Equipment Purchase Costs Research Articles

Modelling and exergoeconomic based design optimisation of combined power plants

In this research a Combined Cycle Power Plant (CCPP) which can provide 80 MW of electrical power has been studied. The design parameters of the plant were chosen as: compressor pressure ratio, compressor isentropic efficiency, gas turbine isentropic efficiency, and turbine inlet temperature, pinch difference temperature, steam turbine inlet temperature, steam turbine isentropic efficiency, condenser pressure, and pump isentropic efficiency. In order to optimally find the design parameters a thermoeconomic approach has been followed. An objective function representing the total cost of the plant in terms of dollar per second was defined as the sum of the operating cost related to the fuel consumption, and the capital investment for equipment purchase and maintenance costs. Finally, the optimal values of decision variables were obtained by minimising the objective function using Sequential Quadratic Programming (SQP) for, 50, 60, 70, and 80 MW of net power output.

The solar home PV program in Fiji – A successful RESCO approach?

The Fiji solar home system (SHS) program provides electricity, primarily for lighting, for remote households located in rural areas where supplying electricity via the grid is not feasible. The program is implemented by the Department of Energy (DoEF) and although initially designed on the RESCO model, the program as currently implemented is based on a partial RESCO approach as the government rather than a service company has full responsibility for program delivery. Donor-supplied capital is used for the initial equipment purchase and installation costs and all equipment and components supplied and installed under the program are owned by the government. A survey of both SHS users and those involved in the program design, planning and implementation was undertaken in order to obtain a better understanding on the Fijian SHS program, the approach used, the delivery method, the policy framework within which it is implemented and the overall the effectiveness of the program. This, in turn, helps to understand how SHS programs being implemented elsewhere can be improved. The main survey finding was that the effectiveness of the implementation of the Fijian SHS program is seen by many stakeholders to suffer from a lack of well developed planning and policy support. This manifests itself in a lack of support infrastructure and in a weak monitoring and maintenance program, which in turn give rise to significant technical problems. Many stakeholders consider there to be significant capacity for increasing the effectiveness of the program by the development of a more comprehensive and robust monitoring system, the provision of quality post-installation services, and the use of higher quality components. A number of measures that could be adopted to improve the effectiveness of the program at little or no cost are suggested.

Cost modeling approach and economic analysis of biomass gasification integrated solid oxide fuel cell systems

This paper presents a cost modeling approach and the economic feasibility for selected plant configurations operating under three modes: air gasification, mixed air-steam gasification, and steam gasification combined cycle solid oxide fuel cell (SOFC) systems. In this study, three cases of biomass gasification integrated SOFC without combined cycle (base case 1) are compared with biomass gasification integrated SOFC-gas turbine (GT) with heat recovery steam generator (HRSG) hybrid configuration (case 2) and biomass gasification integrated SOFC-steam turbine (ST) cycle (case 3) for biomass feed stock. The plant design cases of integrated biomass gasification processes, SOFC, and combined cycles are investigated primarily employing aspen plus™ flow sheeting models. Based on the mass and energy balance results of the system simulations, the economic model calculates the size and cost estimates for the plant configuration equipments. Detailed purchase cost estimations for each piece of equipments and the corresponding total bare module cost were established based on the bare module factor, and the total direct permanent investment were established. The calculated direct permanent investment was used for economic feasibility analysis of the cogeneration plant configuration. The economic feasibility decision parameters, such as purchase cost estimations, total specific plant cost per kW, the financial net present value (FNPV), internal rate of return, and benefit to cost ratio for the system configurations were compared for three design cases. The results shows that the cost of the steam gasification system is shown to be highest compared to the mixed air steam gasification system and air gasification system due to the higher hydrogen production. Other than the SOFC and gasification costs, a significant cost towards the heat exchangers is about 15% to 20% of the total equipment purchase cost. The specific plant cost for the air gasification varied from the 16 600 US$/kW to 19 200 US$/kWe. For the case of biomass gasification-integrated SOFC-GT configuration, the major cost portions are shared by the SOFC, HRSG, and gasifier. The HRSG equipment shared a cost portion of 25% to 30% for all the operating modes. The cost is decreased with a similar trend as that of steam, mixed air-steam and air gasification systems. For the case of biomass gasification integrated with SOFC-ST configuration, the total equipment purchase cost decreases at a rate of 15% to 20% for both mixed air steam and air gasification system. Plant specific cost for the steam gasification mode varied from 15 200 to 17 200 US $/kW which is significantly very high.

