the domestic community. The system loss of 2 USD is allocated among the entire domestic community. The net cash flow from labor and system losses to the community of 19.4 k USD exceed total community expenses of 14 k USD for food. Annual returns to investors of 10.9 k USD match the market cost of capital (15%). The total financial value added to the main stakeholders amounts to 30.3 k USD per year.

Altogether, the base scenario presents an economically feasible solution to provide the domestic community of Kpori with electricity and water free of charge as well as to produce enough maize grain to meet the domestic demand and sell crop surpluses on an external market. Total funds of 98.4 k USD must be raised to finance long-term assets. The maximum capacity of farmland and biogas is utilized; 82% of the consumed electricity is from renewable resources.

#### **4.4 Results of WACC variation scenario S2**

Profit overview illustrates an almost linear relationship between the cost of capital and the system profitability. Results show that for all scenarios between WACC 0% and 20%, the cost-minimizing system is designed in a dimension that the maximum farmland capacity of 15 ha is cultivated. Consequently, the annual demand and supply for all three resources energy, water, and food are almost constant at 80 MWh, 205,000 m<sup>3</sup> , and 263 tons, respectively. For the WACC 30%

### *Economic Development of Rural Communities in Sub-Saharan Africa through Decentralized… DOI: http://dx.doi.org/10.5772/intechopen.90424*

scenario, maize grain production is still at 104 tons per year and hence more than sufficient to meet the annual domestic demand of 70 tons. The domestic demand for electricity and water remains constant, but cultivable farm land decreases.

**Figure 7** provides an overview of the annual revenues and costs of the respective profit maximizing system design. Revenues move proportionally to the food production, remaining constant all through the WACC 20% scenario (52.6 k USD), and decrease by 60% for WACC 30% to 20.9 k USD per year. Agriculture-related labor costs and other operating costs move in line with revenues, accounting for approx. 37 and 21%, respectively. Investment costs and fuel costs increase with higher WACC as they cover investor returns and an increase in consumed diesel; thus, investment costs and fuel costs are the main drivers of profitability.

**Figure 8** shows the EWFS profitability. A fully socially financed system (WACC 0%) generates 14.1 k USD in annual profits, equivalent to a profit margin of 27%. In the case of a WACC 10%, which could represent the support of a financial cooperative, costs would increase by 24%, resulting in an annual net profit of 4.8 k USD, equivalent to a 9% net profit margin. The profit break-even point is reached for a WACC value slightly below the expected market rate of 15%; for WACC 15% a net loss of 1.8 USD is generated. Under the premise of free electricity and water, increasing net losses are generated for WACC values greater than 15%, which implies that the business model is no longer economically sustainable. For the scenario of WACC 30%, costs exceed revenues by the factor of 0.5, resulting in an annual net loss of 10.4 k USD. The profit overview illustrates an almost linear relationship between the cost of capital and the system profitability. An increase in WACC by one percentage point results in a decrease in profits by 880.42 USD.

Regarding the cost analysis, investment costs are the only cost category factored in the cost of capital, as it is assumed that all other expenses can be financed internally going from period to period. Consequently, it is intuitive that with an

**Figure 7.** *Costs and revenues for EWFS for WACC variation from 0 to 30%.*

**Figure 8.** *EWFS profitability for WACC variation from 0 to 30%.*

0.13 USD/kWh, which is the benchmark for small-scale PV systems in Germany [34]. Sufficient profits from maize grain production enable an almost complete subsidization of electricity for the local community and burden households with

**Stakeholder Financial value generated [USD/year]**

Labor 19,425 Community �2 Return to investors 10,869 Total financial value generated [USD/year] 30,293

**Commodity Unit Costs** Electricity total USD/kWh 0.22 Electricity from diesel generator USD/kWh 0.41 Electricity from solar photovoltaics USD/kWh 0.18 Electricity from biogas generator USD/kWh 0.14 Water USD/m<sup>3</sup> 0.05 Food USD/ton 164

**Table 3**. This analysis does not include a financial valuation of the water and electricity that is provided to the domestic community free of charge, nor does it account for social and environmental value added. Some system expenses can be considered as income to the respective shareholders. Consequently, labor expenses of 19,426 USD are income to the domestic community. The system loss of 2 USD is allocated among the entire domestic community. The net cash flow from labor and system losses to the community of 19.4 k USD exceed total community expenses of 14 k USD for food. Annual returns to investors of 10.9 k USD match the market cost of capital (15%). The total financial value added to the main stakeholders amounts

