Minimizing Variance in Variable Renewable Energy Generation in Northern Europe

Matti Juhani Koivisto; Nicolaos Antonio Cutululis; Jussi Ekstrom

doi:10.1109/PMAPS.2018.8440369

Minimizing Variance in Variable Renewable Energy Generation in Northern Europe

Matti Juhani Koivisto, Nicolaos Antonio Cutululis, Jussi Ekstrom

Research output: Chapter in Book/Report/Conference proceeding › Article in proceedings › Research › peer-review

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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.

Original language	English
Title of host publication	2018 IEEE International Conference on Probabilistic Methods Applied to Power Systems (PMAPS)
Number of pages	6
Publisher	IEEE
Publication date	2018
ISBN (Print)	978-1-5386-3597-1
ISBN (Electronic)	978-1-5386-3596-4
DOIs	https://doi.org/10.1109/PMAPS.2018.8440369
Publication status	Published - 2018
Event	2018 IEEE International Conference on Probabilistic Methods Applied to Power Systems - Boise, United States Duration: 24 Jun 2018 → 28 Jun 2018 https://ieeexplore.ieee.org/xpl/conhome/8422007/proceeding

Conference

Conference	2018 IEEE International Conference on Probabilistic Methods Applied to Power Systems
Country/Territory	United States
City	Boise
Period	24/06/2018 → 28/06/2018
Internet address	https://ieeexplore.ieee.org/xpl/conhome/8422007/proceeding

Keywords

Optimization
renewable energy
solar
variance
wind

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

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10.1109/PMAPS.2018.8440369

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NSON-DK: North Sea Offshore Network - Denmark
Sørensen, P. E. S. (Project Coordinator), Das, K. (Project Participant), Koivisto, M. J. (Project Participant), Pade, L.-L. (Project Participant), Skytte, K. (Project Participant), Gea-Bermudez, J. (Project Participant), Papakonstantinou, A. (Project Participant), Boscán Flores, L. R. (Project Participant), Kanellas, P. (Project Participant), Plakas, K. (Project Participant), Kitzing, L. (Project Participant) & Bergaentzlé, C. M. (Project Participant)
01/04/2016 → 31/03/2020
Project: Research

Cite this

@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",

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year = "2018",

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publisher = "IEEE",

address = "United States",

note = "2018 IEEE International Conference on Probabilistic Methods Applied to Power Systems, PMAPS 2018 ; Conference date: 24-06-2018 Through 28-06-2018",

url = "https://ieeexplore.ieee.org/xpl/conhome/8422007/proceeding",

}

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, 2018 IEEE International Conference on Probabilistic Methods Applied to Power Systems, Boise, Indiana, United States, 24/06/2018. https://doi.org/10.1109/PMAPS.2018.8440369

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 proceeding › Article in proceedings › Research › peer-review

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

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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

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DO - 10.1109/PMAPS.2018.8440369

M3 - Article in proceedings

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

PB - IEEE

T2 - 2018 IEEE International Conference on Probabilistic Methods Applied to Power Systems

Y2 - 24 June 2018 through 28 June 2018

ER -

Minimizing Variance in Variable Renewable Energy Generation in Northern Europe

Abstract

Conference

Keywords

UN SDGs

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Projects

NSON-DK: North Sea Offshore Network - Denmark

Cite this