Sustainable renewable energy planning and wind farming optimization from a biodiversity perspective

Dhunny, A.Z.; Allam, Zaheer; Lobine, Devina; Lollchund, Michel Roddy

doi:10.1016/j.energy.2019.07.147

Cited by 40 publications

(21 citation statements)

References 55 publications

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“…Flexibility of multi-objective optimization rather than single objective optimization for solving optimization problems, despite several conflicting goals, is another advantage of this approach. Therefore, a desire for solving multi-objective problems led researchers to utilize more exact and complicated processes and patterns based on Pareto front strategy for increasing energy efficiency [28,52,58,122].…”

Section: Single Objective and Multi-objective Optimizationmentioning

confidence: 99%

“…The effects of climate change, driven largely by fossil fuel consumption and unhealthy lifestyle use, promote a strong and far-reaching use of renewable energy sources. Reference [52] suggests the approach of computational GAs to optimize wind farms for the detection of both the sitting of the wind turbines and the levelized cost of energy to guarantee the optimal production of electricity and sustain fragile ecosystems. The model was used to determine suitable locations for the position of wind turbines on a complex field around a flight and evaluated the electricity offset in terms of demand and supply to facilitate localized, more stable energy networks.…”

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Sustainability and Optimization: From Conceptual Fundamentals to Applications

2020

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In recent years, both sustainability and optimization concepts have become inseparable developing topics with diverse concepts, elements, and aspects. The principal goal of optimization is to improve the overall sustainability including the environmental sustainability, social sustainability, economic sustainability, and energy resources sustainability through satisfying the objective functions. Therefore, applying optimization algorithms and methods to achieve the sustainable development have significant importance. This paper represents a considerable review on the employed optimization methodologies to sustainability and the sustainable development including sustainable energy, sustainable buildings, and sustainable environment. Since energy optimization is one of the major necessities of sustainability, sustainable development is investigated from the energy perspective. In addition, the concept, definitions, and elements of the sustainability and optimization have been presented, and the review of the optimization metaheuristic algorithms used in recent published articles related to sustainability and sustainable development was carried out. Thus, it is believed that this paper can be appropriate, beneficial, and practical for students, academic researchers, engineers, and other professionals.

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Section: Single Objective and Multi-objective Optimizationmentioning

confidence: 99%

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Sustainability and Optimization: From Conceptual Fundamentals to Applications

2020

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“…Distribution changes and habitat displacement/changes caused by wind farms could have individual‐ or population‐level effects regionally and globally, including impacts on survival, breeding success, energy expenditure, and bird‐community structure and stability (Dahl, Bevanger, Nygård, Røskaft, & Stokke, 2012; Gómez‐Catasús et al., 2018; LeBeau et al., 2017; Marques et al., 2020). These effects may eventually lead to declines in bird species and abundance at different levels, and have thus received considerable attention (Dhunny, Allam, Lobine, & Lollchund, 2019; Marques et al., 2020; Thaxter et al., 2019).…”

Section: Introductionmentioning

confidence: 99%

Effect of wind farms on wintering ducks at an important wintering ground in China along the East Asian–Australasian Flyway

Zhao

Song

et al. 2020

Ecology and Evolution

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Wind farms offer a cleaner alternative to fossil fuels and can mitigate their negative effects on climate change. However, wind farms may have negative impacts on birds. The East China Coast forms a key part of the East Asian–Australasian Flyway, and it is a crucial region for wind energy development in China. However, despite ducks being the dominant animal taxon along the East China Coast in winter and considered as particularly vulnerable to the effects of wind farms, the potential negative impacts of wind farms on duck populations remain unclear. We therefore assessed the effects of wind farms on duck abundance, distribution, and habitat use at Chongming Dongtan, which is a major wintering site for ducks along the East Asian–Australasian Flyway, using field surveys and satellite tracking. We conducted seven paired field surveys of ducks inside wind farm (IWF) and outside wind farm (OWF) sites in artificial brackish marsh, paddy fields, and aquaculture ponds. Duck abundance was significantly higher in OWF compared with IWF sites and significantly higher in artificial brackish marsh than in aquaculture ponds and paddy fields. Based on 1,918 high‐resolution satellite tracking records, the main habitat types of ducks during the day and at night were artificial brackish marsh and paddy fields, respectively. Furthermore, grid‐based analysis showed overlaps between ducks and wind farms, with greater overlap at night than during the day. According to resource selection functions, habitat use by wintering ducks was impacted by distance to water, land cover, human activity, and wind farm effects, and the variables predicted to have significant impacts on duck habitat use differed between day and night. Our study suggests that wintering ducks tend to avoid wind turbines at Chongming Dongtan, and landscape of paddy fields and artificial wetlands adjoining natural wetlands is crucial for wintering ducks.

