Evaluation of electric power generation pr ojects in an environment of climate policy uncertainty
Keywords:
Electric generation projects, analysis of investments under uncertainty, emission reduction certificatesAbstract
This article discusses the results of a financial evaluation model for medium-capacity hydroelectric generation plants taking into account uncertainty associated with variables such as electricity price, actual generation level, and climate policy, materialized in the form of the prices of emission reduction certificates. The model consists of two phases. The first is based on the discounted free cash flow method, and the second proposes an analysis based on a Monte Carlo simulation to consider the risk level of critical variables. Electricity prices were simulated by means of a generalized Wiener process, with trend and volatility parameters obtained from an analysis of average prices of bilateral agreements reported on the Colombian electric power market. For actual generation, an adjustment was made to a probability distribution based on plant factor information of a group of small hydroelectric power facilities on the Colombian market. Then, the financial risk indicators of the project were reviewed, and a sensitivity analysis was carried out at different price ranges of emission reduction certificates. The findings show that, while climate policy incentives are well-intentioned, their effectiveness on project profitability is not optimal if consideration is given to perspectives based on the price of emission reduction certificates
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References
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2. ANTUNES, C. H., MARTINS, A. G. & BRITO, I. S. A multiple objective mixed integer linear programming model for power generation expansion planning. In: Energy. Vol. 29, No. 4 (Mar. 2004); p. 613-627.
3. ARANGO, S. & LARSEN, E. R. The environmental paradox in generation: How South America is gradually becoming more dependent on thermal generation. In: Renewable and Sustainable Energy Reviews. Vol. 14, No. 9 (Dec. 2010); p. 2956-2965.
4. BARRIA, C. & RUDNICK, H. Investment under Uncertainty in Power Generation: Integrated Electricity Prices Modeling and Real Options Approach. In: Latin America Transactions, IEEE (Revista IEEE America Latina). Vol.9, No.5 (Sep. 2011); p. 785- 792.
5. BLYTH, W., BRADLEY, R., BUNN, D., CLARKE, C., WILSON, T. & YANG, M. Investment risks under uncertain climate change policy. In: Energy Policy. Vol. 35, No. 11 (Nov. 2007); p. 5766- 5773.
6. CARERI, F., GENESI, C., MARANNINO, P., MONTAGNA, M., ROSSI, S. & SIVIERO, I. Generation Expansion Planning in the Age of Green Economy. In: Power Systems, IEEE Transactions on Power Systems. Vol. 26, No.4 (2011); p. 2214-2223.
7. CHEN, S.-L., ZHAN, T.-S. & TSAY, M.-T. Generation expansion planning of the utility with refined immune algorithm. In: Electric Power Systems Research. Vol. 76, No. 4 (Jan. 2006); p. 251-258.
8. DIXIT, A. & PINDYCK, R. Investment Under Uncertainty, United States of America, Princeton University Press, 1994. 476 p.
9. FIRMO, H. T. & LEGEY, L. F. L. Generation expansion planning: An iterative genetic algorithm approach. In: IEEE Transactions on Power Systems. Vol. 17, No.3 (Ago. 2002); p. 901-906.
10. FLETEN, S.-E. & KRISTOFFERSEN, T. K. Stochastic programming for optimizing bidding strategies of a Nordic hydropower producer. In: European Journal of Operational Research. Vol.181, No.2 (Sep. 2007); p. 916-928.
11. GRIFFES, P., HSU, M. & KAHN, E. Power Asset Valuation: Real Options, Ancillary Services, and Environmental Risks. The New Power Markets: Corporate Strategies for Risk and Reward. London: Risk Books, 1999.
12. HEIDARI, A. R. Generation expansion planning in pool market: A hybrid DP/GT model. In: International Conference on Systems – Proceedings. (2010); p. 87-92.
13. JALILZADEH, S., SHABANI, A. & AZADRU, A. Multi-period generation expansion planning using genetic algorithm. In: International Congress on Ultra Modern Telecommunications and Control Systems and Workshops. (2010); p. 358-363.
14. KARAKI, S. H., CHAABAN, F. B., AL-NAKHL, N. & TARHINI, K. A.. Power generation expansion planning with environmental consideration for Lebanon. In: International Journal of Electrical Power & Energy Systems. Vol. 24, No. 8. (Oct. 2002); p.611-619.
