How spatial policies can leverage energy transitions − Finding Pareto-optimal solutions for wind turbine locations with evolutionary multi-objective optimization

Spielhofer, Reto; Schwaab, Jonas; Grêt‐Regamey, Adrienne

doi:10.1016/j.envsci.2023.02.016

Cited by 12 publications

(7 citation statements)

References 49 publications

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“…Consequently, the authors claim that a more restrictive planning policy leads to more wind turbines in the Alps. There are undeniable visual similarities in the spatial distribution of wind energy infrastructure in the present study and that of Spielhofer et al [ 63 ], particularly with respect to strategy NRG-OS. However, this study observed a wider use of Alpine landscapes for wind energy infrastructure development only when optimizing for ecosystem services (ESS-OS), which is shown by Kati et al [ 64 ] as a preferable scenario for a biodiversity-aware wind energy infrastructure development.…”

Section: Discussionsupporting

confidence: 71%

“…Spielhofer et at. [ 63 ] have demonstrated that the choice of wind turbine type can significantly impact optimization results, particularly in high-elevation mountainous regions. Specifically, the use of adapted wind turbines with smaller rotor diameters and a lower mast base height can yield more favorable outcomes compared with using the same type of wind turbine across all regions.…”

Section: Discussionmentioning

confidence: 99%

“…Specifically, the use of adapted wind turbines with smaller rotor diameters and a lower mast base height can yield more favorable outcomes compared with using the same type of wind turbine across all regions. Further, Spielhofer et al [ 63 ] have shown that minor changes in spatial planning policy, such as a relaxation of regulations regarding suitable sites (as in the case of forests), can have a significant impact on the spatial distribution and number of wind turbines, as this would lead to a centralization of wind energy development on the agriculture- and urban-dominated plateau. Consequently, the authors claim that a more restrictive planning policy leads to more wind turbines in the Alps.…”

Section: Discussionmentioning

confidence: 99%

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Shifting from techno-economic to socio-ecological priorities: Incorporating landscape preferences and ecosystem services into the siting of renewable energy infrastructure

Salak,

Hunziker,

Grêt-Regamey

et al. 2024

PLoS ONE

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This study examines the siting scenarios for renewable energy installations (REI) in a mountainous region of Europe (Switzerland), incorporating the external costs of ecosystem services and, innovatively, social preferences. This approach challenges the prevalent techno-economic siting paradigm, which often overlooks these externalities. To minimize the external costs of the scenarios while maximizing energy yield, Marxan, an optimization software, was employed. The energy target for all scenarios is set at 25 TWh/a, stemming from the energy gap anticipated due to the phase-out of Swiss nuclear reactors by 2050. This target is met using renewable energy infrastructure such as wind, roof-mounted photovoltaic, and ground-mounted photovoltaic systems. By integrating social preferences into the optimization, this study showcases a promising implementation that transcends the software’s intended applications. It complements techno-economic approaches and offers alternative decision-making avenues. The conventional "roof first" strategy proved ineffective in preventing extensive land use for the development of new renewable energy infrastructure. Strategies incorporating ground-mounted photovoltaic infrastructure were more spatially, ecologically, and socially efficient than those without. The strategy optimized for energy yield exhibited the highest spatial efficiency but incurred significant ecosystem service costs and, surprisingly, had low social costs. In contrast, the strategy prioritizing ecosystem services was the most efficient in terms of ecosystem service costs but had elevated social costs and was spatially less efficient than other strategies. The strategy optimized for social preferences incurred the lowest social costs and excelled in spatial efficiency and ecosystem service costs. Notably, this strategy employed a limited number of planning units linked to both high ecosystem service and social costs. The findings underscore that incorporating social preferences significantly enhances the evaluation of siting options. This inclusion allows for the social acceptance of investments to be factored into costs, facilitating more informed and inclusive decisions.

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Section: Discussionsupporting

confidence: 71%

Section: Discussionmentioning

confidence: 99%

Section: Discussionmentioning

confidence: 99%

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Shifting from techno-economic to socio-ecological priorities: Incorporating landscape preferences and ecosystem services into the siting of renewable energy infrastructure

Salak,

Hunziker,

Grêt-Regamey

et al. 2024

PLoS ONE

Self Cite

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“…Moreover, the location decision for wind turbines within a wind farm has been a subject of numerous studies. Spielhofer et al [23] demonstrate how a state-of-the-art evolutionary optimization algorithm can inform policy makers in leveraging various planning policies to optimize the location of wind turbines. Using GH WindFarmer and WAsP software, Mohamed et al [24] improved the placement of wind turbines in the Kaberten park and reduced losses as a result of the trail's influence.…”

