Minimizing variance in variable renewable energy generation in Northern Europe

Matti Koivisto; Nicolaos Cutululis; Jussi Ekstrom

doi:10.1109/PMAPS.2018.8440369

Minimizing variance in variable renewable energy generation in Northern Europe

Matti Koivisto, Nicolaos Cutululis, Jussi Ekstrom

Department of Electrical Engineering and Automation

Technical University of Denmark

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

11 Citations (Scopus)

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	Proceedings of the 2018 International Conference on Probabilistic Methods Applied to Power Systems, PMAPS 2018
Publisher	IEEE
Number of pages	6
ISBN (Print)	9781538635964
DOIs	https://doi.org/10.1109/PMAPS.2018.8440369
Publication status	Published - 17 Aug 2018
MoE publication type	A4 Conference publication
Event	International Conference on Probabilistic Methods Applied to Power Systems - Boise, United States Duration: 24 Jun 2018 → 28 Jun 2018

Conference

Conference	International Conference on Probabilistic Methods Applied to Power Systems
Abbreviated title	PMAPS
Country/Territory	United States
City	Boise
Period	24/06/2018 → 28/06/2018

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

https://orbit.dtu.dk/en/publications/minimizing-variance-in-variable-renewable-energy-generation-in-no

Cite this

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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 = "Matti Koivisto and Nicolaos Cutululis and Jussi Ekstrom",

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Koivisto, M, Cutululis, N & Ekstrom, J 2018, Minimizing variance in variable renewable energy generation in Northern Europe. in Proceedings of the 2018 International Conference on Probabilistic Methods Applied to Power Systems, PMAPS 2018., 8440369, IEEE, International Conference on Probabilistic Methods Applied to Power Systems, Boise, Idaho, 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; Cutululis, Nicolaos; Ekstrom, Jussi.
Proceedings of the 2018 International Conference on Probabilistic Methods Applied to Power Systems, PMAPS 2018. IEEE, 2018. 8440369.

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

TY - GEN

T1 - Minimizing variance in variable renewable energy generation in Northern Europe

AU - Koivisto, Matti

AU - Cutululis, Nicolaos

AU - Ekstrom, Jussi

PY - 2018/8/17

Y1 - 2018/8/17

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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M3 - Conference article in proceedings

AN - SCOPUS:85053161453

SN - 9781538635964

BT - Proceedings of the 2018 International Conference on Probabilistic Methods Applied to Power Systems, PMAPS 2018

PB - IEEE

T2 - 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

Access to Document

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