One of the key barriers to renewable energy implementation is the perception that the economic cost is too high.  Most grid-connected renewable energy technologies have higher investment costs, lower fuel and operating costs and lower environmental impacts than conventional fossil-fueled technologies.   Traditional financial analysis, based on discounted cash-flow accounting, undervalues future fuel price risks and completely ignores the environmental and health costs of fossil-fueled power plant emissions.  

As a result, the current utilization of modern renewable energy (excluding traditional biomass use) in most countries is quite small.  Yet, on a life-cycle cost basis, some renewable energy technologies are already cost competitive with conventional energy sources. However, the potential of these financially viable renewable energy technologies is not fully realized because of a variety of market barriers. 

As shown in the following figure, if the cost of local environmental externalities and global externalities (e.g. through carbon credits are included in the economic valuation, as is done in a typical WBG economic calculation, the economically viable quantity of renewable energy increases.  If the diversification value is also added to the economic cost, the economically viable optimum quantity of renewable energy becomes even larger. 

Given the market distortion that environmental externalities and diversification values are not recognized in the market place as well as a series of market barriers, financial incentives are required to attract investors to achieve the economically viable optimum quantity of renewable energy.

Such economic analyses have been performed for various renewable energy projects, for example, in China¹ , Croatia, Mexico and South Africa, to determine the economically viable optimum quantity of renewable energy.   For information, go to the Rationale Economic Valuation Module

In fact, several countries and jurisdictions have justified and adopted incentives for renewable energy as a means of recognizing their long-term environmental and economic benefits.  These are discussed more in the next section on Designing Policies. 

In many developing countries, studies have shown the high cost of environmental pollution.  As an example, one study for a city in eastern China heavily dependent on coal found that total health damages due to year 2000 anthropogenic emissions was equivalent to 10% of GDP, and that if all health damages resulting from coal use were internalized in the market price of coal, the year 2000 price would have tripled.   For most developing countries, studies to estimate the environmental and health costs of power plant emissions could help support the development and implementation of policy measures to reduce these costs through incentives for renewable energy.  For more information on the methodology and Bank guidelines to calculate environmental externalities, go to the Rationale Module.

The economic risks of fossil fuel price volatility and supply disruptions, are inherently difficult to model and recent studies have shown they are regularly under predicted by electric utility planners.  One solution to this problem is to use hedged or guaranteed fuel prices in the economic analysis rather than uncertain fuel price forecasts².  Another approach is to use historical data to estimate fuel price risk and a portfolio approach to electricity planning.

Mean variance portfolio analysis is an approach to electricity planning that includes both the costs and the economic risks of all technologies in an electricity generation portfolio and computes both the expected cost of electricity and the standard deviation (or risk) of that expected cost for the entire portfolio.   A portfolio approach to electricity planning was used to support this development of a WB/GEF a grid-connected (wind and geothermal) project in Mexico³.  The methodology accounts for construction period, operating cost and fuel price risks in its calculation of the risk-adjusted cost of generation.   The methodology allows a balanced assessment of low capital cost and high fuel cost technologies with renewable technologies with high capital costs and low (or zero) fuel costs.  The results can be quite striking.  For example, in the Mexico project, the likely system generation cost declines by 25% with the addition of wind technology even though the wind technology has a higher cost of energy compared to gas-fired power generation.