The Renewable Energy Contribution

Published Date: 02 Nov 2017

On 2003 the government, which has committed to reduce the GHG emissions, published the White Paper on Renewable Energy, whose main target was:

‘’10,000 GWh (0.8 Mtoe) renewable energy contribution to final energy consumption by 2013, to be produced mainly from biomass, wind, solar and small-scale hydro. This is approximately 4 percent (1,667 MW) of the estimated electricity demand by 2013 (41,539). - The renewable energy is to be utilized for power generation and non-electric technologies such as solar water heating and bio-fuels.’’

South Africa’s total electricity production was 244,607 GWh (2004). Consequently given its strong industrial and financial sectors, one might think that this is a target easy to achieve. In contrast, due to its many years cut off from the international trends, it is difficult to develop a sound renewable energy market and overcome the barriers that have appeared. Therefore the government has asked World Bank’s assistance. At this point, it must be stressed out that the World Bank’s and the GEF’s help did not include lending; the GEF’s funds provided solely technical assistance, since South Africa has sufficient financial resources to fund renewable energy investments.

In brief, the project’s objective was to establish the appropriate policy, regulatory frameworks and build capacity for renewable energy development in South Africa. Its long run target was to help the government to meet the ‘White Paper on Renewable Energy’ target, by eliminating the barriers towards a renewable energy market. It was based in ‘’cost supply curve’’ of various renewable energy technologies, whose technical feasibility was examined in a study conducted before the project (Figure 1).

Looking at Figure 1, one can make some important deductions:

• Wind is not part of the first 10,000 GWh

• All of the landfill gas potential is within the first 10,000 GWh (and occupies a significant portion of the first 1,000 GWh)

• The balance of the 10,000 GWh target is made up of commercial solar water heating, small hydro, pulp & paper, and the sugar industry

Therefore, the project had two main components:

Renewables-based power generation in South Africa: Technical assistance (TA) and capacity building will eliminate the barriers towards a renewable energy market.

Commercial solar water heating: Focusing only on the commercial segment technical assistance will tackle the problems faced by the CSWH market.

This report tries to make a fair critique on the second component’s economic analysis, as part of this project’s appraisal.

Annex 9 of the Project Appraisal Document contains the economic analysis of a potential CSWH investment. A financial analysis did not deemed important, since these systems are already financially feasible. Besides some systems have already be installed in the absence of government’s intervention. While these projects will be financed only by the private sector, the economic analysis is based in the potential investor’s capital cost. Nonetheless, the benefits, in terms of energy savings and hence CO2 avoided, accrued from it, are considered as benefits for the society. The results show that these kind of investments are economically attractive.

Although this method of economic analysis (i.e. economic analysis of a potential project that is promoted by the REMT project in order to be confident that latter can proceed) is clear and simple, one other approach would be much more interesting.

In the subsequent analysis, the data used are coming exclusively from the South Africa: Renewable Energy Market Transformation (REMT) Project - Economic and Financial Analysis Due Diligence and the project’s appraisal document.

Economic and Sensitivity analysis

Economic Analysis

Instead of an economic analysis reflecting the social cost and benefits of the project, they are making an economic analysis for one of the potential projects that this policy will promote. They argue that if this economic analysis result in net benefits (IRR>0) then they will proceed with confidence that they project will succeed its objectives. But, there are some significant cost and benefits that cannot be accounted for in the analysis provided. Benefit = Income and how this project will affect the labour market in South Africa. Cost = the money that GEF provides. Even though this is a technical assistance project, the capital cost should be added to the capital costs of the project, as some analysts argue.

The social profit measures the effect of the project on the fundamental objectives of the whole economy.

‘’Consideration of alternatives is the single most important feature of proper project analysis throughout the project cycle, from the development plan for the particular sector through identification to appraisal. If economic analysis is to make a maximum contribution to the attempt to ensure that scarce resources are used to the best advantage for the country, it should be used from the earliest phases of this process of successive shifting and narrowing down the options that are open to the country. ‘’ Economic Analysis of Projects, Lyn Squire for the World Bank

Sensitivity analysis

Economic Analysis of Projects, Lyn Squire for the World Bank

Uncertainty is inherent in project analysis. Estimates of costs and demand, of shadow prices and the parameters underlying them, and of consumer surplus and externalities are approximate even for the present, and uncertainty increases when those estimates are projected into the future, as the analysis requires. A question, therefore, is how this uncertainty is to be taken into account in the choice of projects.

First, the calculation of NPV and IRR should include the best estimates of the variables and parameters used. These estimates should be the expected values and should not be biased from the analyst (e.g. conservative estimates). However, actual values may diverge from the expected values. It is essential to calculate the NPV’s sensitivity to potential change into key parameters. One very simple way to do that, is to change the most important assumptions, either one by one or some of them together, by a certain percentage and find the respective changes to the project’s NPV.

Such an analysis is essential to identify the factors that play a key role to the project’s outcome. It can help to focus on critical variables’ control which requires greater attention if the uncertainties are to be diminished. Moreover it might be useful for the government to focus on critical areas that need more supervision to ensure the expected outcome.

