Scenario discovery reveals that a gas-fired plant is more cost effective than rehabilitating the existing plant if:

1. The cost of local lignite (US$/ton) is more than 4.5% of the cost of gas (US$/tcm).<sup>13</sup>

Scenario discovery also reveals that rehabilitating the existing plant fails our cost-benefit test, i.e. has an IRR below 12%, if two conditions hold simultaneously:

1. The wholesale price of electricity is below 0.059 US$/kWh

2. Local lignite costs more than 6.3 US$/ton<sup>14</sup> The discount rate, estimated life of the plant, capacity utilization, length of construction time, and capital costs – though highly uncertain and potentially a source of disagreement among stakeholders -- are less important in determining whether or not investing in rehabilitating the plant is economically sound. We could invest significant time discussing what these values should be, when indeed they are not key drivers of the economic performance of our investment.

# **Are those conditions sufficiently likely that we should choose a different energy investment option?**

So far we have sought to better understand the merits and drawbacks of our options under a wide range of conditions, and to identify the conditions that may lead them to fall short of our goals. We have said little about what the future may actually hold. We now turn to the evidence to assess whether those conditions are sufficiently likely that we should choose a different energy investment option. We begin by examining the vulnerabilities to costminimization and then to cost-benefit goals.

Recall that rehabilitating the existing power plant is less cost effective than building a new gas-fired plant if the cost of local lignite (US$/ton) is more than 4.5% of the cost of gas (US$/tcm). The original cost-benefit analysis assumed that with an upgrade, the mine would sell local lignite at an average of 6.05 US$/ton, 2.8% of the 2006 gas price of 220 US$/tcm and well below the 4.5% threshold.<sup>15</sup> However current and historical trends do not guarantee or bound future outcomes, and we should not use them to predict what will be. Instead, we should use them to answer a more useful question, _“Is there evidence that the conditions that threaten the success of our_

> 13 This condition is a statistically strong predictor of when building a new gas-fired plant is more costeffective than rehabilitating the existing plant. Of the 97 futures with this condition, building a new gas-fired plant is more cost effective in 92 of them (95%). However, it is not a complete predictor: this condition exists in 92 of the 153 futures (60%) in which the new gas-fired plant is more cost effective. Further scenario discovery analysis, beyond the scope of this demonstration, would reveal additional sets of conditions that explain the remaining 40%, which policy makers could weigh against additional evidence. Nevertheless, this single condition offers useful information for a policy dialogue on the potential vulnerabilities of the rehabilitation option.

> 14 This condition is also a statistically strong predictor of when rehabilitating the existing plant fails the cost-benefit test. Of the 92 futures with these conditions, rehabilitation fails the cost-benefit test in 73 (79%). Of the 99 cases in which rehabilitation fails the cost-benefit test, this condition occurs in 73 (74%).

> 15 In the time series utilized by the project, the ratio maintains an average of 3.1% and never exceeds the 3.5% thresholds (The World Bank, 2006).

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