Accelerating Decarbonization of Electricity Generation by Incentivizing the Continuous Growth of Wind Energy in Mature Markets

Wind energy has proven to be an effective component in decarbonizing electricity generation all over the world. As nations expand wind energy generation, they have been able to advance the goals of the Paris Climate Change Agreement, reducing greenhouse gas emissions. Wind energy provides significant sustainability benefits, helping to reduce pollutant emissions, improve the lives of local communities, and mitigate climate change. Additionally, it has become the lowest-cost energy source in many regions, even lower than natural gas, making it financially sustainable, not requiring economic subsidies. However, as wind energy expands, it becomes increasingly difficult to identify favorable locations for these facilities, since initial wind farms have occupied the most propitious sites and infrastructure has become more saturated. As electricity requirements grow in these locations, additional demand is being supplied by fossil fuel generation, as incremental wind energy becomes progressively more challenging to develop in these mature markets. This causes the carbon footprint from electric generation to grow, becoming detrimental to sustainability goals. This research aims to initiate the development of a spatio-temporal frameworks that will aid wind energy in mature markets to continue growing to support resilient renewable energy expansion. The proposal for frameworks applies geospatial data analytics to assess the potential growth of wind energy in mature markets, which may have reached levels of saturation. This will aid these mature markets to continue growing wind energy beyond current levels, to expand environmental and socio-economic benefits. Texas was studied in this analysis, applying the proposed method, to identify key factors that may improve sustainable operational results from wind energy. Results were promising, with the proposed framework identifying locations that may provide improved results to satisfy electricity demand in local markets. The study was able to identify locations and operational parameters that will aid stakeholders in future wind energy sustainable development decisions and promote resilient renewable energy growth in mature markets. Results from this study indicate the potential to expand wind energy development in Texas. For instance, the Coastal and South ERCOT Wind Regions reported a positive correlation coefficient between wind generation and electricity consumption, higher than 0.7. This study presents a case study-based framework that requires adaptation and external validation to be applied in other locations. The goal of the proposed spatio-temporal framework is to provide benefits to local communities, reducing greenhouse gas emissions, air pollution and water usage, and reducing the risk associated with climate change.