Minimizing Variance in Variable Renewable Energy Generation in Northern Europe

Research output: Chapter in Book/Report/Conference proceedingArticle in proceedings – Annual report year: 2018Researchpeer-review

Standard

Minimizing Variance in Variable Renewable Energy Generation in Northern Europe. / Koivisto, Matti Juhani; Cutululis, Nicolaos Antonio; Ekstrom, Jussi.

2018 IEEE International Conference on Probabilistic Methods Applied to Power Systems (PMAPS). IEEE, 2018.

Research output: Chapter in Book/Report/Conference proceedingArticle in proceedings – Annual report year: 2018Researchpeer-review

Harvard

Koivisto, MJ, Cutululis, NA & Ekstrom, J 2018, Minimizing Variance in Variable Renewable Energy Generation in Northern Europe. in 2018 IEEE International Conference on Probabilistic Methods Applied to Power Systems (PMAPS). IEEE, IEEE International Conference on Probabilistic Methods Applied to Power Systems, Boise, United States, 24/06/2018. https://doi.org/10.1109/PMAPS.2018.8440369

APA

Koivisto, M. J., Cutululis, N. A., & Ekstrom, J. (2018). Minimizing Variance in Variable Renewable Energy Generation in Northern Europe. In 2018 IEEE International Conference on Probabilistic Methods Applied to Power Systems (PMAPS) IEEE. https://doi.org/10.1109/PMAPS.2018.8440369

CBE

Koivisto MJ, Cutululis NA, Ekstrom J. 2018. Minimizing Variance in Variable Renewable Energy Generation in Northern Europe. In 2018 IEEE International Conference on Probabilistic Methods Applied to Power Systems (PMAPS). IEEE. https://doi.org/10.1109/PMAPS.2018.8440369

MLA

Koivisto, Matti Juhani, Nicolaos Antonio Cutululis and Jussi Ekstrom "Minimizing Variance in Variable Renewable Energy Generation in Northern Europe". 2018 IEEE International Conference on Probabilistic Methods Applied to Power Systems (PMAPS). IEEE. 2018. https://doi.org/10.1109/PMAPS.2018.8440369

Vancouver

Koivisto MJ, Cutululis NA, Ekstrom J. Minimizing Variance in Variable Renewable Energy Generation in Northern Europe. In 2018 IEEE International Conference on Probabilistic Methods Applied to Power Systems (PMAPS). IEEE. 2018 https://doi.org/10.1109/PMAPS.2018.8440369

Author

Koivisto, Matti Juhani ; Cutululis, Nicolaos Antonio ; Ekstrom, Jussi. / Minimizing Variance in Variable Renewable Energy Generation in Northern Europe. 2018 IEEE International Conference on Probabilistic Methods Applied to Power Systems (PMAPS). IEEE, 2018.

Bibtex

@inproceedings{218dce1239d34e1586db401a2fb349d3,
title = "Minimizing Variance in Variable Renewable Energy Generation in Northern Europe",
abstract = "The growing installations of variable renewable energy (VRE) sources, which are driven by weather patterns, can cause challenges to the operation and planning of power systems. This paper minimizes the variance of aggregate VRE generation based on the amount of different VRE technology types installed in different countries over a large geographical area. A mixture of offshore and onshore wind, and solar photovoltaic generation is considered. In the presented case study in Northern Europe, the optimized scenario provides a doubling of the expected annual VRE energy with a much lower increase in the aggregate VRE generation variability compared to other scenarios. The optimized scenario shows clearly the benefit of having a mixture of different VRE technologies with geographically highly spread installations.",
keywords = "Optimization, renewable energy, solar, variance, wind",
author = "Koivisto, {Matti Juhani} and Cutululis, {Nicolaos Antonio} and Jussi Ekstrom",
year = "2018",
doi = "10.1109/PMAPS.2018.8440369",
language = "English",
isbn = "978-1-5386-3597-1",
booktitle = "2018 IEEE International Conference on Probabilistic Methods Applied to Power Systems (PMAPS)",
publisher = "IEEE",

}

RIS

TY - GEN

T1 - Minimizing Variance in Variable Renewable Energy Generation in Northern Europe

AU - Koivisto, Matti Juhani

AU - Cutululis, Nicolaos Antonio

AU - Ekstrom, Jussi

PY - 2018

Y1 - 2018

N2 - The growing installations of variable renewable energy (VRE) sources, which are driven by weather patterns, can cause challenges to the operation and planning of power systems. This paper minimizes the variance of aggregate VRE generation based on the amount of different VRE technology types installed in different countries over a large geographical area. A mixture of offshore and onshore wind, and solar photovoltaic generation is considered. In the presented case study in Northern Europe, the optimized scenario provides a doubling of the expected annual VRE energy with a much lower increase in the aggregate VRE generation variability compared to other scenarios. The optimized scenario shows clearly the benefit of having a mixture of different VRE technologies with geographically highly spread installations.

AB - The growing installations of variable renewable energy (VRE) sources, which are driven by weather patterns, can cause challenges to the operation and planning of power systems. This paper minimizes the variance of aggregate VRE generation based on the amount of different VRE technology types installed in different countries over a large geographical area. A mixture of offshore and onshore wind, and solar photovoltaic generation is considered. In the presented case study in Northern Europe, the optimized scenario provides a doubling of the expected annual VRE energy with a much lower increase in the aggregate VRE generation variability compared to other scenarios. The optimized scenario shows clearly the benefit of having a mixture of different VRE technologies with geographically highly spread installations.

KW - Optimization

KW - renewable energy

KW - solar

KW - variance

KW - wind

U2 - 10.1109/PMAPS.2018.8440369

DO - 10.1109/PMAPS.2018.8440369

M3 - Article in proceedings

SN - 978-1-5386-3597-1

BT - 2018 IEEE International Conference on Probabilistic Methods Applied to Power Systems (PMAPS)

PB - IEEE

ER -