Section: Literature Reviewmentioning

confidence: 99%

Research on Wind Turbine Location and Wind Energy Resource Evaluation Methodology in Port Scenarios

Huang,

Liu,

Zhong

et al. 2024

Sustainability

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Wind energy is widely distributed in China as a renewable energy source. Aiming to alleviate the issues resulting from fossil fuel consumption faced by developing and developed countries (e.g., climate change) and to meet development needs, this study innovatively proposed methods for the location selection of wind farms and wind turbines in port areas based on the fuzzy comprehensive evaluation method. Considering that the wind turbine location is crucial to wind power generation, this paper focuses on locating wind turbines within a specific set of sea ports. The primary objectives of this paper are to evaluate the potential of wind power generation under different port scenarios and develop a method for assessing the potential of wind energy resources in wind farm areas. Firstly, a method is proposed for identifying the boundaries of wind farms in the port areas and locating wind turbines at sea ports. Furthermore, this study used the National Aeronautics and Space Administration (NASA) wind speed database to test the proposed method with the real-world wind power projects of the Ports of Tianjin, Shanghai, Xiamen, Shenzhen, and Hainan, which are top ports within five major coastal port clusters in China. It is found that the potential power generation capacity of the wind power farms at the above ports is 30.71 GWh, 19.82 GWh, 16.72 GWh, 29.45 GWh, and 24.42 GWh, respectively. Additionally, sensitive results for different types of wind turbines are conducted in the following experiment. The results of this study are fundamental for enriching the research of evaluating wind energy resources of sea ports and promoting the development and use of clean energy in practical environments. Further, the method proposed in this study is essential for optimizing the location and construction of wind turbines, which may help ports in adopting a low-carbon and green development path, thereby mitigating air pollution, and promoting sustainable development.

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“…Perceived top-down approaches may risk diminishing social acceptance at the local scale [141], leaving little room for counter-arguments against the 'greater good' [161]. Spielhofer et al [162] identi ed spatial trade-offs between wind energy policies for the Swiss case. In some cases and countries, spatial planning for the marine environment is also discussed to foster 'post-political planning' [74,76,150,163,164 A holistic and multidisciplinary planning approach thus appears necessary aside positive planning to balance the needs of various stakeholder interests and coordinate efforts through a consensus-driven planning process as far as possible, while such a process is not always easy to achieve [125,157,167 on participatory dialogues].…”

Section: Possible Constraintsmentioning

confidence: 99%

Coordination challenges in wind energy development: Lessons from cross-case positive planning approaches to avoid multi-level governance ‘free-riding’

Weber

2023

Preprint

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Achieving national renewable energy targets presents multi-level governance challenges, such as uneven progress and discrepancies arising from varying subordinate specifications and incentives on wind energy development. Governments have commenced adopting ‘positive planning’ that aim to integrate energy targets with spatial and land use planning, yet detailed discussions regarding wind energy development remain scarce. This paper assesses three cases in Germany and Sweden within criteria-based explanatory case studies to provide planners and policy makers with knowledge on key factors, lessons learned, and challenges. Positive planning appears to center on a strong energy target focus, limited space, and a balanced approach, shaped by the socio-political context. While Germany more recently embraces positive planning, Sweden started ambitiously on a national level but encounters policy and planning challenges. Planning agencies play an important role in promoting wind energy targets at mid-scale levels; however, legally binding targets matter. Striking a balance between energy targets and addressing land use concerns without disregarding them requires managing a delicate trade-off. Early communication and inter-agency collaboration, as seen in Sweden, might facilitate identifying compromises, navigating trade-off between species protection and renewable energy and offering municipal incentives. Nonetheless, satisfactory spatial trade-offs for long-term proof of concept remains a challenge.

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How spatial policies can leverage energy transitions − Finding Pareto-optimal solutions for wind turbine locations with evolutionary multi-objective optimization

Cited by 12 publications

References 49 publications

Shifting from techno-economic to socio-ecological priorities: Incorporating landscape preferences and ecosystem services into the siting of renewable energy infrastructure

Shifting from techno-economic to socio-ecological priorities: Incorporating landscape preferences and ecosystem services into the siting of renewable energy infrastructure

Research on Wind Turbine Location and Wind Energy Resource Evaluation Methodology in Port Scenarios

Coordination challenges in wind energy development: Lessons from cross-case positive planning approaches to avoid multi-level governance ‘free-riding’

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