Cite Article

Multi-Stage Statistical Approach to Wind Power Forecast Errors Evaluation: A Southern Sulawesi Case Study

Choose citation format

BibTeX

@article{IJASEIT12385,
   author = {Dhany Harmeidy Barus and Rinaldy Dalimi},
   title = {Multi-Stage Statistical Approach to Wind Power Forecast Errors Evaluation: A Southern Sulawesi Case Study},
   journal = {International Journal on Advanced Science, Engineering and Information Technology},
   volume = {11},
   number = {2},
   year = {2021},
   pages = {633--641},
   keywords = {Statistical approach; multi-stage; wind power forecast errors.},
   abstract = {Wind Power Plant (WPP) is part of renewable energy sources, with rapid expansion worldwide. It has the advantages of clean and green energy, but its uncertainty leads to an additional grid integration cost. The uncertainty of wind power output is much dependent on the accuracy of the wind power forecast (WPF) result. Since there is no perfect wind power forecast, understanding the current system's forecast accuracy characteristics is essential in expecting typical errors faced in the future. This paper proposed a new algorithm of the statistical approach method to evaluate characteristics of wind power forecast errors (WPFE) from an observed power system with high-penetration WPP. This method combined the approach of scatter diagram, statistical distribution, standard error performance, and score weighting in a multi-stage algorithm. It consists of serial and parallel processes to check the consistency of the results. In this study, a comprehensive analysis was made of various scenarios based on location and timescale. This proposed algorithm has been successfully tested on statistical data of Sidrap WPP and Jeneponto WPP in the Southern Sulawesi power system. The result showed that the scenario with the aggregation of both WPPs in hour-ahead timescale has the most accurate and consistent performance among all scenarios. It demonstrated specific characteristics of WPFE in the observed power system that can be used as an essential starting point in conducting future wind integration expansion studies.},
   issn = {2088-5334},
   publisher = {INSIGHT - Indonesian Society for Knowledge and Human Development},
   url = {http://ijaseit.insightsociety.org/index.php?option=com_content&view=article&id=9&Itemid=1&article_id=12385},
   doi = {10.18517/ijaseit.11.2.12385}
}

EndNote

%A Barus, Dhany Harmeidy
%A Dalimi, Rinaldy
%D 2021
%T Multi-Stage Statistical Approach to Wind Power Forecast Errors Evaluation: A Southern Sulawesi Case Study
%B 2021
%9 Statistical approach; multi-stage; wind power forecast errors.
%! Multi-Stage Statistical Approach to Wind Power Forecast Errors Evaluation: A Southern Sulawesi Case Study
%K Statistical approach; multi-stage; wind power forecast errors.
%X Wind Power Plant (WPP) is part of renewable energy sources, with rapid expansion worldwide. It has the advantages of clean and green energy, but its uncertainty leads to an additional grid integration cost. The uncertainty of wind power output is much dependent on the accuracy of the wind power forecast (WPF) result. Since there is no perfect wind power forecast, understanding the current system's forecast accuracy characteristics is essential in expecting typical errors faced in the future. This paper proposed a new algorithm of the statistical approach method to evaluate characteristics of wind power forecast errors (WPFE) from an observed power system with high-penetration WPP. This method combined the approach of scatter diagram, statistical distribution, standard error performance, and score weighting in a multi-stage algorithm. It consists of serial and parallel processes to check the consistency of the results. In this study, a comprehensive analysis was made of various scenarios based on location and timescale. This proposed algorithm has been successfully tested on statistical data of Sidrap WPP and Jeneponto WPP in the Southern Sulawesi power system. The result showed that the scenario with the aggregation of both WPPs in hour-ahead timescale has the most accurate and consistent performance among all scenarios. It demonstrated specific characteristics of WPFE in the observed power system that can be used as an essential starting point in conducting future wind integration expansion studies.
%U http://ijaseit.insightsociety.org/index.php?option=com_content&view=article&id=9&Itemid=1&article_id=12385
%R doi:10.18517/ijaseit.11.2.12385
%J International Journal on Advanced Science, Engineering and Information Technology
%V 11
%N 2
%@ 2088-5334

IEEE

Dhany Harmeidy Barus and Rinaldy Dalimi,"Multi-Stage Statistical Approach to Wind Power Forecast Errors Evaluation: A Southern Sulawesi Case Study," International Journal on Advanced Science, Engineering and Information Technology, vol. 11, no. 2, pp. 633-641, 2021. [Online]. Available: http://dx.doi.org/10.18517/ijaseit.11.2.12385.