The financial attractiveness of the project for all major stakeholders is shown in

Altogether, the base scenario presents an economically feasible solution to provide the domestic community of Kpori with electricity and water free of charge as well as to produce enough maize grain to meet the domestic demand and sell crop surpluses on an external market. Total funds of 98.4 k USD must be raised to finance long-term assets. The maximum capacity of farmland and biogas is utilized;

Profit overview illustrates an almost linear relationship between the cost of capital and the system profitability. Results show that for all scenarios between WACC 0% and 20%, the cost-minimizing system is designed in a dimension that the maximum farmland capacity of 15 ha is cultivated. Consequently, the annual demand and supply for all three resources energy, water, and food are almost

, and 263 tons, respectively. For the WACC 30%

only 0.03 USD for electricity per year to cover the loss of the system.

82% of the consumed electricity is from renewable resources.

**4.4 Results of WACC variation scenario S2**

constant at 80 MWh, 205,000 m<sup>3</sup>

**108**

to 30.3 k USD per year.

**Table 2.**

**Table 3.**

*Unit costs of electricity, water, and food.*

*Regional Development in Africa*

*Total financial value generated.*

increase in cost of capital, the system design shifts towards CapEx-light technologies. Therefore, the share of CapEx in the cumulative investment costs continuously decreases, and the share of investment costs in total costs tendentially increases (**Figure 9**). This in turn implies that investment costs are generally impacted stronger by the increasing returns to investors than by the reduction in CapEx. Nevertheless, there are some exceptions which explain the dip around WACC 16% where the increase in cost of capital is overcompensated by a drastic decrease in CapEx of 11%. Highest capital expenditures and thus largest external funding requirements occur in the WACC 0% scenario, in which 139.0 k USD is invested in long-term assets. With an increase in WACC, the required funding decreases by 70% to 41.7 k USD in the WACC 30% scenario. At the WACC market rate of 15%, total required funding amounts to 98.4 k USD and accounts for 30% of cumulative investment costs. **Figure 10** shows the variation of process capacity and electric power generation with the increase of WACC. Since PV is the most CapExintensive power generation technology with 1400 USD/kW of installed capacity followed by the biogas generator with 675 USD/kW and diesel generator with 500 USD/kW (see Appendix), PV is continuously substituted by diesel generators as the WACC increases. With the decrease in installed capacity of the inflexible but volatile solar power source—and the limited storage capacity due to high investment costs related to the corresponding battery system—diesel-generated electricity increases as biogas is already fully utilized. For low WACC values, diesel power accounts for only a small share of the total electricity, but starting at WACC 13%, diesel-generated electricity already accounts for a substantial share of 12% and continues to increase to around one third of total produced electricity for WACC 20%. Biogas capacity and energy remain almost constant at their maximum levels.

**Table 4** outlines the variation of the unit costs of electricity, water, and food with increasing WACC. With an increase in WACC, the weighted average LCOE increases from 0.08 USD/kWh (WACC 0%) to 0.29 USD/kWh (WACC 30%). This is not only because the LCOE from PV and LCOE from biogas system (BG) increase by a factor of 3.9 and 2.6, respectively, but predominantly because the electricity mix shifts from the relatively cheaper technologies with high CapEx (PV and BG) to the more expensive but investment light diesel generator (DG). The LCOE from DG slightly decrease from 0.46 USD/kWh (WACC 0%) to 0.41USD/kWh for WACC 15% before again increasing to 0.45 USD/kWh (WACC 30%). This variation in LCOE from DG is related to the opposing impact of an increasing utilization rate and increasing specific investment costs. The development of LCOE is also reflected in the development of the unit costs of water and food as both—the access to water

*Economic Development of Rural Communities in Sub-Saharan Africa through Decentralized…*

*DOI: http://dx.doi.org/10.5772/intechopen.90424*

and the production of food—require a substantial amount of electricity.