15. KJÆRLAND, F. A real option analysis of investments in hydropower--The case of Norway. In: Energy Policy.Vol. 35, No. 11 (Nov. 2007); p. 5901-5908.
16. LAURIKKA, H. Option value of gasification technology within an emissions trading scheme. In: Energy Policy. Vol. 34, No. 18 (Dic. 2006); p. 3916-3928.
17. LAURIKKA, H. & KOLJONEN, T. Emissions trading and investment decisions in the power sector—a case study in Finland. In: Energy Policy. Vol. 34, No. 9 (Jun. 2006); p.1063-1074.
18. LAURIKKA, H. & SPRINGER, U. Risk and return of project-based climate change mitigation: a portfolio approach. En: Global Environmental Change. Vol. 13, No. 3 (Mar. 2003); p. 207-217.
19. LEMMING, J. Financial risks for green electricity investors and producers in a tradable green certificate market. In: Energy Policy. Vol. 31, No. 1 (Jan. 2003); p. 21-32.
20. LUCIA, J. & SCHWARTZ, E. Electricity Prices and Power Derivatives: Evidence from the Nordic Power Exchange. In: Review of Derivatives Research. Vol. 5, No. 1 (Jan. 2002); p. 5-50.
21. MALCOLM, S. A. & ZENIOS, S. A. Robust optimization for power systems capacity expansion under uncertainty. In: Journal of the Operational Research Society. Vol.45 (Sep. 1994); p. 1040-1049.
22. MASUD, A., MEZA, J. & YILDIRIM, M. A Multi-Objective Model for Power Generation Expansion Planning. IIE Annual Conference. Proceedings. (2007).
23. MISHRA, S., SINGAL, S. K. & KHATOD, D. K. Optimal installation of small hydropower plant—A review. In: Renewable and Sustainable Energy Reviews. Vol.15, No. 8 (Oct. 2011); p. 3862- 3869.
24. PARK, Y. M., PARK, J. B. & WON, J. R. A hybrid genetic algorithm/ dynamic programming approach to optimal long-term generation expansion planning. In: International Journal of Electrical Power & Energy Systems. Vol.20, No.4 (May. 1998); p. 295-303.
25. PEREIRA, A. J. C. & SARAIVA, J. T. Generation expansion planning (GEP) - A long-term approach using system dynamics and genetic algorithms (GAs). In: Energy. Vol. 36, No.8 (Ago. 2011); p. 5180- 5199.
26. PINDYCK, R. S. The Dynamics of Commodity Spot and Futures Markets: A Primer. In: The Energy Journal. 22, 3. (2001); p. 1-29.
27. SANTOLIN, A., CAVAZZINI, G., PAVESI, G., ARDIZZON, G. & ROSSETTI, A. Techno-economical method for the capacity sizing of a small hydropower plant. In: Energy Conversion and Management. 52, 7. (Jul. 2011); p. 2533-2541.
28. SCHWARTZ, E. Valuing long-term commodity assets. In: Journal of Energy Finance & Development. Vol. 3, No. 2 (1998); p. 85-99.
29. SHRESTHA, R. M. & ABEYGUNAWARDANA, A. M. A. K. Evaluation of economic rent of hydropower projects. En: Energy Policy. Vol.37, No. 5 (May. 2009); p.1886-1897.
30. SIRIKUM, J. & TECHANITISAWAD, A. Power generation expansion planning with emission control: A nonlinear model and a GA-based heuristic approach. In: International Journal of Energy Research. Vol. 30, No. 2 (Feb. 2006). p. 81-99.
31. TEKINER, H. Multi-objective stochastic models for electricity generation expansion planning problems considering risk. 2010. 251 p. PhD Thesis Industrial Engineering. Rutgers The State University of New Jersey.
32. TEKINER, H., COIT, D. W. & FELDER, F. A. Multi-period multiobjective electricity generation expansion planning problem with Monte-Carlo simulation. In: Electric Power Systems Research. Vol. 80, No. 12 (Dic. 2010); p. 1394-1405.
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2017-06-30
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Evaluation of electric power generation pr ojects in an environment of climate policy uncertainty. (2017). Entramado, 9(1), 102-177. https://revistas.unilibre.edu.co/index.php/entramado/article/view/3447
