Solar photovoltaics (PV) is already the cheapest form of electricity generation in many countries and market segments. Market prices of PV modules and systems have developed so fast that it is ...difficult to find reliable up to date public data on real PV capital (CAPEX) and operational expenditures (OPEX) on which to base the levelised cost of electricity (LCOE) calculations. This paper projects the future utility‐scale PV LCOE until 2050 in several European countries. It uses the most recent and best available public input data for the PV LCOE calculations and future projections. Utility‐scale PV LCOE in 2019 in Europe with 7% nominal weighted average cost of capital (WACC) ranges from 24 €/MWh in Malaga to 42 €/MWh in Helsinki. This is remarkable since the average electricity day‐ahead market price in Finland was 47 €/MWh and in Spain 57 €/MWh in 2018. This means that PV is already cheaper than average spot market electricity all over Europe. By 2030, PV LCOE will range from 14 €/MWh in Malaga to 24 €/MWh in Helsinki with 7% nominal WACC. This range will be 9 to 15 €/MWh by 2050, making PV clearly the cheapest form of electricity generation everywhere. Sensitivity analysis shows that apart from location, WACC is the most important input parameter in the calculation of PV LCOE. Increasing nominal WACC from 2 to 10% will double the LCOE. Changes in PV CAPEX and OPEX, learning rates, or market volume growth scenarios have a relatively smaller impact on future PV LCOE.
Utility‐scale PV LCOE in Europe with 7% nominal WACC ranges from 24 €/MWh in Malaga to 42 €/MWh in Helsinki in 2019 and will be 9‐15 €/MWh by 2050, making PV clearly the cheapest form of electricity generation. With location, WACC is the most important LCOE input parameter: increasing nominal WACC from 2 to 10% doubles the LCOE. Changes in PV CAPEX and OPEX, learning rates, or market volume growth have a relatively smaller impact on future LCOE.
Outsourcing the production process to suppliers often places product quality beyond the direct control of buyers. While providing financial support to these suppliers can assist in overcoming working ...capital constraints in quality investments, there remains uncertainty regarding the reliability of suppliers in utilizing such investments for quality improvement. In theory, few papers have examined how effective the financial support is in encouraging quality investments by unreliable suppliers in a coopetitive context. This paper addresses the research gap by exploring whether a buyer will provide financial support to an unreliable supplier for quality improvement in a dual-channel supply chain. We develop models for cases where the buyer refrains from providing financial support, employs an advance payment scheme, or adopts an investment cost-sharing arrangement. Analysis of the equilibrium outcomes reveals that if the supplier has low working capital, the advance payment scheme benefits both parties; if the working capital is medium, no financial support is provided; otherwise, the investment cost-sharing scheme leads to a mutually beneficial outcome. Moreover, the advance payment (cost-sharing) scheme is more likely to be used when the supplier is perceived as more (less) reliable, the interest rate (cost-sharing ratio) decreases, or channel competition is lessened (intensified). Furthermore, we extend the base model to encompass scenarios where the retail prices are set simultaneously and where the supplier consistently leverages the investment to enhance product quality. We validate that the key findings remain valid in either case. Overall, our findings provide insights for buyers seeking to incentivize capital-constrained suppliers to enhance product quality through financial support under coopetition.
•We study financial support to a supplier from a buyer in a dual-channel supply chain.•The initial working capital of the supplier affects the financial support equilibrium.•Providing financial support to the supplier for quality improvement may be harmful.•Conditions for a mutually beneficial outcome under financial support are derived.•Effects of factors such as supplier reliability and channel competition are discussed.
•Installed equipment cost takes the higher share of capital investment cost.•Irrespective of technology type, feedstock takes most of biodiesel production cost.•Economic feasibility of biodiesel ...production is largely affected by feedstock cost.•Acid catalysts are cost effective to produce biodiesel from cheap feedstock.•Cheap & reusable catalysts reduce manufacturing cost and improve productivity.
Biodiesel is an alternative fuel similar to conventional diesel. It is usually produced from straight vegetable oil, animal fat, tallow, non-edible plant oil and waste cooking oil. Its biodegradability, non-toxicity and being free of sulfur and aromatics makes it advantageous over the conventional petrol diesel. It emits less air pollutants and greenhouse gases other than nitrogen oxides. In addition, it is safer to handle and has lubricity benefits than fossil diesel. However, with all these environmental benefits, biodiesel could not be extensively applied as a complete substitute fuel for conventional diesel. The main reason, repeatedly mentioned by many researchers, is its higher cost of production. Reduction of the cost of biodiesel production (unit cost of production) can be attained through improving productivity of the technologies to increase yield, reducing capital investment cost and reducing the cost of raw materials. These demand a thorough execution of economic analysis among the available possible technology alternatives, catalyst alternatives, as well as feedstock alternatives so that the best option, in economic terms, can be selected. With this respect, there are a number of researches done to investigate economically better way of producing biodiesel as a substitute fuel. Accordingly, this paper is meant to review the researches done on economics of biodiesel production, emphasizing on the methods of assessment and determination of total investment cost and operation cost, as well as on assessment of economically better technology, catalyst and feedstock alternatives. It also gives emphasis on profitability of biodiesel production and the major system variables affecting economic viability of biodiesel production.