The importance of good working environments

NURSING STANDARD Research grants the general Nursing Council for england and Wales trust is offering around £20,000 of funding for research that contributes to nursing policy, practice or education. the lead applicant must be a nurse and the trust will not fund organisational overheads, equipment purchase or dissemination costs such as conference attendance. Payment is conditional on ethical and research governance approval. the closing date is April 10. www.gnct.org.uk/apply-for-grant

Economic Evaluation of Syngas Production: Model Development and Analysis

The objective of this study was to develop and apply an economic model to predict the unit cost of syngas production from a micro-scale bio-gasification facility. The economic model was programmed in C++ and developed using a parametric-cost approach, which included processes to calculate the total capital costs and the total operating costs of a bio-gasification facility. The model used data measured from the bio-gasification facility at Mississippi State University. The modeling results showed a unit cost and energy cost of syngas production of $1.258 Nm-3 and $0.217 MJ-1, respectively, for a 60 Nm3 h-1 bio-gasifier capacity. The operating cost was determined to be a large proportion of the total production cost, in which equipment purchase cost and labor cost were a major part of the total capital cost and the total operating cost, respectively. When the production capacity increased from 60 to 2,400 Nm-3 h-1 with a higher operating mode, the total annual production cost increased while the syngas unit cost decreased. Sensitivity analysis of the model results indicated that equipment purchase cost ranked highest, followed by employee pay rate, feedstock price, loan life, interest rate, electricity price, and waste treatment price. The unit cost of syngas production increased with the increase of all parameters with the exception of loan life. The loan life and annual interest rate showed a non-linear relationship, while the other parameters showed a linear relationship with percent changes in the unit cost of syngas production. The economic model and analysis techniques developed in this study were found to be useful and can be applied in other similar conditions as needed.

Multi-objective optimization of a recuperative gas turbine cycle using non-dominated sorting genetic algorithm

A regenerative gas turbine cycle with two particular tubular recuperative heat exchangers in parallel is considered for multi-objective optimization. It is assumed that tubular recuperative heat exchangers and its corresponding gas cycle are in design stage simultaneously. Three objective functions including the purchased equipment cost of recuperators, the unit cost rate of the generated power, and the exergetic efficiency of the gas cycle are considered simultaneously. Geometric specifications of the recuperator including tube length, tube outside/inside diameters, tube pitch, inside shell diameter, outer and inner tube limits of the tube bundle and the total number of disc and doughnut baffles, and main operating parameters of the gas cycle including the compressor pressure ratio, exhaust temperature of the combustion chamber and the air mass flowrate are considered as decision variables. Combination of these objectives anddecision variables with suitable engineering and physical constraints (including NO x and CO emission limitations) comprises a set of mixed integer non-linear problems. Optimization programming in MATLAB is performed using one of the most powerful and robust multi-objective optimization algorithms, namely non-dominated sorting genetic algorithm. This approach is applied to find a set of Pareto optimal solutions. Pareto optimal frontier is obtained, and a final optimal solution is selected in a decision-making process.

Volume Ultrasound in Uterine and Tubal Evaluation

ABSTRACT After the development of the new technologies and rendering modes, it became possible to acquire valuable diagnostic images of the female genital organs. There appear to be few differences in the diagnostic accuracy of standard 2D vs 3D images in detecting pelvic pathology, but 3D scanning can improve efficiency by reducing scanning time and therefore improving patient throughput. Furthermore, 3D ultrasound is able to rapidly acquire and store ultrasonographic data that can later be retrospectively analyzed with little loss of information. The most important advantage is the visualization of the coronal plane. It is therefore likely that the application of 3D ultrasound scanning will increase in the future for diagnostic purposes, particularly when the purchase cost of ultrasound equipment falls. The purpose of this review is to highlight the benefits of volume ultrasound in evaluation of uterine and tubal pathology.