**Commodity Unit Costs**

Electricity total USD/kWh 0.08 0.22 0.29 Electricity from diesel generator USD/kWh 0.46 0.41 0.45 Electricity from solar photovoltaics USD/kWh 0.08 0.18 0.31 Electricity from biogas generator USD/kWh 0.08 0.14 0.22 Water USD/m<sup>3</sup> 0.03 0.05 0.05 Food USD/ton 132 164 178

decreases from there on.

*Unit costs of electricity, water, and food.*

*Total financial value generated for WACC variation from 0 to 30%.*

**Table 4.**

**Figure 11.**

**111**

The total financial value generated, visualized in **Figure 11**, includes the system costs 19.4 k USD (WACC 0–20%) of annual labor expenses related to farming that can be paid to domestic workers. Because the WACC 30% scenario does not utilize the maximum farmland capacity, labor costs are as low as 7.7 k USD. As the WACC represents the relative return to investors, this increases as long as CapEx decreases slower than the increase in cost of capital compensates for. Net profits to the domestic community behave reversely and decrease with an increasing WACC. The maximum total financial value added by the system to the major stakeholders is reached for WACC 0%, where the annual cumulative financial value added to the domestic community and investors adds up to 33.5 k USD and continuously

**WACC 0% WACC 15% WACC 30%**

#### **Figure 9.**

*Capital expenditure and cumulative investment costs for WACC variation from 0 to 30%.*

#### **Figure 10.**

*Process capacities and electric power generation for WACC variation from 0 to 30%.*

*Economic Development of Rural Communities in Sub-Saharan Africa through Decentralized… DOI: http://dx.doi.org/10.5772/intechopen.90424*

**Table 4** outlines the variation of the unit costs of electricity, water, and food with increasing WACC. With an increase in WACC, the weighted average LCOE increases from 0.08 USD/kWh (WACC 0%) to 0.29 USD/kWh (WACC 30%). This is not only because the LCOE from PV and LCOE from biogas system (BG) increase by a factor of 3.9 and 2.6, respectively, but predominantly because the electricity mix shifts from the relatively cheaper technologies with high CapEx (PV and BG) to the more expensive but investment light diesel generator (DG). The LCOE from DG slightly decrease from 0.46 USD/kWh (WACC 0%) to 0.41USD/kWh for WACC 15% before again increasing to 0.45 USD/kWh (WACC 30%). This variation in LCOE from DG is related to the opposing impact of an increasing utilization rate and increasing specific investment costs. The development of LCOE is also reflected in the development of the unit costs of water and food as both—the access to water and the production of food—require a substantial amount of electricity.

The total financial value generated, visualized in **Figure 11**, includes the system costs 19.4 k USD (WACC 0–20%) of annual labor expenses related to farming that can be paid to domestic workers. Because the WACC 30% scenario does not utilize the maximum farmland capacity, labor costs are as low as 7.7 k USD. As the WACC represents the relative return to investors, this increases as long as CapEx decreases slower than the increase in cost of capital compensates for. Net profits to the domestic community behave reversely and decrease with an increasing WACC. The maximum total financial value added by the system to the major stakeholders is reached for WACC 0%, where the annual cumulative financial value added to the domestic community and investors adds up to 33.5 k USD and continuously decreases from there on.


#### **Table 4.**

increase in cost of capital, the system design shifts towards CapEx-light technologies. Therefore, the share of CapEx in the cumulative investment costs continuously decreases, and the share of investment costs in total costs tendentially increases (**Figure 9**). This in turn implies that investment costs are generally impacted stronger by the increasing returns to investors than by the reduction in CapEx. Nevertheless, there are some exceptions which explain the dip around WACC 16% where the increase in cost of capital is overcompensated by a drastic decrease in CapEx of 11%. Highest capital expenditures and thus largest external funding requirements occur in the WACC 0% scenario, in which 139.0 k USD is invested in long-term assets. With an increase in WACC, the required funding decreases by 70% to 41.7 k USD in the WACC 30% scenario. At the WACC market rate of 15%, total required funding amounts to 98.4 k USD and accounts for 30% of cumulative investment costs. **Figure 10** shows the variation of process capacity and electric power generation with the increase of WACC. Since PV is the most CapExintensive power generation technology with 1400 USD/kW of installed capacity followed by the biogas generator with 675 USD/kW and diesel generator with 500 USD/kW (see Appendix), PV is continuously substituted by diesel generators as the WACC increases. With the decrease in installed capacity of the inflexible but volatile solar power source—and the limited storage capacity due to high investment costs related to the corresponding battery system—diesel-generated electricity increases as biogas is already fully utilized. For low WACC values, diesel power accounts for only a small share of the total electricity, but starting at WACC 13%, diesel-generated electricity already accounts for a substantial share of 12% and continues to increase to around one third of total produced electricity for WACC 20%. Biogas capacity and energy remain almost constant at their maximum levels.

