Power Generation Expansion Planning Including Large Scale Wind Integration: A Case Study of Oman

Abstract

Offshore wind power provides a valuable source of renewable energy that can help reduce carbon emissions. Technological advances are allowing higher capacity turbines to be installed and in deeper water, but there is still much that is unknown about the effects on the environment. Here we describe the lessons learned based on the recent literature and our experience with assessing impacts of offshore wind developments on marine mammals and seabirds, and make recommendations for future monitoring and assessment as interest in offshore wind energy grows around the world. The four key lessons learned that we discuss are: 1) Identifying the area over which biological effects may occur to inform baseline data collection and determining the connectivity between key populations and proposed wind energy sites, 2) The need to put impacts into a population level context to determine whether they are biologically significant, 3) Measuring responses to wind farm construction and operation to determine disturbance effects and avoidance responses, and 4) Learn from other industries to inform risk assessments and the effectiveness of mitigation measures. As the number and size of offshore wind developments increases, there will be a growing need to consider the population level consequences and cumulative impacts of these activities on marine species. Strategically targeted data collection and modeling aimed at answering questions for the consenting process will also allow regulators to make decisions based on the best available information, and achieve a balance between climate change targets and environmental legislation.

Breeding density, fine‐scale tracking, and large‐scale modeling reveal the regional distribution of four seabird species

“…As such, potential impacts cannot be reliably apportioned to breeding colonies, hampering attempts to predict their demographic consequences (Bailey et al. ). Similarly, the impacts of oil pollution and bycatch may be highly localized (Williams et al.…”

“…Current assessments of the potential barrier, displacement, and collision impacts, both at the individual windfarm level and the region-wide level, rely either on data from boat or aerial surveys (Furness et al 2013, Maclean et al 2013, tracking from very few colonies (Perrow et al 2006) or the radius method (Thaxter et al 2012, Bradbury et al 2014). As such, potential impacts cannot be reliably apportioned to breeding colonies, hampering attempts to predict their demographic consequences (Bailey et al 2014). Similarly, the impacts of oil pollution and bycatch may be highly localized (Williams et al 1995, Zydelis et al 2013) so colony-level distribution estimates will facilitate spatial planning decisions that more effectively balance seabird conservation with competing interests, by linking marine aggregations of seabirds to specific colonies.…”

Predicting the offshore distribution and abundance of marine birds with a hierarchical community distance sampling model

“…, Langston , Bailey et al. ). Understanding seasonality in species richness and abundance is also an important consideration in marine spatial planning, particularly in regions where distinct groups of birds use the area throughout the year for different activities.…”

Classification of birds and bats using flight tracks

“…Methods used to assess risk and effects to bird populations at multiple scales during pre-and post-construction included direct observation or video surveys along boat and aerial transects (Banks et al, 2005;Camphuysen et al, 2004), collision risk models (Band, 2012;Smales et al, 2013), and field experiments to assess turbine avoidance (Guillemette and Larsen, 2002). As research efforts in Europe have gained a greater understanding of effects from wind farms, the need for additional tools and techniques to appropriately assess impacts has become apparent (Bailey et al, 2014). Efforts have been initiated to gather broad-scale wildlife distribution and abundance information off the Atlantic and Pacific coasts of the U.S. to assess potential offshore wind-wildlife conflicts and to aid in the leasing of offshore sites for wind energy development (Adams et al, 2014;Maclean et al, 2009;Normandeau, 2012;USGS, 2014).…”