Techno-economic analysis of dimethylfuran (DMF) and hydroxymethylfurfural (HMF) production from pure fructose in catalytic processes

Techno-economic studies of processes for production of dimethyl-furan (DMF) and hydroxymethyl-furfural (HMF) from fructose are performed based on published laboratory results. The early stage of technology development necessitates use of simplified process models to analyze a conceptual bio-refinery producing fuel and chemical intermediates. HMF and DMF production processes are divided into four and six processing areas respectively that include synthesis and purification sections. The HMF process employs a biphasic (aqueous–organic phases) continuously stirred tank reactor (CSTR), and the DMF process has an additional 3-train fixed bed catalytic plug flow tubular reactor (PFTR). The processing capacities are 300 metric ton/day of fructose and the plants will operate for 20 years. Installed equipment costs are estimated (US$2007) as $102.4 million for the HMF and $121.9 million for the DMF process, respectively. The DMF process uses a copper–ruthenium–carbon (Cu–Ru/C) catalyst. Catalyst cost is estimated as $36.4 million for the first charge with replacement cost of $258,500/2-years. Cost analysis is performed following the discounted cash flow method. The minimum selling prices for HMF and DMF are estimated as $1.33/l ($5.03/gal) and $2.02/l ($7.63/gal), respectively. Sensitivity analyses are performed to assess the relative importance of key assumptions on minimum HMF and DMF selling prices. The most significant parameters are feedstock cost, product yields, by-product prices, catalyst cost and total purchased equipment costs. Process and economic uncertainties can be reduced by incorporating better performance (through laboratory and pilot trials) and cost data.

Thermodynamic analysis and thermoeconomic optimization of a dual pressure combined cycle power plant with a supplementary firing unit

In this paper, a combined cycle power plant (CCPP) with a supplementary firing system is first thermodynamically analyzed through energy and exergy. The optimal design of operating parameters of the plant is then performed by defining an objective function and applying a generic algorithm (GA) type optimization method. In order to optimally find the design parameters, a thermo-economic method is employed. An objective function representing the total cost of the plant in terms of dollar per second is defined as the sum of the operating cost related to the fuel consumption and the capital investment for equipment purchase and maintenance costs. Subsequently, different parts of the objective function are expressed in terms of decision variables. Finally, the optimal values of decision variables are obtained by minimizing the objective function using a GA. Moreover, the influences of changes in the demanded power and fuel cost are studied by considering three different output powers (i.e., 160, 180 and 200 MW). To validate the present model, the results of the present simulation code are compared with the actual data. The results show that the average difference between the model results and the actual data is about 1.41%. Moreover, various cases are investigated to determine how to decrease the objective function (cost, mass flowrate, etc.) for the optimized design and operating parameters (fuel cost, power output, etc.).

Multi-objective optimization of a combined heat and power (CHP) system for heating purpose in a paper mill using evolutionary algorithm

SUMMARY The present study deals with a comprehensive thermodynamic modeling of a combined heat and power (CHP) system in a paper mill, which provides 50 MW of electric power and 100 ton h−1 saturated steam at 13 bars. This CHP plant is composed of air compressor, combustion chamber (CC), Air Preheater, Gas Turbine (GT) and a Heat Recovery Heat Exchanger. The design parameters of this cycle are compressor pressure ratio (rAC), compressor isentropic efficiency (ηAC), GT isentropic efficiency (ηGT), CC inlet temperature (T3), and turbine inlet temperature (T4). In the multi-objective optimization three objective functions, including CHP exergy efficiency, total cost rate of the system products, and CO2 emission of the whole plant, are considered. The exergoenvironmental objective function is minimized whereas power plant exergy efficiency is maximized using a Genetic algorithm. To have a good insight into this study, a sensitivity analysis of the results to the interest rate as well as fuel cost is performed. The results show that at the lower exergetic efficiency, in which the weight of exergoenvironmental objective is higher, the sensitivity of the optimal solutions to the fuel cost is much higher than the location of the Pareto Frontier with the lower weight of exergoenvironmental objective. In addition, with increasing exergy efficiency, the purchase cost of equipment in the plant is increased as the cost rate of the plant increases. Copyright © 2010 John Wiley & Sons, Ltd.