In order to meet the IMO Tier III emissions regulations and reduce environmental pollution, many ocean-going vessels have installed the marine SCR system to reduce NOx emissions. However, the ...investment cost and operation cost of the marine SCR system, as well as the factors affecting the SCR cost are still the problems that need to be studied. In this paper, MAN S46 diesel engine matched SCR system was taken as the research object, and a cost calculation model of Marine SCR system based on cost analysis method has been proposed. The relationship between SCR system cost and some factors such as unit capacity, unit running time and inlet NOx concentration have been analyzed. The research we have done suggests that operating time, NOx inlet concentration, and emission limits are the three main important factors in the operating cost of an SCR system. Among the various secondary costs of operating costs, the reducing agent cost, fuel increase cost, and indirect annual cost account for 60%, 24%, and 7%, respectively. Moreover, the results suggest that the unit denitration cost of the matched SCR system is highly affected by the power of the diesel engine and annual running time. This study demonstrated clearly the relationship between emission control and economic cost of SCR system for marine diesels and was expected to provide a theoretical basis for sustainable development in marine environmental protection policies.
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•The analysis model of the investment cost and annual operation cost of a marine SCR system was established.•The model separately analyzes the proportion of each secondary cost in the total cost.•The model analyzes the main influencing factors of the annual operating cost of the marine SCR model.
Over the last decade because of an outstanding technological advancement concerning desalination technology particularly in RO systems which gave rise to a significant reduction in the cost of ...desalinated water and ever-increasing water demand, desalination capacity has sharply escalated. Regardless of capital and operating costs, other factors like subsidies or local incentives might cause a significant variation in produced water costs between different areas and facilities. Most of the present cost calculation tools offer limited details and their usages are restricted to certain conditions. Site-specific costs associated with raw materials like transportation and tariffs, the local difference in energy costs, plant retrofit, or treatment are particular conditions that have contributed to higher produced water delivery costs. Hence, the precise estimation of ultimate water cost is extremely challenging as it is highly volatile. As a result, the presence of a highly translucent and well-established methodology to cost estimation will greatly assist in the selection of a suitable desalination technology for each site taking to account all cost-related crucial and affecting factors. The present paper takes into spotlight economic assessment and a thorough exploration of major influential factors which contributed to the total water cost using various desalination methods. To decrease complexity of precise cost estimation, a mathematical modeling to estimate the ultimate water cost of the RO system was proposed. Moreover, the authors propose several recommendations to demarcate future research pathways and minimize water final costs. The application of integrated systems using renewable energy sources, and advancements in material and process design besides increasing unit capacity are current developments that caused a drastic decrease in both cost and energy consumption. The emergence of cutting-edge desalination technologies can have a marked effect on the calculation of cost differences in the future.
Energy recovery device (ERD) is a crucial part in the seawater desalination system. The past decade has seen a growth in attempts to carry out the structure and working principle of different types ...of ERDs, yet fewer quantitative comparisons have been made on two mainstream ERDs: pressure exchanger (PX) and turbine ERD. In this study, the effective energy conversion efficiency (EECE), energy consumption, and noise of two types of ERDs applied in an island in China are obtained by collecting and collating their long-term operation data. The results showed that the EECE of PX ERD was 93.9%, 15.5% higher than that of turbine ERD. The energy consumption of PX ERD is 3.03 kWh/m3, slightly lower than that of turbine ERD, about 0.34 kWh/m3. The gap between EECE and energy consumption is caused by the different structures and working principles of two types of ERDs. Moreover, the operating noise of turbine ERD is better than that of PX due to its high rotation speed. This study also makes an economic analysis on the investment and operation cost of the whole system, and gives the engineering application suggestions and selection guidance of ERDs.
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•Quantitative comparison of PX and turbine ERDs was innovatively carried out in engineering application.•The equipment selection and process design of two types of ERDs were introduced in the same process parameters, respectively.•The EECE, energy consumption and noise were analyzed from the collated operation data in a long-term.•The investment and operation costs of two types of ERDs were analyzed, and their characteristic also were summarized.
As the share of renewable energy resources rapidly increases in the electricity mix, the recognition, representation, quantification, and eventually interpretation of their uncertainties become ...important. In this vein, we propose a generic stochastic simulation-optimization framework tailored to renewable energy systems (RES), able to address multiple facets of uncertainty, external and internal. These involve the system's drivers (hydrometeorological inputs) and states (by means of fuel-to-energy conversion model parameters and energy market price), both expressed in probabilistic terms through a novel coupling of the triptych statistics, stochastics and copulas. Since the most widespread sources (wind, solar, hydro) exhibit several common characteristics, we first introduce the formulation of the overall modelling context under uncertainty, and then offer uncertainty quantification tools to put in practice the plethora of simulated outcomes and resulting performance metrics (investment costs, energy production, revenues). The proposed framework is applied to two indicative case studies, namely the design of a small hydropower plant (particularly, the optimal mixing of its hydro-turbines), and the long-term assessment of a planned wind power plant. Both cases reveal that the ignorance or underestimation of uncertainty may hide a significant perception about the actual operation and performance of RES. In contrast, the stochastic simulation-optimization context allows for assessing their technoeconomic effectiveness against a wide range of uncertainties, and as such provides a critical tool for decision making, towards the deployment of sustainable and financially viable RES.
