Economic risk analysis of decentralized renewable energy infrastructures – A Monte Carlo Simulation approach

Arnold, Uwe; Yildiz, Özgür

doi:10.1016/j.renene.2014.11.059

Cited by 202 publications

(104 citation statements)

References 17 publications

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“…Using AHP allows you to check the consistency of assessment and help those responsible for managing the project to make the best decision. This study focuses on applying the model for risk identification; however there are studies [21] that focus on economic risk analysis in renewable energy infrastructure. These studies [22] propose models for risk analysis covering the entire life cycle of renewable energy projects using Monte Carlo simulation and sensitivity analysis for the likelihood of occurrence.…”

Section: Discussionmentioning

confidence: 99%

“…A recent study [20] conducted a comparative analysis of energy management of financial risk between countries of the European Union and Turkey; later [17] modeled the risks in renewable technology companies. After 2014, [21] analyzed the economic risk in decentralized renewable energy infrastructure by Monte Carlo simulations and recently, [22] analyzed the solar potential in emerging markets. Typical methods of environmental assessment and environmental impact assessment, risk assessment and life cycle assessment are generally conducted to assist decision making [19].…”

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confidence: 99%

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Decision-Making for Risk Management in Sustainable Renewable Energy Facilities: A Case Study in the Dominican Republic

et al. 2016

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Today, Renewable Energy Sources (RES) are a key pillar to achieving sustainable development, which is the main reason why energy projects are being carried out not only in developed countries but also in many emerging countries. Since the technical and financial risk remains a major barrier to financing renewable energy projects, several mechanisms are available to reduce risks on investment into clean energy projects. This paper discusses risk management tools in solar photovoltaic facilities based on the guide to the Project Management (PMBOK Guide). To do this, a combination of different decision-making methodologies will be carried out. These methodologies enable to not only extract the knowledge by experts but also to know the causes and effects that help to make the best decision. In order to do so, techniques to seek information (Delphi and Checklist) as well as diagram techniques such as cause and effect diagrams or Strengths Weaknesses Opportunities and Threats (SWOT) are applied. The categorization and prioritization of risks will be carried out through the Analytic Hierarchy Process (AHP). Finally, a sensitivity analysis will allow for providing consistency to the obtained results. A real case in the Dominican Republic will also be presented as case study.

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Section: Discussionmentioning

confidence: 99%

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Decision-Making for Risk Management in Sustainable Renewable Energy Facilities: A Case Study in the Dominican Republic

et al. 2016

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“…One of the conditions used to demonstrate the attractiveness of a project is to identify the individual risks that impact the cash flow of the financial investment project [46]. These risks can be analyzed through sensibility analysis that plays an important role in scenario reasoning, and hence decision making [47].…”

Section: Resultsmentioning

confidence: 99%

Multibody Dynamic Stress Simulation of Rigid-Flexible Shovel Crawler Shoes

Frimpong

Thiruvengadam

2016

Minerals

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Abstract:The uncertainty in road transportation of wood is inherent to its operational costs, to the amount of transported wood, to the traveled distance, to its revenue, and more. Although it is not possible to measure this uncertainty fully, it can be quantified by the investment risk, which is the probability and degree of financial loss. The objective of this study is to quantify the financial risk of the investment in wood transportation through Monte Carlo simulation, which uses realistic situations to estimate the operational cost of vehicles used for road transportation of wood. We quantify these uncertainties by assessing financial risk and building pseudorandom scenarios with the Monte Carlo simulation method, in addition to the Net Present Value techniques, the Modified Internal Rate of Return, and the Profitability Index, all commonly used in financial investment projects. The results show that the estimated operational costs are equivalent to the actual ones, along with the evidence that the cost of fuel, the driver's manpower, and tires are components that mainly increase the degree of financial risk for an investment project in road transportation of wood. In contrast, optimizing the amount of transported wood and maximizing wood transportation cost have a significant and positive correlation with the volume of transported wood and the average price of wood transportation, leading to a reduction in the degree of financial risk.

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“…The combination of several sources of renewable energy based on local efficiency will be able to replace only part of the energy sources based on fossil fuels. However, after the coal reserves have been exhausted, economic, social and environmental factors will have to be re-evaluated in order to stabilize the economy of the region (Fais, et al, 2014;Arnold, 2015;Menegaki, 2013;Pereira et al, 2014) …”

Section: Discussionmentioning

confidence: 99%

Multicriteria analysis for sources of renewable energy using data from remote sensing

Matějı́ček

2015

Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci.

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ABSTRACT:Renewable energy sources are major components of the strategy to reduce harmful emissions and to replace depleting fossil energy resources. Data from remote sensing can provide information for multicriteria analysis for sources of renewable energy. Advanced land cover quantification makes it possible to search for suitable sites. Multicriteria analysis, together with other data, is used to determine the energy potential and socially acceptability of suggested locations. The described case study is focused on an area of surface coal mines in the northwestern region of the Czech Republic, where the impacts of surface mining and reclamation constitute a dominant force in land cover changes. High resolution satellite images represent the main input datasets for identification of suitable sites. Solar mapping, wind predictions, the location of weirs in watersheds, road maps and demographic information complement the data from remote sensing for multicriteria analysis, which is implemented in a geographic information system (GIS). The input spatial datasets for multicriteria analysis in GIS are reclassified to a common scale and processed with raster algebra tools to identify suitable sites for sources of renewable energy. The selection of suitable sites is limited by the CORINE land cover database to mining and agricultural areas. The case study is focused on long term land cover changes in the 1985-2015 period. Multicriteria analysis based on CORINE data shows moderate changes in mapping of suitable sites for utilization of selected sources of renewable energy in 1990, 2000, 2006 and 2012. The results represent map layers showing the energy potential on a scale of a few preference classes (1-7), where the first class is linked to minimum preference and the last class to maximum preference. The attached histograms show the moderate variability of preference classes due to land cover changes caused by mining activities. The results also show a slight increase in the more preferred classes for utilization of sources of renewable energy due to an increase area of reclaimed sites. Using data from remote sensing, such as the multispectral images and the CORINE land cover datasets, can reduce the financial resources currently required for finding and assessing suitable areas.* Corresponding author. This is useful to know for communication with the appropriate person in cases with more than one author.

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Economic risk analysis of decentralized renewable energy infrastructures – A Monte Carlo Simulation approach

Cited by 202 publications

References 17 publications

Decision-Making for Risk Management in Sustainable Renewable Energy Facilities: A Case Study in the Dominican Republic

Decision-Making for Risk Management in Sustainable Renewable Energy Facilities: A Case Study in the Dominican Republic

Multibody Dynamic Stress Simulation of Rigid-Flexible Shovel Crawler Shoes

Multicriteria analysis for sources of renewable energy using data from remote sensing

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