The engineering precision required and the complexity of power plant equipment means that critical and expensive components such as turbines, heat exchanges and pumps can have extensive manufacturing and shipping lead times. Because geothermal projects are dependent on the natural geological conditions, the viability of the plant site selected is highly uncertain until the drilling of wells begins. Therefore, if equipment is ordered before the wells are drilled, there is a risk it may never be used or could be under-specified, significantly impacting the production capacity of the plant. However, if an order is made too late during the construction process, it could delay the plant's income generation.
Enex used PrecisionTreeÂ®, the decision analysis tool in The DecisionTools Suite, to model potential scenarios that could occur, given different procurement timescales. For instance, although ordering equipment before drilling the first well will ensure that there are no delays in the project, Enex would risk making a substantial investment without being certain of its suitability. In addition, after the last drilling, Enex would have more information on the state of the well, which will enable it to better determine the equipment specifications and therefore optimise plant efficiency.
The different scenarios highlighted in the PrecisionTree model were evaluated by Enex using @RISK, Palisade's Monte Carlo simulation tool in The DecisionTools Suite. This showed all potential outcomes, as well as the likelihood of every single event occurring. This sophisticated analysis has enabled Enex to conclude that it can expect the highest profitability if it takes the untraditional approach of pre-ordering critical power plant equipment before the drilling of the first well. By pre-ordering critical equipment, even though Enex exposes itself to a high degree of uncertainty, it expects to minimise delay in commissioning the plant so that revenue generation can begin earlier. This will enable Enex to maximise expected profitability of the project.
Based on historical and geological data, Enex also used @RISK to estimate the distribution of the potential peak production capacity of the plant, which has huge ramifications on its costs and profitability.
Viktor Thorisson, analyst at Enex, commented, âThe sophisticated technology of Palisadeâs PrecisionTree and @RISK tools has given us the self-assurance to take a rather untraditional approach. The benefits of being able to start generating revenue earlier by pre-ordering crucial components more than compensates for the risk we take by purchasing equipment that potentially may not be suitable for the project. We expect drilling for this plant to start in Europe shortly.â