occurrences. Dynamic transmission limits require forecasts to ensure the changing resource mix can be most efficiently used, extracting the most possible out of a potentially constrained transmission system. Dynamic operating reserve requirements are forecast so that sufficient quantities are ready when risk is high but reduced when it is low to keep costs down. Finally, forecasts are required to help anticipate extreme events that may have devastating impacts on the power system. With a changing climate, forecasting techniques will need to evolve to incorporate these shifting conditions from the planning to operating timeframe. The Integration of Renewable Energy Into Market Operation Increasingly, renewable energy generation assets are asked to participate in electricity markets and compete against Remote Sensing Onsite Data Offsite Data Accuracy (Percent Forecast Skill Improvement) 1 Weather Modeling and Forecasting a Renewable Energy Source Power Forecasting Models 2 Collaborative Forecasting and Data Markets 3 4 Decision-Aid Models d c b Power System Forecast Value Operational Planning Electricity Market (Profit Increase and Renewable Energy Source Maximum) Need for Business Cases That Show Uncertainty Forecast Value to Industry Legend Bottlenecks in the Connection 1 Lack of Open Data (Privacy Issues) 2 Lack of Price-Based Incentives to Share Data 3 Accuracy Remaining Low and Lack of Standardization 4 Open Loop Between Use of Forecasts and Generation Bottlenecks in the Models a b c d Need for Numerical Weather Prediction Products Adapted to Renewable Energy Source Use Cases Limitation of Models to Exploit Large and Heterogeneous Data Decaying Commercial Value of Forecast Products Need for Models Adequate in High-Renewable Energy Source Integration Scenarios and Digitalization of the Energy Sector figure 1. The current bottlenecks of the renewable energy forecasting value/model chain. (Source: Smart4RES project; used with permission.) november/december 2021 ieee power & energy magazine 79