Economic and operational risks in wind energy projects in Latvia


D. Bezrukovs and A. Sauhatas

 

2017/04/25

Abstrac

The paper addresses the problem of economic and operational uncertainty in wind energy projects associated with the volatility of wind speed, concurrent electricity market prices and technical characteristics of wind turbines. The study proposes a comprehensive approach towards the feasibility evaluation of wind energy projects in the conditions of limited wind speed data availability at high altitudes and deregulated electricity market in Latvia. The study performs a sensitivity analysis of wind generator efficiency and revenue generation potential across the range of technical and economic factors. The study uses Stochastic Differential Equation (SDE) models for the out-of-sample forecasting of wind speed and electricity prices in combination with Monte Carlo simulation technique in order to come-up with the distribution of revenue projections and efficiency estimates for a hypothetical wind park. A broad range of project development scenarios involving several wind generator types and multiple mast height options is considered. The study is based on proprietary high frequency wind measurements data gathered in the north-western coastal part of Latvia at the range of altitudes of up to 50m and daily electricity market prices from the Latvian segment of Nord Pool power market. The results of the study provide quantitative basis for optimal decision-making process at the planning stage of wind energy projects and highlight the importance of the initial choice of wind generator models.

Published in: Renewable Energy & Power Quality Journal (RE&PQJ, Nº. 15)
Pages: 377-382 Date of Publication: 2017/04/25
ISSN: 2172-038X Date of Current Version:
REF: 326-17 Issue Date: April 2017
DOI:10.24084/repqj15.326 Publisher: EA4EPQ

Authors and affiliations

D. Bezrukovs and A. Sauhatas
Department of Electric Power Systems. Riga Technical University. Riga (Latvia)

Key word

Wind speed forecasts, sensitivity analysis, wind measurements, wind turbines, SDE models.

References

[1] Brigo, D., Dalessandro, A., Neugebauer, M. and Triki, F. (2009). A stochastic processes toolkit for risk management: Geometric Brownian motion, jumps, GARCH and variance gamma models. Journal of Risk Management in Financial Institutions, 2: 365-393
[2] Bezrukovs V., A. Zacepins, Vl. Bezrukovs, V. Komasilovs Comparison of methods for evaluation of wind turbine power production by the results of wind shear measurements on the Baltic coast of Latvia. Renewable Energy, RENE-D-15-00512R2, 2015, in print, 18 p.
[3] Vasicek, O. (1977). An Equilibrium Characterization of the Term Structure. Journal of Financial Economics, 5, 177-188.
[4] Seifert, Jan, Uhrig-Homburg, Marliese, Modelling Jumps in Electricity Prices: Theory and Empirical Evidence, Review of Derivatives Research, Vol. 10, pp 59-85, 2007.
[5] Lucia, Julio J., Schwartz, Eduaro, Electricity Prices and Power Derivatives: Evidence from the Nordic Power Exchange, Review of Derivatives Research, Vol. 5, Issue 1, pp 5-50, 2002.
[6] Escribano, Alvaro, Pena, Juan Ignacio, Villaplana, Pablo, Modeling Electricity Prices: International Evidence, Universidad Carloes III de Madrid, Working Paper 02-27, 2002.
[7] Review of RES perspective in Baltic countries till 2030 (2015) http://elering.ee/public/Infokeskus/Uuringud/Review_of_RES_pers pective_in_Baltic_countries_till_2030.pdf
[8] Kwiatkowski, D., P.C.B. Phillips, P. Schmidt, Y. Shin (1992): Testing the Null Hypothesis of Stationarity against the Alternative of a Unit Root, Journal of Econometrics, 54, pp. 159-178, North- Holland.