The grid is a constant balancing act of supply and demand, and sudden shifts in either can threaten reliability and safety. Without intervention, supply and power surges will ripple down the wires and potentially damage power equipment. Conversely, if demand exceeds supply, brownouts and blackouts ensue.
Wind and solar energy depend on the weather to determine their output, which can vary moment to moment. Spread out over a large geographical area with many renewable systems connected, these supply blips are largely smoothed over. But at a localized level, for both the system owner and the distribution grid, variability is a necessary concern.
Enhanced forecasting capabilities combined with digitalization and data can help integrate variable renewables by enabling operators to more intelligently match energy output to meet demand so less clean energy can be curtailed, and system value can be maximized. Smart controls, inverters and energy storage can also be utilized with enhanced predictive capabilities when the sun is shining, and the wind is blowing to optimize system performance and efficiency.
Asset management and performance are critical to ensuring that large renewable energy systems connected to the grid are not disruptive to operations and reliability, and instead are part of the solution to grid variability by matching dynamic output to dynamic demand. In competitive marketplaces, power forecasting can also enable more efficient and exact bidding, maximizing revenue potential and shortening return on investment.
The constantly fluctuating nature of renewables is well suited to digitalization, and by applying data analytics and forecasting, systems can be better managed, and performance optimized across an entire portfolio of renewable assets.
Scipher.Fx by Utopus is a scalable, secure, and flexible energy analytics platform designed for accurate renewable energy forecasting. The software is a comprehensive wind and solar PV power forecasting tool that helps renewable asset framer owner, operators, and power traders to make better informed decisions. Scipher.Fx helps comply with regulatory requirements, minimize penalties and imbalance costs, and optimize asset O&M activities based on high yield production forecasts. The product’s proprietary machine learning models leverage historical measurement data from solar and wind farms to predict intra-day and next-day available power forecasts.
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