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The reliability of power systems, in terms of uninterrupted electricity supplies, is dependent on the reliability of the system's elements, especially the generation sources and transmission lines. The reliability of a coal-fired power unit's operation is essentially affected by the unit's main components, i.e. the turbine, the boiler and the generator. According to the statistics, the boiler is the most failure-prone element of the power unit. Therefore, efforts aimed at improving the reliability must include actions that enable early diagnostics of the state of the individual devices. In this paper it has been proposed that the optimal time to perform diagnostic testing of boiler tubes should be determined using risk analysis. Using the net present value (NPV) discounted cash flow index and the avoided risk criterion, a procedure has been put forward that optimizes the time when diagnostic tests should be carried out. The method has been applied to optimize diagnostic testing of boiler tubes, where corrosion is the principal cause of damage. Methods have also been given to determine the probability of the failure of such elements.

This paper assesses the economic feasibility of ethanol and higher alcohols production through a thermochemical route in Brazil. This route comprises mainly sugarcane bagasse gasification, syngas cleaning, and synthesis of alcohols. Ethanol production costs and associated risks are evaluated in different scenarios. A case study of a virtual plant to be located adjacent to a sugarcane mill, in the state of Sao Paulo, is presented with the objective of finding the minimum ethanol selling price (MESP) that makes the plant’s project economically feasible. The analysis utilizes first the traditional discounted cash flow method and then proceeds to use a stochastic approach, which is more suitable to study economic feasibility under uncertainty conditions. In the latter approach, prices of raw materials and products are modelled through a mean reverting stochastic process, and economic feasibility is analysed with the help of Monte Carlo simulations. Results are summarized via a histogram of the MESPs obtained for different simulated price scenarios. Finally, the project’s risk is evaluated by computing the number of instances in which the MESP is greater than the ethanol market price.

The power generation from renewable sources is an interesting alternative to the diversification of the energy matrix of a country. This paper presents a probabilistic valuation method for power generation projects from renewable sources. It focuses on biomass plants that use sugarcane bagasse. The main objective is to bring a wider knowledge surrounding projects for investors that participate in energy auctions. Therefore, the highlight is for the net present value that allows us to analyze the financial viability of projects. Two stochastic variables are involved in the problem, the power generation and the energy price in the short-term market. Monte Carlo Simulation and Discounted Cash Flow methods are employed. A case study is carried out for a biomass plant. Sensitivity analysis is presented for different values of investment, bid, and minimum attractive rate of return. For each simulated scenario, the probability distribution of the net present value, the average net present value, and the internal rate of return are calculated. For the analyzed case study, the return of the project is more sensible to the bid value than the investment cost. The proposed method can be used as a tool to assist investors in energy auctions from renewable sources.

Herein a novel path is analysed for its economic viability to synergize the production of biomethane and dimethyl ether from biogas. We conduct a profitability analysis based on the discounted cash flow method. The results revealed an unprofitable process with high cost/revenues ratios. Profitable scenarios would be reached by setting prohibitive DME prices (1983–5566 €/t) or very high feed-in tariffs subsidies (95.22 €/MWh in the best case scenario). From the cost reduction side, the analysis revealed the need of reducing investment costs. For this purpose, we propose a percentage of investment as incentive scheme. Although the size increase benefits cost/revenues ratio, only the 1000 m3/h biogas plant size will reach profitability if 90% of the investment is subsidized. A sensitivity analysis to check the influence of some important economical parameters is also included. Overall this study evidences the big challenge that our society faces in the way towards a circular economy.

Two probabilistic models are presented to assess the costs of power plants. One of them uses requirement trees, value functions and the analytic hierarchy process. It is also based on Monte Carlo simulation. The second one is a mathematical model for calculating the levelised cost of electricity (LCOE) based on discounted cash flow techniques, and combined with Monte Carlo simulation. The results obtained with both models are compared and discussed. On the one hand, the LCOE model provides the most reliable results. These results reinforce the idea that conventional or coal, lignite, oil, natural gas and nuclear power plants are still the most competitive options, with the LCOE falling in a range of around 25 to 200 €/MWh and mean values approaching 70 €/MWh. Generally, renewable power plants obtained the worst results, with a LCOE varying from around 30 to more than 450 €/MWh. Nevertheless, this study demonstrates that renewable alternatives can compete with their conventional counterparts under certain conditions.

The present work discusses the potential and the economic feasibility of DH (district heating) delivery using industrial excess heat from a petrochemical cluster at the Swedish West Coast. Pinch Analysis was used for estimating the DH capacity targets and for estimating the cost of heat exchanger installation. A discounted cash flow rate of return of 10% was used as a criterion for identifying the minimum yearly DH delivery that should be guaranteed for a given DH capacity at different DH sales prices. The study was conducted for the current scenario in which no heat recovery is achieved between the cluster plants and for a possible future scenario in which 50% of the fuel currently used for heating purposes is saved by increasing the heat recovery at the site. The competition between excess heat export and local energy efficiency measures is also discussed in terms of CO2 emission consequences. The maximum capacity of DH delivery amounts today to around 235 MW, which reduces to 110 MW in the future scenario of increased site heat recovery. The results of our analysis show that feasible conditions exist that make DH delivery profitable in the entire capacity range.

