Effects of Predictive Wind Speed, Temperature, and Cloud Cover Change on Co-Located Wind and Solar Energy Farms in Maryland

With changing climates and financial incentives to develop clean energy, the appetite for renewable energy is expected to increase in the foreseeable future. However, building plants can be costly and difficult to adapt to significant weather changes.

This project aimed to determine the ideal location and cost allocations for a co-located plant in the Delaware – Maryland – Virginia (DMV) region. Co-located plants are multifunctional energy plants with wind, solar, and battery components. Plants can take advantage of cyclical, predictable sunshine and variable wind while storing energy in their battery components. Understanding asset allocations towards each component combined with trends in climate (mainly wind speeds, temperature, and cloud coverage, which affects power production) is critical in assessing plant viability.

Energy production from each component was calculated using the Co-Located Storage, Wind & Solar Model (CSWSM) tool developed by Ulimmeh Ezekiel at BloombergNEF. Financial data, industry costs, and projections were sourced from the Bloomberg Terminal. We modified the CSWSM with wind speed, cloud coverage, and temperature data forecast using the Regional Climate-Weather Research and Forecasting Model (CWRF) from Dr. Xin-Zhong Liang from the University of Maryland.

Testing five locations across the DMV region, it was determined that Ocean City, MD, and Annapolis, MD, had the greatest potential financial value of $16.2M (equity return 14.3%) and $11.5M (equity return 13.2%), respectively, given their region’s long-term climate outlook. Despite concerns that rising temperatures could potentially reduce solar panel efficiency, newer technology will mitigate these effects, ensuring their viability in the DMV region.