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[1] Ermolenko, G.V., Tolmacheva, I.S., Ryapin I.Y., Fetisova Y.A., Matshura A.A. & Reutiva A.B., Handbook on Renewable Energy the European Union, Institute of Energy SRU GSE: Moscow, p. 96, 2016.
[2] Dia-Core project, The Impact of Risks in Renewable Energy Investment and the Role of Smart Policies, available at http://diacore.eu/results/item/enhancing-res-investments- final-report (accessed 01 April 2019).
[3] Panepinto, D., Gitelman, L., Kozhevnikov, M., Magaril, E., Magaril, R. & Zanetti, M.C., Energy from biomass for sustainable cities. IOP Conference Series: Earth and Environ- mental Science, 72(1), 2017. [Crossref]
[4] Chebotareva, G., Leading factors of market profitability of the renewable energy compa- nies. Proceedings of the 2nd International Conference on Social, Economic and Academic Leadership, Vol. 217, pp. 277–287, 2018. [Crossref]
[5] International Renewable Energy Agency (IRENA), Renewable Energy Statistics 2017. http://www.irena.org/DocumentDownloads/Publications/IRENA_Renewable_Energy_ Statistics_2017.pdf (accessed 10 January 2019).
[6] International Renewable Energy Agency (IRENA), Renewable energy highlights. http:// www.irena.org/DocumentDownloads/Publications/IRENA_Renewable_energy_high- lights_July_2017.pdf (accessed 10 Febraury 2019).
[7] Renewable Energy Policy Network for the 21st Century (REN21), State of renew- able energy 2016. Global report, http://www.ren21.net/wp-content/uploads/2016/10/ REN21_GSR2016_KeyFindings_RUSSIAN.pdf (accessed 11 February 2019).
[8] Renewable Energy Policy Network for the 21st Century (REN21), State of renewable energy2017.Globalreport.http://www.ren21.net/wp-content/uploads/2017/10/17-8399_ GSR_2017_KEY-FINDINGS_RU_low.pdf (accessed 20 March 2019).
[9] Renewables 2018, Global status report. http://www.ren21.net/gsr-2018 (accessed 20 March 2019).
[10] Frankfurt School-UNEP Centre/BNEF 2018, Global Trends in Renewable Energy Investment 2018. http://www.greengrowthknowledge.org/sites/default/files/down- loads/resource/Global_Trends_in_Renewable_Energy_Investment_Report_2018.pdf (accessed 20 March 2019).
[11] Chebotareva, G., Risk-oriented approach to competition assessment in the global renewable energy sources market. WIT Transactions on The Built Environment, 179, pp. 345–355, 2018. [Crossref]
[12] Mokhov, V.G., Chebotareva, G.S. & Khomenko, P.M., Modelling of ‘green’ invest- ments risks. Vestnik Yuzhno-Ural’skogo gosudarstvennogo universiteta. Seriya ‘Matematicheskoe modelirovanie i programmirovanie’, 11(2), pp. 154–159, 2018. [Crossref]
[13] Sorland B.F. & Rudel M.G.N., What drives Financial Distress Risk and Default Rates of Leveraged Buyout Targets? Empirical Evidence from European Transactions, Norwegian School of Economics: Norway, 2015.
[14] Khaidarshina G.A., Integrated model to assess the risk of bankruptcy. Finance, 2, pp. 67–69, 2009.
[15] Lombardi, P. & Schwabe, F., Sharing economy as a new business model for energy storage systems. Applied Energy, 188, pp. 485–496, 2017. apenergy.2016.12.016 [Crossref]
[16] Ascione, F., Bianco, N., De Stasio, C., Mauro, G.M. & Vanoli, G.P., Multi-stage and multi-objective optimization for energy retrofitting a developed hospital reference building: a new approach to assess cost-optimality. Applied Energy, 174, pp. 37–68, 2016. [Crossref]
[17] Johnston, S., Nonrefundable tax credits versus grants: The impact of subsidy form on the effectiveness of subsidies for renewable energy. Journal of the Association of Environmental and Resource Economists, 6(3), pp. 433–460, 2019. https://doi. org/10.1086/702736
[18] Gonzalez, A., Riba, J.R., Esteban, B. & Rius, A., Environmental and cost optimal design of a biomass–Wind–PV electricity generation system. Renewable Energy, 126, pp. 420–430, 2018. [AQ2] [Crossref]
[19] Bhattacharya, M., Paramati, S.R., Ozturk, I. & Bhattacharya, S., The effect of renewable energy consumption on economic growth: evidence from top 38 countries. Applied Energy, 162, pp. 733–741, 2016. [Crossref]
[20] Rediske, G., Siluk, J.C.M., Gastaldo, N.G., Rigo, P.D. & Rosa, C.B., Determinant factors in site selection for photovoltaic projects: a systematic review. International Journal of Energy Research, 43(5), pp. 1689–1701, 2019. [Crossref]
[21] Zhang, C. & Yang, J., Economic benefits assessments of ‘coal-to-electricity’ project in rural residents heating based on life cycle cost. Journal of Cleaner Production, 213, pp. 217–224, 2019. [Crossref]
[22] [McInerney, C. & Bunn, D.W., Expansion of the investor base for the energy transition.
Energy Policy, 129, pp. 1240–1244, 2019. [Crossref]
[23] Oliveira, T., Varum, C. & Botelho, A., Econometric modeling of CO2 emissions abatement: comparing alternative approaches. Renewable and Sustainable Energy Reviews, 105, pp. 310–322, 2019. [Crossref]
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Open Access
Research article

