Portfolio components (mix)
X- Y plot results for the informal urban area community scenario
8.1 Research findings
8.1.5 Optimal portfolios of energy supply technologies for low-income households One of the critical objectives of this study was the selection of an optimal portfolio of energy
supply technologies for low-income households. The portfolios were built using the GP technique linked to a value function to integrate qualitative and quantitative objectives. In the final stage of the project, portfolio adjustment was applied to enable decision-makers to use their knowledge and experience to adjust the portfolio by adding or deleting alternatives.
It was observed that portfolios comprised of energy supply technologies with the least consumption of lifecycle financial resources were preferred. Secondly, portfolios with higher overall scores on qualitative criteria performed better overall. The typical viable and optimal strategy would be a policy option whose portfolio consisted of a combination of solar PV, wind and bioethanol fuel and with solar and wind forming part of a micro-grid catering for electrical needs. The study findings confirmed what has been reached from empirical investigations (Ramanathan and Ganesh,1994, 1995); Doukas et al., 2007); Cherni et al., 2007); Lhendup, 2008); Silva and Nakata, 2009); Stein (2013) and Bueno-López et al., 2019). Cherni (2007) cautioned against the adoption of exclusive and cure-all solutions in an environment characterised by technological advancements.
It is worth noting that a bioethanol fuel portfolio would be more sustainable if bioethanol fuel were produced locally. This will ensure that the community would benefit from the job creation potential of bioethanol fuel. Youth unemployment and underemployment are serious problems in South Africa and are often more severe in rural than in urban areas. White (2012) notes that
“small-scale agriculture is the developing world's single biggest source of employment. With the necessary support, it can offer a sustainable and productive alternative to expanding large- scale, capital-intensive, labour-displacing corporate farming”. The portfolio would also be more successful if combined with a forestry management programme to ensure sustainable growth of bioethanol fuel and the planting of new trees. These GP and MAVT results are consistent with results observed in the literature.
The study established the goal of minimising upfront capital costs was an important one. The economics of energy supply technologies is evolving. For example, as shown under the three study scenarios, the cost of renewable energy technologies is improving, with significant reported declines in the cost of manufacturing and installing some technologies such as solar and wind as technical advances materialise.
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172 The study observed that minimising the operational lifecycle costs was also an equally important goal. Renewable energy technologies are associated with near-zero fuel costs, making them cheaper from a lifecycle cost perspective. As highlighted above, this contrasts with rising costs for the conventional systems, primarily affected by increasing market- determined prices of fossil-based fuels (such as coal, gas etc.). Consequently, it is not surprising that the resulting optimised energy mix from the GP model and MAVT applications was made up of electricity from a micro-grid comprised of a combination of solar PV, wind and bioethanol and LPG and none for all other technologies considered.
The study established that poverty eradication interventions aimed at the poor in rural areas should not be limited to these areas only but also to low-income families living in informal urban settlements. The framework developed for the study was designed to cover different scenarios.. Figure 37 presents a graphical summary of the resulting energy portfolios obtained from applying the augmented Chebychev GP procedure in Chapter 6.
Figure 37: Summary of the Augmented Chebychev GP model results
GP portfolio [Rural area] GP portfolio [Informal urban area]
Source: Augmented Chebychev GP model
Notable differences between the MAVT results and the GP scenarios for informal urban areas are the high proportions of firewood under the technical scenario for informal urban areas.
These differences can be explained by the inclusion of non-qualitative criteria such as safety and cultural considerations, which are included in the MAVT models.
The results imply that decision-makers should consider both quantitative and qualitative criteria, given the ever-increasing informal urban area populations and the expansion of informal settlements in South Africa in planning energy interventions. These populations are primarily people migrating from rural areas to informal urban areas and people who continue
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173 to abide by cultural practices. Figure 38 summarises the energy portfolios obtained from applying the MAVT technique in Chapter 7.
Figure 38: Summary of MAVT model results
MAVT Portfolio [Rural area] MAVT Portfolio [Informal urban area]
Source: MAVT model
Regardless of the differences between MAVT results and GP scenarios, as has been observed in the empirical literature (refer to Section 8.1.2 and Chapter 4), the study results show that rudimentary fuels such as firewood and kerosene, and central grid electrification, have no place in the energy mix for low-income households.
It is also worthwhile noting that despite the results of both the MAVT and GP models indicating that there is no place for firewood, firewood will nonetheless continue to be relied upon among the poorest, as posited in empirical investigations (Davis, 1998; Goldemberg, 2000; Thom, 2000; Gaunt, 2005; and Madubansi and Shackleton, 2006; Matsika et al., 2013, Shackleton, 2017). Figure 39 presents a summary of the current energy portfolios based on 2018 GHS data (Stas SA, 2019).
As discussed in Chapter 2 and as shown in Figure 39 (see also Section 2.4), firewood accounts for approximately 48 per cent of energy requirements for cooking in traditional dwellings and 51 per cent in informal urban areas. In the informal urban dwellings, over 30 per cent of households rely on kerosene and 7 per cent on firewood, respectively, for cooking.
Around 40 per cent and seven per cent of households in traditional houses rely on firewood and kerosene, respectively, for cooking (Stats SA, 2019). The high use of kerosene in informal urban area dwellings is attributed to its affordability.
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174 Figure 39: Status quo: energy portfolio for low-income households (cooking)
Status quo: Rural area Status quo: Informal urban area
Source: Stats SA (2019)
This study shows how decision-makers can make decisions about both sources and uses of energy. It points to several overlooked opportunities that could be activated to help low-income households fully transition to greater use of and benefit from modern energy supply technologies. By focusing on poor communities and examining their energy portfolios, the researcher discovered previously overlooked opportunities that encourage the adoption and use of modern and improved energy sources.
The study results showed that there is an opportunity to enable continued and greater use of new energy sources. However, the affordability and reliability of these sources are barriers to continued and greater consumption. Few households could afford to solely use a new, improved energy source at desired levels. Most poor communities, it was also discovered, cannot afford to pay for ongoing operational costs on a regularly. Households accustomed to utilising free firewood or living without grid power may find it difficult to meet the new costs of R0.59 per meal for grid electricity and R1.32 per meal for LPG, respectively.
This study established that the expansion of the primary grid has not decreased the use of rudimentary solid fuels and paraffin for cooking. There is, therefore, an ample opportunity to grow the energy portfolios of rural households in beneficial ways through entirely new uses of energy, through the addition of cooling, small to medium refrigeration, heating and entertainment appliances. The study shows that there are strong linkages and trade-offs between goals. Synergies would need to be exploited further to maximise the quality of the decisions. At the same time, trade-offs would also need to be handled in a manner that results
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175 in the development of a fully optimised portfolio. The projected declining costs of renewable energy technologies are likely to narrow the trade-offs between goals, particularly the minimisation of upfront capital costs and environmental goals that appeared at a tangent at the time of the study.