As Brennan and Schwartz [Brennan M, Schwartz E. Evaluating natural resource investment. Journal of Business 1985;58:135–57] point out in their pioneering work, the valuation of natural resources projects is particularly difficult due to the high degree of uncertainty in output prices of resources. In general, there are two competing procedures to evaluate risky projects in natural resources developments. One is decision analytic, based on traditional discounted cash flow and stochastic dynamic programming [Fleten SE, Maribu KM, Wangensteen I. Optimal investment strategies in decentralized renewable power generation under uncertainty. Energy 2007;32:803–15; Smith J, McCardle K. Valuing oil properties: integrating option pricing and decision analysis approaches. Operations Research 1998;46(2):198–217; Szklo AS, Carneiro JTG, Machado G. Break-even price for upstream activities in Brazil: evaluation of the opportunity cost of oil production delay in a non-mature sedimentary production region. Energy 2008;33:589–600], and the other is contingent claims analysis, based on the no-arbitrage theory of financial markets [Brennan M, Schwartz E. Evaluating natural resource investment. Journal of Business 1985;58:135–57; Emhjellen M, Alaouze CM. A comparison of discounted cash flow and modern asset pricing methods – project selection and policy implications. Energy Policy 2003;31:1213–20; Laughton D. The management of flexibility in the upstream petroleum industry. The Energy Journal 1998;19:83–114; Paddock L, Siegel D, Smith J. Option valuation of claims on real assets: the case of offshore petroleum leases. Quarterly Journal of Economics 1988;103(3):479–508; Schwartz ES. Valuing long-term commodity assets. Journal of Energy Finance and Development 1998;3(2):85–99; Sezgen O, Goldman CA, Krishnarao P. Option value of electricity demand response. Energy 2007;32:108–19]. In this paper, we use the second approach to develop a new model, and the main contributions are providing a tractable and realistic means of incorporating the option value and optimal timing into the investment decision in natural resources and presenting an example that shows option and timing considerations to be important. We demonstrated the validity of the model using both numerical analysis and real data.

Some Latin American policy-makers and analysts state that it would be better to hold oil reserves in place than to produce and cash it now, given the recent oil prices spikes and the fear related to future oil supply disruptions. This article evaluates the strategy of delaying the start-up of oil production in a discovered field with proved reserves. A Reference Discounted Cash Flow (FCD-R) for a typical 350 million barrel Brazilian oil field was simulated. The study estimated which future oil price may render the project insensitive to a delay of 5, 10, 15 or 20 years in its production beginning. Additionally, the value of the in situ oil stock was calculated, providing the opportunity cost for delaying oil production in a frontier area, such as Brazil. It is an application of the Hotelling Principle. Findings indicate that progressive delays of 5 years in the start-up of operation of a typical oil field reduce its revenues by a factor of 2. A delay of 10 years would be justifiable at international oil prices higher than US $15/bbl. Delays higher than 10 years lead this break-even price to values between US $200 and 350/bbl.

Italy produces approximately 4,520,000 tons of pasta annually, which is about 67% of its total productive potential. As factories need electric and thermal energy simultaneously, combined heat and power (CHP) systems are the most suitable. This paper describes a feasibility study of a CHP plant in a pasta factory in Italy while analyzing energy saving and environmental benefits. Commercially available CHP systems suitable for the power range of energy demand in pasta production use reciprocating engines or gas turbines. This study demonstrates how their use can reduce both energy costs and CO2 equivalent greenhouse gas emission in the environment. An economic analysis was performed following the methodology set out by Italian National Agency for Technology, Energy and Environment (ENEA) based on a discounted cash flow (DCF) method called “Valore Attuale Netto” (VAN), which uses a cash flow based on the saving of energy when using different energy processes.

We discuss the results of a statewide (Georgia) survey of industry to investigate the factors which influence business decision makers to proceed with energy conservation investments. The objectives of the research were, first, to determine whether energy-conservation investment decisions are made along classically rational lines (using some form of discounted cash flow analysis), and second, suspecting the answer to be no to the first question, to identify and understand the true factors. This research focused on 156 firms, which had extensive plant energy audits over the four years, 1978–1982. Through individual computer-tailored questionnaires, extensive data were collected on plant and company demographics, management structure, attitudes and decision-making procedures, plant responses to specific energy audit recommendations, and planned energy conservation investments. We found that conventional investment analysis does not explain the energy-conservation activities. Fewer than a quarter of the 345 recommendations made to the audited firms were substantially carried out, and less than half were even partially carried out. Although the recommendations were cost-justified by the audit team, the most often cited reasons offered by the firms for not implementing the recommendations involved the costs of the projects. While the uses of analytic decision making techniques, judgemental techniques, and joint analytic-judgemental techniques were about evenly distributed among firms, there was no relation between techniques used and recommendations adopted. In fact, plant size, industry, financial health, energy intensity, energy cost forecasts, and whether the firms could pass through energy costs to customers did not significantly explain compliance with recommendations. However, low cost and housekeeping recommendations, which could be implemented at the plant level without top management involvement, did tend to get done. We conclude that while energy conservation decision making does not follow the classically rational discounted cash flow approach, neither is it (actively) irrational. Rather, due to low priority and low visibility, energy conservation is neglected by top management. In many firms, it is not a question of good or bad decisions but of no decisions at all.

Both the discounted cash flow (DCF) and revenue requirement (RR) methods are frequently used in the cost analysis of energy projects. Each is especially well suited in special circumstances. For most forward looking ventures, the RR method appears to be more useful. This paper provides simple formulations for the two methods and some special cases of interest for costing practices. Both formulations are applicable to either free or regulated enterprises and also under constant-dollars or inflationary conditions. The interpretation of cost results depends on the selection of cash-flow streams and/or the intent of revenue requirements. Several numerical examples are given.