Optimal design of gas turbine CHP plant with preheater and HRSG

Located in the south of Iran, Jiroft Paper Mill Company requires an integrated combined heat and power plant, which can provide 50 MW of electric power and 100 ton h−1 saturated steam at 13 bar, to produce paper from an adjacent eucalyptus forest. The plant is composed of an air compressor, combustion chamber, air preheater, turbine, as well as a heat recovery steam generator. The design parameters of the plant were chosen as: compressor pressure ratio (rc), compressor isentropic efficiency (ηAC), gas turbine isentropic efficiency (ηT), combustion chamber inlet temperature (T3), and turbine inlet temperature (T4). In order to optimally find the design parameters a thermoeconomic approach has been followed. An objective function representing the total cost of the plant in terms of dollar per second was defined as the sum of the operating cost related to the fuel consumption and the capital investment for equipment purchase and maintenance costs. Subsequently, different parts of the objective function have been expressed in terms of decision variables. Finally, the optimal values of decision variables were obtained by minimizing the objective function using sequential quadratic programming. The influence of changes in the demanded power and steam on the design parameters has also been studied for 40, 50, 60, and 70 MW of net power output, and 100, 120, and 150 ton h−1 of saturated steam mass flow rate. Finally, the sensitivity analysis of change in design parameters with change in fuel or investment cost was performed. Copyright © 2009 John Wiley & Sons, Ltd.

Pressure drop considerations for heat exchanger network grassroots design

Pressure drop is an important issue in design of a heat exchanger network (HEN), which has yet to be addressed properly. To overcome pressure losses incurred when streams flow through heat exchangers, pumps/compressors must be installed. The total cost for a system of pumps and compressors consists of the purchase cost of equipment and the electricity cost to run these equipment. This cost could occupy a significant part of the overall cost for a HEN design. Therefore, the pressure drop aspect should be considered together with the costs for heat exchanger area and utility consumption. A new approach is proposed to consider the pressure drop aspect in the overall context of a HEN design. Firstly, the optimal Δ T min is determined through three-way trade-offs between area, utility and pressure drop at the targeting stage. As a result of targeting, targets for area, utility and pressure drops can be established ahead of the network design. Then a network structure is initialised at the determined Δ T min and optimised to achieve a final design. In this procedure, the pressure drop is considered at both the targeting stage and the design stage in a systematic manner.

New Factors for Capital Cost Estimation in Evolving Process Designs

Capital cost assessment is an integral part of an evolving process design. The assessment should consider installed equipment costs inclusive of plant bulk items and not solely purchased equipment costs. The ratio of installed equipment cost to purchased equipment cost varies much more widely for individual equipment items than for entire plants; the ratio depends on equipment class, design, size and construction materials as well as plant layout. The factored (IChemE) method outlined in the Institution of Chemical Engineers ’blue booklet’ is of immediate use and provides a basis for checking detailed estimates. Some experience in the application of the IChemE method by the authors is reviewed. Recommendations are made for broadening the inputs for estimating, and some factors are proposed for estimating installed costs of equipment of different classes. Quantitative data are also presented for cost breakdown in entire plants arising from project reviews by the authors.

Economics of fed-batch operation: a computer-aided approach

The widely anticipated economic potential of fed-batch operation was quantified for a therapeutic product by flowsheet simulation. A process for production of t-PA from CHO cells based on fed-batch operation was compared to a base process that operates in batch mode. Two cases of fed-batch operation were considered, case A, where the product concentration was assumed to be four times the concentration obtained with base process and case B, where the concentration was eight times. The simulator, Bioprocess Simulator (BPS) from Aspen Technology, reported the final bioreactor volume and the total amount of the continuous feeds added during the fed-batch operation. BPS was also used to simulate the downstream processes. Comparison of the economic performances of the processes revealed that return on investment (ROI) of the base process would increase by 112% by switching to case A fed-batch operation from batch mode. Case B, on the other hand, would result in an increase of 288%. The importance of downstream processing for recovery of high-value products became apparent from this study. A breakdown of equipment purchase cost showed that the contribution from the product recovery section increased from 62% for base case to 77% for case A as the product concentration increased by fed-batch operation. For a fixed recovery of 40%, contribution from the downstream section was found to decrease to 70% for case B compared to case A. It was concluded from the results that higher product concentration would not result in proportionate increase in ROI because of limitations in the recovery section. A sensitivity analysis was carried out on several uncertainties of the simulated fed-batch process.

