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components and equipment are expressed as function of some design parameters. The indirect capital cost can be expressed as a function of the purchase cost of equipment or as a function of design parameters and operating conditions [29]. In the following analysis, the equipment purchasing cost is calculated as function of the components design parameters. The correlations used in this analysis are stated in the form of turbine work output, pumps power and heat exchangers surface area. These correlations are formed based on manufacturing data and give the costs in US Dollars [8, 14, 30]. For the organic fluid expander, the following correlation is utilized to calculate the purchase cost: () (̇) [(̇)] (32) where the expander work, ̇ , is provided in kW. The purchase cost for the heat exchangers, i.e; evaporator, condenser and regenerative heat exchanger, is calculated using the following correlation as a function of the heat transfer surface area: [] (33) The purchase prices of the organic Rankine cycle pump and geothermal fluid circulation pump are where A is surface area of the heat exchanger in m2. determined by applying the following formula which is a function of the pump power: () (̇)[(̇)] (34) The total capital investment (TCI) is calculated for each component as 6.32 times the purchase equipment cost as given by Bejan et al. [16]. The O&M cost of each specific equipment is taken as 20~25% of the purchase equipment cost [16] . The fuel cost and O&M costs are exposed to cost escalation over the years of operation. The levelized values of these expenditures are obtained by using the constant-escalation levelization factor (CELF). This factor links the calculations of expenditures at the first year to an equivalent annuity [16]. (35) where k is function of the effective annual cost of money rate, and the nominal escalation rate, , and CRF is the capital recovery factor. They factors are applied to the fuel cost and O&M costs and they are defined as follows [16]: () () (36) (37) 8PDF Image | Exergoeconomic Analyses and Optimization of Geothermal ORC
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