Optimal Allocation of Norwegian Offshore Wind Power : A Copula Approach : How can a thoughtful placement of offshore wind parks reduce variability in production output?

This thesis investigates how to optimize stable wind production along the coast of Norway. The research is carried out by studying how well a compound dependency model, consisting of a time series and copula model, for simulation of wind power data performs compared to historical data when optimizin...

Full description

Bibliographic Details
Main Authors: Alfsvåg, Henrik Heltne, Sollie, Sander
Other Authors: Berentsen, Geir Drage
Format: Master Thesis
Language:English
Published: 2023
Subjects:
Online Access:https://hdl.handle.net/11250/3094350
id ftnorgehandelshs:oai:openaccess.nhh.no:11250/3094350
record_format openpolar
spelling ftnorgehandelshs:oai:openaccess.nhh.no:11250/3094350 2023-11-05T03:45:24+01:00 Optimal Allocation of Norwegian Offshore Wind Power : A Copula Approach : How can a thoughtful placement of offshore wind parks reduce variability in production output? Alfsvåg, Henrik Heltne Sollie, Sander Berentsen, Geir Drage 2023 application/pdf https://hdl.handle.net/11250/3094350 eng eng https://hdl.handle.net/11250/3094350 business analytics Master thesis 2023 ftnorgehandelshs 2023-10-11T22:49:37Z This thesis investigates how to optimize stable wind production along the coast of Norway. The research is carried out by studying how well a compound dependency model, consisting of a time series and copula model, for simulation of wind power data performs compared to historical data when optimizing a portfolio for wind power production areas. The weights for the areas in the portfolio are computed so that the areas with the most stable joint power production are included. The findings of this research will contribute to the understanding of how effective different optimization approaches for offshore wind park placements are and provide insights into the selection of optimal areas for offshore wind power development in Norway. The study's findings indicate that portfolio optimization performed on simulated data performs better than on historical data. Consequently, zero and low production values are reduced, and stability is increased for the portfolio made with simulated data. Moreover, Value at Risk (VaR) is argued to be a better performance measure for stable wind production than variance. The portfolio distribution when maximizing VaR is more left-skewed than the portfolio minimizing variance. Thus, maximizing VaR results in a higher variance, but less zero and low production values, and a higher average production which is argued to be more important. The positive effect of dispersed wind parks regarding stable wind production is evident. Following the pattern of diminishing correlation as distance increases, the optimal combination of wind parks includes places throughout the Norwegian coast. All areas are included in the optimal solution, but the most influential areas which should be prioritized are Sørlige Nordsjø 2, South of Kristiansand, West of Tromsø, and North of Tanafjorden. When the criteria for stable wind production is extended to include a penalty factor for low average production, diversification is partly de-prioritized to include areas with high average production, among these, more ... Master Thesis Tromsø NHH Brage Open institutional repository (Norwegian School of Economics)
institution Open Polar
collection NHH Brage Open institutional repository (Norwegian School of Economics)
op_collection_id ftnorgehandelshs
language English
topic business analytics
spellingShingle business analytics
Alfsvåg, Henrik Heltne
Sollie, Sander
Optimal Allocation of Norwegian Offshore Wind Power : A Copula Approach : How can a thoughtful placement of offshore wind parks reduce variability in production output?
topic_facet business analytics
description This thesis investigates how to optimize stable wind production along the coast of Norway. The research is carried out by studying how well a compound dependency model, consisting of a time series and copula model, for simulation of wind power data performs compared to historical data when optimizing a portfolio for wind power production areas. The weights for the areas in the portfolio are computed so that the areas with the most stable joint power production are included. The findings of this research will contribute to the understanding of how effective different optimization approaches for offshore wind park placements are and provide insights into the selection of optimal areas for offshore wind power development in Norway. The study's findings indicate that portfolio optimization performed on simulated data performs better than on historical data. Consequently, zero and low production values are reduced, and stability is increased for the portfolio made with simulated data. Moreover, Value at Risk (VaR) is argued to be a better performance measure for stable wind production than variance. The portfolio distribution when maximizing VaR is more left-skewed than the portfolio minimizing variance. Thus, maximizing VaR results in a higher variance, but less zero and low production values, and a higher average production which is argued to be more important. The positive effect of dispersed wind parks regarding stable wind production is evident. Following the pattern of diminishing correlation as distance increases, the optimal combination of wind parks includes places throughout the Norwegian coast. All areas are included in the optimal solution, but the most influential areas which should be prioritized are Sørlige Nordsjø 2, South of Kristiansand, West of Tromsø, and North of Tanafjorden. When the criteria for stable wind production is extended to include a penalty factor for low average production, diversification is partly de-prioritized to include areas with high average production, among these, more ...
author2 Berentsen, Geir Drage
format Master Thesis
author Alfsvåg, Henrik Heltne
Sollie, Sander
author_facet Alfsvåg, Henrik Heltne
Sollie, Sander
author_sort Alfsvåg, Henrik Heltne
title Optimal Allocation of Norwegian Offshore Wind Power : A Copula Approach : How can a thoughtful placement of offshore wind parks reduce variability in production output?
title_short Optimal Allocation of Norwegian Offshore Wind Power : A Copula Approach : How can a thoughtful placement of offshore wind parks reduce variability in production output?
title_full Optimal Allocation of Norwegian Offshore Wind Power : A Copula Approach : How can a thoughtful placement of offshore wind parks reduce variability in production output?
title_fullStr Optimal Allocation of Norwegian Offshore Wind Power : A Copula Approach : How can a thoughtful placement of offshore wind parks reduce variability in production output?
title_full_unstemmed Optimal Allocation of Norwegian Offshore Wind Power : A Copula Approach : How can a thoughtful placement of offshore wind parks reduce variability in production output?
title_sort optimal allocation of norwegian offshore wind power : a copula approach : how can a thoughtful placement of offshore wind parks reduce variability in production output?
publishDate 2023
url https://hdl.handle.net/11250/3094350
genre Tromsø
genre_facet Tromsø
op_relation https://hdl.handle.net/11250/3094350
_version_ 1781707518028808192