Risk Assessment of Renewable Energies: Global Exposure

g.s. chebotareva
Academic Department of Energy and Industrial Enterprises Management Systems, Ural Federal University, Russia
International Journal of Energy Production and Management
|
Volume 4, Issue 2, 2019
|
Pages 145-157
Received: N/A,
Revised: N/A,
Accepted: N/A,
Available online: N/A
View Full Article|Download PDF

Abstract:

The current stage of renewable energy (RE) development poses new challenges to this sector. The existing mechanisms of state stimulation of Renewable energy system are gradually exhausting its capacity. This requires the development of new methods to support the industry, or giving them up altogether. This article presents the results of the theoretical analysis of the systemic features of RE risk assessment at each stage of a project’s life cycle. A sectoral approach to the risk assessment of energy projects is proposed. It is based on the well-known logit-model that studies a set of external and internal indicators. Based on this model, a study of the dynamics of the risk indicators of RE projects on three basic stages was conducted. Calcula- tions were made for RE projects implemented in different countries of the world, including China, USA, Canada, Japan, India and a number of European countries. Initially, all projects were divided into three main groups depending on the types of state support: concessional lending, subsidies or the lack thereof. Based on the results of the calculations, the overall and average dynamics of risk by group and by project stage allowed for assessing the global effectiveness of state measures to support the sector, as well as for drawing appropriate conclusions in the context of individual countries. The results of the study are of prac- tical importance and will be used in developing a new approach to risk assessment, taking into account the specifics of the RE market, as well as in enhancing the concept of competition in the global energy market.

Keywords: energy, investment project, logit-model, project’ stages, renewable energy, renewable energy sources, risk, risks’ distribution, state support
Data Availability

The data used to support the findings of this study are available from the corresponding author upon request.

Conflicts of Interest

The authors declare that they have no conflicts of interest.