*Regional Development in Africa*

*Capital expenditure and cumulative investment costs for WACC variation from 0 to 30%.*

*Process capacities and electric power generation for WACC variation from 0 to 30%.*

**Figure 9.**

**Figure 10.**

**110**

*Unit costs of electricity, water, and food.*

*Total financial value generated for WACC variation from 0 to 30%.*

**Figure 11.**

For WACC 0%, the system profits of 14.1 k USD are distributed to the domestic community, corresponding to 45.61 USD per capita—0.10 more than the total expenses required for food. The market-based financing scenario (WACC 15%) breaks even (net loss of 1.8 USD). A finance system with WACC 30% generates a loss of 10.4 k USD, which implies an electricity price of 0.25 USD/kWh or annual costs of 33.84 USD per capita for electricity and total costs of 79.45 USD per capita for energy, water, and food.

fully fledged EWF system generates an annual net loss of 10.4 k USD, while the DG + PV EWF system loses 18.7 k USD and the pure DG EWF system 18.9 k USD. On a per capita level, this means that total annual costs for energy and water for a domestic inhabitant amounts to 33.8 USD (DG + PV + BG), 60.6 USD (DG + PV), and 61.4 USD (DG). In terms of consumed electricity, this implies a price of 0.25 USD/kWh for the fully fledged EWF system, 0.44 USD/kWh for the DG + PV EWF

*Economic Development of Rural Communities in Sub-Saharan Africa through Decentralized…*

Out of this analysis, it is clear that a purely diesel-based EWF system is not sufficiently economical to provide the domestic community with free electricity and water on a sustainable basis, regardless of the cost of capital. The extension of this system by photovoltaics is only the first step towards a superior economic solution in which biogas generators are included as well. Especially for higher cost of capital, the positive financial impact of photovoltaics decreases as investor returns increase and the area of application decreases as agricultural activities decline. Regardless of the WACC, from a financial standpoint, the deployment of

This contribution presents an economic analysis of decentralized energy-waterfood systems and their capability to provide economic-feasible solutions for rural electrification and thus the potential to enable economic development of the rural population in sub-Saharan Africa. Their decentralized design avoids the financial and governmental obstacles coming with electrification through grid extension. Biogas motors as controllable power generators substitute the costly and environmental unfriendly use of diesel generators. Although the deployment of water pumps increases the system investment costs, they lead to two major advantages compared to micro-grids without their utilization. Firstly, they are flexible loads opposite to most private power consumers (e.g., light bulbs). The water pumps are powered by cheap solar power during daytime with little or even without use of costly battery storage. Secondly, water pumps are productive power consumers opposite to private consumption, because their utilization enables year-round agriculture, which increases local productivity. Hence the local population is enabled to pay back the investment costs despite their formerly low purchase power. The leastcost modeling on the case study of the rural community Kpori, a 300-inhabitant farming village in northern Ghana, confirmed this hypothesis. The system integration of biogas generators and water pumps to closed-loop energy-water-food systems reduces the costs significantly compared to current electrification approaches with diesel generators only or diesel generators combined with solar photovoltaics and batteries. The decreased demand of costly batteries and diesel and increased profits from year-round agriculture lead to annual costs of 2 USD for the for electricity and water supply of the community compared to 17,326 USD for power supply just with diesel, assuming WACC of 15% and that the profits from agricultural sales subsidize the power supply. The cost analysis of these modeling results shows that 37% of the costs are spent for farming salaries and just 9% on CAPEX but 21% on capital costs due to the WACC of 15%. The remaining costs result from costs for fuel and other operation costs such as maintenance. The conducted variation of WACC showed on the one hand that this has a strong impact on the LCOE, which are 0.08 USD/kWh for WACC of 0%, 0.22 USD/kWh for WACC of 15%, and 0.29 USD/kWh for WACC of 30%. On the other hand, increasing WACC leads to significant reduction of installed PV capacities and increased share of power from diesel generators. The utilization of biogas is almost independent of the WACC

system, and 0.45 USD/kWh for the pure DG EWF system.