Which parameters should be examined is a matter of judgement but it is important to cover all the plausible scenarios. Attention must be draws, not only to the magnitude of a variable, but also to the range that this variable is most likely to attain. Furthermore it is very important to identify any correlations between different variables. This problem would make the analysis very difficult but some techniques that have been developed could be used (risk analysis).

Even though risk analysis can identify the risk that a project might face, cannot do anything to eliminate them. None the less, it gives a great tool to the decision maker to tackle these uncertainties. However, some times the investigation cost might exceed the benefit of expected risk reduction, therefore a risk analysis might not worth.

The use of net present expected value as a measure of a project’s outcome implies that the government is indifferent to risk. Although this might be justifiable, as the total risk is spread to the whole nation and to each one of the citizens, this is not the case in some projects, which have a great impact on income or focus on a specific relatively small group of people.

Whether or not we structure a CBA explicitly in terms of contingencies and their probabilities, we always face some uncertainty about the magnitude of the impacts we predict and the value we assign to them. The purpose of sensitivity analysis is to acknowledge these uncertainties. In particular, it should convey how sensitive predicted net benefits are to changes in assumptions. If the sign of net benefits does not alter when we consider the range of reasonable assumptions, then we can have enough confidence to proceed with the project.

But there is a complex problem when we are trying to find all the possible combinations among the different assumptions. The number of plausible combinations increases exponentially. Even if we were able to compute the net benefits that accrue from each one of these combinations, it would be very difficult to sort them and interpreter them efficiently.

For these reasons project appraisers usually use 3 different approaches when they are conducting a sensitivity analysis.

Partial sensitivity analysis: How do net benefits change as we vary a single assumption while holding all the other constant? It is mainly applied to the most important/uncertain assumptions and to those for which it is believed that their change will result in a significant NPV change.

Worst- and Best-case analysis: Does any combination of reasonable assumptions change the NPV’s sign? Analysts want to know what will happen in case of the least favourable or most conservative assumptions.

Monte Carlo sensitivity analysis: What distribution of net benefits results from treating the numerical values of key assumptions as draws of probability distributions? The mean and variance of the distribution of net benefits convey information about the riskiness of the project.

Discount rate

Vary each parameter about which there is uncertainty and recalculate the NPV. If the policy recommendations are robust (i.e. NPV remains either positive or negative) under all plausible scenarios, we can have greater confidence that the recommendations are valid. As the discount rate rises, the NPV decreases. This common pattern arises for investments projects whose costs occur early and whose benefits occur later. Using higher discount rates results to lower NPV, because the future benefits are discounted more than the immediate costs. As long as the discount rate is higher than the IRR (NPV=0), the project has a negative NPV and should not be adopted. Society should only invest in projects that earn a higher return than could be earned by investing the resources elsewhere. In other words, the appropriate discount rate should reflect the opportunity cost of the funds. Check the discount rate that are used usually from the World Bank for renewable energy projects. To prove the importance of it, reproduce the financial analysis, find the irr, and show the discount rate of SA the last 10 years. The supply curve depends highly on the discount rate. A change in it, would move the supply curve. (see project draft for more and take some examples) ‘’ the choice of discount rate does have a significant effect on the economically optimal quantity of renewable energy ‘’

Vary each parameter about which there is uncertainty and recalculate the NPV. If the policy recommendations are robust (i.e. NPV remains either positive or negative) under all plausible scenarios, we can have greater confidence that the recommendations are valid. As the discount rate rises, the NPV decreases. This common pattern arises for investments projects whose costs occur early and whose benefits occur later. Using higher discount rates results to lower NPV, because the future benefits are discounted more than the immediate costs. As long as the discount rate is higher than the IRR (NPV=0), the project has a negative NPV and should not be adopted. Society should only invest in projects that earn a higher return than could be earned by investing the resources elsewhere. In other words, the appropriate discount rate should reflect the opportunity cost of the funds.

Social Carbon Cost

Although the social cost of carbon might not constitute an actual risk for this project, it should be recognised that its value range according to some studies. The CER price is a product of market transactions, supply and demand, and does not reflect the true damage incurred to the environment, future generations, rest of the world etc.

Electricity Price â€" long run marginal cost

South Africa electricity prices are very low due to the fact that the energy mix is heavily coal-fired. South Africa is a major coal producer. Therefore this price should be treated with attention and included in a sensitivity analysis.

Capital and Maintenance Cost

These costs can change NPV’s sign. They are the most significant costs in the economic analysis and can vary. Most of the systems are imported. Therefore the mechanisms that form their price, exceed South Africa’s borders and cannot be predicted with great confidence.

Electricity grid’s carbon footprint

South Africa’s goal is produce 10000GWH/year from renewable energy sources. This will definitely clean the energy mix, and might reduce its carbon footprint. A sensitivity analysis is needed to check NPV sensitivity to this assumption. However, due to SA’s dependence on coal, huge changes in this parameter are fairly not impossible.

Market development assumptions

The high cost of the systems, albeit their NPV is positive in the financial analysis, might avert potential investors to install them. Economic crisis might reduce financial sector’s capability to support these investment. As consequence an analysis to measure the sensitivity of NPV to market development is deemed compulsory.