Risk factors for stakeholders in renewable energy investments

Jankauskas, Vidmantas; Rudzkis, Paulius; Kanopka, Adomas

doi:10.6001/energetika.v60i2.2935

Cited by 16 publications

(7 citation statements)

References 8 publications

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“… Sources: Diógenes et al (2019), Zhao et al (2019), Islam et al (2018), Guo et al (2018), Liu et al (2018), Loannou et al (2017), Xinyao et al (2017), Macchiaroli et al (2017), Rolik (2017), Tavakolan and Etemadinia (2017), Angelopoulos et al (2017), Noothout et al (2016), Guerrero-Liquet et al (2016), Gatzert and Kosub (2016), Li and Li (2015), Gang (2015), Jankauskas et al (2014), Jin et al (2014), Michelez et al (2011) and De Jager et al (2008). …”

Section: Resultsmentioning

confidence: 99%

Risk Evaluation Model of Wind Energy Investment Projects Using Modified Fuzzy Group Decision-making and Monte Carlo Simulation

Erfani

Tavakolan

2020

Arthaniti: Journal of Economic Theory and Practice

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The recent increasing trend of investments in wind energy projects to support sustainable development requires an appropriate risk evaluation model to ensure the success of these projects. Early studies focus on opinion and discussion from subject matter experts. However, the expertise level in the subject is varied, and evaluation without considering expert competency can cause biased results. On the other hand, most of the project cost estimation models do not consider uncertainty in all cash flow parameters. In response, this article proposes a model that evaluates risks in wind energy investment projects by considering the knowledge and background of experts. Then, an integrated model of risk evaluation and cost estimation is developed. The model consists of three main stages: risk identification based on a systematic literature review (SLR); risk analysis phase 1 based on a modified fuzzy group decision-making; and risk analysis phase 2 based on a Monte Carlo simulation method. The main advantages of the proposed model are: (a) providing a comprehensive risk identification in wind energy investment projects; (b) using a modified fuzzy model to improve the risk assessment process by considering the expert competency in wind energy projects; and (c) establishing an integrated model to evaluate the cash flow of the investment. A wind farm in the Middle East is selected as the case study to examine the usability and practicality of the proposed model. The results show that the most important risks are ‘change in regulation and policy’, ‘dependency on the international market for importing raw materials’ and ‘market competitiveness’. On the other hand, the financial assessment under uncertainty shows that the profitability of the investment can be varied, and it emphasises the importance of an appropriate risk management process to guarantee the success of the investment.

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Section: Resultsmentioning

confidence: 99%

Risk Evaluation Model of Wind Energy Investment Projects Using Modified Fuzzy Group Decision-making and Monte Carlo Simulation

Erfani

Tavakolan

2020

Arthaniti: Journal of Economic Theory and Practice

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“…The risk factors included in the study was based on the risk registers proposed by Zou et al . (2012), Holburn (2012), Jankauskas et al . (2014), Gatzert and Kosub (2015), Mosannenzadeh et al .…”

Section: Methodsmentioning

confidence: 98%

“…The authors suggested that besides insurance, diversification is one of the important tools for risk mitigation. Jankauskas et al . (2014) identified and assessed risks factors of renewable energy investment projects from the perspective of stakeholders.…”

Section: Previous Studiesmentioning

confidence: 99%

Key risk factors affecting renewable energy independent power producer (IPP) set-up projects in developing countries

Addy

Akunyumu

Sımons

2019

JEDT

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Purpose Sustained access to efficient electricity plays an essential role in improving living conditions of people and contributes to the economic development of the nation as a whole. Volta River Authority (VRA) mainly manages the generation plants (hydropower sources and thermal plants) alongside independent power producers (IPPs). Power generation in the country has been influenced by myriads of factors. Thus, the purpose of this study is to assess the key risk factors affecting renewable energy of IPPs set-up project in Ghana. Design/methodology/approach Quantitative approach was adopted for the study. Empirical investigation was carried out using the survey approach. The likelihood of occurrence of the risk and the degree of impact of same motivated the use of risk significance index to analyze the data and make deductions from the results. Findings From the study, three key risk factors have high level of severity, which include long and complex procedures for authorization of project activities, stability of the policy environment and ease of obtaining rights to land. These risks could be found in the business/strategic risks and policy/regulatory risks categories, respectively. A total of 25 key risk factors had moderate level of severity and 12 key risk factors have low level of severity on renewable energy IPP set up projects. Practical implications Top-ranked risk factors require maximum attention. The identified risks should be alleviated with strategies to reduce levels of severity by targeting either the likelihood of occurrence or the level of impact. This will serve as a catalyze to promoting renewable energy IPP set-up projects in Ghana. Originality/value Key contribution of the paper to the body of knowledge is demonstrated by the empirical evidence of the risks IPPs are likely to encounter in setting up renewable energy plants in Ghana. The distinctive attribute of this study is further demonstrated by the fact that it focused on the set-up stage, which is a critical stage in the renewable energy provision value chain.

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“…The topics of risk, uncertainty and information have been always crucial in economics (Knight 1921;Hirshleifer, Riley 1992;Ching, Colombo 2014;Iglesias-Casal et al 2016;Chen et al 2017). There is no field in economics in which risk is not an important dimension of the decision-making environment (Gollier 2001;Taleb 2010;Chen, Zhang 2014;Rudzkis 2014;Jankauskas et al 2014;Zeng et al 2017). There is a small amount of decisions that can be taken in the situation of complete certainty.…”

Section: Introductionmentioning

confidence: 99%

Reliability as Main Factor for Future Value Creation

Rutkauskas¹,

Stasytytė²,

Rutkauskas³

2017

Proceedings of 5th International Scientific Conference Contemporary Issues in Business, Management and Education ‘2017

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The main objective of the paper is to present the solution to the problem of possibilities’ reliability management, which is an important problem of uncertainty (risk) economics. Also, the paper aims to propose adequate methods of stochastic optimization and reveal their broad implementation possibilities. Along with that, the concept of utility function is being disclosed, when we take into account not only the possibilities of prices and costs, but also their reliability, in order to achieve the highest value added in this process. The original methods of stochastic optimization are used, while searching for the optimal allocation of invested capital among the investment assets. Adequate investment portfolio is treated as theoretically sound and practically effective instrument for investment decision-making in capital and currency markets, as well as for other problems related with optimal resource allocation. The adequate portfolio supplements the modern portfolio by adding the third portfolio parameter – the reliability of return. Also, the utility function based on return, reliability and risk is used to find the optimal investment possibility for particular investor. The formed portfolio solutions were tested in the markets of NYSE, UK and France.

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Risk factors for stakeholders in renewable energy investments

Cited by 16 publications

References 8 publications

Risk Evaluation Model of Wind Energy Investment Projects Using Modified Fuzzy Group Decision-making and Monte Carlo Simulation

Risk Evaluation Model of Wind Energy Investment Projects Using Modified Fuzzy Group Decision-making and Monte Carlo Simulation

Key risk factors affecting renewable energy independent power producer (IPP) set-up projects in developing countries

Reliability as Main Factor for Future Value Creation

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