S&P Global Market Intelligence launched the latest energy transition dataset that incorporates hourly price predictions for power plant hubs as part of its Power Forecast series.
FREMONT, CA: S&P Global Market Intelligence launched the latest energy transition dataset that incorporates hourly price predictions for power plant hubs as part of its Power Forecast series. The new dataset allows market participants to analyze as well as forecast the time of day when a facility can maximize value from energy output, as well as gain insights regarding how daily price shapes may change in the future.
This new dataset coupled with other S&P Global Market Intelligence insights including project mapping, battery storage projects, Independent System Operator (ISO) market prices, transmission lines routes, and state-level renewable portfolio standards provides a unique fundamental outlook as to how a plant or type of generation may fare over the length of its operational life.
"Understanding how the economics of the grid impact of a power plant is key to decoding the signals that are driving the transition from traditional generation sources to renewable energy," stated Steve Piper, Research Director for Energy at S&P Global Market Intelligence. "Having deep on-the-ground differentiated insights provides a unique view into the broader market trends, such as whether a region is more suited to a particular technology and where the investments will likely flow."
Using this new dataset, S&P Global Market Intelligence came to know that wind resources in California are now in a better position to capitalize on intraday peak pricing. The analysis highlighted that as the sun sets and solar generation stops working, more conventional and potentially expensive resources come online to compensate for the night-time loss of solar. The evening hours are the time when wind farms capture more economic value than solar, hence becoming a potential renewable alternative.