2023-03-20 スイス連邦工科大学チューリッヒ校(ETHZurich)
アルプス地方やスイス全体で風力タービンをできるだけ少なくする場合、西スイス高原の風の強い農地を利用することを検討することが価値があるとされた。
この調査により、2050年までにスイスが目指す年間4.3 TWhの風力発電量を達成するためには約760基の風力タービンが必要であることが明らかにされ、その内40％がアルプス地方に必要とされることも示された。
＜関連情報＞
- https://ethz.ch/en/news-and-events/eth-news/news/2023/03/where-should-wind-turbines-be-constructed-in-switzerland.html
- https://www.sciencedirect.com/science/article/pii/S1462901123000497
空間政策によるエネルギー転換の実現 – 進化型多目的最適化で風車立地のパレート最適解を見出す How spatial policies can leverage energy transitions − Finding Pareto-optimal solutions for wind turbine locations with evolutionary multi-objective optimization
Reto Spielhofer, Jonas Schwaab, Adrienne Grêt-Regamey
Environmental Science & Policy Available online: 27 February 2023
DOI:https://doi.org/10.1016/j.envsci.2023.02.016
Highlights
- •Optimization of wind turbine allocations under different policy scenarios.
- •Reveal policy trade-offs of wind turbine planning targets.
- •Uncover spatial effects of wind energy planning policies.
- •In Switzerland, restrictive policies lead to more alpine wind turbines.
- •In Switzerland, crop rotation areas show high potential for wind energy production.
Abstract
Energy production from the power of wind is being increasingly promoted around the world to reach climate and energy targets and gain independence from fossil fuels. The identification of possible sites for on-shore wind energy production faces multiple challenges. National wind energy strategies cite various physical, ecological, social and economic constraints in defining wind turbine locations. Furthermore, the acceptance of new infrastructure is highly dependent on regional and local conditions.Consequently, the design of policy guidelines that simultaneously consider various constraints and goals in a spatially explicit manner is highly challenging. To tackle this challenge, we demonstrate how a state-of-the-art evolutionary optimization algorithm can inform policy-makers in leveraging various planning policies to optimize wind energy production. We investigate the spatial and non-spatial effects of different policies considering multiple planning targets and constraints. Moreover, we analyze trade-offs between different wind turbine planning targets. Based on the results, we outline several policy implications to support the identification of development areas for wind turbines in Switzerland. The proposed optimization method enables us to better understand the national planning horizon within a regional context and vice versa.