RefMan/ProCite (RIS)

TY  - JOUR
AU  - Barus, Dhany Harmeidy
AU  - Dalimi, Rinaldy
PY  - 2021
TI  - Multi-Stage Statistical Approach to Wind Power Forecast Errors Evaluation: A Southern Sulawesi Case Study
JF  - International Journal on Advanced Science, Engineering and Information Technology; Vol. 11 (2021) No. 2
Y2  - 2021
SP  - 633
EP  - 641
SN  - 2088-5334
PB  - INSIGHT - Indonesian Society for Knowledge and Human Development
KW  - Statistical approach; multi-stage; wind power forecast errors.
N2  - Wind Power Plant (WPP) is part of renewable energy sources, with rapid expansion worldwide. It has the advantages of clean and green energy, but its uncertainty leads to an additional grid integration cost. The uncertainty of wind power output is much dependent on the accuracy of the wind power forecast (WPF) result. Since there is no perfect wind power forecast, understanding the current system's forecast accuracy characteristics is essential in expecting typical errors faced in the future. This paper proposed a new algorithm of the statistical approach method to evaluate characteristics of wind power forecast errors (WPFE) from an observed power system with high-penetration WPP. This method combined the approach of scatter diagram, statistical distribution, standard error performance, and score weighting in a multi-stage algorithm. It consists of serial and parallel processes to check the consistency of the results. In this study, a comprehensive analysis was made of various scenarios based on location and timescale. This proposed algorithm has been successfully tested on statistical data of Sidrap WPP and Jeneponto WPP in the Southern Sulawesi power system. The result showed that the scenario with the aggregation of both WPPs in hour-ahead timescale has the most accurate and consistent performance among all scenarios. It demonstrated specific characteristics of WPFE in the observed power system that can be used as an essential starting point in conducting future wind integration expansion studies.
UR  - http://ijaseit.insightsociety.org/index.php?option=com_content&view=article&id=9&Itemid=1&article_id=12385
DO  - 10.18517/ijaseit.11.2.12385

RefWorks

RT Journal Article
ID 12385
A1 Barus, Dhany Harmeidy
A1 Dalimi, Rinaldy
T1 Multi-Stage Statistical Approach to Wind Power Forecast Errors Evaluation: A Southern Sulawesi Case Study
JF International Journal on Advanced Science, Engineering and Information Technology
VO 11
IS 2
YR 2021
SP 633
OP 641
SN 2088-5334
PB INSIGHT - Indonesian Society for Knowledge and Human Development
K1 Statistical approach; multi-stage; wind power forecast errors.
AB Wind Power Plant (WPP) is part of renewable energy sources, with rapid expansion worldwide. It has the advantages of clean and green energy, but its uncertainty leads to an additional grid integration cost. The uncertainty of wind power output is much dependent on the accuracy of the wind power forecast (WPF) result. Since there is no perfect wind power forecast, understanding the current system's forecast accuracy characteristics is essential in expecting typical errors faced in the future. This paper proposed a new algorithm of the statistical approach method to evaluate characteristics of wind power forecast errors (WPFE) from an observed power system with high-penetration WPP. This method combined the approach of scatter diagram, statistical distribution, standard error performance, and score weighting in a multi-stage algorithm. It consists of serial and parallel processes to check the consistency of the results. In this study, a comprehensive analysis was made of various scenarios based on location and timescale. This proposed algorithm has been successfully tested on statistical data of Sidrap WPP and Jeneponto WPP in the Southern Sulawesi power system. The result showed that the scenario with the aggregation of both WPPs in hour-ahead timescale has the most accurate and consistent performance among all scenarios. It demonstrated specific characteristics of WPFE in the observed power system that can be used as an essential starting point in conducting future wind integration expansion studies.
LK http://ijaseit.insightsociety.org/index.php?option=com_content&view=article&id=9&Itemid=1&article_id=12385
DO  - 10.18517/ijaseit.11.2.12385