*DOI: http://dx.doi.org/10.5772/intechopen.90424*

biogas systems is indispensable.

**5. Conclusions and outlook**

**113**

Altogether, there is a strong impact of the costs of capital on the financial and technical parameters of the system. The maximum field capacity is utilized up to the WACC 20% scenario, and even for WACC 30%, the food production of a leastcost system would be sufficient to meet the domestic demand. An increase in the cost of capital by 1% leads to a decrease in system profits by 880 USD. The required funds to finance long-term assets amount to 139.0 k USD for WACC 0% and decrease from there on as CapEx-intensive technologies such as PV are increasingly substituted with investment light technologies such as diesel.

#### **4.5 Results of technology variation scenario S3**

The costs, revenues, and profit for scenario S3 are depicted in **Figure 12**. For WACC 0%, the cost-minimizing system is designed in a dimension that the maximum farmland capacity is utilized, regardless of the available power generation technologies. Since revenues are directly proportional to the maize grain production, annual revenues are constant at 52.6 k USD. It can be clearly seen that system costs rise with the constraints on combination of power generation technologies. While the total annual costs for the fully fledged system amount to 38.5 k USD, the omission of biogas leads to a cost increase by 29%, while the omission of biogas and photovoltaics leads to an increase by 74% to 66.8 k USD. Hence, a system in which electricity is exclusively generated from diesel is not even net-profitable in a fully socially financed scenario and thus cannot sustainably provide the domestic community with energy and water free of charge. In order to cover the net losses, 46.4 USD per capita and year or 0.34 USD/kWh are charged for electricity. As the WACC increases to 15%, only the fully fledged EWF system operates at full food production, while the omission of biogas reduces the agricultural productivity by 16% and the absence of both renewable energy sources reduces the productivity by 68% to 70 tons per year, which is just sufficient to feed the domestic community. While the fully fledged EWF system breaks even, the unavailability of biogas prevents the systems from being profitable. Net losses for the DG + PV EWF system of 15.4 k USD and 17.3 k USD for the pure DG EWF system imply annual electricity and water expenses of 50 USD and 56.3 USD per capita, respectively; allocated to power consumption, this equals 0.36 USD/kWh and 0.41 USD/kWh, respectively.

In the WACC 30% scenario, none of the EWF systems utilizes the maximum field capacity. While the fully fledged system still produces enough maize grain to provide for the domestic community (104 tons), the DG + PV EWF system and the pure DG EWF system produce just 13 tons and 8 tons, respectively. As the trend of declining profitability with an increase in WACC continues to proceed, even the

**Figure 12.**

*Costs and revenues variation in power generation technology choice for WACC = 0, 15, and 30%.*

*Economic Development of Rural Communities in Sub-Saharan Africa through Decentralized… DOI: http://dx.doi.org/10.5772/intechopen.90424*

fully fledged EWF system generates an annual net loss of 10.4 k USD, while the DG + PV EWF system loses 18.7 k USD and the pure DG EWF system 18.9 k USD. On a per capita level, this means that total annual costs for energy and water for a domestic inhabitant amounts to 33.8 USD (DG + PV + BG), 60.6 USD (DG + PV), and 61.4 USD (DG). In terms of consumed electricity, this implies a price of 0.25 USD/kWh for the fully fledged EWF system, 0.44 USD/kWh for the DG + PV EWF system, and 0.45 USD/kWh for the pure DG EWF system.

Out of this analysis, it is clear that a purely diesel-based EWF system is not sufficiently economical to provide the domestic community with free electricity and water on a sustainable basis, regardless of the cost of capital. The extension of this system by photovoltaics is only the first step towards a superior economic solution in which biogas generators are included as well. Especially for higher cost of capital, the positive financial impact of photovoltaics decreases as investor returns increase and the area of application decreases as agricultural activities decline. Regardless of the WACC, from a financial standpoint, the deployment of biogas systems is indispensable.
