Scholarly record
VARIABILITY ASSESSMENT OF RENEWABLE ENERGY SOURCES BASED ON POWER GENERATION RECORDINGS
Abstract
Reliability of renewable energy generation forecast became particularly important since its share denotes a constant growth in the global energy mix and the uncertainty of supply continuity resulting from this rises. Given the numerous geographic and meteorological factors that greatly influence the results of a more general probabilistic determination, an accurate prospect is hardly possible when enlarging the territory or the time span. Moreover, power systems disturbances and load variation, also unpredictable, overlap the inherent intermittency of renewable energy based plants electricity output, further complicating to obtain a satisfactory estimates. This paper aims to assess the variation trend of wind energy, photovoltaic, biomass and hydro energy based on momentary recording of power generation and demand for the last decade in Romania. First, the multiple variables influencing the recorded power generated by each source were identified and coefficient matrices determined by regression, for each day. Forwards, the cumulative probability of achieving a certain renewable energy share in meeting electricity demand for selected days is calculated after fitting the most suitable distribution. Results are presented for the minimum and maximum average electricity demand days, considered to be representatives in terms of system loading. Using the most recent registrations of system's electricity generation and demand, for 2017, the assessments are estimated dependences are evaluated. Available data processing and computational algorithms were developed in Matlab programming environment.
Publication Impact Profile
Publication details
References14
Katinas V., Marčiukaitis M., Gecevičius G., Markevičius A., Statistical analysis of wind characteristics based on Weibull methods for estimation of power generation in Lithuania, Renewable Energy, vol. 113, pp. 190-201, 2017;
Chupong C., Plangklang B., Forecasting power output of PV grid connected system in Thailand without using solar radiation measurement, Energy Procedia, vol. 9, pp. 230-237, 2011;
Ciupăgeanu D. A., Lăzăroiu G., Tîrșu M., Carbon dioxide emissions reductions by renewable energy employment in Romania, 2017 International Conference on Electromechanical and Power Systems (SIELMEN), 11-13 October, Iași, Romania, 2017, pp. 281-285;
Mandal P., Madhira S. T. S., Ulhaque A., Meng J., Pineda R. L., Forecasting power output of solar photovoltaic system using wavelet transform and artificial intelligence techniques, Procedia Computer Science, vol. 12, pp. 332-337, 2012;
Inman R. H., Pedro H. T. C., Coimbra C. F. M., Solar forecasting methods for renewable energy integration, Progress in Energy and Combustion Science, vol. 39, pp. 535-576, 2013;
Monfared M., Rastegar H., Kojabadi H. M., A new strategy for wind speed forecasting using artificial intelligent methods, Renewable energy, vol. 34, pp. 845-848, 2009;
Barelli L., Bidini G., Bonucci F., A micro-grid operation analysis for cost-effective battery energy storage and RES plants integration, Energy, vol. 113, pp. 831-844, 2016;
Foley A. M., Leahy P. G., Marvuglia A., McKeogh E. J., Current methods and advances in forecasting of wind power generation, Renewable Energy, vol. 37, pp. 1-8, 2012;
Murata A., Ohtake H., Oozeki T., Modeling of uncertainty of solar irradiance forecasts on numerical weather predictions with the estimation of multiple confidence intervals, Renewable Energy, vol. 117, pp. 193-201, 2018;
Zhang Y., Wang J., Wang X., Review on probabilistic forecasting of wind power generation, Renewable and Sustainable Energy Reviews, vol. 32, pp. 255-270, 2014;
www.transelectrica.ro
data.un.org
globalwindatlas.info
rem.jrc.ec.europa.eu
Citing literature
Number of times cited according to Crossref: 6
View or Download full articleAccess options
SWS access login
Login as SWS Scientific CommitteeLogin as SWS Scientific PartnerLogin as SWS AuthorAuthors and approved SWS contributors will read and export their own linked papers after identity matching by SWS profile, email and SGEM GlobalID.
For librarian assistance: [email protected]
Purchase Instant Access
- Article can be downloaded after successful payment.
- Article may be used according to SWS library access terms.
- Article cannot be redistributed.