References
[1] Ermolenko, G.V., Tolmacheva, I.S., Ryapin I.Y., Fetisova Y.A., Matshura A.A. & Reutiva A.B., Handbook on Renewable Energy the European Union, Institute of Energy SRU GSE: Moscow, p. 96, 2016.
[2] Dia-Core project, The Impact of Risks in Renewable Energy Investment and the Role of Smart Policies, available at http://diacore.eu/results/item/enhancing-res-investments- final-report (accessed 01 April 2019).
[3] Panepinto, D., Gitelman, L., Kozhevnikov, M., Magaril, E., Magaril, R. & Zanetti, M.C., Energy from biomass for sustainable cities. IOP Conference Series: Earth and Environ- mental Science, 72(1), 2017. [Crossref]
[4] Chebotareva, G., Leading factors of market profitability of the renewable energy compa- nies. Proceedings of the 2nd International Conference on Social, Economic and Academic Leadership, Vol. 217, pp. 277–287, 2018. [Crossref]
[5] International Renewable Energy Agency (IRENA), Renewable Energy Statistics 2017. http://www.irena.org/DocumentDownloads/Publications/IRENA_Renewable_Energy_ Statistics_2017.pdf (accessed 10 January 2019).
[6] International Renewable Energy Agency (IRENA), Renewable energy highlights. http:// www.irena.org/DocumentDownloads/Publications/IRENA_Renewable_energy_high- lights_July_2017.pdf (accessed 10 Febraury 2019).
[7] Renewable Energy Policy Network for the 21st Century (REN21), State of renew- able energy 2016. Global report, http://www.ren21.net/wp-content/uploads/2016/10/ REN21_GSR2016_KeyFindings_RUSSIAN.pdf (accessed 11 February 2019).
[8] Renewable Energy Policy Network for the 21st Century (REN21), State of renewable energy2017.Globalreport.http://www.ren21.net/wp-content/uploads/2017/10/17-8399_ GSR_2017_KEY-FINDINGS_RU_low.pdf (accessed 20 March 2019).
[9] Renewables 2018, Global status report. http://www.ren21.net/gsr-2018 (accessed 20 March 2019).
[10] Frankfurt School-UNEP Centre/BNEF 2018, Global Trends in Renewable Energy Investment 2018. http://www.greengrowthknowledge.org/sites/default/files/down- loads/resource/Global_Trends_in_Renewable_Energy_Investment_Report_2018.pdf (accessed 20 March 2019).
[11] Chebotareva, G., Risk-oriented approach to competition assessment in the global renewable energy sources market. WIT Transactions on The Built Environment, 179, pp. 345–355, 2018. [Crossref]
[12] Mokhov, V.G., Chebotareva, G.S. & Khomenko, P.M., Modelling of ‘green’ invest- ments risks. Vestnik Yuzhno-Ural’skogo gosudarstvennogo universiteta. Seriya ‘Matematicheskoe modelirovanie i programmirovanie’, 11(2), pp. 154–159, 2018. [Crossref]
[13] Sorland B.F. & Rudel M.G.N., What drives Financial Distress Risk and Default Rates of Leveraged Buyout Targets? Empirical Evidence from European Transactions, Norwegian School of Economics: Norway, 2015.
[14] Khaidarshina G.A., Integrated model to assess the risk of bankruptcy. Finance, 2, pp. 67–69, 2009.
[15] Lombardi, P. & Schwabe, F., Sharing economy as a new business model for energy storage systems. Applied Energy, 188, pp. 485–496, 2017. apenergy.2016.12.016 [Crossref]
[16] Ascione, F., Bianco, N., De Stasio, C., Mauro, G.M. & Vanoli, G.P., Multi-stage and multi-objective optimization for energy retrofitting a developed hospital reference building: a new approach to assess cost-optimality. Applied Energy, 174, pp. 37–68, 2016. [Crossref]
[17] Johnston, S., Nonrefundable tax credits versus grants: The impact of subsidy form on the effectiveness of subsidies for renewable energy. Journal of the Association of Environmental and Resource Economists, 6(3), pp. 433–460, 2019. https://doi. org/10.1086/702736
[18] Gonzalez, A., Riba, J.R., Esteban, B. & Rius, A., Environmental and cost optimal design of a biomass–Wind–PV electricity generation system. Renewable Energy, 126, pp. 420–430, 2018. [AQ2] [Crossref]
[19] Bhattacharya, M., Paramati, S.R., Ozturk, I. & Bhattacharya, S., The effect of renewable energy consumption on economic growth: evidence from top 38 countries. Applied Energy, 162, pp. 733–741, 2016. [Crossref]
[20] Rediske, G., Siluk, J.C.M., Gastaldo, N.G., Rigo, P.D. & Rosa, C.B., Determinant factors in site selection for photovoltaic projects: a systematic review. International Journal of Energy Research, 43(5), pp. 1689–1701, 2019. [Crossref]
[21] Zhang, C. & Yang, J., Economic benefits assessments of ‘coal-to-electricity’ project in rural residents heating based on life cycle cost. Journal of Cleaner Production, 213, pp. 217–224, 2019. [Crossref]
[22] [McInerney, C. & Bunn, D.W., Expansion of the investor base for the energy transition.
Energy Policy, 129, pp. 1240–1244, 2019. [Crossref]
[23] Oliveira, T., Varum, C. & Botelho, A., Econometric modeling of CO2 emissions abatement: comparing alternative approaches. Renewable and Sustainable Energy Reviews, 105, pp. 310–322, 2019. [Crossref]
Cite this:
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Chebotareva, G. S. (2019). Risk Assessment of Renewable Energies: Global Exposure. Int. J. Energy Prod. Manag., 4(2), 145-157. https://doi.org/10.2495/EQ-V4-N2-145-157
G. S. Chebotareva, "Risk Assessment of Renewable Energies: Global Exposure," Int. J. Energy Prod. Manag., vol. 4, no. 2, pp. 145-157, 2019. https://doi.org/10.2495/EQ-V4-N2-145-157
@research-article{Chebotareva2019RiskAO,
title={Risk Assessment of Renewable Energies: Global Exposure},
author={G.S. Chebotareva},
journal={International Journal of Energy Production and Management},
year={2019},
page={145-157},
doi={https://doi.org/10.2495/EQ-V4-N2-145-157}
}
G.S. Chebotareva, et al. "Risk Assessment of Renewable Energies: Global Exposure." International Journal of Energy Production and Management, v 4, pp 145-157. doi: https://doi.org/10.2495/EQ-V4-N2-145-157
G.S. Chebotareva. "Risk Assessment of Renewable Energies: Global Exposure." International Journal of Energy Production and Management, 4, (2019): 145-157. doi: https://doi.org/10.2495/EQ-V4-N2-145-157
CHEBOTAREVA G S. Risk Assessment of Renewable Energies: Global Exposure[J]. International Journal of Energy Production and Management， 2019， 4(2)： 145-157. https://doi.org/10.2495/EQ-V4-N2-145-157