•We offer a generic stochastic simulation-optimization framework to quantify the key facets of uncertainty across renewables.•Uncertainty refers to hydrometeorological drivers and model elements, expressed as stochastic processes and random variables.•The representation of uncertainties is based on effective coupling of the triptych statistics, stochastics and copulas.•The framework is demonstrated in the design of a small hydropower plant and the long-term assessment of a wind power system.•The method in practice can serve as a decision-making tool, towards deploying sustainable and financially viable systems.
Buildings have significantly contributed to high energy demand (30.3%) and GHG emissions (26.1%) worldwide. Consequently, many developed countries have set carbon-neutral targets for 2050, mandating ...that all new constructions thereafter be designed as net-zero emission buildings (NZEBs). To achieve this goal, one of the most practical sources of renewable energy, solar power, is employed in this study to estimate the economic feasibility of implementing NZEBs in the non-residential sector of the United States. While past studies have typically estimated the economic payback period of solar power technology by assuming fixed values for “PV energy conversion rates (%)” and “investment costs ($USD)”, this paper carefully investigated the economic feasibility of “solar-based NZEBs” by precisely tracking these dynamic future changes in PV panels. These techno-economic variables were carefully predicted using a statistical technique known as the five-parameter logistic (5 PL) function. The results show that Site 4 is the only solar region suitable for implementing “PV-integrated NZEBs”, reaching a payback period of 8.44 years in 2040 (Scenario 1). Furthermore, with small technological improvements in PV energy efficiency (%), buildings located in Site 3 and Site 4 can meet the net-zero emission target with payback periods of less than 10 years in 2034 (Scenario 2). Finally, starting in 2044, the “PV-integrated system” will have a payback period of approximately 7 years in most study locations, even without federal support for the solar investment tax credit (SITC). Accordingly, federal support for solar power generation will be more effective if the SITC rate is gradually reduced by 2.5% annually starting in 2033. In conclusion, this paper suggests the economic feasibility of implementing solar-based NZEBs in the United States non-residential sector by considering the synergetic effect of technological improvement and cost reduction in PV-integrated systems.
•This study predicted the cost and efficiency of PV panels to estimate the economic feasibility of solar-based NZEBs.•The cost reduction and technical advancement in PV panels can remarkably improve the economics of solar power.•The 5 PL function is systematically modeled to predict the total investment cost and efficiency of PV panels.•In most study locations, solar-based NZEBs are projected to achieve a 7-year payback period beginning in 2044.•The federal support for the SITC rate (%) is recommended to be gradually lowered starting in 2033.
The economics of renewable energy sources are very important factors to encourage its use in the short and long run. The most important economic factor is associated with the initial investment cost ...of renewable energy systems. Despite their significance, operational costs do not primarily drive the decision to adopt specific renewable energy systems. The objective of this review is to investigate the economics of renewable energy systems in the agricultural sector concerning the initiative investment cost, the operational cost, and the economic returns of these systems. The results showed that the initiative investment cost in the solar energy systems was the cheapest compared to the systems. This fact contributed to the high distribution of these systems in agricultural activities. The operational cost of the other systems including the wind, geothermal, and bioenergy systems were lower than the solar energy system, but still, their use in agricultural activities was for specific purposes. The economic returns of various renewable energy systems depend on their intended use and the nature of agricultural activities.
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•A solar-driven Kalina cycle is investigated by advanced exergoeconomic analysis.•The highest exergy efficiencies are related to the separator and turbine with the values.•Rotary ...machinery have more than 83% avoidable share of exergy destruction rate.
A Kalina cycle driven by solar energy resource is evaluated by conventional exergy and exergoeconomic analysis methods. Because conventional exergy analyses isn’t able to give information about costs of the irreversibilities and investment, advanced exergy is investigated. Based on the conventional exergy analyses, the most exergy destruction occurs in a heater with a value of 94.44 kW. Also the highest exergy efficiencies are related to the separator and turbine with the values of 99.67% and 89.81%, respectively. Advanced exergy analyses demonstrates absorber (1.3 $/h) and one of the pumps (0.009 $/h) have the highest and lowest exergy destruction cost rate, respectively. Also the results show turbine (85.88%) and separator (1.105%) have the highest and lowest exergoeconomic factor, respectively. Finally, in order to determine optimum point of the inlet temperatures and pressure ratio of the pumps and turbine (rotary machines), a parametric study is applied at different stages.
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