Short-term load forecasts, which estimate electricity demand over short periods ranging from a few hours to a few days ahead, are valuable tools for electricity system operators, utilities, and energy market participants. These forecasts help in efficient power system operation, optimal energy scheduling, resource planning, and cost optimization. However, the accuracy of short-term load forecasts can vary depending on various factors, such as weather conditions, time of year, day of the week, and unforeseen events. While advancements in data analytics, machine learning, and advanced modeling techniques have significantly improved forecast accuracy, there is always a level of uncertainty associated with short-term load forecasting due to the dynamic nature of energy consumption patterns and external factors. Therefore, continuous improvements in modeling methodologies and the integration of real-time data into forecasting algorithms are still essential to enhance the accuracy of short-term load forecasts.
This mind map was published on 15 October 2023 and has been viewed 136 times.