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“…Thus, identifying optimal energy portfolios that meet economic, environmental and social constraints requires not only a stakeholder-engaged process that addresses social acceptance of emerging technologies 22,23 , but also the development of analytical frameworks that integrate multiple targets and consider the cumulative effects of energy development [24][25][26][27] . While many studies have focused on identifying optimal sites of renewable energy resources based on physical attributes of their target area and technical specifications of a particular technology, only few attempted to expand the optimization criteria to biotic, economic, or social factors [28][29][30][31] .…”

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Quantifying biodiversity trade-offs in the face of widespread renewable and unconventional energy development

Popescu

Munshaw

Shackelford

et al. 2020

Sci Rep

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the challenge of balancing biodiversity protection with economic growth is epitomized by the development of renewable and unconventional energy, whose adoption is aimed at stemming the impacts of global climate change, yet has outpaced our understanding of biodiversity impacts. We evaluated the potential conflict between biodiversity protection and future electricity generation from renewable (wind farms, run-of-river hydro) and non-renewable (shale gas) sources in British Columbia (BC), Canada using three metrics: greenhouse gas (GHG) emissions, electricity cost, and overlap between future development and conservation priorities for several fish and wildlife groups-smallbodied vertebrates, large mammals, freshwater fish-and undisturbed landscapes. Sharp trade-offs in global versus regional biodiversity conservation exist for all energy technologies, and in BC they are currently smallest for wind energy: low GHG emissions, low-moderate overlap with top conservation priorities, and competitive energy cost. GHG emissions from shale gas are 1000 times higher than those from renewable sources, and run-of-river hydro has high overlap with conservation priorities for small-bodied vertebrates. When all species groups were considered simultaneously, run-of-river hydro had moderate overlap (0.56), while shale gas and onshore wind had low overlap with top conservation priorities (0.23 and 0.24, respectively). The unintended cost of distributed energy sources for regional biodiversity suggest that trade-offs based on more diverse metrics must be incorporated into energy planning. Biodiversity is declining at an alarming rate as a result of habitat loss, overexploitation, and climate change 1,2. To address this challenge, 196 countries have signed the Convention on Biological Diversity, which aims to halt biodiversity loss by 2020 by reducing direct harm, increasing protected areas, mitigating climate, and reducing global carbon emissions. With global energy demand projected to increase by 14-33% by the year 2035 3 , these commitments have contributed to an exponential increase in the development of renewable electricity sources (e.g., wind, solar, biomass, hydropower 4). Concomitantly, unconventional fossil fuels such as shale gas, are being developed worldwide (International Energy Agency; iea.org), and presented as less GHG intensive alternatives to coal-fired electricity generation 5. The development of new renewable electricity has been dominated by distributed energy resources (e.g. wind, solar, small hydropower) that are assumed to be more environmentally benign than traditional, large scale technologies, such as large dams or coal-fired plants 6. For example, the widespread adoption of renewable energy has resulted in spatially distributed interconnected networks of facilities that can

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Sustainable renewable energy planning and wind farming optimization from a biodiversity perspective

Cited by 40 publications

References 55 publications

Sustainability and Optimization: From Conceptual Fundamentals to Applications

Sustainability and Optimization: From Conceptual Fundamentals to Applications

Effect of wind farms on wintering ducks at an important wintering ground in China along the East Asian–Australasian Flyway

Quantifying biodiversity trade-offs in the face of widespread renewable and unconventional energy development

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