Single versus multiple bioreactor scale-up: economy for high-value products

The economy of scaling-up a bioreactor by increasing the number of units was investigated with respect to an integrated flowsheet. For the production of t-PA from animal cells, a base case flowsheet using a single large bioreactor was compared to a multiple bioreactor case. Simulation of the complete flowsheets for the two cases showed that a multiple bioreactor approach to scale-up increases the return of investment (ROI) of the base process by 122%. This enormous increase in ROI results from the smaller size of the downstream units compared to the base case, since downstream processing accounts for about 80% of the total cost for high value products like t-PA. Proper scheduling of the downstream units allowed sharing of the equipment by the bioreactors. A breakdown of the equipment purchase cost showed that cost related to cell culture equipment increased from 14% for the base case to about 37% for the multiple bioreactor case. The contribution from chromatography columns to the total equipment purchase cost, on the other hand, decreased from 52 to 33%.

Innovative uses of speciality ion exchange resins provide new cost‐effective options for metals removal

AbstractIon exchange treatment of water for boiler and process systems is a documented, proven unit operation. The recent development of a group of novel resins has expanded the potential use of ion exchange processes to a new range of applications. By applying a different functional group onto the traditional styrene/divinyl‐benzene polymer backbone, ion exchange technology becomes a cost‐effective treatment option for metals removal from plant process that and waste streams. This paper will report on the use of a diphosphonic acid functional group ion exchange resin in a number of industrial applications. Key performance characteristics of the material include: Superior Reactivity: The diphosphonic acid functional group incorporated into the resins reacts more completely with metal ions in solution, lowering effluent metals concentrations. Selectivity: While reacting with metal ions, diphosphonic acid functionalized resin capacity is not consumed by common earth elements such as calcium, magnesium and sodium. By selectively applying capacity to target metals, the number of regenerations required is dramatically reduced, improving system cost‐effectiveness. Kinetics: The diphosphonic acid functionalized resin also includes a second functional group, sulfonic acid, as is used in most industrial cation exchange resins. The inclusion of sulfonic acid groups improves ion access to the diphosphonic acid exchange sites, improving exchage kinetics over other specialty resin types. Suprior kinetics allows for a smaller resin bed, saving on both equipment and resin purchase costs. Each industrial application cited applies these performance characteristics in such a way to allow for new or improved system performance.

Economic Performance of the SCE Stirling Dish

In 1982 McDonnell Douglas Aerospace (MDA) and United Stirling AB (USAB) of Sweden formed a joint venture to develop and market a solar Stirling dish system. Eight modules were built and extensively tested from 1984 to 1988. Power production and daily energy-conversion efficiency as determined by field testing were characterized and modeled into a computer program. Included in this simulation are models of mirror soiling rate, wind spillage loss, mirror washing, and other maintenance outage time, operation and maintenance (O&M) costs, and equipment purchase cost. An economic model of a hybrid (combustion) receiver has been included in the simulation for illustrating the value of using solar energy when available and other fuels such as methane, natural gas, hydrogen, etc. when solar energy is not available or adequate. This paper describes the simulation and presents comparisons of the simulation to test data. The simulation also estimates both the O&M expenses and levelized energy costs for different production volumes.

Estimating capital costs from an equipment list: A case study

This paper presents a new method of determining the direct cost of a plant once the equipment list has been prepared. The method has a more rational basis for obtaining the direct cost from the equipment list than do methods based solely on equipment factors applied to the purchase cost of equipment. New correlations have been obtained for the various components of the direct cost from actual plant construction data and the procedure outlined is no more involved than that for any equipment factor method. The method is a significant departure from the established factor methods, yet its simplicity and logic should appeal to most engineers.

Forest Harvesting Equipment Ownership and Operating Costs in 1984

Abstract Forest harvesting equipment purchase costs in 1984 were determined by a survey of equipment dealers and manufacturers operating in the South. Based on delivered purchase prices, fixed costs for equipment ownership were calculated using machine rate formulas. Equipment operating costs were estimated based on general guidelines, fuel consumption data, and historical records. The fixed and operating cost data can be used when considering equipment investments and analyzing actual or potential harvesting systems.