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This paper presents an agent-based model to investigate interactions between wind farm developers and landowners. Wind farms require hundreds of square miles of land for development and developers typically interact with landowners to lease land for construction and operations. Landowners sign land lease contracts without knowing the turbine layout, which affects aesthetics of property as well as value of the lease contract. Having a turbine placed on one's land is much more lucrative than alternative land uses, but landowners must sign over the use of their land without knowing whether they will receive this financial benefit or not. This process, typically referred to as “Landowner Acquisition,” is highly uncertain for both stakeholders—a source stated up to 50% of wind projects fail due to landowner acquisition issues. We present an agent-based model to study the landowner acquisition period with unique decision-making characteristics for nine landowners and a developer. Citizen participation is crucial to the acceptance of wind farms; thus, we use past studies to quantify three actions a developer can take to influence landowners: (1) community engagement meetings, (2) preliminary environmental studies, and (3) sharing the wind turbine layout with the landowner. Results show how landowner acceptance rates can change over time based on what actions the developer takes. While still in the “proof of concept” stage, this model provides a framework for quantifying wind stakeholder interactions and potential developer actions. Suggestions for how to validate the framework in the future are included in the discussion.

In this paper, we define True Decommissioning as the removal of internal combustion engine light-duty vehicles from the road permanently, quickly, and equitably. We discuss each interlinked component of True Decommissioning. We then outline the next steps for implementation, including engaging stakeholders, evaluating economic costs and benefits, and understanding policies and programs. Finally, we present a table of unanswered research questions in this area, including those our research group is working on. We welcome discussions on how we can achieve True Decommissioning and work together to facilitate an equitable transition to clean light-duty vehicle mobility for all.

This paper presents a new approach to building a decision model for government funding agencies, such as the U.S. Department of Energy (DOE) solar office, to evaluate solar research funding strategies. High solar project costs - including technology costs, such as modules, and soft costs, such as permitting - currently hinder many installations; project cost reduction could lead to a lower project levelized cost of energy (LCOE) and in turn, higher installation rates. Government R&D funding is a crucial driver to solar industry growth and potential cost reduction; however, DOE solar funding has not aligned with the priorities for LCOE reduction. Solar technology has received significantly higher research funding from the DOE compared to soft costs. Increased research funding to soft cost programs could spur needed innovation and accelerate cost reduction for the industry. To this end, we build a cost model to calculate the LCOE of a utility-scale solar development using technology and soft costs and conduct a sensitivity analysis to quantify how the inputs influence the LCOE. Using these results, we develop a multi-attribute value function and evaluate six funding strategies as possible alternatives. We find the strategy based on current DOE allocations results in the lowest calculated value and the strategy that prioritizes soft cost results in the highest calculated value, suggesting alternative ways for government solar agencies to prioritize R&D funding and potentially spur future cost reduction.

This paper presents an agent-based model to investigate interactions between wind farm developers and landowners. Wind farms require hundreds of square miles of land for development and developers typically interact with landowners to lease land for construction and operations. Landowners sign land lease contracts without knowing the turbine layout, which affects aesthetics of property as well as value of the lease contract. Having a turbine placed on one’s land is much more lucrative than not, but landowners have to sign over the use of their land without knowing if they will receive this financial benefit or not. The timing of this process, typically referred to as “Landowner Acquisition,” introduces high uncertainty for both stakeholders and represents a major pain point of the industry — a source stated up to 50% of wind projects fail due to landowner acquisition issues. We present an agent-based model that models the land lease contract period with unique decision-making characteristics for a set of landowners and a wind farm developer. Citizen participation is an integral part of community acceptance of wind farms, thus we use principles from past studies to quantify three actions a developer can take to influence landowner decisions: (1) community engagement meetings; (2) preliminary environmental studies; and (3) sharing the wind turbine layout with the landowner. The results show how landowner acceptance rates can potentially change over time based on what actions the developer takes. Overall, developers can use this model to better understand interactions with landowners and determine what actions may help positively influence landowner acceptance rates.